Chapter 8: FLUID DISPENSING 

AND DISPERSION

Jiann C. Yang, Ph.D. 

National Institute of Standards and 

Technology

David Keyser, Ph.D. 

Naval Air Systems Command (retired)

TABLE OF CONTENTS

8.1 Introduction......................................................................................................................722 

8.1.1 Characteristics of Aircraft Engine Nacelle Fires...................................................722 

8.1.2 Summary of Suppressant Fluid Dynamics............................................................723 

8.1.3 Scope .....................................................................................................................724 

8.2 Fluid Storage....................................................................................................................725 

8.3 Fluid Transport through Piping........................................................................................726 

8.3.1 Introduction ...........................................................................................................726 

8.3.2 Previous Work.......................................................................................................729 

8.3.3 Base Code Selection..............................................................................................730 

8.3.4 Code Development Work......................................................................................732 

8.3.5 Code Theory ..........................................................................................................733 

8.3.6 Supporting Laboratory Data..................................................................................753 

8.3.7 Comparison of Code Predictions to Experimental Data .......................................786 

8.3.8 Assessment of Fluid Transport Model ..................................................................804 

8.4 Dynamics of Fluid Transport in Cluttered Spaces...........................................................805 

8.4.1 Spray Transport past Generic Clutter Elements....................................................805 

8.4.2 Spray Interaction with Unheated and Heated Clutter Elements............................809 

8.4.3 Transport around Clutter and Recirculation Zones...............................................821 

8.4.4 Low Temperature Effects on Agent Dispersion....................................................829 

8.5 Modeling of Fluid Dispersion in a Nacelle......................................................................839 

8.5.1 Background ...........................................................................................................839 

8.5.2 CFD Models..........................................................................................................839 

8.5.3 Code Assessment Using Quarter-Scale Nacelle Tests and Simulations ...............847 

8.5.4 Assessment of VULCAN Fire Suppression Sub-model........................................854 

8.5.5 Assessment of VULCAN in Suppressant Distribution in a Full-Scale Nacelle....863 

8.5.6 Assessment of VULCAN in Pool Fire Suppression in a Full-Scale Nacelle ........868 

8.6 Full-Scale Nacelle Fire Suppression Tests ......................................................................871 

8.6.1 Experimental Design .............................................................................................871 

8.6.2 Test Facility...........................................................................................................872 

8.6.3 Test Matrices and Decision Tree...........................................................................876 

8.6.4 Actual Test Program..............................................................................................878 

8.6.5 Instrumentation......................................................................................................879 

8.6.6 Test Procedure.......................................................................................................879 
722 Fluid Dispensing and Dispersion 

8.6.7 Test Results and Comparisons to Simulations ......................................................882 

8.7 Improved Transport of Water to Fires .............................................................................889 

8.7.1 Background ...........................................................................................................889 

8.7.2 Electrically Charged Water Mist...........................................................................889 

8.7.3 A Self-Atomizing Form of Water .........................................................................909 

8.8 Summary of Lessons Learned..........................................................................................916 

8.9 References........................................................................................................................918

8.1 INTRODUCTION 

8.1.1 Characteristics of Aircraft Engine Nacelle Fires 

Serious fires in aircraft engine nacelles, sufficient to terminate a mission, usually involve liquid fuel, 

either jet fuel or hydraulic fluid, supplied by a leak in its supply system. The primary types of fire are 

spray fires and pool fires. Fuel sprays occur when a pressurized line develops a relatively small opening, 

caused by battle or other damage, which results in a misting or atomized discharge of droplets. Fuel from 

larger openings in pressurized lines may flow over the hot surfaces and ignite there, or end up in pools 

below the engine contained by aircraft structure or other clutter. Typical ignition sources are electrical 

sparking and hot surfaces. Because aircraft engines normally produce and reject a lot of heat, the 

consequence is many and large hot surfaces on the outside of the engine. The air required to maintain 

combustion is furnished by flow from the atmosphere for which the original purpose is to cool the engine. 

The most likely region for fires in engine nacelles is the long, narrow, annular space between the engine 

core and the outer aerodynamic skin. A large number of components are located within this region, 

resulting in a complex, cluttered geometry. The nacelle design typically includes ventilation airflow, 

either via an external scoop or other source, to both cool the nacelle and to avoid the build-up of 

flammable mixtures. In general, this engineered airflow has sufficient momentum to dominate the 

buoyancy produced by burning. The dynamics of a fire within an aircraft engine nacelle are typically 

dominated by the designed airflow.

Presently, aircraft survivability and suppression system proving tests are performed under conditions 

intended to replicate the nacelle airflow while the aircraft is in flight. Test fixtures, such as the Aircraft 

Engine Nacelle Fire Test Simulator (AEN) at Wright-Patterson Air Force Base (WPAFB) in Dayton, 

Ohio, have been constructed to represent variable geometries typical of aircraft nacelles. Extensive sets 

of experiments and live-fire tests with varying degrees of complex internal geometry have been conducted 

to evaluate the performance of suppression systems and new agents. These tests and experiments have 

provided significant insight into the essential features of successful systems and serve as the basis for 

present system acceptance. However, the results from these tests, particularly when fire extinguishment 

(as opposed to merely the concentration of agent) is the criterion, are often difficult to understand given 

the lack of a well-characterized flow field.

Adding to the difficulty in extinguishing fires in nacelles, especially in flight, is their cluttered interiors. 

These bluff bodies create many “flame-holders” regions with various sizes and shapes downstream of the 

recirculating zones into which the suppression agents have difficulty penetrating. In the case of pool fires 

resulting from flammable liquid accumulating at the bottom of the nacelle, one can encounter an 

unwanted situation where the pool fire is temporarily suppressed by an agent but rapidly flares up again 
Introduction 723

after the agent is exhausted from the nacelle. The re-ignition of the liquid pool is probably due to 

continuing fuel vapor generation from the pool and adjacent hot nacelle surfaces not being cooled below 

the ignition point of the fuel vapor as a result of the suppression action. 

A phenomenon, termed accelerated burning, has been observed in a diversity of fire suppression tests and

was witnessed in this test program as well. It resulted from slow injection of insufficient agent to 

suppress nacelle engine fires. The injection transient only served to facilitate mixing of fuel vapor and air 

for combustion. In these cases, the resulting fire could be more intense than if nothing had been done. 

This phenomenon has been studied by Hamins et al.1

8.1.2 Summary of Suppressant Fluid Dynamics 

Conventional fire suppression systems for aircraft engine nacelle protection typically consist of a pressure 

vessel, in which a liquid fire suppressant is stored and pressurized with an inert gas, such as nitrogen or

carbon dioxide. The fire-suppressant is released remotely by a fast-opening valve upon the indication of

fire. The pressurized agent is ejected into the piping manifold and is distributed to the locations in the 

nacelle, which have been selected by design and analysis for optimum delivery and dispersion of the 

agent in order to suppress any foreseen fire. A schematic of a fire suppressant system is shown in

Figure 8-1. 

The pressure vessel governs the initial conditions for agent discharge that affect the subsequent dispersion

of the suppressant. The aspects of fluid storage in a pressure vessel are related to the determination of the 

thermodynamics state of the fluid in the bottle and the sizing of the bottle required to accommodate 

adequate amount of agent required for fire suppression without compromising the bottle’s structural 

integrity.

Fast Acting Valve

Agent Distribution Piping System

Figure 8-1. Schematic of Storage and Distribution System for Fire Suppression. 

Once the valve is opened, the pressurized liquid agent is forced out into the distribution system (straight 

pipes, bends, tees, etc.), which may be at a temperature greater than the boiling point and at ambient 

pressure. This can cause a multi-component, two-phase flow, which is quite complicated to analyze and 

measure. 
724 Fluid Dispensing and Dispersion 

A gaseous suppressant can be easily dispersed throughout the protected space. If a superheated liquid 

agent is released, flashing will occur, which will greatly facilitate the agent dispersion. Halon 1301, with 

a boiling point of −58 °C, is an example of such a fluid. Because of its flashing characteristics and rapid 

evaporation, the dispersion of halon 1301 in an enclosure, even cluttered with obstacles, is rapid and 

effective. 

If the suppressant has a high normal boiling point and/or is released at temperatures below its normal 

boiling point, the liquid droplets formed at the discharge nozzle will persist as they flow through the 

nacelle. The actual droplet size distribution delivered to the fire will be different from the initial 

distribution at the discharge nozzle. After liquid droplets form, depending on the droplet number density 

and droplet ballistics (velocities and trajectories) and even before they arrive at the fire zone, dropletdroplet and droplet-surface interaction may happen in an aircraft engine nacelle due to its highly cluttered 

environment. These processes may alter the initial droplet size and velocity distributions significantly. 

The presence of high-speed airflow can also affect the droplet size and velocity distributions. If the 

dispersing spray encounters a solid obstacle, pooling, dripping, splitting, splashing, or shattering of the 

droplets will result. Dripping and pooling causes local retention of liquid on the nacelle bottom surface, 

cutting or splitting of the droplet due to impact at the edge of the surface may result in smaller droplets, 

and droplet splashing and shattering can generate smaller daughter or satellite droplets. The nacelle 

surface temperature also plays a role in the droplet-surface interaction. 

8.1.3 Scope 

The NGP determined that, following the discharge of a suppressant from the storage bottle, more needed 

to be understood about the behavior of the two-phase suppressant flow in the distribution plumbing and 

the subsequent dispersion of the suppressant from the plumbing outlets to the fire location through the 

cluttered environment in a nacelle. This chapter presents new understanding of and bases for 

improvements in the storage, the distribution, delivery, and dispersion of fire suppressants in an aircraft 

engine nacelle. Prior to the NGP, such a comprehensive approach to the study of fluid dispensing and 

dispersion for nacelle fire protection applications had never been attempted. 

The two-phase distribution flow is discussed in detail in section 8.3. A two-phase computer code, based 

on a code widely used in the nuclear industries, was developed further for this application. The program 

was benchmarked against transient experimental data available in the literature, as well as experiments 

conducted in the NGP study. 

The phenomena of liquid suppressant interacting with cluttered elements are discussed in section 8.4. In 

addition, the effects of liquid boiling point, storage bottle temperature, and nacelle and airflow 

temperatures on agent dispersion were examined using CF3I as a surrogate. 

Sections 8.5 and 8.6 focus on the study of agent dispersion in a nacelle using computer simulations and 

full-scale nacelle fire tests. Computational fluid dynamics (CFD) programs were used to simulate these 

processes, to aid the design of the experiment, to facilitate the formulation of the test matrices, and to 

predict the outcomes of fire-tests. CFD simulations provide detailed visualization of agent dispersion 

throughout the nacelle to optimize the locations and number of agent discharge nozzles needed for 

prototype fire suppression system designs. Agent concentration and agent interaction with probable flame 

loci can also be predicted to determine the appropriate amount of agent to be stored and the agent 
Fluid Storage 725

injection duration. Such information leads to the design pressure for the storage bottle and design 

guidance for efficient agent deployment and provides a high degree of confidence in using simulation 

tools to guide fire protection system design for nacelles. These advances will also benefit other 

applications of complex geometry where flame extinguishment must be accomplished in time frames of 

the order of seconds or faster. 

In section 8.7, two other potential strategies to facilitate fluid dispersion have been explored and will be 

discussed. One involves the use of an electrically charged, water-mist system, and the other examines a 

self-atomizing form of water employing CO2 hydrates. Given the geometrical and physical constraints of 

a nacelle, these two techniques have not been proven to be promising for nacelle applications. 

8.2 FLUID STORAGE 

When the fire suppressant is a fluid, it will most likely be stored in a pressure vessel. In most 

applications, the release or discharge of the bottle content depends solely on the prevailing internal 

pressure within the bottle ullage. Yang and coworkers2

 have developed a methodology for predicting this 

pressure. 

For a pure fluid, the ullage pressure will be the vapor pressure of the fluid at the prevailing temperature. 

If the applications are limited to room temperature or above, fluids with high vapor pressures at room 

temperature can be released at a moderate rate with adequate driving force within the bottle. However, 

the discharge can become problematic at very low temperatures where the vapor pressure becomes subatmospheric. The conventional way to alleviate this problem is to use a suppressant gas (e.g., nitrogen) to 

enhance the ullage pressure above the vapor pressure of the fluid at room temperature. In this case, the 

ullage pressure is maintained at a relatively high level, even at low temperatures, to facilitate the 

discharge processes. An alterative way to address the low ullage pressure problem at low temperatures is 

to use the so-called hybrid system wherein an SPGG (solid propellant gas generator), upon activation, 

provides the pressure source to drive the fluid out of the bottle (see Chapter 9). The focus of this section 

is on a pure fluid pressurized with a suppressant gas. 

The prevailing ullage pressure is critical to the discharge of the bottle content. The pressure can be 

derived from the thermodynamic state of the suppressant fluid with the pressurized gas under different 

ambient conditions. The myriad ambient conditions are the result of bottle location and in-flight or onthe-ground environments of an aircraft. The thermodynamic state of the fluid in the bottle not only 

determines the initial conditions for fluid agent discharge in case of a fire, but also provides data for bottle 

design in terms of its size and ability to withstand increased internal pressure at elevated temperature. 

The ullage pressure in the bottle is a complex function of ambient temperature because of the temperature 

dependence of the fluid vapor pressure, the partial pressure of pressurized gas in the ullage, and the 

solubility of the pressurized gas in the fluid. For halon 1301, the bottle pressure-temperature relationship 

and the solubility of pressurized gas nitrogen in the agent have been well characterized. By contrast, such 

a relationship and solubility data are scarce or do not exist for many of the halon alternative fluids. 

The thermodynamic state of the storage container can be determined by an appropriate equation of state 

applicable to mixtures (fluid and pressurized gas) with empirical binary interaction coefficients.3

 Other 

thermodynamic frameworks have also been used.4

 In the following, a brief discussion of the development 

of a computer code, named PROFISSY, in the Technology Development Program (TDP) to calculate the 
726 Fluid Dispensing and Dispersion 

thermodynamics state of the bottle will be presented. Detailed description of the code can be found in 

Yang et al.2

PROFISSY (acronym for PRoperties Of FIre Suppression SYstems) was developed for the primary 

purpose of helping fire suppression bottle designers or users to obtain temperature-pressure characteristics 

of bottle contents. Simply put, given a vessel charged with agent and nitrogen at room temperature, one 

would like to know what the final vessel pressure will be when the vessel is at a different temperature. 

Only four pieces of input information are required to run the program: (1) agent mass, (2) vessel volume, 

(3) fill temperature, and (4) either nitrogen mass needed to pressurize the vessel, or the fill pressure of the 

vessel. 

The program also predicts whether a liquid-full condition (i.e., the storage vessel is completely filled with 

liquid with no ullage) would occur at elevated temperatures for a given initial fill density, defined as the 

amount of liquid divided by the vessel volume. When the initial fill density is above the critical density 

of the fluid, a liquid-full condition will result due to the thermal expansion of the liquid, to the point that 

the vessel becomes completely filled as it is heated. A liquid-full condition is undesirable and must be 

avoided because the internal pressure of the vessel will rise sharply with temperature once a liquid-full 

condition has been reached.4

 This could result in rupture of the vessel. 

PROFISSY incorporates a thermodynamics model known as “extended corresponding states” (ECS).5

 

The central idea of extended corresponding states is that all points on the PVT (pressure-volumetemperature) surface of any fluid may be represented by scaling the PVT surface of a reference substance. 

These “scale factors” involve the critical properties of the fluid of interest and the reference fluid and may 

also be functions of temperature and density. The ECS model is a powerful tool, applicable to the entire 

range of fluid states, from dense liquid to dilute gas, as well as to the supercritical fluid regime. It may be 

used with only minimal information on a fluid: the critical point, the normal boiling point, and the 

molecular weight. Additional information on a fluid, such as vapor pressures, saturated liquid densities, 

and liquid viscosities can be used to refine the model predictions. 

The current PROFISSY code, running on a PC, supports thermodynamics state calculations for 

halon 1301, FC-218, CF3I, HFC-125, and HFC-227ea. Experimental data have been obtained to compare 

to the code predictions for these fluids.6

 In general, the predictions were found to be within 10 % of the 

measurements.6

 The code can be easily extended to include other fluid/nitrogen systems, if desired. 

8.3 FLUID TRANSPORT THROUGH PIPING 

8.3.1 Introduction 

As stated above, the current halon delivery systems generally consist of a suppressant vessel connected to 

the delivery location by a piping network. Prior to the NGP, there was no publicly available simulation 

tool for transient, two-phase flow through a complex pipe system. There is a need to determine whether 

the existing piping system for halon 1301 can be used for a replacement agent. For the NGP, Tuzla and 

coworkers7

 have developed a computer code for two-phase fire suppressant flow in a complex piping 

system. 
Fluid Transport Through Piping 727

Since halon and its potential replacement fluids are in a vapor state at standard pressure and temperature, 

at the discharge location the fluid will be a two-phase mixture of superheated liquid and vapor. Thus 

significant thermodynamic and thermal non-equilibrium can be expected between the phases. Also, due 

to the large pressure difference between upstream source vessel and downstream exit, continuous flashing 

is anticipated as the fluid travels through the piping, and two-phase critical (choked) flow can occur at 

various locations. 

There has been some work conducted on modeling halon 1301 flows. In a 1988 summary of the state-ofthe-art, DiNenno and Budnick8

 indicated that most of the flow calculations were performed using 

proprietary methods. These methods were verified against standard NFPA procedures for calculations 

and by discharge testing in sealed tests. However, there were significant uncertainties in the calculations 

and also in extrapolation of test results to actual configurations. 

Pitts et al.9

 described a mathematical model for calculating the discharge of fire-suppressant fluids from a 

pressurized discharge tank across an orifice at the exit and showed that the transient pressure history in 

the discharge vessel calculated by the model compared reasonably well to data from experiments. Elliott 

et al.10 developed a computer program called HFLOW for predicting the discharge of halon 1301 from a 

discharge vessel through a piping system. The results of the program compared favorably to the results of 

experiments conducted with halon 1301 in several piping arrangements. The theoretical model was based 

on a homogeneous model of two-phase flow. Elliott et al.10 also modified an existing computer program 

called SOLA-LOOP,11 which was originally written for steam-water flows, to be able to model halon 

1301. This computer program was a non-equilibrium, non-homogeneous model of two-phase flow, using 

the drift flux approach to calculate slip between the phases. It was shown that this program, modified to 

account for halon 1301 properties, was able to capture the physics of the agent discharge more accurately 

than its predecessor. 

The methods described by Yang et al.2

 and Elliott et al.10 appear to be the only methods available in the 

public domain for calculating performance of fire-suppressant fluid delivery systems. One way to 

develop a general, flexible computer program that would be able to model a variety of piping networks 

and handle several candidate fluids would be to extend this work by modifying these methods. Another 

approach is to take advantage of the advances in two-phase flow modeling that have taken place in the 

nuclear power industry, which have resulted in several computer codes available in the public domain. 

The development of the computer code described here followed the latter approach. 

Hence, to predict the performance of the delivery system accurately, a computer code should be a 

transient two-phase code, which allows for phase non-equilibrium. The short delivery times require fairly 

high flows, which promote homogeneous two-phase flow, i.e., little slip. However, in imbalanced piping 

networks, with side tees and other fittings, some separated flow could occur (stratified flows, slug/plug 

flow, etc.). Hence, the code should be able to predict slip between phases and the corresponding effect on 

pressure drop. This can be especially important when separated flow encounters directional change, such 

as at a side tee. The ability to predict the transport of non-condensable gas is also important. The fluid, 

pressurized with a driver gas, is initially saturated with the gas. During the delivery, as the system 

depressurizes, the driver gas comes out of the solution and expands. This gas evolution phenomenon 

needs to be accounted for. One additional requirement is that the code should be useful for estimation of 

the transient hydrodynamic loads in the piping network. Thus, the momentum equations need to be 

sufficiently detailed to estimate the unbalanced force in piping sections between locations of elbows and 

other fittings. 
728 Fluid Dispensing and Dispersion 

A key technical approach in the present program was utilization of advancements made in other 

applications that deal with multi-phase flows. In particular, the highly sophisticated computer codes that 

have been developed for thermal-hydraulic analysis of nuclear power systems have all the characteristics 

required for analysis of fire suppressant systems. These include models that account for relative slip 

between liquid and vapor phases, thermodynamic non-equilibrium between the phases, changes in twophase flow regimes, critical choke flows, and transport of non-condensable gases. Such codes are also 

structured for numerical analysis of fast transients, well capable of the transients anticipated for 

suppressant systems. 

Since the fluids being considered for use in fire suppressant systems are different from the water/steam 

system of nuclear power systems, physical property packages need to be modified and expanded. Here 

again, the NGP leveraged existing technology by borrowing from existing property packages. 

Specifically, the REFPROP package, developed by NIST12, covers many refrigerant fluids, including 

those that are potential candidates for the fire suppressant systems. 

The effort contained an experimental task to obtain data needed to assess the code. The experimental 

program utilized a discharge loop using several proposed fire suppressants. Major flow parameters, 

which have not been measured heretofore, were successfully measured. These include measurements of 

instantaneous discharge flow rate, fluid temperature, and void fraction at various locations along a 

discharge pipe. 

The program is based on a one-dimensional, two-fluid model of two-phase flow. In this model, separate 

conservation equations are written for the liquid and gas phases for mass, momentum, and energy. 

Constitutive relationships are specified for interphase transport of mass, momentum, and energy. Heat 

transfer between the fluid and passive structures such as pipe walls are modeled. The program also 

contains built-in models for wall friction and two-phase critical flow. The transport of non-condensable 

gas in the system, namely the nitrogen fill gas, as well as the nitrogen released from solution during agent 

discharge, is modeled via separate mass conservation equations, with constitutive relations to specify the 

rate of gas release. The conservation equations are solved using a semi-implicit numerical method, with 

user-supplied boundary and initial conditions. 

The program was deliberately made flexible in terms of types of fluids and piping layout. The current 

version of the program allows the user to select any one of five fluids: water, halon 1301, CO2, 

HFC-227ea or HFC-125. Modules are available in the program with which the user can model a delivery 

system, including one or more supply tanks and a combination of piping networks. The user can also 

model valves in the system, with specified valve opening times if needed. 

The suppressant discharge is a highly transient process, generally lasting from less than a second to a few 

seconds. The program was benchmarked against transient experimental data available in the literature, as 

well as experiments conducted as a part of this project, on the discharge of HFC-227ea and HFC-125 in a 

specially prepared discharge loop. The present experiments lasted between 1.5 s to 6 s. In addition to 

transient system pressure at various points, these experiments also measured critical parameters, such as 

the transient mass discharge history, fluid temperature, and the void fraction near the exit. These are the 

first dynamic measurements of mass flow, fluid temperatures, and void fraction during suppression 

discharge. These new data allowed a more comprehensive assessment of the computer program than 

possible with previously available experimental data. The results of the assessment showed that the 

program is capable of predicting the performance of various delivery systems with several fluids. 
Fluid Transport Through Piping 729

Detailed description of the development of the computer code can be found in Tuzla et al.7, which 

comprises two volumes. The first volume provides a detailed description of the experimental work and 

discussion of the results. It also includes a brief description of the theory and numerical solution method, 

instructions for installation on a personal computer with the WINDOWS operating system, and 

instructions on preparation of the input needed to describe the system being analyzed. The second 

volume consists of three appendices: (a) an input manual for the computer program, (b) information on 

the experimental data, and (c) comparison of the present data to predictions of the computer program. A 

copy of the computer code can be found in the CD-ROM enclosed in that report. 

8.3.2 Previous Work 

To fully test the computer code developed in this research, comparisons of code predictions against 

experimental data were made. A literature survey was conducted to find possible sources for 

experimental data for transient two-phase flows. One widely referenced study is “The Marviken Tests,” 

conducted using water/steam for the nuclear reactor industry and documented in the two reports.13,14 

These tests used a liquid/vapor-filled vessel under high pressure and measured the vertical discharge 

characteristics as this system was released to atmospheric conditions. A similar test was carried out by 

Edwards and O'Brien15, but focused on the effects of a horizontal discharge. Even though the Marviken 

and Edwards tests were conducted with water/steam systems, they still provide some means for assessing 

portions of the code, which use mechanistic models for predicting non-homogeneous, non-equilibrium 

two-phase flows. These mechanistic models are fluid-independent and can be invoked for all fluids.

Three studies, which more closely reflect the intentions of the current study, have used fire suppressants 

as their test fluids, rather than water and steam. The work undertaken by Elliot et al.10 in 1984 includes 

both theoretical and experimental investigations. In this work, halon 1301 was used as the suppressant 

fluid. The tests discharged halon under nitrogen gas pre-pressure, resulting in flow of a liquid/vapor/noncondensable-gas mixture through a configuration of piping and an end nozzle. This study provides data 

on pressure decay as a function of time, allowing for the estimation of discharge flow rates, which are 

useful for accessing code predictions. This study also provides observations of experimental phenomena 

as the discharge proceeded. An example is the phenomenon of evolution of the dissolved nitrogen from 

the liquid halon, which causes an increase in the pressure of the discharge vessel and an increase in the 

driving force propelling the discharge of the fluid. 

The most comprehensive tests conducted to this date were launched in the mid 1990s by the National 

Institute of Standards and Technology (Yang et al.2

 and Pitts et al.9). Their tests not only utilized 

halon 1301 as a test fluid, but also utilized HFC-125, HFC-227ea, and CF3I. They conducted several 

experimental runs with each fluid, providing extensive data for various pipe configurations and operating 

conditions. Experiments with different initial fill volumes, pressures, and temperatures were performed to 

determine their effects on the two-phase system. Their findings provide important information about the 

characteristics of the two-phase transient flow as it discharges from the source vessel and through the 

piping. The pressure histograms from this earlier program are used as a benchmark in gauging the 

effectiveness of the code being developed in the current program. 

These prior studies provided the beginning of an experimental database. However, there were no data on 

several key parameters important to computational code assessment. Primary among these is the 

instantaneous mass discharge rate and void fraction, both at the exit of the source vessel and at the exit of 
730 Fluid Dispensing and Dispersion 

the distribution pipe. Such parameters reflect the mechanisms of phase change (vaporization) and 

interfacial momentum transfer (slip velocity) that must be correctly modeled in the computer code. 

Without specific experimental measurements of such key parameters, it is impossible to fully assess the 

validity of any prediction. This is the reason why the current experimental program was structured to 

obtain a number of additional measurements, above and beyond the usual measurement of pressure decay. 

Two-phase flow calculations require thermodynamic and transport properties of the fluid. These 

properties are required for single-phase liquid, for single-phase vapor, and for saturated vapor/liquid 

mixtures. The following thermodynamic properties are needed as functions of absolute pressure: 

• Saturation temperature 

• Specific heat for gas and liquid phases 

• Thermal expansion coefficient for gas and liquid phases 

• Isothermal compressibility for gas and liquid phases 

• Specific volume for gas and liquid phases 

• Specific entropy for gas and liquid phases 

In addition, the following transport properties are also required for two-phase flow calculations: 

• Dynamic viscosity for gas and liquid phases 

• Thermal conductivity for gas and liquid phases 

• Surface tension 

Most fire suppressants are also used as refrigerants. The refrigerant property package REFPROP 

developed at NIST by Gallagher et al.12 covers most of the fire suppressants. For example, it contains 

properties of halon 1301, and present fire suppressant candidate HFC-227ea. After evaluation, it was 

found that REFPROP was a suitable package for determining the properties required by the new code for 

two-phase flow calculations with suppressant fluids. 

8.3.3 Base Code Selection 

Desired Feature of the New Code 

The base code was developed with some specific features in terms of its technical ability to model the 

basic phenomena of two-phase flows. In addition, user convenience and ease of development were also 

desirable features. The present development sought to include the following features in the new code. 

Required features: 

• Non-proprietary, publicly available 

• Portable to various computer and operating systems 

• Ease of development (well-documented, flexible architecture) 
Fluid Transport Through Piping 731

Desired features: 

• Non-homogeneous two-phase flow accounting for relative slip between phases 

• Non-equilibrium two-phase flow, allowing for metastable conditions during flashing 

• Choking under single and two-phase conditions 

• Non-condensable (dissolved gas) transport 

• Multi-component mixtures (liquids, gases, powders) 

• Flexible system modeling capability (choice of piping components and layout) 

• Robust set of equations, for simulation of fast transient two-phase flows (for example, 

momentum equation to include frictional losses, energy equation to include dissipation) 

• Demonstrated ability to model representative systems (assessment against experiments) 

• Ease of application (user-friendly inputs) 

There are other intangible features that have also been considered, such as the existence of an active user 

group, which would facilitate future modifications and developments. 

Two-phase Codes Considered 

The relevant codes are those used in the nuclear industry for loss-of-coolant accident analyses (LOCA). 

These codes address the major phenomena of interest (non-homogeneous, non-equilibrium two-phase 

flows, choking conditions, fast transients). The survey was limited to codes developed and available in 

the United States and consisted of RELAP5, RETRAN, TRAC-P, TRAC-B and GOTHIC. Codes 

developed in other countries that could be used (ATHLET, CATHARE) were not considered because 

easy access to these codes may not be available. 

All these codes have many of the required and desirable features for the present application. They are all 

based on a two-fluid model of two-phase flow, with constitutive equations to specify the interfacial 

transport terms. Although some of them have multi-dimensional modeling capability, they are 

predominantly used in a one-dimensional mode. A brief history of these codes is presented below, with 

some relevant information: 

RELAP5. The version examined of this code was RELAP5/MOD3, version 3.2, available since 1995, 

RELAP5/MOD3 Code Manual.16,17 This code was developed at the Idaho National Engineering and 

Environmental Laboratories (INEEL) under sponsorship of the U.S. Nuclear Regulatory Commission 

(USNRC). It is used for a variety of reactor accident analyses, including LOCA analyses, for a variety of 

types of reactors. It is also used in a variety of general thermal-hydraulic analyses in nuclear and nonnuclear systems. It is non-proprietary, and is publicly available, for a transmittal fee, from the USNRC. 

An active user group, including U.S. and international organizations, meets once a year. Information on 

user problems, error correction, etc. is transmitted to user group members once every three months. 

RETRAN. The version examined of this code was RETRAN-03, RETRAN-03 (1992).18 This code was 

developed by Computer Simulations and Analysis, Inc., under sponsorship of the Electric Power 

Research Institute (EPRI). It is used primarily for analyses of reactor systems, with focus on the primary 

cooling system, and usually for non-LOCA scenarios. It is proprietary, and can be obtained from EPRI, 
732 Fluid Dispensing and Dispersion 

with license fees and user group membership fees. The user group, including U.S. and international 

organizations, is active and meets regularly. 

TRAC-P. The examined version of this code was TRAC-PF1/MOD2, TRAC-PF1/MOD2 Code (1992).19 

It was developed by the Los Alamos National Laboratory (LANL) under USNRC sponsorship. It is used 

primarily for LOCA analysis of pressurized water reactors. It is non-proprietary and can be obtained, for 

a transmittal fee, from the USNRC. There are a relatively small number of users and no regular user 

group meetings. 

TRAC-B. The version examined of this code was TRAC-BF1/MOD1, TRAC-BF1/MOD1 Code (1992)20

and TRAC-BF1/MOD1 Models (1992).21 It was developed by INEEL under USNRC sponsorship. It is 

used for accident analyses of boiling water reactors. It is non-proprietary and can be obtained from the 

USNRC for a transmittal fee. The user group is active and meets regularly. 

GOTHIC. The version examined of this code was GOTHIC version 5.0, GOTHIC Containment Analysis 

Package Version 5.0 (1995).22 It was developed by Numerical Applications, Inc., under EPRI 

sponsorship. It is used primarily for analysis of reactor containments. It was developed from the 

COBRA series of codes originally developed at the Pacific Northwest Laboratory under USNRC 

sponsorship. The original COBRA series of codes are non-proprietary, but were not maintained by the 

USNRC after the mid-1980's, and are now difficult to obtain. The GOTHIC code is proprietary and can 

be obtained from EPRI for license fees and user membership fees. The user group is active and meets 

regularly. 

Code Selected 

The documentation for each of the candidate codes was reviewed. It was concluded that all the codes 

listed above have many of the required and desirable features, but none have all of them. The RELAP5 

code (MOD3, version 3.2) had more of the required and desirable features than the other codes. In 

addition, the code had been adapted previously for operation with a fluid other than water, and the code 

architecture to accomplish this was available in the latest version of the code. This was especially helpful 

for insertion of new property packages for suppressant fluids. In addition, significant operating and code 

development experience with RELAP5 had been accumulated, thus providing confidence that the 

program objectives could be met successfully with this code. Based on these characteristics, 

RELAP5/MOD3, version 3.2 was selected as the base code platform for the present development. 

8.3.4 Code Development Work 

Scope of Program 

The FSP computer code, which was derived by modifying the RELAP5/MOD3.2 computer code, is 

referred to in this section as the base code or, sometimes, as RELAP5. A detailed description of the code, 

particularly the numerical solution method, is not given here because the base code has been documented 

extensively.16,17 Most of the RELAP5 documentation applies to the FSP code. Users interested in the 

details of the solution method should refer to that documentation. 

The main modifications to the base code in developing the FSP code were: 
Fluid Transport Through Piping 733

1. Fluid Properties: The base code was based on water-steam systems. This was supplemented 

in the FSP code by using the REFPROP fluid properties package.12 In this version of FSP, 

four fluids have been incorporated, halon 1301, CO2, HFC-227ea, and HFC-125. Any of 

these alternate fluids can be selected by the user. Water properties, which were the default 

option in the base code, have not been removed, and hence water is also one of the fluid 

options in FSP. 

2. Constitutive Relationships: The code requires specification of constitutive relationships, such 

as for the calculation of wall drag and interphase drag, to provide closure for the basic twophase flow conservation equations used by the two-fluid model. In the base code, several of 

these relationships were based on experimental data from water-based systems and were 

uniquely applicable to these systems. These relationships were modified in FSP to be fluidindependent. The specific areas modified were the interphase drag models in vertical flow, 

and wall heat transfer models for critical heat flux and transition boiling. 

3. Release of Dissolved Gas: The base code contained transport equations for non-condensable 

gas in the gas phase and also for a solute (boron) in the liquid phase. In FSP, these transport 

equations were modified. The noncondensable gas transport equation was modified to 

include a source term to account for release of dissolved gas. The boron transport equation 

was altered to reflect transport of dissolved gas as the solute instead of boron. A sink term 

was added to this equation for conserving the total amount of noncondensable gas in the 

system. This approach allowed modeling the release of gas anywhere in the system based on 

local conditions. New constitutive relations were added to represent the gas release rate. 

This requires specification of two additional parameters, a critical bubble radius for initiating 

the gas release, and a rate constant. These parameters have been implemented in FSP as user 

input variables. 

The above major modifications were made to the base code to develop the FSP code. There were some 

additional minor modifications, primarily for making the code usable on PC-based computer platforms. 

This version of FSP runs on a WINDOWS 95/98 operating system. Installation and detailed code 

implementation instructions can be found in Tuzla et al.7

8.3.5 Code Theory 

The base code, RELAP5, was originally written in Standard FORTRAN-77 to run on the UNIX 

Operating System, but had been adapted to other operating environments. The version of RELAP5 

chosen for further development is generally considered to be machine-independent and portable to a 

variety of commonly used operating systems. 

To run this program, the user generates an input file. This input file is essentially the description of the 

problem to be executed. It contains the geometrical description of the system under analysis, the 

necessary boundary and initial conditions, and other constraints imposed by the user, such as partition of 

the system into control volumes (nodalization), selection of particular code options and control of the time 

step used in the numerical solution. 

During execution, FSP generates two files, an output file that can be read by the user, and a restart file 

written in binary format. The output file provides information at time intervals requested by the user in 
734 Fluid Dispensing and Dispersion 

the input file. The restart file contains all the information the code needs such that the user can restart the 

code to run for a longer time period, with or without additional changes to the problem description, and is

also used for generating graphical output. 

The RELAP5 code also contains many user-convenient features and special models, which were

developed primarily for nuclear plant analyses, such as the definition of specific components in nuclear 

systems, and code models to capture the transient behavior of nuclear fuel rods. Some of these are useful 

for the intended application to fire suppressant fluids and fluid systems, and some are not. In the

development of the FSP code, most of the existing features of RELAP5 were retained, although not 

necessarily useful in modeling fire suppressant delivery systems. 

The description of the code presented here is a brief summary, intended to provide basic information for

the user. The base code has been documented in great detail,16,17 and the user is referred to that

documentation for additional information, particularly the numerical solution method. 

Governing Equations 

The thermal-hydraulic model solves eight field equations for eight primary variables as a function of time 

(t) and distance (x). The eight primary dependent variables are pressure (P), phasic specific internal 

energies (Ug, Uf), vapor volume fraction or void fraction (αg), phasic velocities (vg, vf), noncondensable

quality (Xn), and solute density (ρb). Note that the noncondensable quality is defined as the mass fraction 

of noncondensables in the gas phase, the remaining fraction being the mass fraction of fluid in the gas 

phase. Of these eight variables, six are state variables (P, Ug, Uf, αg, Xn, ρb) and two are velocities (vg, vf). 

The corresponding eight field equations are the conservation equations for mass, momentum and energy

for each phase, and the conservation of mass for the noncondensables in the gas and liquid phases. The

equations are described in detail in RELAP5-1, 1995. The simple forms of these equations are shown 

below, as one-dimensional area-averaged equations, on a per unit volume basis. 

Conservation of Mass: 

Gas Phase: 

g g g g g A g N v

t A x

α ρ = Γ + Γ

∂

∂

α ρ +

∂

∂ ( ) 1 ( ) (8−1)

Liquid Phase: 

f f f f f A f v

t A x = Γ∂

∂

+

∂

∂ ( ) 1 (α ρ ) α ρ (8−2)

The terms on the right hand side of Equation 8–1 are the interfacial vapor generation per unit volume, and

the noncondensable gas released from solution per unit volume. The terms on the right hand side of 

Equation 8−2 are the corresponding terms for the liquid phase. For continuity across the interface, Γg + Γf

= 0. The source term for noncondensable gas, ΓN, which is the rate of dissolved gas release per unit 

volume, is treated similar to an external source term. Thus, there is no corresponding term in the liquid 

phase mass conservation equation. Essentially, this assumes that the liquid density is not affected by the

presence of dissolved gas. 
Fluid Transport Through Piping 735

Conservation of Momentum: 

Gas Phase: 

⎥

⎦

⎤ ⎢

⎣

⎡

∂

∂ − ∂∂

+

∂

∂ − − α α ρ

+ Γ − − Γ − α ρ −

+ α ρ − α ρ ∂

∂ = −α

∂

∂

+ α ρ ∂

∂

α ρ

x

v

v

x

v

v

t

v v

C A

A v v Av A FIG v v

B A A FWG v

x

P A

x

v

A

t

v

A

f

g

g

f

g f

g f m

g gI g N g g g g f

g g g x g g g

g

g g

g

g g

( )

( ) ( ) ( )

( ) ( ) 2

1 2

(8−3)

Liquid Phase: 

⎥

⎦

⎤ ⎢

⎣

⎡

∂

∂ − ∂

∂

+

∂

∂ − −

+ Γ − − −

+ − ∂

∂ = − ∂

∂

+

∂

∂

x

v

v

x

v

v

t

v v

C A

A v v A FIF v v

B A A FWF v

x

P A

x

v

A

t

v

A

g

f

f

g

f g

f g m

f fI f f f f g

f f f x f f f

f

f f

f

f f

( )

( ) ( ) ( )

( ) ( ) 2

1 2

α α ρ

α ρ

α ρ α ρ α α ρ α ρ

(8−4)

On the right hand side of Equation 8−3, the second term is the body force and the subsequent terms are 

the wall friction, momentum transfer due to mass transfer (from vapor generation as well as dissolved gas 

release), interfacial frictional drag and force due to virtual mass. 

Conservation of Thermal Energy: 

Gas Phase: 

wg ig g g N N gf g

g g

g

g g g g g g g

Q Q h h Q DISS

v A

A x

P

t

U v A P

A x

U

t

+ + Γ + Γ − +

∂

∂ − ∂

∂ = − ∂

∂

+

∂

∂ ( ) ( ) 1 ( ) α

α

α ρ α ρ (8−5)

Liquid Phase: 

wf if f f gf f

f f

f

f f f f f f f

Q Q h Q DISS

v A

A x

P

t

U v A P

A x

U

t

+ + Γ + +

∂

∂ − ∂

∂ = − ∂

∂

+

∂

∂ ( ) ( ) 1 ( ) α

α

α ρ α ρ (8−6)

On the right hand side of Equation 8−5, the third to last terms are the wall heat transfer, interfacial heat 

transfer, energy transfer due to mass transfer (vapor generation as well as release of dissolved gas), 

sensible heat due to presence of noncondensables, and dissipation. 

Conservation of Mass for Noncondensables in Gas Phase: 

g g n g N

g g n X v A

t A x

X = Γ

∂

∂

+

∂

∂

( ) 1

α ρ

α ρ (8−7)
736 Fluid Dispensing and Dispersion 

where 

Xn = mass fraction of noncondensable gas in the gaseous phase 

ΓN = noncondensable gas generation rate 

This equation conserves mass of noncondensables in the gas phase, and allows transport/distribution of 

the noncondensables along with the gas phase. It is assumed that the noncondensables are transported at

the same velocity as the fluid in the gas phase, that they are in thermal equilibrium with the vapor, and 

that the properties of the gas phase are mixture properties of the vapor/noncondensable mixture. The 

sensible heat transfer terms due to the presence of noncondensables in the energy equations represent heat

transfer at the noncondensable gas-liquid interface. This is necessary because the interfacial terms use 

saturation temperature based on the local vapor partial pressure. 

Conservation of Mass for Noncondensables in Liquid Phase (Dissolved Gas):

s f s

s v A

t A x = Γ∂

∂

+

∂

∂ ( ) 1

ρ ρ (8−8)

where 

ρs = density of the dissolved nitrogen (solute), i.e., mass of dissolved nitrogen per unit volume 

Γs = negative of mass rate of nitrogen released per unit volume, or solute generation rate 

This equation provides the means to model the release of dissolved gas at any location based on local 

conditions. The gas release model itself is described in a subsequent section, along with the assumptions 

used in its implementation in the code. 

In the base code, it is assumed that at the gas-liquid interface, there is no storage of mass, momentum or

energy. In FSP, the dissolved gas release term is modeled similar to that for an external source. It is

assumed separately that Γg + Γf = 0 (similar to the base code), and that ΓN + Γs = 0. Summing Equations 

8−3 and 8−4 provides a relationship between the interfacial drag terms FIG and FIF. Summing 

Equations 8−5 and 8−6 provides a relationship between the interfacial mass transfer and interfacial heat

transfer. These are essentially the interface jump conditions needed for closure of the conservation

equations. Note that in FSP, because of the way in which the dissolved gas release term has been treated, 

the conservation of mass, momentum and energy at the gas-liquid interface is only approximately

satisfied. This is an inherent assumption in the code. The results of executing the code for typical FSP 

applications have not shown significant effects due to this approximation. If new applications show 

significant effects, this assumption would have to be re-visited. 

To complete the equation set, several terms on the right hand side of the conservation equations need to

be specified, such as FWG, FIG, Qwg, and Qig. These are the constitutive relations, described in a 

subsequent section. Typically, these are based on mechanistic models and empirical correlations, and are

written in terms of velocities, thermodynamic and transport properties, and the temperatures of the liquid 

and gas phases. Thus, additional relationships have to be defined to relate these to the primary dependent 

variables of the code. 
Fluid Transport Through Piping 737

Numerical Solution 

To solve the above set of equations, the differential conservation equations are cast into a numerically

convenient set of finite difference equations, using a staggered spatial mesh arrangement. In this method, 

mass and energy are conserved over a control volume while momentum is conserved over a cell bounded 

by the mass and energy cell centers. A semi-implicit method is used for time advancement, where the 

implicit terms are formulated to be linear in the dependent variables at the new time. Essentially, this

requires specification of the partial derivatives of fluid density with respect to the primary dependent 

variables. Most of the source terms on the right hand side of the equations are also treated semiimplicitly. The noncondensable dissolved gas release term is treated explicitly.

Figure 8-2 shows the staggered mesh concept used in the numerical solution. In the method, scalar

variables (pressure, internal energies and void fraction) are defined at the cell centers, at K, L, and so on.

Vector quantities (velocities) are defined at the cell boundaries, at the junctions connecting the cells, at j, 

j + 1, and so on. In this method, to define the flux terms at the boundaries of the mass and energy

conservation cells, the void fraction and fluid properties are “denoted” from the upstream cells. Similarly,

to estimate friction losses needed in the momentum conservation, “volume velocities” are estimated at

cell centers using an averaging procedure of the velocities at the junctions connecting to each cell. The

documentation of the base code (RELAP5) provides a detailed description of the method.16,17

 Here, it is 

noted that the user can access “junction properties” as well as “volume properties” in developing the input 

model and examining the output of the code. 

The governing equations, together with the interface jump conditions, constitutive relations, 

thermodynamic and transport properties, and property derivatives, as a function of the primary dependent

variables, form a closed set of equation. The code solves this set for the primary dependent variables as a

function of time and spatial location. Details of derivation of the finite difference equations and the

numerical solution method are described in the base code documentation. 16,17

Vector Node,

Mass and Energy

Cell 

j-1 j 

Scalar Node,

Momentum 

Cell

K L 

CL

Flow

Figure 8-2. Staggered Mesh Numerical Method. 
738 Fluid Dispensing and Dispersion 

State Relationships a

ry dependent state variables: 

α: gas phase volume fraction 

: gas phase specific internal energy 

U : liquid phase specific internal energy 

ve five state variables. In addition, several 

state derivatives are needed for the numerical scheme. Detailed descriptions of fluid property estimation 

s include models for defining two-phase flow regimes and flow-regime-related 

 and shear, the coefficient of virtual mass, wall friction, wall heat transfer, and 

ented into the code. In addition, wall heat 

g f N wg wf ig if

gf g f general, these relationships are dependent on the thermodynamic state, void 

maps will not be encountered by the user and are not discussed here. The 

ons and mechanistic models to describe flow regime transitions. 

nd Fluid Properties 

As discussed previously, the code uses five prima

P: total pressure 

Ug

f

Xn: mass fraction of noncondensable gas in the gas phase 

All thermodynamic variables are expressed in terms of the abo

and calculations of thermodynamic variables for the code can be found in Tuzla et al.7

Constitutive Models 

The constitutive relation

models for interphase drag

interphase heat and mass transfer. Heat transfer regimes are defined and used for wall heat transfer. For 

the virtual mass, a formula based on the void fraction is used. 

Note that while the FSP code contains models for wall heat transfer, these models have not been exercised 

or assessed with the various new fluids that have been implem

transfer is not expected to play a significant role in the analysis of typical suppressant delivery systems 

because of the short time period of the expected transient. If a user encounters a special application of 

FSP where wall heat transfer may need to be included in the model, the base code documentation contains 

the needed information.16,17

The constitutive relations needed are for the terms: Γ , Γ , Γ , FWG, FWF, FIG, FIF, C, Q , Q , Q , Q , 

Q , DISS , and DISS . In

fraction, fluid properties and velocities. As shown in Figure 8-2, the thermodynamic state, void fraction 

and fluid properties are defined at volume centers, while the velocities are defined at the junctions. Fluid 

properties and the void fraction are “donored” to junctions, and volume velocities are estimated by 

momentum flux weighting of the velocities at the junctions that connect to each volume. It is convenient 

to use flow regimes to characterize the two-phase flow. This allows specifying a more mechanistic form 

to the various constitutive relations, which is desirable since the code is structured to handle various 

different fluids. 

Four flow regime maps are included in the base code, but only two of these are relevant for applications 

of FSP. The other flow regime 

flow regime maps in FSP address flow regimes and transitions between flow regimes for horizontal flow 

and vertical flow. 

The flow regime maps are based on the work of Taitel et al.23 and Mishima and Ishii24, who have 

developed flow regime classificati
Fluid Transport Through Piping 739

However, some of their transition criteria are quite complex, and further simplification has been carried 

out in order to efficiently apply these criteria in the code. When wall heat transfer is not modeled, the 

flow regimes and the transition criteria are dependent on hydrodynamic conditions only. When wall heat 

transfer is modeled, there is a possibility that the wall may encounter the condition of critical heat flux 

(CHF). In the post-CHF condition, the wall will mostly not be wetted by the liquid. This alters the flow 

regime. To capture this effect, the code recognizes the effect of wall heat transfer explicitly, and if postCHF conditions are indicated, a separate flow regime map is used to characterize the two-phase flow 

patterns. Again, note that the post-CHF regimes would be invoked only if the user models wall heat 

transfer, and the local fluid and wall conditions indicate post-CHF conditions. As discussed above, wall 

heat transfer is not expected to be required in most applications of the FSP code. Hence, these flow 

regimes are not described here, and the base code documentation contains detailed description, if 

needed.16,17

The vertical flow regime map (for both up and down flow) is for volumes whose elevation angle φ is such 

that 45° < |φ| < 90°. This map is modeled as nine regimes − four for pre-CHF heat transfer, four for 

hat 0° < ⏐φ⏐ < 45°. This 

map does not distinguish between pre- and post-CHF regimes. Otherwise it is similar to the vertical flow 

de, RELAP5/MOD3.2, it was found that most of the constitutive relations were 

structured to be reasonable for the fluids included in FSP. The only areas where correlations specific to 

all friction terms are FWG and FWF in the phasic momentum equations. Note that the 

wall friction force terms include only wall shear effects. Losses due to abrupt area change are calculated 

e an overall two-phase frictional pressure drop. This was done using a 

standard two-phase multiplier method (as shown in Wallis25). The two-phase friction was then partitioned 

post-CHF heat transfer, and one for vertical stratification. As noted previously, the post-CHF regimes 

will not be encountered if wall heat transfer is not modeled by the user. The pre-CHF regimes are the 

same flow regimes as would exist if there was no wall heat transfer. For pre-CHF heat transfer, the 

regimes modeled are the bubbly, slug, annular mist, and mist-pre-CHF regimes. 

The horizontal flow regime map is for volumes whose elevation angle φ is such t

regime map. The horizontal flow regime map consists of horizontally stratified, bubbly, slug, annular and 

mist-pre-CHF regimes. 

In reviewing the base co

water were used were in the computation of interphase drag in vertical flow, and in wall heat transfer. 

Thus only these calculations were modified. In the description presented below, the emphasis is on 

providing the user with basic information on what is contained in FSP. Details of the various models can 

be found in the base code documentation.16,17 Additional information is provided below in the specific 

areas where the base code was modified. The dissolved gas release model was developed especially for 

FSP, and so it is described in more detail than the other models. 

Wall Friction 

The relevant w

using mechanistic form loss models. Other losses due to elbows or complicated flow passage geometry 

are modeled using energy loss coefficients supplied by the user in the input for junction information.7

These terms are also directly used in computing the energy dissipation terms, DISSg and DISSf in the 

phasic thermal energy equations. 

The approach was to first calculat

between the phases (Chisolm26) to get the phasic wall friction components. A further adjustment was 

made to incorporate flow regime effects, using a wetted wall fraction. This provides a more physical 
740 Fluid Dispensing and Dispersion 

representation for certain regimes where it is clear that one phase would be more influenced by wall 

friction than the other, as in annular flow, where the wall is fully wetted by the liquid phase. 

The model uses the hydraulic diameter and surface roughness data provided by the user for each volume. 

There is an option for the user to turn off wall friction altogether, but this is not recommended unless as a 

n (or drag) per unit volume in the phasic momentum equations is expressed in terms

of a phasic interphase friction coefficient as: 

sensitivity study to debug results from a specific analysis. 

Interphase Friction 

The interphase frictio

( ) Fig g g g f = α ρ FIG v − v (8−9)

and 

( ) if f f g f F = α ρ FIF v − v (8−10)

The magnitude of the interphase drag force per unit volume on the liquid is assumed to be equal to that on 

the gas phase. This provides a relationship between FIG and FIF, 

αg ρg FIG = α f ρ f FIF (8−11)

The interphase drag force per unit volume represents the interphase momentum transfer rate and is due to 

the difference between the phasic velocities. Thus, analogous to the transfer of heat or mass, it can be 

expressed as:

( ) i gf i g f F = F v − v , (8−12)

where Fi is a momentum conductance term, and can be expressed as: 

Fi = Agf Bgf (8−13)

where Agf is the interfacial area per unit volume, and Bgf is a momentum transfer coefficient. 

rms of fluid 

properties, flow geometry, phasic velocities and the void fraction. These are then related back to the

the above calculations, except for vertical

flow in the pre-CHF regimes. In this case, the base code uses a correlation developed empirically from 

parameter, b, that allows the user to select an optional interphase drag 

modeling approach for rod bundles. In FSP, in addition to replacing the interphase drag models for 

The code uses the flow regime characterization to derive relationships for Agf and Bgf in te

terms FIG and FIF needed in the phasic momentum equations. 

The base code, RELAP5/MOD3.2, uses mechanistic models for

water data. In FSP, to make this independent of the fluid type, the empirical correlation (called the Drift

Flux correlation or the EPRI correlation) has been replaced with the mechanistic models. The models are

similar to what exists in the base code for the various flow regimes and therefore are not further described 

here. It is noted that for the calculation of interphase drag in vertical flow in FSP, the vertically stratified

regime is not explicitly used. Vertical stratification is recognized primarily for the calculation of

interphase heat and mass transfer. 

In building the input file, there is a
Fluid Transport Through Piping 741

vertical flow, this option has been essentially de-activated. Thus choosing a value of 0 or 1 for this 

parameter will not have an effect. It is recommended that the user choose the default value, which is zero. 

Interphase Heat and Mass Transfer 

The interphase heat and mass transfer rates are related by the assumption that energy is not stored at the

interface. It should be noted that the code separately recognizes interphase mass transfer in the bulk fluid 

and at an interface near the wall. This allows the code to mechanistically treat some special cases, such as

subcooled boiling. In this case, there is a radial temperature gradient within the liquid, and boiling occurs

near the wall, while there is condensation in the bulk fluid. Thus, the general treatment is: 

Γg = Γig + Γw (8−14)

where Γw is computed by the wall heat transfer models. When wall heat transfer is not modeled, this term

is zero. Γig is computed from the heat transfer at the bulk interface. The interface is assumed to be at the 

saturation temperature. The heat transfer at the bulk interface is then: 

( ) g

s Qig = Hig T − T (8−15)

( )f

s Qif = Hif T − T (8−16)

Qig + Qif + Γig (hg − hf ) = 0

here hg and hf can be at saturation or at the value corresponding to the local pressure and temperature,

epending on whether the process is one of boiling or condensation

re conveniently modeled as products 

of the interphase area per unit volume and the interphase heat transfer coefficient. These are in turn

x, q′′, is modeled as a sum of heat fluxes to the vapor and liquid phases: 

(8−17)

w

d .

The terms Hig and Hif are the interphase heat conductance terms and a

determined as a function of the flow regime, and modeled as a function of fluid properties, flow

geometry, velocities and the void fraction. 

Wall Heat Transfer 

The total wall heat flu

( ) ( ) q = hg Tw − Tref , g + hf Tw − Tref , f ′′ (8−18)

where hg and hf are heat transfer coefficients to the gas and liquid phases respectively (per unit wall 

rface area), and Tref,g and Tref,f are gas and liquid reference temperatures. The reference temp

t is used, based on the heat flux, wall temperature and saturation 

temperature, to decide the mode of heat transfer (such as convection to single phase liquid, bulk nucleate

su eratures

can be the local gas or liquid temperature or the saturation temperature, depending on the correlation used 

for the heat transfer coefficient. 

A heat transfer surface concep

boiling, condensation). Correlations are used for the heat transfer coefficients in the various heat transfer 

regimes to compute the heat flux. The total heat flux is ensured to be continuous over the heat transferwall temperature surface, to avoid numerical difficulties as the heat transfer regimes go through

transitions. 
742 Fluid Dispensing and Dispersion 

Also calculated is the portion of the wall heat flux ( w Qig and w Qif ) that contributes directly to mass transfer.

Then the interphase mass transfer due to wall heat transfer is calculated from:

+ + Γw ( g − f ) = 0 w w Q Q h ig if (8−19)

where, as before, h and h can be either at saturation conditions or at the loca

h

g f l pressure and temperature,

epending on whether the process is boiling or condensation. 

bly fluid-independent. In two areas, the

correlations are more empirical and also based solely on water data. Hence, these have been modified in 

d

The base code, RELAP5/MOD3.2 contains generic models for the heat transfer coefficients in most of the

heat transfer regimes that can be considered to be reasona

the FSP code. One area is the critical heat flux (CHF). The base code uses a table look-up procedure for 

calculating CHF, using data obtained for water at a variety of conditions. This was replaced in FSP by a

simpler model, based on a modification to the Zuber correlation (Zuber et al.27). 

( ) [ ( ) ] 2 1/ 4 1.31 0.96 / qCHF = − αg ρg hfg σg ρf − ρg ρg (8−20)

Zuber’s correlation has been shown to match CHF data for a variety of fluids under pool boiling

nditions. The modification to Zuber’s correlation is the term (0.96 - αg) and has shown to match flo

ata with water and Freon. Note that this condition of CHF is normally one that is associated with 

tial decay form to capture the decrease of wetted area 

fraction as the wall temperature increases. The decay constant was derived as a function of flow rate and 

The last term in the phasic momentum equations is the dynamic drag term due to virtual mass effects, also 

per unit volume. In the base code, in the numerical solution procedure, the

spatial dependence of the velocities in this term was neglected. Thus the term only includes the timeand, 

C = 0.5 (3 - 2αg) / αg for 0.5 ≤ αg ≤ 1 

co

d

w

hydrodynamic dryout of a heated surface. This is the type of CHF one may expect when wall heat 

transfer is modeled with only passive heat structures, such as typical pipe walls in fire-suppressant

delivery systems. In implementing the above model in FSP, a lower limit of 1000 W/m2

 was imposed to 

prevent negative values, at high void fractions. 

The other area modified is in the correlation for wetted area fraction used for computing post-CHF heat 

transfer. This correlation utilizes an exponen

void fraction, from water data. In FSP, the decay constant has been set to a fixed value. This is

considered reasonable because this heat transfer regime is rarely encountered, and will provide continuity

for the heat transfer surface if encountered. 

Coefficient of Virtual Mass 

called the inertial drag force

dependent portion. This was a compromise, because the spatial terms were dependent on the nodalization 

selected by the user to represent a particular system, and there was some user experience that suggested 

that this led to numerical errors. The main intent of this term is to capture sudden accelerating flows, and

the time-dependent term provides that capability. The coefficient, C, in this term is called the coefficient

of virtual mass. It is given as: 

C = 0.5 (1 + 2αg) / (1 - αg) for 0 ≤ αg ≤ 0.5 
Fluid Transport Through Piping 743

Release of Dissolved Gas 

The liquid agen tored under pressure of a noncondensable gas (N2). It is 

assumed that the agent has been stored for a long enough period for the liquid to be saturated with N2

At equilibrium, the concentration of dissolved N2 in the liquid medium is 

proportional to the partial pressure of N in the gaseous space above the liquid. This is Henry’s law: 

N 2 pe. 

s the system is depressurized, nitrogen will come out of the solution since the partial pressure de

due to surface tension. Considering a micro-bubble of dissolved gas with radius r , the difference

t in the storage vessel is s

(equilibrium condition).

2

N H PN x = * (8−21)

where *

Nx is the equilibrium concentration (mole fraction of solute in solution), H is Henry’s constant and

P is the partial pressure of N above the liquid. H is usually a function of temperature and the liquid ty

A creases.

According to Henry’s law, the corresponding concentration of nitrogen in the solution must also decrease. 

Hence the excess must be released. In a fast depressurization transient, the excess can still be in solution

c

between the pressure inside and outside the bubble is given by

c

NUC

r

P σ ∆ = 2

(8−22)

where σ is the surface tension. As the pressure outside decreases, the pressure difference builds up until a

point where surface tension can no longer hold the bubble together, and the excess N2 is then released.

his initiation mechanism is similar to nucleate boiling, in which the liquid is superheated before boiling 

can occur. The radius of the micro-bubble can be empirically determined by observing the point at which

T

N2 release occurs. In this model, this radius is assumed known (user input). The release pressure is then

given by

c

rel i NUC i r

P P P P σ = − ∆ = − 2

(8−23)

where Pi is the initial system pressure. 

he above determines the initiation of release. The rate of release i mined as follows. Henr

determines the equilibrium concentration for given conditions. As the system is depressurized, the 

s. The corresponding equilibrium concentration will be less. The 

T s deter y’s law

corresponding partial pressure decrease

solution is therefore at a state of non-equilibrium. The release is a means to achieve a new equilibrium. 

Thus, the release rate is postulated to be proportional to the difference between the actual concentration 

and the equilibrium concentration (dictated by Henry’s law) as follows: 

( ) *

rel 0 N N Γ = Γ x − x (8−24)

where Γ0 is some release coefficient, xN is the actual concentration, and * x is the equilibrium

concentration as given by Henry’s law. Thus 

N

( ) rel N H PN Γ = Γ0 x −

The release will be zero when the actual concentration approaches the equilibri concentration, as it 

should be. The release model is similar to o

um

ther transfer phenomena, such as heat transfer and mass 

transfer. 

(8−25)
744 Fluid Dispensing and Dispersion 

The model requires that users specify, as input, the parameters c and Γ0, and the initial pressure

value, but the value above the liquid-gas interface. A compromise is made by using the local 

by using a larger release coefficient. Thus, the release rate is numerically implemented

r Pi and

temperature Ti. 

The numerical implementation of the release rate model poses a problem, since the partial pressure is not

the local

total pressure in place of the partial pressure in calculating the equilibrium concentration using Henry’s 

law. This over-predicts the equilibrium concentration, and hence under-predicts the release rate. It may

be compensated

as, for the k

th volume: 

( ) rel k N k H Pk Γ , = Γ0 x , − (8−26)

HPk is the mole fraction of N2 in solution. To convert to mass of N2 per unit mass of solvent, one gets 

( ) k f

k N

H P W

H P W N − = 1

Mass Fraction 2 (8−27)

here WN is the molecular weight of nitrogen (28.0) and Wf w is the molecular weight of the fluid. The

actual concentration is related to the solute density as 

k ⎝ f f ⎠

The solute generation rate is therefore the negative of the release rate: 

s

N k x ⎟

⎟

⎞

⎜

⎜

⎛

α ρ

ρ , = (8−28)

( ) ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

− − ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

α ρ

ρ Γ = −Γ = −Γ

k f

k N

k f f

s

s k N k H P W

H P W

1 , , 0

ilibrium concentration. Otherwise 

the release rate should be zero. Hence 

(8−29)

The above is only valid if the local concentration is greater than the equ

min ( ,0.0) Γs, k = Γs, k (8−30)

Also, the amount of release in one time step should not be more than the total amount dissolved in the 

volume. Thus the maximum release rate is given by 

t

s

rel ,k ,max ∆

ρ Γ = (8−31)

where ∆t is the current time step. Hence the final expression for the solute generation term is 

( ) ⎭

⎬

⎫

⎩

⎨

⎧

∆

ρ Γ = Γ − t

s

s k s k max min ,0.0 , , , (8−32)

he Henry’s constant is estimated from the PROFISSY Code (see Yang et al.2 T ) as follows. Assuming

Henry’s law to be valid, the equilibrium concentration is given by 

N H PN x = (8−33)
Fluid Transport Through Piping 745

In PROFISSY, the concentration of nitrogen in the agent liquid (xN, mole fraction) is calculated given the

system pressure (P), temperature (T), total volume (V), and total agent mass (ma). The partial pressure of

nitrogen can be determined from

PN = P − Pv (8−34)

where Pv is the saturation pressure of the agent fluid at T. Table 8-1 lists the output from PROFISSY, and 

the calculation of H as described above. Three fluid systems are considered: HFC-227ea, HFC-125 and 

halon 1301. As can be seen, the solubility of nitrogen in all three agents is very similar, and Henry’s

nstant can be correlated as a quadratic function of temperature, as shown in Figure 8-3. The an

ROFISSY Results for Henry’s Constants. 

co alytical

form of the correlation is given by

2 H = H0 + C1T + C2 T (8−35)

where H is in mol/Pa, and T is in K and H0 = 2.35 × 10-7, C1 = -1.55 × 10-9, and C2 = 2.96 × 10-12 

Table 8-1. P

HFC-227ea/N2 Halon 1301/N2 HFC-125/N2

T (K) H (mol/Pa) H (mol/Pa) H (mol/Pa) 

190 n/a 4.70E-08 n/a 

200 n/a 4.20E-08 n/a 

210 n/s 3.87E-08 3.65E-08

220 3.77E-08 3.67E-08 3.80E-08

230 3.62E-08 3.59E-08 3.37E-08 

240 3.52E-08 3.30E-08 3.37E-08 

250 3.47E-08 3.45E-08 3.47E-08

260 3.30E-08 3.15E-08 3.41E-08

270 3.34E-08 3.27E-08 3.25E-08

280 3.29E-08 3.28E-08 3.48E-08

290 3.29E-08 3.22E-08 3.40E-08

300 3.36E-08 3.35E-08 3.76E-08

310 3.49E-08 3.74E-08 3.90E-08

320 3.58E-08 3.96E-08 4.45E-08

330 3.79E-08 4.88E-08 5.39E-08

340 4.15E-08 n/a n/a

350 4.59E-08 n/a n/a

360 5.42E-08 n/a n/a

Figure 8-4 shows the calculated bottle pressure as a function of time for various release c

critical radius was specifie 10-9 m. The initial concentration was estimated as 0.02916 kg N2/ kg 

liquid phase. This value i o the reported initial concentration of Test 146 in Elliott et al.10 

t about 0.1 s, as the pressure decreases to a value of about 4 MPa, there is a noticeable change in the rate 

oefficients. The 

d at 7.5 ×

s comparable t

A

of pressure decrease. This is the pressure at which gas begins to be released from the liquid, and

experimental results generally indicate that this would happen at about the same pressure for a given fluid 

type and system configuration. As discussed earlier, this pressure is controlled by the value of the critical 

gas bubble radius, rc, chosen by the user. The lower the value of rc specified, the lower the pressure at 

which gas release would be initiated. 
746 Fluid Dispensing and Dispersion 

Temperature (K)

100 150 200 250 300 350 400

Henry constant (mol/

Pa)

3e-8

4e-8

5e-8

6e-8

7e-8

Figure 8-3. Curve Fit for Henry’s Constant. 

HFC-227ea/N2

Halon 1301/N2

HFC-125/N2

Curve fit

time (s)

P (

Pa)

time (s)

p (Pa P

Pa)

time (s)

p (Pa

Figure 8-4. Effect of Release Coefficient on Calculated Pressure Response. 
Fluid Transport Through Piping 747

The value of Γ0 controls th f release is small, and the 

pressure continues to decrease monotonically below the pressure at which gas release was initiated. As 

e value of Γ0 is increased, there is a noticeable decrease in the depressurization rate at the gas release 

pressure

modeling the gas release f 

release coefficients without numerical difficulty. 

One of these sensitivity cases, corresponding to a Γ0 of 10,000 kg/m3

 s and an initial concentration of 

0.02196 kg N2/kg liquid, was used to further check out the model. Figure 8-5 compares the calculated 

pressure with experimental measurements. Figure 8-6 shows the void fraction responses for the various 

cells used to model the supply bottle. Volume 203-01, not shown in the figure, is at the top of the bottle, 

and Volume 203-10 is at the bottom. The figure shows a relatively smooth emptying of the bottle, with 

the void fractions in the lower cells increasing to 1.0 subsequent to the void fractions in the cells above 

them. The void fraction in the last cell, Volume 203-10, increases to 1.0 after all the other cells, at about 

1.0 s. This represents the time in the calculation when the bottle is emptied. 

This calculation was also used to check out other parameters. The solute concentration profiles showed 

smooth changes, following expected trends. A mass balance was carried out to ensure that the code 

conserved the mass of nitrogen, between the initial amount and the additional amount released from the 

liquid. Essentially, these checks ensured that the gas release model was implemented in the code as 

intended, and the mechanistic gas release model produced the expected trends. There is of course some 

uncertainty in how to specify the correct values for the parameters rc and Γ0. However, as shown in other 

sections of this report, comparisons to experiments with different fluids and system configurations 

indicate reasonably good agreement between code calculations and experimental data, with these 

parameters varying over a relatively narrow range. This has been useful in arriving at a range of 

recommended values for these parameters. Further, from a design perspective, while variation of these 

parameters causes a noticeable variation in the initial pressure history, there is not much variation in the 

time required to empty the supply bottle. Hence it is believed that this gas release model, used with the 

range of recommended values for rc and Γ0, would adequately serve the needs of a design engineer 

evaluating the performance of a suppressant delivery system. 

Special Process Models 

This section describes certain models in the code that simulate special processes. The user can select 

many of these processes via input. A detailed description of these process models can be found in the 

base code documentation.16,17 The information below is a brief summary, to provide some basic 

information and where appropriate, some user guidelines on the use of these models. 

Choked Flow 

Choking is defined as the condition where the mass flow rate becomes independent of the downstream 

conditions. Choking occurs because acoustic signals can no longer propagate upstream as the fluid 

velocity equals or exceeds the propagation velocity. In typical FSP applications, choking can occur at the 

bottle exit, as soon as the discharge begins, and also at the discharge location from the system. The 

choked flow model in FSP is by Trapp and Ransom28 and is used to calculate the mass discharge from the 

e rate of gas release. At low values of Γ0, the rate o

th

 (at about 0.1 s). This is the expected trend. Test runs of the code indicate that this method of

works relatively smoothly, and the code appears to handle a wide range o
748 Fluid Dispensing and Dispersion 

system. The model can also be used to predict the existence of and calculate choked flow at interior 

points in the system. 

The user can select the choking model as a part of the junction control flag information in the input file. 

The user can select this option at all junctions. In fact, the default option will select the choked flow 

model. It is recommended, however, that the user only select this model at the system exit location(s) and 

at the junction representing the exit of the supply vessel. The model should be turned off at all other 

1.0, a two-phase discharge 

coefficient of 0.8 to 0.9, and a single-phase vapor discharge coefficient equal to the two-phase discharge 

5. Comparison of Calculated and Measured Bottle Pressure for Test 146. 

phases. The normal code equations are based on assuming uniform transverse pressure distribution. To 

account for the nonuniform pressure distribution, adjustments are made to the momentum equations to 

internal junctions. This is because the sonic velocity (propagation velocity) in two-phase flow can be a 

strong function of the void fraction, and the choked flow model imposes an external criterion on the 

code’s normal numerical solution method. This can lead to difficulties in code execution and a drastic 

reduction in the computational time step. 

Also note that the input for junctions allows the use of discharge coefficients for subcooled liquid, 

saturated fluid and single-phase vapor. Current assessment of the code against experiments suggests that 

best results are obtained by using a subcooled discharge coefficient of 

coefficient. 

Figure 8-

Horizontal Stratification and Entrainment 

Flow at low velocity in a horizontal pipe can be stratified due to buoyancy forces. The horizontal flow 

regime map in the code contains a mechanistic model to predict when stratification occurs. When the 

flow is stratified, the area average pressures are affected by the nonuniform transverse distributions of the 

time (s)

p (Pa)

Time (s)
Fluid Transport Through Piping 749

consider area average pressures for the vapor and liquid phases, and the interfacial pressure between 

them. This model is always active in the code, but becomes significant only when the code’s 

stratification criterion is met. The code then calculates a liquid level in the channel (circular pipe 

the

upstream h

d fraction in 

 the 

void 

lculated to

The ill

automatically be invoked as needed. 

Abrupt Area Change 

geometry is assumed) and uses this information to estimate the hydrostatic pressure in the transverse

direction. 

tiTimmee((ss))

Figure 8-6. Void Fraction Responses in Lower Portion of Bottle. 

Also, when the flow is stratified, the void fraction flowing in a junction may be different than 

 volume void fraction. A typical example would be when there is an area contraction. Wit

stratified conditions in the upstream volume, if the level is below the pipe centerline, the voi

the junction would be significantly higher than the upstream volume. If the level is above the pipe 

centerline, the junction void fraction would be lower than the upstream volume. In addition to the 

formation of a level and its effect, the vapor can entrain liquid through the junction, and similarly

liquid can pull through some gas. The code considers these possibilities, and adjusts the junction 

fraction to be different than the upstream volume void fraction when the upstream volume is ca

be stratified. 

user does not actively engage these models. It is part of the code’s internal structure and w

A general piping network system can contain sudden area changes and orifices. The code contains builtin models for the user to access in simulating these geometries. The basic hydrodynamic model in the

code is formulated for slowly varying flow area. Hence, special models are needed when the flow area

undergoes an abrupt change, such as at an orifice. 
750 Fluid Dispensing and Dispersion 

Basically, the user can select the abrupt area change option at any junction in the model, as a part of the 

junction control flag input information. The code will calculate the energy loss coefficients associated

with the abrupt area change internally. In a case where the flow is going through a sudden contraction, 

the code will also internally compute the losses associated with the formation of a vena contracta. Along 

with selecting the abrupt area change option, if the user also enters form loss coefficients, these will be 

added to the internally calculated form losses. 

User-Spe

d

geometries, a om

standard handboo at known flow 

rates, that can

 would be a

function 

The code’s n

are applications ysical 

simu

typical place to use the crossflow junction would be in modeling a standard 90o

 tee. The crossflow

nction would be used to model the connection to the branch line, as shown in Figure 8-7. In this case,

the momentum am. Thus the

tains a variety of generic components that are used to build system models. These include 

ts and features.

cified Form Losses 

In the junction control flag information card, the user can specify a junction to be a smooth or abrupt area

change junction. The user can also specify form loss coefficients at the junction. For standar

nd configurations such as elbows and tees, these form loss coefficients can be obtained fr

ks. If the user has frictional pressure drop data for a particular system

 be used to back out form loss coefficients. 

The user can also enter flow dependent form loss coefficients. Typically, the form losses

of the Reynolds Number. The code input allows a standard form and the user has to enter the 

desired constants for the Reynolds Number dependence. 

Cross Flow Junction 

umerical method is generally formulated using one-dimensional elements. However, there 

where an approximate treatment of transverse flow can provide an improved ph

lation. The crossflow junction component provides this feature. 

A

ju

flux in the side branch is assumed to be perpendicular to the main flow stre

mainstream momentum flux does not contribute to the crossflow momentum formulation. Essentially, in 

the crossflow junction formulation, there is no transport of axial direction momentum due to the flow in 

the transverse direction. 

The user selects the crossflow junction option by specifying the appropriate connection code when 

describing the ‘From’ and ‘To’ volumes for a junction. 

Component Models and Systems 

The code con

components such as Single Volume, Time-Dependent Volume, Single Junction, Pipe, Valve, etc. Most of

these are self-explanatory. This section provides some additional information on building a system model

and the use of some of the componen

Branch 

There are several ways to simulate branching flows. Several single junctions can be connected to the exit 

of a single volume to simulate flow splits. A BRANCH component is also provided in the code. 

Essentially, this functions no differently than a single volume to which more than two junctions are 
Fluid Transport Through Piping 751

connected. Primarily, it is a user-convenience, which allows all the junction information to be entered 

along with the volume information in one component instead of using several separate components. A 

crossflow junction can be used to connect a branch component to another component. Two typical uses 

are in modeling branching flows in a one-dimensional branch, and a tee branch. 

A one-dimensional branch is one where more than two normal junctions connect to a volume, and where 

it is assumed that multidimensional effects are small compared to system interaction effects. Typically, 

d flows that occur in headers or plena. Fluid entering a header and then 

splitting into several parallel paths would be modeled as a one-dimensional branch. 

without a crossflow junction, by using a branch 

component with normal junctions, as shown in Figure 8-8. This approach has the advantage that fewer 

roach seems acceptable. 

 flux weighted average of the flows in the junctions 

 it. Also, the volume cross-sectional area is apportioned between the various streams in 

the volumetric flow in these streams. The consequence is that, if one stream has a very high 

this would be used in branche

A tee branch is formed by the arrangement shown in Figure 8-7, where the crossflow junction was used. 

In this case, the Volume V2 may be specified as a branch component, and the crossflow junction 

connecting to it could be defined by the appropriate connection code, described in the input manual in 

Tuzla et al.7

 The tee connection could also be modeled 

volumes are used. The disadvantage is that if the tee is really a standard 90° tee, then it may not be the 

best representation of the physical process. In typical FSP applications, very little difference has been 

observed between the two approaches. Hence, either app

Figure 8-7. 90° Tee Model with Crossflow Junction. 

Note that a volume with more than two junctions connected to it is treated by the code as a branch 

component, even if it has not been defined as such in the input. What this really means is that the volume 

velocity in this volume is determined as a momentum

connecting to

proportion to 

velocity, there would be excess error in conserving momentum (and mechanical energy) around this 

volume. One place where this has an impact is if one of the junctions connecting to the branch is the exit 

junction for the system and it is choked at a high velocity. To avoid this situation, it is recommended that 

the user allow some straight pipe length connected to all the junctions of a branch. It is also 

Volume

V4

Junction J1 Junction J2

Junction J3

Crossflow

Volume

V

Volume

V

Volume

V 1 2 3

Volume

V4

Junction J1 Junction J2

Junction J3

Crossflow

Volume

V

Volume

V

Volume

V 1 2 3
752 Fluid Dispensing and Dispersion 

recommended that when the BRANCH component is used, the junctions of the component use the abrupt 

area change option. 

Volume

V3

Figure 8-8. Tee Model with Normal Junctions.

Valves 

Valves are quasi-ste model or to simulate

control mechanisms d to describe 

them is similar. Ther stantly or those that open

and close gradually. pes are envisioned to be

useful in modeling ty ed here. 

A Trip Valve is one that is fully closing will 

occur in one time st

open or closed position, if 

A Motor Valve has the me. The operation of

this valve is e parameter

ally used with 

this com cient as a function of the 

Typical use of this co ion that connects the

suppressant supply vessel to the piping system. The valve could be opened as fast as desired by the user

ady models that are used to either specify an option in a system

. They are essentially treated as single junctions and the input require

e are two categories of valves, those that open and close in

 The base code contains several types of valves. Only two ty

pical fire suppressant delivery systems, and these are describ

open or fully closed based on a trip setting. The opening or 

ep following the trip signal. The trip signal can be structured to latch the valve in an 

desired. 

ability to control the junction flow area as a function of ti

controlled by two trips, one to open and one to close. A user-specified rat

controls the rate at which the valve area changes. The abrupt area change option is norm

ponent to allow the code to automatically compute the form loss coeffi

valve area. 

mponent in FSP applications would be to describe the junct

to simulate the initiation of the discharge transient. 

Trip Systems

The Trip System consists of the evaluation of logical statements. Each trip statement has a true or false

result, and an associated variable, TIMEOF. This variable is the time in the transient at which the trip 

became true and has a value of –1.0 when the trip is false. This variable can be used to set time delays

based on events during the transient. Within the code structure, the trip system only evaluates the logical

statements (such as, is the transient time greater than 2.0 s?). The decision of what action is needed based 

Junction J1

Junction J2

Volume

V1

Volume

V2

(Branch)

Volume

V3

Junction J2

Junction J1

Volume

V1

Volume

V2

(Branch)
Fluid Transport Through Piping 753

on the trip status resides within other models. In the above example, the trip system would assign a true 

or false value to a particular trip number depending on whether the transient time was less or greater than

2.0 s. If this trip number is invoked by a valve component, the valve models would decide whether to

close or open the valve, at what rate, et , and directions 

are provided in Tuzla et al.

Control Systems 

The control system nd differential equations. 

This allows simu s. Another use is to

define auxiliary files as tables or

plots. 

In ty Hence, control systems are 

primarily used al code variable, 

nd if it is needed for some reason, it can be computed using several control systems (such as the SUM

and MULTIPLIER comp cific volume, 

which are all normal cod ted to know the Froude

at the system exit, for evaluating mixing characteristics in the discharge area. A variety of 

ystems are provided in Tuzla et al.7

AP5/MOD3.2,

the source code was obtained from the Idaho Engineering National Laboratory. This code was adaptable 

PC with a Pentium 233 MHz processor, 64 MB RAM and 3.2 GB

hard drive. The compiler used was the DigitalTM Visual FORTRAN compiler (Standard Edition, Version 

andidate fluids. These data were then used in the

 the product code for simulating possible suppressant delivery systems. Descriptions of 

nsions and design features of the test facility are provided below. 

c. Using the trip system is fairly self-explanatory

7

 provides the capability to evaluate simultaneous algebraic a

lation of control systems typically used in hydrodynamic system

 output quantities, which can then be extracted from the output or restart

pical FSP applications, no complicated trip and control logic is required. 

 to define auxiliary output variables. For example, enthalpy is not a norm

a

onents) to calculate it from the internal energy, pressure and spe

e variables. Another example would be if a user wan

Number

control s

Code Architecture 

The FSP code was developed from the base code RELAP5/MOD3.2, which was written in FORTRAN 77

for a variety of 64-bit and 32-bit computers. In developing FSP from the base code, REL

to other computing environments. The code was configured to work on a PC with WINDOWS 95 

operating system and tested to ensure that the code options would function properly. The hardware 

chosen for installation was a laptop

5.1) for WINDOWS 95 operating system. The coding is modular, using top-down structuring. The 

various models and procedures are isolated in separate subroutines. Detailed description of the top-level

organization of the code, code installation and execution, input file processing, and graphics for output

can be found in Tuzla et al.7

8.3.6 Supporting Laboratory Data 

Experiments were performed to obtain data for several baseline fire suppressants and to establish a 

protocol for obtaining such data for any future c

assessment of

pertinent dime

Experimental Test Facility

The test facility consists of a source vessel for the suppressant fluid, a quick opening discharge valve, a 

holding rack, a piping network, and a collection tank. This arrangement allows the system to be operated
754 Fluid Dispensing and Dispersion 

as a closed loop to recycle the test fluid. A simple schematic is provided in Figure 8-9, showing the 

layout of the facility. The dimensions of this test system adhere as closely as possible to standard sizes 

used in present-day fire suppression systems. 

Figure 8-9. Schematic of Test Facility: Source Vessel, Discharge Piping, and Collection 

Vessel. 

The source vessel, one of the main components of the facility, is shown in Figure 8-10. The source vessel 

has a total internal volume of 3.81 L and was initially charged with liquid to about 60 % of that volume. 

The source vessel was constructed from a 2 m long piece of 5.08 cm nominal diameter stainless steel pipe 

with an internal diameter of 4.93 cm and a wall thickness of 0.55 cm. Using a vessel of large lengthdiameter ratio improves the accuracy of measuring liquid inventory. A pressure difference associated 

sel is used to measure the liquid inventory in the vessel at any 

time during the experimental run. The long length, or height, of the source vessel provides a greater 

d in place. The top plate 

has an identical outer diameter as the flanges, at 16.51 cm, and was tapped to allow for a mixing line inlet 

 plate has a larger diameter of 27.94 cm for the purpose of anchoring the 

vessel to the holding rack while minimizing any vibration or movement during operation. This plate was 

with the static head of the liquid in the ves

range of static head measurements, thus increasing the accuracy of determining the transient liquid 

inventory. This pipe was positioned vertically and capped at both ends by stainless steel pipe flanges 

approximately 2.54 cm thick. Two slip-on flanges with O-ring grooves for the pressure seals were 

welded to either end of the pipe so that the top and bottom plates could be bolte

and a fill/relief line. The bottom

also tapped to allow the discharge valve to be screwed into place and sealed with a crushable, tempered 

aluminum gasket. Other features incorporated into the source vessel include pressure and temperature 

200 cm (6.56')

Tsvs

Psv

Tsvu

4.93 cm (1.94") ID

DISCHARGE 

VALVE

SOURCE TANK

V = 3.8 Liters

Tcv

COLLECTION VESSEL

V = 30 Liters

PIPING SYSTEM

Pcv

24.3 cm (9.56")

50.8 cm (20")

P1

T1

P2

T2

P3

T3

CIRCULATION LINE

SUPPRESSANT RECYCLE LINE

Rapid Discharge Facility (RDF)

Lehigh University

CAPACITANCE SENSOR

∆P
Fluid Transport Through Piping 755

ports, a liquid level gauge, a mixing line, and the differential pressure transducer with fluid transmission 

line for measurement of liquid inventory. 

ince tests required pressures up to (4.04 to 5.05) MPa in the source vessel, pressurization by nitrogen 

w

fluids only reaches about 0.505 MPa at room tem insufficient for the desired pressure without the

additional partial pressure of an inert pressurization gas such as nitrogen. A potential problem with this 

Figure 8-10. Schematic of Source Vessel Showing 

Mass Inventory Measurement. 

S

200 cm (6.56')

Tsvs

Psv

Tsvu

4.93 cm (1.94") ID

∆P

as employed. As shown in Figure 8-11, for HFC-227ea, the equilibrium vapor pressure of suppressant

perature,

method is that the total pressure in the vessel will not reach equilibrium until the liquid has become 

saturated with dissolved nitrogen. In order to expedite this process, a mixing system has been 

incorporated into the design, using a pump to recycle liquid suppressant from the bottom of the source

vessel to a spray nozzle located in the vapor/gas space. By spraying small droplets of liquid through the

nitrogen gas, the surface area of liquid in contact with nitrogen will increase, therefore increasing the rate

at which nitrogen can be dissolved into the liquid. 

Additional ports in the source vessel include an opening near the top, which serves as the connection to 

the nitrogen supply and as one leg of the transmission line for the differential pressure transducer. A 

liquid level gauge made of armored glass has also been attached to the middle section of the vessel to

visually determine the liquid fill level in the vessel at the beginning of each experimental run. Also, there 

are two thermocouple ports for the vapor and liquid spaces and a pressure port in the vapor space. The 

last port is in the top plate, providing access for filling of the vessel and also serving as a connection for a

safety pressure-relief device. 
756 Fluid Dispensing and Dispersion 

Figure 8-11. Pressure vs. Temperature Saturation Curve for HFC-227ea and HFC-125. 

 in the design is the release mechanism of the source vessel, for initiating 

ischarge of the test agent. A quick-opening plunger valve with an inlet diameter of 3.18 cm and an exit 

 the O-ring seals on the plunger for lubrication. 

ed in Figure 8-13. They will also be the first and last locations of the 

pressure and temperature measurement ports. Ports for the pressure transducers and film thermocouples 

used for these measurements required special weld fittings in order to insure a complete pressure seal in 

The next pertinent item

d

diameter of 4.45 cm was used for this purpose. This valve, shown in Figure 8-12, is a Model MV121KJ-2 

valve made by Marotta Scientific Controls Inc. A feature of this valve is the use of the fluid pressure to 

drive the plunger upon command; thereby eliminating the need for springs or motors. To set or close the 

valve, the plunger is pushed up into its armed position and held in place by a small locking latch. Two 

O-rings are attached to the plunger to form a pressure seal along the valve casing. Pressure must then be 

provided on the inlet side of the valve for the valve to operate properly. To open the valve, an electrical 

charge provided by a 20V DC power source releases the latch, allowing the fluid pressure to rapidly drive 

open the plunger. This release is much faster than that of traditional solenoid valves, and is similar to that 

of a burst diaphragm or explosive-charge release, which is used in present-day suppression systems. The 

valve is connected to the 1/2-in discharge piping in the loop by a tapered transition piece. This transition 

incorporates a flange connection to permit access to

The piping in the test facility consists of 1.27 cm nominal diameter stainless steel pipe with an internal 

diameter of 1.39 cm and a wall thickness of 0.38 cm. There are five other pieces, including the adapter 

piece described above, which make up the discharge piping system. Two of these pieces are 

approximately 30.5 cm in length with flanges at either end to provide for easy disassembly. All the 

flanges are machined with an O-ring groove to provide an adequate seal against the high pressures 

experienced in the tests. These 30.5-cm sections will be used as access points at the beginning and end of 

the piping system, as indicat

0

500

1000

1500

2000

2500

3000

3500

-60 -40 -20 0 20 40 60 80 100 120

4000

Temperature [degrees Celsius]

Pressure [kPa]

HFC-125

HFC-227ea

Temperature (oC)

Pressure (kPa)

0

500

1000

1500

2000

2500

3000

3500

-60 -40 -20 0 20 40 60 80 100 120

4000

Temperature [degrees Celsius]

Pressure [kPa]

HFC-125

HFC-227ea

Temperature (oC)

Pressure (kPa)
Fluid Transport Through Piping 757

the loop. These fitting were specially designed to cause minimal disturbance to the flow, while allowing

r to be as close to the flow as possible. See Figure 8-14 for a schematic diagram

Figure 8-12. Schematic of a Marotta valve. 

for the senso of these 

fittings. 

4.45 cm

3.18 cm

Inlet

Outlet

Electric

Switch

4.45 cm

3.18 cm

Inlet

Outlet

Electric

Switch

14 cm

19 cm

107 cm

112 cm

15 cm

317 cm

P Port

T Port

P Port

T Port

Source Vessel & Holding Rack

Specially Designed Section for

Void Fraction Measurement

P Port

19 cm

Collection Vessel

T Port

(not to scale)

Figure 8-13. Top View of Test Facility; Schematic of Discharge Piping System.

The other two pieces in the piping system include a special section used for the void fraction

measurement and a long middle section of pipe. The long middle section of pipe represents the

distribution spool piece often found in fire-suppressant piping systems. Both ends are flanged and are

capped by valves, allowing for the isolation of this section when dismantling. The middle piece will be

tapped in the middle for temperature and pressure ports as described previously. This middle piece of 

long discharge piping allows for easy reconfiguration to different piping schemes (i.e., inclusion of tees or 

elbows). This whole piping system is then connected by a flange to the collection vessel, providing a

closed flow path from the source vessel, through the piping system, to the collection vessel. 
758 Fluid Dispensing and Dispersion 

Figure 8-14. Schematic of 

Pressure Fittings for 

re and Pressure

Ports. 

The collection vessel is designed to serve two purposes: to catch the test fluid for recycle and to enable 

monitoring of the transient discharge pressure during test runs. The collection vessel has an internal 

volume of approximately 30 L, chosen to limit the final pressure after discharge to less than 1.01 MPa to 

1.212 MPa. This vessel is made of a 25.4 cm diameter stainless steel pipe with an internal diameter of

24.3 cm and a wall thickness of 1.50 cm. The bottom of the collection vessel is a hemispheric cap with a 

1.27 cm port, to be used for emptying the contents. At the top end is a pair of 4.445 cm thick flanges 

sealed by an O-ring. The outside flange has access holes to allow for a cooling coil, a vacuum line, and a 

temperature measurement port. The cooling coil can carry either cold water or liquid nitrogen for the 

purpose of condensing the spent suppressant fluid for recycling. The vacuum line is connected to the top 

of the vessel for the purpose of relieving the excess pressure before the next run. The line is connected to 

knock-back condenser to prevent a minimal amount of suppressant from escaping. Additional ports in 

the sides of the vessel provide connections for the piping system and a fast-response pressure transducer. 

In anticipation of potentially large reaction forces during fluid discharge, a rugged framework was 

amping to the 

5.08 cm pipe. The last shelf, positioned lower down on the beam, is used to hold the mixing pump. The 

Temperatu

0.15"

1/8"

11/32"

1/8" NPT

T Port Fitting

Thermocouple

Fitting

1/2" Pipe

11/32"

1/2" Pipe

P Port Fitting

Pressure

Transducer

PRESSURE TRANSDUCER PORT

THERMOCOUPLE PORT

3.2 mm

26.2 mm

26.2 mm

3.8 mm

12.7 mm

Pipe

12.7 mm

Pipe

a

designed to support the test facility. As shown in Figure 8-15, a 20.3 cm I-beam, 305 cm high, was 

chosen to give a rigid backing for the source vessel while being heavy enough to dampen any vibrations

exhibited during the test runs. This rack I-beam is directly bolted to the building structure for rigidity. 

The rack I-beam has three welded shelves for use in supporting the source vessel. The first is positioned

just below the middle of the beam and is used to hold the source vessel from the bottom. Since this area

experiences most of the forces during the discharge tests, the shelf in this area is bolted to the large flange

at the bottom of the source vessel. This shelf is equipped with support legs for added stability. The next

shelf is located near the top of the rack and anchors the top section of the source vessel by cl
Fluid Transport Through Piping 759

I-beam is also equipped with bolt holes along its face in order to add support structures for the level

gauges and mixing lines. As for the piping system, it is supported by a metal framework, which has

provisions for clamping the pipe and preventing movement in both horizontal and vertical directions. The 

collection vessel is attached to a movable dolly to allow for opening of the piping system when access is

necessary. To account for substantial forces associated with the fluid discharging into the vessel, the 

collection vessel is held in place by support braces attached to a building I-beam. A picture of this entire

system is shown in Figure 8-16, where the source vessel, straight piping system, collection vessel, support 

structure and instrumentation can be seen. 

Figure 8-15. Schematic of Rack Used to Hold 

the Source Vessel.

38 cm

308 cm

51 cm

108 cm

20 cm

Side View Front View

(not to scale)

Pressure Sensors 

The test facility is equipped to measure instantaneous pressure readings in the source vessel, along the 

piping system, and in the collection vessel by means of fast response pressure transducers. Two types of 

transducers were used in the experiments conducted, the Entran Model EPX-V01 with a range of (0 to 

6.87) MPa-g and the Validyne Model DP15 with varying ranges from (0 to 6.87) MPa-g. The Entran

transducers were primarily used in the early runs when the temperature drop during operation was not a 

concern. The Validyne transducers were used for both pressure drop measurements and absolute pressure 

measurements. The Validyne transducers were used with a transmission fluid for speed of transmitting 

the pressure wave in the pressure drop readings and also for insulation when the temperature drop was
760 Fluid Dispensing and Dispersion 

considerable, as in the HFC-125 tests. The Entran transducers have a diaphragm, which deflects 

according to the difference of the pressures experienced at its front and backsides, and provides an output 

through a strain gauge bridge located on the backside of the diaphragm. The Validyne transducers used a 

magnetically permeable diaphragm, which when deflected caused a magnetic reluctance, which was then 

interpreted by the inductance value of coils in the transducer body. In order to install these transducers at 

measurement locations, special fittings had to be designed and fabricated. It is desirable to locate the 

transducers as flush to the inside surface of the pipe as possible, in order to minimize disturbances to the 

flow. This was accomplished with the specially designed fittings shown in Figure 8-14. With these 

fittings welded into place on the pipe, the transducers can be screwed into the tapped hole, allowing an 

O-ring to seal against the high fluid pressures. Bench top experiments were conducted to determine 

whether the transducers had appropriate response times for the fast transient tests conducted. Both 

transducers were found to have response times at acceptable level of 140 ms for pressurization and 

190 ms for depressurization when operating at 2.02 MPa to 3.03 MPa. The best test for the 

instrumentation was to view their performance in actual testing situations. 

Figure 8-16. Picture of Test Facility: Source Vessel, Discharge Piping, Collection Vessel, 

Support Structure and Instrumentation.7

Figure 8-17 shows a typical output (Run #5) from the pressure transducers installed in the test facility. 

This run used HFC-227ea as a test fluid and was initially charged to a source vessel pressure of 4.22 MPa. 

As shown in the figure, the pressures in the source vessel, pipe, and collection vessel remained constant 

until the moment when the valve was actuated (time = 0 ms). Then the pressure in the source vessel 

dropped quickly while the pressures in the rest of the facility rose. This occurred until the pipe was filled 
Fluid Transport Through Piping 761

with fluid (time ≈ 200 ms) and then there was a steady decrease in all of the pressures until all of the fluid 

was discharged from the source vessel (time ≈ 1500 ms). At this point a small pressure increase or 

“bump” was prevalent in the piping pressure traces due to the exit of the remainder gas contents of the 

source vessel. A set of runs with similar initial conditions was also curried out to check the repeatability

of the measurements and the reliability of the instrumentation. The operating conditions are shown in 

Table 8-2. 

Table 8-2. Operating Condition for Repeatability Tests.

Run 

Fill volume 

(mL) 

Ambient temperature 

(°C)

Source vessel pressure 

(kPa) 

Downstream pressure 

(kPa) 

#3 2358 32 4180 720 

#4 2370 29 4195 525 

#5 2388 31 4220 720 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Collection vessel

Time (ms)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Collection vessel

Time (ms) Time (ms)

Pressure (kPa)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Collection vessel

Time (ms)

3000

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500

Time [msec]

Pressure [kPa]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Collection vessel

Time (ms) Time (ms)

Pressure (kPa)

Figure 8-17. Pressure Traces for Experimental Run #5. 

All the tests used HFC-227ea. The repeatability was very good as shown by Figure 8-18, which 

compares the source vessel pressure traces of the three experimental runs. The slight discrepancies are

most likely caused by differences in the initial and environmental conditions and are believed to be not

due to the instrumentation. The transducers did a good job in tracking the pressure fluctuations during the 

experimental runs. 
762 Fluid Dispensing and Dispersion 

0

500

1000

1500

0

3000

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

3500

4000

4500

Run #3

Run #4

Run #5

Figure 8-18. Repeatability of the Source Vessel Pressure Traces. 

There was also a necessity to measure the pressure drop across particular sections of the piping system.

While the absolute measurements at different locations allowed us to measure the variation of absolute

pressure across the discharge pipe, there was also an interest in measuring pressure drops across fittings in 

order to determine frictional losses across these piping elements. Figure 8-19 and Figure 8-20 show the

two other piping configurations tested in this study in addition to the straight pipe configuration. 

Validyne pressure transducers were connected on either side of the fittings to measure the distinct

pressure drop associated with these fittings. This can be seen by the ports specifically designated to the

fittings shown on the diagrams (i.e., PT2-PT3 across a 90° elbow). A typical output from this 

measurement is shown in Figure 8-21, where pressure drop versus time is displayed. This plot shows the

pressure drop across a 90° elbow from Run #9 using HFC-227ea as a test fluid and an initial pressure of 

3

deteriorates 

915 kPa. There is a notable pressure drop instantly as the fluid front passes through the elbow, which 

as time passes. This continues until approximately 2300 ms when the last liquid is 

ischarged and the remaining gas leaves the system, denoted by the sudden drop in pressure attributed to 

a reduction in the frictional co liquid flow. 

Similar plots were d unions. Also, a 

d

mponent of pressure drop associated with gas flow over

made for the pressure drop across capped tees, through tees an

comparison was done between the vertical branches of a through tee to study the effect of phasic 

composition on the separation of the flow. With these measurements, it was possible to successfully

analyze the effects of different fittings on the pressure losses in the discharge piping. 

200

2500

Time (ms)

0

500

1000

1500

0

3000

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

3500

4000

4500

Run #3

Run #4

Run #5

200

2500

Time (ms)

Pressur

e (k

P

a)

0

500

1000

1500

0

3000

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

3500

4000

4500

Run #3

Run #4

Run #5

200

2500

Time (ms)

0

500

1000

1500

0

3000

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

3500

4000

4500

Run #3

Run #4

Run #5

200

2500

Time (ms)

Pressur

e (k

P

a)
Fluid Transport Through Piping 763

Union

Capped Tees

Discharge

Valve

Collection

Vessel

2 - 45o Elbows

90o Elbow

PT1

PT3 PT4

PT2

Figure 8-19. Schematic of Alternate Piping Configuration #1. 

Discharg

Valve

e Co

Vessel Tees llection

Union

2 - 45o Elbows

90o Elbow

PT1

PT2

PT3

Figure 8-20. Schematic of Alternate Piping Configuration #2. 

2 - 45o Elbows

Union

90o Elbow
764 Fluid Dispensing and Dispersion 

Figure 8-21. Transient pressure drop across a 90° elbow from Run #9. 

Flow Rate Sensor 

As mentioned previously, a key parameter to measure is the instantaneous mass flow rate of fluid during

transient discharge from the source vessel. This has not been successfully measured in prior experiments 

due to its inherent difficulty. If fluid inventory in the source vessel could be measured as a function of

time, then the rate of discharge would be given by the gradient of inventory versus time. Because of 

possible void generation in the liquid (due to gas evolution) and associated level swelling, observation of

the liquid level does not provide an indication of fluid inventory. The approach is to measure the static 

head of fluid in the source vessel, as a dynamic function of time. Since frictional and kinetic terms are

negligible in the overall momentum balance for conditions in the vessel, the fluid inventory in the vessel

can be obtained directly from static head measurements: 

P

g

A M = ∆ (8−36)

where M is the fluid inventory, A is the cross-sectional area of the vessel, g is gravitational acceleration,

∆P is the pressure difference from the bottom to the top of the vessel (static head). The instantaneous

te of mass flow out of the vessel is then obtained from the time derivative: 

and 

ra

dt

d P

g

A

dt

dM

m

∆ = = •

(8−37)

0

20

40

60

80

100

120

140

-500 350

160

0 500 1000 1500 2000 2500 3000 0

Time [msec]

Pressure Drop [kPa]

Time (ms)

Pressure Dro

p (kPa)

0

20

40

60

80

100

120

140

-500 350

160

0 500 1000 1500 2000 2500 3000 0

Time [msec]

Pressure Drop [kPa]

Time (ms)

Pressure Dro

p (kPa)
Fluid Transport Through Piping 765

In order to obtain the desired accuracy for the rate of mass flow, a precise measurement of ∆

ary. A Validyne Model DP15 differential pressure transducer was used to obtain this static

P. As shown in Figure 8-10 and Figure 8-22, this transducer was connected to the vapor space and the 

volume at the top and bottom of the source vessel, respectively. The transmission line connecting 

the vapor space to the liquid space was filled with a Meriam Red fluid with a specific gravity of 2.95 to 

mize response time. The theory behind this was that the pressure signals would be transmitted to the 

transducer at the speed of sound in liquid, sufficiently fast to obtain dynamic data during suppressant

discharge and much quicker than through a compressible gas volume. Therefore, the connections to the 

liquid and vapor spaces were made at the wall of the Marotta valve and the wall of the source ves

respectively. This allowed for an almost flush-mounted differential pressure transducer with an excellent 

response time for measuring liquid inventory. Figure 8-22 shows a diagram of the setup for this

differential pressure transducer. Note that it was attempted to fill the transmission line as close to the

source vessel as possible, therefore reducing any pockets of fire suppressant vapor and making a m

accurate measurement. 

P is 

necess head

∆

liquid 

maxi

sel,

ore 

left the source 

vessel and continued gradually until the source vessel was empty, at approximately 3.37 kg. This 

rresponded with the pressure drop in the source vessel own in Figure 8-17 and with the end of the 

Figure 8-22. Diagram of Transducer Setup for Mass Inventory Measurement. 

This technique worked very well, as shown in Figure 8-23, a plot of the cumulative mass leaving the 

source vessel versus time. This example shows the same experimental run described in the previous 

section. It shows that at the point when the valve was actuated, a quick release of test fluid 

+

Diaphragm

Source Vessel

Side of Valve

Fill Level

Differential Pressure Transducer

co sh

liquid flow and beginning of the gas flow at a time of ≈ 1500 ms. This is what one would expect; the fact 

that the pressure trace did not fluctuate very much indicated that there was a steady flow of fluid through 

the facility. Once again, this method for measuring the instantaneous liquid inventory gave excellent 

repeatability. 
766 Fluid Dispensing and Dispersion 

0.0

0.5

-500 0 500 1000 1500 2000 2500 300

1.0

1.5

2.0

2.5

3.0

3.5

e thermocouple is comprised of the metallic film, it is essential to maintain a continuous electric 

conduc he test

fluid, and the erosive effects of the flow on the film. In past experiments, a metallo-organic paint was 

etallic film was determined by an increased fluctuation 

in the output signal of the thermocouple or in some cases a loss in the signal altogether. Many of the 

ilures in the thermocouple were not attributed to the metallic film at all, but to the disintegration of the 

inner wiring of the thermocouple. This was most likely due to the vibration encountered in the test 

facility when the experimental runs were conducted and the tight seal on the thermocouple casing needed 

to hold the thermocouple in place during testing. 

Figure 8-23. Transient Mass Inventory of Run #5. 

Temperature Measurement Sensors 

Fluid temperatures along the discharge pipe were measured using film thermocouples. It has been

experimentally shown,29 that this type of thermocouple can provide response times on the order of

milliseconds. A schematic of the film thermocouple is shown in Figure 8-24. Since the hot junction of

th

tive-path through that film. Two issues are involved: compatibility of the film material to t

used to make the film at the tip of the thermocouple. This film worked well in experiments with high

temperature steam and water. The same material was used for the junction film in the test series. A

bench setup was prepared to test the thermocouple with this film junction. After forming the film, the 

thermocouple assembly was exposed to test liquids for durations of up to five minutes. Tests with the 

primary test fluid, HFC-227ea, indicated that the junction film holds up well to such exposure. No bench

test for erosion of the film was attempted prior to the running of the test facility, due to the significant 

effort involved. It was found that the film held up for anywhere from 5-10 experimental runs before 

deterioration in the film deemed it necessary to remove the thermocouple from the facility and reapply the 

metallic film. The need for reapplication of the m

fa

0

Time [msec]

Cumulative Mass [kg]

Time (ms)

0.0

0.5

-500 0 500 1000 1500 2000 2500 300

1.0

1.5

2.0

2.5

3.0

3.5

Cumulativ

e Mass (kg) Cumulative Mass [kg]

0

Time [msec] Time (ms)

Cumulativ

e Mass (kg)
Fluid Transport Through Piping 767

Figure 8-24. Schematic of Thermocouple Construction. 

An example of a typical output from the four film thermocouples located throughout the test facility is 

shown in Figure 8-25. The top set of data is the signal from the film thermocouple located in the vapor 

space of the source vessel. The next three sets are from the film thermocouples in pipe positions #3, #2,

and #1, respectively from top to bottom. This plot shows no significant temperature change in the vapor 

space, which is due to the fact that there was only a gas expansion involved in this region. While an

adiabatic gas expansion from a volume of 1.5 L to 34 L should have resulted in a large decrease in

temperature, this was not an adiabatic expansion due to the availability of a large heat sink in the stainless 

steel walls. With the considerable warming from the facility walls and the thermocouple’s location at the 

top most portion of the entire facility, the only temperature drop experienced is minimal. As for the other 

set of thermocouple traces, it is believed the most significant reason for the difference in temperature drop 

along the pipe is also due to the warming effects. 

- +

Negative Lead

Positive Lead Insulators

Conductive Paint (Metallic Film) 
768 Fluid Dispensing and Dispersion 

Figure 8-25. Transient Temperature Trace from Film Thermocouples of Run #5. 

There were also two standard 0.79 mm diameter, shielded thermocouples in the source and collection 

vessels. Figure 8-26 shows a typical temperature trace from these thermocouples, again from Run #5. 

ces shown in this diagram are significantly different from each other. The collection vessel 

mperature does a quick dip and then warms back up to room temperature. This is due to the filling of 

the vessel with cold lution of nitrogen 

from liquid suppressant. Also, there is an energy loss associated with the phase change of the suppressant 

The two tra

te

 fluid, which is probably still going through the process of disso

fluid as it goes from liquid in the pipe to gas in the collection vessel. This goes on until the collection 

vessel reaches the saturation pressure of the suppressant fluid, and then the vessel begins to heat up due to 

compression of the gas in the volume. On the other hand, the thermocouple located at the bottom of the 

source vessel initially does not change much since it is submersed in liquid suppressant. Then as the 

liquid in the source vessel runs out, it experiences the vaporization of the suppressant fluid on its surface 

and the expansion of the remaining gas in the system. To fully understand the complete picture of the 

changes of phase taking place in the experimental runs, a representation of the void in the facility is 

needed, which is described below. 

0

5

10

15

20

25

30

35

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Temperature [C]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

0

5

10

15

20

25

30

35

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Temperature [C]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Time (ms)

Temperature (oC)

0

5

10

15

20

25

30

35

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Temperature [C]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

0

5

10

15

20

25

30

35

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Temperature [C]

Source vessel

Pipe position #1

Pipe position #2

Pipe position #3

Time (ms)

Temperature (oC)
Fluid Transport Through Piping 769

0

5

10

15

20

25

30

35

0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Temperature [C]

Source vessel

Collection vessel

0

5

10

15

20

25

30

35

0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Temperature [C]

Source vessel

Collection vessel

Time (ms)

Temperature (oC)

0

5

10

15

20

25

30

35

0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Temperature [C]

Source vessel

Collection vessel

0

5

10

15

20

25

30

35

0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Temperature [C]

Source vessel

Collection vessel

Time (ms)

Temperature (oC)

Fi .

Based on previous experience, a capacitance sensing method for this measurement was selected, in 

expectation that this method would satisfy all of the above desirable features. 

A number of different capacitance probes were designed, fabricated, and bench tested. The final probe 

configuration is shown schematically in Figure 8-27. As indicated the probe consists of a positive 

electrode and a ground electrode, both placed on the outside surface of the discharge pipe. The section of 

the discharge pipe at this location needs to be electrically nonconductive to allow capacitance 

.

Based on previous experience, a capacitance sensing method for this measurement was selected, in 

expectation that this method would satisfy all of the above desirable features. 

A number of different capacitance probes were designed, fabricated, and bench tested. The final probe 

configuration is shown schematically in Figure 8-27. As indicated the probe consists of a positive 

electrode and a ground electrode, both placed on the outside surface of the discharge pipe. The section of 

the discharge pipe at this location needs to be electrically nonconductive to allow capacitance 

gure 8-26. Transient Temperature Trace from Shielded Thermocouples of Run #5

Void Fraction Sensor 

One of the major flow variables for two-phase flow is the void fraction. Many flow parameters, such as

thermodynamic quality, vapor and liquid mass fluxes, and transport properties of vapor and liquid affect

the void fraction. In turn, the void fraction strongly affects pressure drop, holdup inventory, and flow rate 

for any given operating condition. Thus, it is desirable to experimentally measure the void fraction during 

the transient discharge of suppressant. Once again, this is a difficult measurement in two-phase flows and

was not attempted in prior experiments of suppressant flow. In the present work, an attempt was made to 

measure the transient void fraction at the end of the discharge pipe. The desirable features of a sensor for

void fraction are: 

• No disturbance on flow 

• Integrate the void fraction over the cross-section 

• Fast response 

Void Fraction Sensor 

One of the major flow variables for two-phase flow is the void fraction. Many flow parameters, such as

thermodynamic quality, vapor and liquid mass fluxes, and transport properties of vapor and liquid affect

the void fraction. In turn, the void fraction strongly affects pressure drop, holdup inventory, and flow rate 

for any given operating condition. Thus, it is desirable to experimentally measure the void fraction during 

the transient discharge of suppressant. Once again, this is a difficult measurement in two-phase flows and

was not attempted in prior experiments of suppressant flow. In the present work, an attempt was made to 

measure the transient void fraction at the end of the discharge pipe. The desirable features of a sensor for

void fraction are: 

• No disturbance on flow 

• Integrate the void fraction over the cross-section 

• Fast response 
770 Fluid Dispensing and Dispersion 

measurements. For the purpose of these bench tests, a glass tube was used as the pipe material. The 

positive electrode is a strip of copper in contact with the outer surface of the pipe. The electrode span is 

as wide as the ID of the pipe. The ground electrode is placed on the opposing side of the pipe. When 

powered by a high-frequency voltage, this probe would measure an overall capacitance between the two

electrodes, which includes the whole cross-section of the tube. This capacitance can then be calibrated to

give the void fraction of the vapor/liquid mixture in the pipe. There is a guard electrode around the 

positive electrode to prevent/reduce stray capacitance. 

a calibration using the signals associated with all liquid and all vapor. An example of 

the outp f Figure 8-29. It is seen that initially the probe senses 100 % liquid in 

the tube ensor, the signal slowly starts to show some

void in e id level is within the sensing volume, the 

variation of linear with liquid level. Again, there is an edge effect when the

liquid level is close to the bottom edge of the sensing volume. Later, when the liquid level falls clear of

ated with HFC-134a under

Figure 8-27. Schematic of Capacitance Probe for Bench Setup. 

This probe was tested on a bench loop with water and HFC-134a. The schematic of the bench setup is 

shown in Figure 8-28. The test started with the glass tube filled with water. During the test, the tube was 

emptied from the bottom so that the liquid level receded with a constant speed. The recorded signal from 

the capacitance sensor was compiled as a voltage signal from the capacitance meter and then reduced into

void fraction with

ut rom this test is shown in

. As the liquid level approaches the top edge of the s

th sensing volume (edge effect). When the liqu

measured void fraction is 

the sensing volume, the probe senses all air in the tube. Despite the fact that the sensing area is guarded, 

there are some edge effects in the axial direction. The above test was repe

pressure and similar results were observed. 

Section B-B

B

Ground electrode (-)

Positive Probe

Insulation

B

45 mm

Glass tube

BNC connector

Guard electrode (+)

20 m

m

 6 mm
Fluid Transport Through Piping 771

Figure 8-29. Void Fraction from Bench Tests of Capacitance Sensor. 

Figure 8-28. Bench Setup to Test 

Capacitance Sensor. 

level 0

Ground 

electrode

capacitance 

probe

20 mm

Positive

electrode

Water

volume

Sensing 

-0.200

0.000

0.200

0.400

0.600

0 10 20 30 40

Water height [mm]

void fraction 

0.800

1.000

1.200

α

Sensing

All Air volume

All Water
772 Fluid Dispensing and Dispersion 

The biggest problem with changing this design to fit the conditions experienced in the experimental test

facility was to contain the higher pressures. In the previous bench examples, only low-pressure systems

were dealt with and in the present application the sy pressure was as high as 1250 kPa at the location

of the void probe. The other difficulty was that an electrically conductive surface between the probe and 

the tested medium was not allowed. Due to these li itations, a design that would be constructed on the

inner surface of the pipe was developed, as shown in Figure 8-30. There were three main pieces to this

design; the first was the electrical plug welded to the eal and as an 

electrical connection to the capacitance meter. The next two pieces were the guard and the probe

separated by a small layer of insulation. To insure at these pieces were not washed away in the flow

during the runs, they were covered in a thin layer of pipe wall as

its ground creating an electrical field similar to the o

Figure 8-30. 

Schematic of 

Capacitance Probe for 

Test Facility.

Figure 8-31. Cross-section of Capacitance 

Setup Showing Electrical Field. 

stem

m

metal pipe, which served as a pressure s

th

epoxy. This capacitance probe used the

ne shown in Figure 8-31. 

Brass made piece

to screw in 

BNC Connector for

guard electrode

Teflonferrule

1.2"

positive electrode

probe tip

Flow

Epoxy

Ground electrode

Probe tip

19mm

16mm

Insulation between guard and pipe

& between probe and guard

probe tip side view

30.5 mm

positive electrode

Ground electrode
Fluid Transport Through Piping 773

While the orientation of this design was horizontal as compared to vertical in the bench test setup, it was 

believed that the results were similar. An in situ calibration by filling the area with all liquid suppressant 

and then letting it run out so that only suppressant vapor remained was conducted. 

An example of the final output of an actual experimental run is provided in Figure 8-32, where void 

fraction versus time for Run #5 is shown. The signal initially starts out at a void fraction of 1.0 (all 

vapor) and then shoots down to approximately 0.4 as the area is flooded with the transient flow of twophase fluid. The signal fluctuates as the mixture of the two phases changes depending on the speed and 

location of the dissolution of the nitrogen from the liquid suppressant. As the flow slows down, so do the 

fluctuations in the capacitance signal, until the liquid runs out (time = 1700 ms), and the remaining gas is 

e 1.0 region. The largest 

 the fast moving dispersed 

ing effort to be conducted. 

pite th

vented into the collection vessel, causing the signal to abruptly go back to th

problem with the capacitance signal resulted from the static charge build up of

flow. It caused the signal to jump out of range and required a significant filter

This is also the reason for the offset in the final value at the end of the run. Des ese slight problems, 

it was felt that the capacitance probe design gave an excellent representation of the void fraction values 

experienced during the experimental runs. 

Figure 8-32. Transient Void Fraction of Run #5. 

Test Matri

After the completion of the test facility, it was necessary to choose the appropriate initial conditions in 

which to conduct the experimental runs. The main goal was to encompass a wide variety of test 

parameters while keeping the total number of runs at a minimum to lessen the wear on the 

instrumentation. Table 8-3 shows the experimental runs conducted in this study. HFC-227ea was used as 

x Performed in Study 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

00

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

00
774 Fluid Dispensing and Dispersion 

the primary test fluid since it was recommended at the time as the alternative fire suppressant with the

best fire-retarding ability. HFC-125 was also used since it had been studied recently, and there was some

uple without exposing

them to high pressure or a corrosive fluid. Run #18 also used water and had the intent of testing the mass

The majority of the experimental runs used HFC-227ea as a test fluid and was broken into three main 

f

the pipi

e 

the 2 ined

that a oal

°

in Run 

e two

m 

so 

uids, changing the piping configurations and the repeatability of the instrumentation. 

A Typical Experimental Run 

First the plunger in the Marotta valve is set into the closed position using the arming tool. Once the valve 

test data that could be used for future comparison. In the preliminary experiments, water and carbon 

dioxide were used to test the new instrumentation after installation. For example, Run #19 used water as 

a test fluid and was undertaken to test the capacitance sensor and film thermoco

flow sensor response and all of the thermocouples in the facility. In a similar manner, Runs #20 and #21, 

which used CO2, were used to measure the response of the film thermocouples to a sudden drop of 

temperature as low as –40 °C, while also allowing us to gauge the error encountered by the pressure

transducers at this temperature. These four runs utilized the straight pipe configuration in the test facility

shown previously in Figure 8-13. The HFC-125 Runs (#14-#17) were conducted with only one objective,

to test the influence of changing the source vessel pressure. The four runs were carried out at source 

vessel pressures varying from 2050 kPa to 5000 kPa. It must also be noted that any runs using source

vessel pressures with initial conditions using low pressures were conducted at fill levels between 85 % 

and 90 %. This was done in an attempt to facilitate as much vaporization during the flow discharge as 

possible since the downstream pressure would remain at a lower pressure with the smaller amount of

nitrogen gas available to expand. 

piping configuration groups. First, there were the tests using the straight pipe configuration. These tests 

had three different goals: (1) to test the repeatability of the instrumentation, (2) to observe the effect o

changing the source vessel pressure, and (3) to determine the effect of a heat source or “hotspot” along 

ng system. The repeatability Runs (#3 to #5) were conducted at an initial source vessel pressure 

of about 4.242 MPa. The result of the source vessel pressure trace is shown in Figure 8-18. While th

“hotspot” Run (#7), was conducted at a similar starting pressure with a foot long section at 55 °C between 

nd and 3rd instrumentation ports on the pipe, only one such run was needed since it was determ

minimal effect resulted from the heat addition under such rapid transient conditions. The third g

was to observe the effect of varying the initial source vessel pressure from 2125 kPa to 4910 kPa (Runs

#1 to #6). The second main piping configuration group used the piping configuration shown in 

Figure 8-19, where a vertical “U” turn was built into the piping system to allow the measurements of the 

effect of pipe fittings on the pressure loss in the system. The pressure drops across a capped tee, 90

elbow and union were measured with varying initial source vessel pressures from 2120 kPa to 4910 kPa

#8 to Run #10. The third piping configuration group used a complete vertical split as shown in 

Figure 8-20, where the tee was no longer capped but used to join two symmetric piping sections. Th

sections were identical to the one used in the previous grouping although this time the pressure drop 

across the split was measured. A sensor was placed before the tee and after the 90° elbows on either ar

of the split to test whether there was an effect from the splitting of the flow. These tests were al

conducted at three varying initial source vessel pressures from 2140 kPa to 4910 kPa in Run #11 to Run

#13. These tests examined the effects of changing the initial source vessel pressures, changing the test 

fl

is closed, the next task is to recycle any fluid remaining in the collection vessel back to the source vessel

using a magnetically driven centrifugal pump. If there is not enough test fluid in the collection vessel to 
Fluid Transport Through Piping 775

reach the desired initial fill level for the next run, then the recycle line is closed and a line to a freshsupply tank above the test facility is opened, allowing the remaining liquid needed for the run to be 

pumped into the source vessel. Once this is accomplished, the supply line is closed and a circulation line 

is opened allowing the liquid at the bottom of the source vessel to be pumped to a spray nozzle at the top 

of the vessel. The spray nozzle then creates a fine mist of liquid to float through the vapor space of the 

vessel before joining the rest of the liquid. At this point, nitrogen gas is slowly added to the source vessel 

through a connection at the top of the vessel. The circulation pump is continuously run until the liquid is 

saturated with nitrogen. This is recognized by a constant pressure in the source vessel, which usually 

takes about 120 min. The circulation pump is then turned off, and the contents of the source vessel are 

allowed to settle and cool down to room temperature. The data acquisition system is initiated and run for 

500 ms before the Marotta valve is actuated. This allows for the collection of the initial conditions of the 

system. Once the valve is actuated, the contents of the source vessel discharge through the Marotta valve 

into the piping system and finally collect in the collection vessel. 

Table 8-3. Matrix of Experimental Runs Conducted. 

Run # Test Fluid Piping Configuration 

Fill Volume 

(mL) 

Psvo 

(kPa) 

Pcvo 

(kPa) 

Temperature 

(°C) 

1 HFC-227ea Straight Pipe 3571 2125 10 32 

2 HFC-227ea Straight Pipe 2340 3235 635 33 

3 HFC-227ea Straight Pipe 2358 4180 720 32 

4 HFC-227ea Straight Pipe 2370 4195 525 29 

5 HFC-227ea Straight Pipe 2388 4220 720 31 

6 HFC-227ea Straight Pipe 2150 4910 715 31 

7 HFC-227ea Straight Pipe 

w/ Hotspot @ 55°C 2200 4230 710 27 

8 HFC-227ea Capped Tee (Config. #1) 3420 2120 125 21 

9 HFC-227ea Capped Tee (Config. #1) 2500 3915 575 24 

10 HFC-227ea Capped Tee (Config. #1) 2450 4910 615 25 

11 HFC-227ea Through Tee (Config. #2) 3507 2140 600 26 

12 HFC-227ea Through Tee (Config. #2) 2400 3935 655 24 

13 HFC-227ea Through Tee (Config. #2) 2460 4910 615 25 

14 HFC-125 Straight Pipe 2900 2050 110 26 

15 HFC-125 Straight Pipe 2363 3635 175 26 

16 HFC-125 Straight Pipe 2400 4245 165 26 

17 HFC-125 Straight Pipe 2467 5000 125 24 

18 Water Straight Pipe 3585 2875 120 28 

19 Water Straight Pipe 3100 4150 100 23 

20 CO2 Straight Pipe ~1000 5215 100 20 

21 CO2 Straight Pipe ~1000 5360 100 20 

To fully understand the output from a single run, a typical experimental run (Run #5) will be examined in 

more detail. The pressure traces can be seen in Figure 8-17 where the traces go from the source vessel at 

the top, to the collection vessel at the bottom, and the pipe ports in the middle. Specifically, the black line 

(diamond) is the source vessel trace and the green (circle), red (square) and blue (triangle) traces are the 

first, second and third pipe positions, respectively, with the orange (cross) line being the trace for the 

collection vessel. Initially the source vessel is at 4220 kPa and the pressure downstream of the closed 
776 Fluid Dispensing and Dispersion 

valve is at 720 kPa. After the valve is opened, the pressure in the source vessel quickly drops as its 

contents fill the piping system, explaining the sudden rise in pressure there. At the point when the pipe is 

(diamond) symbols are for the bottom, 

fluid space of the source vessel, and the orange (cross) symbols are for the top, vapor space of the 

collection vessel. Th as the fluid initially 

reaches the large volume of the vessel and then it war o r mpe rath s 

fo ur mper le expe s a te re ue to the expansion 

of th gas t mocouple in the vapor space t. Th ost l due to the fact that 

the f the t the top of the vessel is in contact with stagnant gas and did not have enough time 

to se e its , while th ocouple experienced the shock of uick expansion from 

the f t flow

The next insight derived from as provided e diff l pr e transducer, which 

measured the mass flow rate of the discharge. As seen in Figure 8-23, this instrumentation allowed for 

the m asur cum id leaving the system s pro s a good e ate of 

how uch liquid has left th ht pos nd on sire tination, in s case, 

into the collection vessel ave liked to locate such a or near the desired 

des ion n a method of measuring the collected fluid could not be 

dev ed, the . Fig 3 veri hat h en already served 

from e p ur emper At fi re is imarily liquid flow, 

starting rapidly and slowly ry is relinquished to the pipi stem, until no liquid 

is left at ≈ Along w ional meas nt to b other assessments, the void 

frac leav e was als y use of a c ance sensor loca the end of the pipe. 

Thi trum ed an ele which pertained to a ca nce urement of the flow 

pas thro ction. Th then converted into a m ment of void fraction through 

a previous calibration where a value of 0.0 denotes all liquid flow and a value of 1.0 denotes all vapor 

flow with eve in the middle being a mixture of the two. Figure 8-32 shows the output from this 

sensor during the experimental run. Once again, the m id flo ms he 1 ms to 

1800 ms range. The slight discr en this measurement and the mass inventory measurement is 

ost likely caused by the fact that the ends of the pipe. This trace shows that at the 

eginning there is a flow of predominately liquid, void fraction of 0.4-0.2, which slowly rises to a more 

completely filled, ≈ 200 ms, there is a consistent drop in pressure as the fluid empties into the collection 

vessel. At ≈ 1600 ms, the fluid begins to run out and the flow in the system is predominately vapor. This 

quickly causes the entire system to equilibrate to the same ending pressure, ≈ 1100 kPa. 

Not only can the pressure traces be followed for the discharge, but the temperature change also can be 

followed throughout the system. Figure 8-25 shows the output of the highly sensitive film thermocouples 

placed at the top of the source vessel in the vapor space and along the bottom of the piping system at the 

three port locations. The same color and symbol scheme is used as in the pressure traces with the source 

vessel being on top, followed by the third, second, and first pipe positions, respectively. There was little 

temperature change experienced in the fluid flow portion of the discharge since there was little flashing of 

the suppressant. The main temperature drop occurs at the point when the vapor discharge begins 

(≈ 1600 ms). This is due to the sudden expansion of the remaining nitrogen gas and falls as low as 10 °C 

at the first pipe position. There are lesser temperature drops farther down the pipe due to the increased 

distance from the initial point of expansion and the warming of the vapor by the system walls. There 

were also two 0.79 mm shielded thermocouples placed in both the source vessel and collection vessel. 

The outputs of these are shown in Figure 8-26, where the black 

ere is a small dip in the temperature of the collection vessel

ms back up t oom te rature er quickly. A

r the so ce vessel te ature, this thermocoup rience mperatu drop d

e hat the film ther did no is is m ikely

ilm rmocouple a

ns temperature e lower therm the q

as ing gas. 

this study w by th erentia essur

e ement of the ulative mass of liqu . Thi vide stim

m e source vessel and mig sibly la the de d des thi

. Ideally, one would h sens

tinat , but since a ccurate, quick response 

elop this seemed most suitable alternative ure 8-2 fies w as be ob

 th revious meas ements of pressure and t ature. rst the a pr

 dying out as the invento ng sy

1600 ms. ith this addit ureme ackup

tion ing the pip o measured b apacit ted at

s ins ent obtain ctrical signal, pacita meas

sing ugh this se is signal was easure

rything

ain liqu w see to end in t 600

epancy betwe

m y are on either

b
Fluid Transport Through Piping 777

consistent value of 0.5 until the liquid runs out and the value jumps back up to an all vapor level. There 

are many peaks in the trace due to the fact that the flow is highly turbulent at this period in the flow, with 

the phasic composition changing with the rate of nitrogen coming out of the solution. The flow slows 

down a little near the end, and the trace smoothes out until the end when there is no more flow. These 

four different methods of taking measurements indicate that the transport processes occurring during the 

rapid transient phase of the experimental runs can be adequately assessed. The detailed output of all of 

the experimental runs conducted in this study can be found in Appendix B of the report by Tuzla et al.7

Observations and Conclusions 

The analysis of the full range of experiments conducted in this study provided many findings and 

observations. The most exciting developments in this study pertained to the previously unsuccessful 

as the speed at which the source vessel discharged its contents into the piping 

system and hence, into the collection vessel. All the runs exhibited the same basic phenomena as seen in 

measurements of mass flow, void fraction, and local temperature. The transient fluid inventory method 

gave excellent results, providing not only another check for the computer code developed in this work, 

but also an innovative technique currently unavailable in two-phase flow experiments. The void fraction 

measurement using a capacitance sensor has been used in other applications, but never in such a rapidtransient setting. In addition, most methods used in previous studies required the probe to extend out into 

the measured flow, which causes obstruction to the flow and obvious changes in the resulting flow 

characteristics. The current method provides a quick, accurate signal with minimal disturbance to the 

flow, resulting in the measurement of more realistic flow characteristics. Last, the film thermocouples 

used in this study also allowed measurements to be made without disturbing the fluid flow. In previous 

studies, thermocouples were always extended into the middle of the pipe in order to get the most accurate 

representation of the local temperatures, causing them to break and deflect the fluid as it flowed. These 

techniques had another shortcoming of not allowing a fast response due to the thermocouple sheathing. 

In the current case, only a paper-thin layer was present to shield the thermocouple junction from the flow 

while having no effect on the flow, due to their flush-mounted design. These techniques allowed this 

study to provide a more comprehensive data set for the computer code simulations to be tested against. 

The experiments in this study primarily focused on the use of HFC-227ea as a test fluid. The first set of 

experimental runs examined the effect of changing the initial source vessel pressure on the flow 

characteristics through a straight, 12.7 mm nominal diameter pipe, see Figure 8-13. The main difference 

between these runs w

Figure 8-17: (1) a quick pressure drop as the pipe filled, (2) a continuous drop in the pressure as the 

source vessel discharged its remaining fluid, and (3) a slight pressure “bump” in the pressure 

measurements in the pipe due to the venting of the remaining gas and vapor in the source vessel. Similar 

behaviors are evident when examining the void fraction and mass flow measurements. The lowest void 

fraction is seen at the beginning of the runs (Figure 8-32) when the liquid content in the flow is the 

greatest. Near the end of the run, a marked increase in the void fraction is observed as more nitrogen 

comes out of solution causing it to rise. The corresponding mass flow measurement (Figure 8-23) shows 

the fastest discharge at the beginning of the run when the source vessel pressure is at its highest value, 

thus providing the greatest driving force. Once the pressure begins to wane, so does the flow, until it ends 

at the end of the liquid flow for the run. 

The second set of experiments was conducted using an alternative piping system which contained tees, 

elbows, and a union as shown in Figure 8-19. The main goal for these runs was to measure the pressure 
778 Fluid Dispensing and Dispersion 

drop associated by adding specific pipe fittings into the piping network. As expected, the flow was 

significantly reduced by the pipe fittings, as shown in Figure 8-33. The comparison shows that Run #1

with the straight pipe finishes discharging its contents at approximately 4600 ms compared with Run #8

that used the piping layout containing two capped tees, a 90° elbow, a union and two 45° elbows, which

finished at about 7500 ms. To study these pressure drop measurements, a comparison to literature values 

for non-compressible, turbulent flow through pipe fittings using the friction loss factor method was 

conducted. This method is based on the procedure where pipe fittings are set equal to equivalent lengths 

of pipe depending on the anticipated pressure drop associated with the fitting. In the experimental setup,

the pressure ports used to measure the pressure drop across the fittings included not only the fitting but 

also some piping in between (see Figure 8-19) In each case the additional piping plus the fitting between

the pressure ports was included in order to remain as accurate as possible. For example, the 90° elbows 

were made up of the pressure port then 5.08 centimeters of piping, then the elbow, then 7.62 more 

centimeters of piping and the final pressure port. Therefore, the designation,“90° elbow”, is actually the

elbow plus 12.7 cm of piping. Predicted literature values were obtained by using the literature value for 

icular fitting and adding it to the calculated value for the additional 

piping, found by using Equation 8−38. 

the friction loss factor, K, for the part

D

L K f f = 4 (8−38)

where ff is the friction factor of the pipe found by using a chart in the literature with the diameter and

estimated roughness of the pipe, L and D are the length and diameter of the pipe, respectively. Once a

total K is found for the fitting and additional piping, it can be used in Equation 8−39 to find the literature

value for ∆P. 

2

2 K v P ρ ∆ = (8−39)

where ρ is the mixture density calculated using the experimental void fraction measurements, and v is the

flow mixture velocity calculated from the experimental values of mass flow through the pipe and the 

mixture density. 

Since the experiments took place under two-phase conditions, the mixture density was used in order to get

as close to the actual conditions in the pipe as possible. The one drawback of this method was that the

void fraction sensor was not located at the local position of the fitting, but at the end of the pipe so it

might not be a precise representation of the void conditions at the fitting. For this reason and because the 

literature values for K were developed using liquid turbulent flow, a comparison to values using the liquid 

density and liquid velocity in place of the mixture density and mixture velocity was also included. See 

Table 8-4 for the detailed values of this comparison. As the comparison shows, there are some

discrepancies between the literature and the experimental values, with the calculations using liquid 

density being in reasonable agreement. In order to compare whether the mixture or the liquid density is 

best used when calculating the literature value for ∆P, the error has been provided in parentheses. This

error was determined using the experimental value as the actual value. The experimental values for

pressure, void fraction, density and velocity were taken in the middle of the runs, with Run #8 being from 

1500 ms to 3500 ms and Runs #9 and #10 being from 500 ms to 1500 ms. Some of the possible reasons 

for the discrepancies in the comparison between the calculations using the liquid density and those using

the mixture density may be: 
Fluid Transport Through Piping 779

1. The phasic composition of the flow at the particular time during the run. For example, at the 

beginning of the run there is a large amount of liquid flowing, but there is also a large 

quantity of nitrogen degassing, so it is hard to tell how this will effect the calculations. 

2. The capped tee is near the beginning of the piping layout, while the void sensor that is used 

for the calculation of the mixture density is at the end. 

3. The fact that the literature value for the union is actually considered as if the fitting is just a 

section of straight pipe. In theory, this should be the case since the union when assembled 

should not interfere with the flow, but there are still ridges from the male and female sections 

connecting on the inside of the union, possibly causing disturbances to the flow. 

4. The role of the two-phase flow in the experiments. An assumption made when modeling 

two-phase flow through pipe fittings is that the differences from single-phase liquid flow are 

marginal, but this may not be the case. The void fraction may play a large part in the pressure 

drop experienced through a pipe fitting since it will influence the flow conditions through the 

fitting. 

Figure 8-33. Cumulative Mass as a Function of Time for Runs #1 and #8. 

Time (ms)

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Cu ass (kg mulative M ) 0.0

0.5

1.0

1.5

3.0

3.5

2.0

2.5

4.0

4.5

5.0

Run #1

Run #8
780 Fluid Dispensing and Dispersion 

Overall, the liquid density yielded a better calculation than the mixture assumption with an average error

of 47 % compared with 155 %. These findings suggests that the phasic composition of the flow through

the fitting plays a major role in the pressure drop experienced at any instantaneous time during the

discharge and that local flow characteristics will play a large role in determining the magnitude of the

pressure drop. 

Table 8-4. Comparison of Experimental Pressure Drop Values to Literature Values. 

Run #8 Run #9 Run #10

Initial source vessel pressure (kPa) 2120 3915 4910

Void fraction 0.649 0.507 0.485 

Liquid density (kg/m3) 1403.5 1392.8 1389.0

Mixture density (kg/m 704.73 733.18 3) 514.43

Velocity (m/sec) 3.446 9.007 7.630 

90o Elbow 

Experimental ∆P (kPa) 9900 27800 36000

Literature value ∆P (mixture ρ) (kPa) 21594 (118 %) 106073 (282 %) 72775 (102 %) 

Literature value ∆P (liquid ρ) (kPa) 7915 (20 %) 53673 (93 %) 38414 (7 %)

Capped Tee 

Experimental ∆P (kPa) 11300 40400 62600

Literature value ∆P (mixture ρ) (kPa) 29778 (164 %) 195398 (384 %) 134059 (114 %)

Literature value ∆P (liquid ρ) (kPa) 14580 (29 %) 98871 (145 %) 70763 (13 %)

Union 

Experimental ∆P (kPa) 11100 31500 50400 

Literature value ∆P (mixture ρ) (kPa) 17048 (54 %) 83742 (166 %) 57454 (14 %)

Literature value ∆P (liquid ρ) (kPa) 6248 (44 %) 42373 (35 %) 30327 (40 %)

The third set vertical split 

ould be any 

difference in ation of the

flow m n

all the liquid he top

would have 

observed, as vertical

e case for the

entire test the bubbly 

of experiments also used an alternative-piping configuration, which included a 

of the flow (see Figure 8-20). The goal of these runs was to examine whether there w

pressure drop between the two legs of the split. At slower flow velocities, separ

ay occur based on the flow regime of the discharge. For example, if the flow were stratified the

may flow through the bottom leg of the split and the entire vapor may travel through t

leg. This would be evident from the difference in pressure drop between the two legs since the vapor 

a much lower pressure drop than the liquid. In the experimental runs, no such trend was

can be seen in Figure 8-34, which depicts the pressure drop across both legs after a

tee split. The plots for both the top and bottom branch are almost identical, which was th

ed pressure range of 2140 kPa to 4910 kPa. At these high velocities the flow is in

flow regime resulting in an even split between the two branches. 
Fluid Transport Through Piping 781

ops across ottom from 

The fourth set of experiments used the same pipin uration as th et, the straigh but the 

te The main rved er th ns 

w the liquid vaporized. If a c made #5 

(HFC-227ea) and Run #16 (HFC-125), which have initial source vessel pressure within 5 kPa of each 

other, there is an undeniable difference in the temp traces in the collection vessel. 

A re in Run abou d to a rop 

o other temper etwee re simi be 

ue to the fact that the flow passes through the pipe at a fast rate with a high convective heat transfer 

y, a sudden slow down in the pressure 

 after the initial pressure drop was observed, which might indicate a slight recovery. 

Figure 8-34. Pressure dr top and b branch tees Run #13. 

g config e first s t pipe, 

st fluid was changed to HFC-125. difference obse in these runs ov e HFC-227ea ru

as the drop in temperature as omparison is between Run

erature 

s Figure 8-35 shows, the temperatu #5 only drops t 3 °C compare temperature d

f almost 35 °C in Run #16. The ature traces b n these runs a lar. This may

d

coefficient, which causes the fluid to warm up. However, in the collection vessel, the volume/surface 

ratio is much larger and convective heat transfer to surface area is smaller. Although, it would have been 

beneficial to measure the temperature at the end of the pipe to justify this theory, it was unable to take this 

measurement due to a thermocouple failure. Once the liquid reaches the collection tank, it must vaporize 

to reach the saturation conditions in the collection vessel, causing a drop in temperature. These 

conditions did not significantly effect the other measurements near the end of the pipe for either fluid. 

For instance, for either fluid, the void fraction followed a similar trend as expected from the previous 

runs, it dropped off as the initial flow passed the sensor and then rose slowly until the liquid ran out, then 

it returned to the all vapor value, as shown in Figure 8-36 and Figure 8-37. During runs with both of 

these fluids, a noticeable pressure recovery due to the degassing of the nitrogen was not observed, which 

was seen in previous studies. Although, when examined closel

decay

Run #13

Time (ms)

0 500 1000 1500 2000 2500 3000

Pressur

e Drop across Tee (kPa)

0

20

40

60

80

100

120

140

160

Top Branch

Bottom Branch
782 Fluid Dispensing and Dispersion 

Time (ms)

0 500 1000 1500 2000 2500 3000

Temperature (

oC)

-10

-5

0

5

10

15

20

25

30

35

Run # 5

Run #16

Figure 8-35. Comparison of Temperature Traces in the Collection Vessel from Runs #5 

Figure 8-36. Void Fraction Measurements from Run #5. 

and #16. 

0.0

0.2

0.4

0.6

0.8

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction 1.0

1.2

Time (ms)

Void Fraction

0.0

0.2

0.4

0.6

0.8

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction
Fluid Transport Through Piping 783

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

V

oid Fraction

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

V

oid Fraction

T

shown on the source vessel pressure trace bet itial pressure drop and the filling of the pipe. 

This can be seen best by once again comparing Runs #5 & #16, where there is a slight “bump” in the 

source vessel pressure trace at about 400 ms of Run #16, as shown in Figure 8-38 and Figure 8-39. The

absence of a more pronounced pressure recovery due to the degassing of nitrogen can be accounted for by

either of two reasons: the speed of the flow is too great for a noticeable increase in pressure from 

degassing to be observed at any one point, or the degassing took place so gradually over the run 

preventing any noticeable increase. It was unknown whether the degassing occurred at some point since 

the void fraction validated that a two-phase flow existed. However, it was certain that this was not due to 

vaporization since there was no temperature drop. 

The last sets of runs were conducted during preliminary tests of the instrumentation after installation in 

the system. The first test using water, Run #18, allowed for testing the mass flow rate sensor. As can be

seen in Figure 8-40, this test worked out very well and gave an excellent representation of the

instantaneous mass inventory in the source vessel. This test also showed that the thermocouples could 

pick up quick drops in temperature, as shown in the pipe position 1 trace of the film thermocouple, which 

picked up the nitrogen expansion at the end of the run, as shown in Figure 8-41. The second test, Run

#19, provided an excellent sample of the capabilities of the capacitance probe for measuring void fraction. 

Since there was no vaporization or dissolution of gas in this run, the void fraction should go from a value 

of 1.0 to 0.0 as the liquid flowed. This is exactly what was found at the beginning of the run until it

stopped at precisely the same point as the temperature dropped, signifying the start of the nitrogen

xpansion through the system, as can be seen in Figure 8-42. The final set of experimental runs used 

carbon dioxide as a test fluid and was conducted with an open collection vessel to prevent a high pressure 

Figure 8-37. Void Fraction Measurements from Run #16. 

his conclusion is supported by the fact that in the HFC-227ea runs there was a much smoother transition

ween the in

e
784 Fluid Dispensing and Dispersion 

at the end of the r e time of the film

thermocouples and what range of temperature drop they could collect. The thermocouples were able to

pick up a quick drop in temperature of up to -40 °C.

un. The goal of these tests was to get a grasp on the respons

Time (ms)

Pressure (kPa)

Time (ms)

Pressure (kPa)

Figure 8-38. Pressure Traces from Run #5. 

Figure 8-39. Pressure Traces from Run #16. 

Time (ms)

Pressure (kPa)

Time (ms)
Fluid Transport Through Piping 785

3.0

3.5

4.0

Figure 8-41. Temperature Traces at Various Positions from Run #18. 

Figure 8-40. Mass Inventory in the Source Vessel from Run #18. 

0.0

0.5

1.0

1.5

2.0

2.5

-500 0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Cumulative Mass [kg]

Time (ms)

C

umulativ

e Mass (k

g) 0.0

0.5

1.0

1.5

2.0

2.5

-500 0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Cumulative Mass [kg] 3.0

3.5

4.0

Time (ms)

C

umulativ

e Mass (k

g)

Time (ms)

Temperature (oC)
786 Fluid Dispensing and Dispersion 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

Figure 8-42. Void Fraction Measurements from Run #19. 

8.3.7 Comparison of Code Predictions to Experimental Data 

ment of 

ere

nt, a 

from or 

code 

 these 

throug

carried 

e

f discharge, and also measured the void fraction near the pipe exit. 

This section discusses some of the code assessments carried out against experiments. Early assess

the FSP code was against halon 1301 discharge experiments reported by Elliott et al.10 These tests w

carried out with three different system configurations. These included a bottle-nozzle arrangeme

bottle with straight pipe, and a bottle with a straight pipe branching to two separate exit legs. Test 146 

 Elliott et al.10 was a bottle-nozzle arrangement. This test was used in early assessment of FSP f

the gas release model. The other configurations tested by Elliott et al.10 were also simulated during

various developmental stages of the code. The results generally showed good agreement between 

calculations and experimental data. A re-assessment of the final code version against data from

configurations was not carried out. This was primarily because the tests were conducted with halon 1301,

and the intent of code development was for alternate fluids. The expectation is that the final version of

FSP would be able to simulate these tests quite well. Other experimental data on suppressant discharge

h typical delivery systems have been compiled and reported by Yang et al.2 and Pitts et al.9

This section presents the assessment of the code carried out against some of the experiments reported in 

Yang et al.2 The experiments were conducted at NIST, and included a series of discharge tests using 

several agents (including halon 1301). The code was also assessed against current experiments 

out as a part of this code development project by examining several piping configurations, with

HFC-227ea and with HFC-125. These experiments are particularly useful for code assessment because, 

in addition to the usual measurement of pressure, the experiments were able to estimate the mass flow rat

o
Fluid Transport Through Piping 787

Code Assessment against NIST Test Data 

The basic design of the NIST experimental apparatus consisted of a storage vessel (or pressure vessel)

discharge piping, and a recovery tank. A nitrogen make-up tank was connected to the pressure vessel t

ulate constant-head discharge if needed. The pressure vessel was fitted with a quick release va

the bottom. Figure 8-43 shows the test apparatus. The data included vessel pressure and pressures a

various locations along the discharge piping. Several discharge piping configurations were used. These 

included: (1) 3.5 m straight pipe discharge; (2) 3.5 m pipe with 90° bend; (3) 4.5 m pipe with 90°

(4) 3.5 m straight pipe with expansion from 9.5 mm ID to 15.9 mm ID; (5) 3.5 m straight pipe with 

contraction from 15.9 mm ID to 9.5 mm ID; and (6) 4.5 m, 15.9 mm ID tee configuration. Two pipe sizes 

 used for all configurations, unless otherwise stated, and these were 9.5 mm ID and 15.9 mm ID.

The various configurations are shown in Figure 8-44. 

,

o

sim lve at

t

 bend;

were

nducted

with HFC-227ea. Note that the test identifier in the first column is actually the Figure Number in

Figure 8-43. NIST Test Apparatus.2

Four agents were tested in these experiments. These were halon 1301, HFC-125, HFC-227ea and CF3I. 

The assessment presented here is only for the HFC-227ea experiments. Table 8-5 lists the tests co

Appendix II of the NIST Report (Yang et al.2

). 

Four tests were simulated using FSP. These are Tests B-59, B-68, B-61, and B-60. Together they

represent a variety of piping configurations. The results of the simulations are presented below. 

A FSP input model for each discharge piping configuration was developed. The following geometrical 

information was obtained from Yang et al.2 
788 Fluid Dispensing and Dispersion 

Storage Vessel Volume: 4.06 × 10-3 m3

 m

Storage Vessel ID: 100 mm

Discharge Valve: 31.8 mm inlet to 44.5 mm exit 

Discharge Valve Stroke: order of 10 ms 

Nitrogen Make-up Tank: 88 × 10-3 m3

Nitrogen Charge Tubing: 19.1 mm ID 

Nitrogen Solenoid Valve: 30 kPa pressure difference opening, stroke 50 ms

Discharge Piping Sizes: 9.5 mm and 15.9 mm ID 

Discharge Piping Lengths: 3.5 m and 4.5

Recovery Tank Volume: 15 × 10-3 m3 

Figure 8-44. Piping Configurations 

for NIST Experiments. 

FLOW CONFIGURATION

(a) 

3.5 m, straight

(b) 

3.5 m, with 90o bend

(c) 

4.5 m, with 90o

 bend

(d) 

Expansion, 9.5x15.9 mm

(e) 

Contraction, 15.9x9.5 mm

(f) 

Tee 

Receiver 

Receiver 

Receiver 

Receiver 

Receiver 

Receiver 
Fluid Transport Through Piping 789

Table 8-5. Test Matrix from NIST Experiments. 

Test 

Identifier 

Pressure 

(MPa) 

Fill Volume 

(%) Configuration 

B-54 2.75 56.5 straight pipe, 9.5 mm ID, 3.5 m long 

B-56 4.12 60.2 straight pipe, 9.5 mm ID, 3.5 m long 

B-58 4.12 49.2 3.5 m, 90-deg bend, 9.5 mm ID 

B-59 4.12 49.2 4.5 m, 90-deg bend, 9.5 mm ID 

B-60 4.12 49.0 straight pipe with contraction 

B-61 4.12 49.0 straight pipe with expansion 

B-66 2.75 54.1 straight pipe, 15.9 mm ID, 3.5 m long 

B-68 4.12 49.4 straight pipe, 15.9 mm ID, 3.5 m long 

B-71 4.12 49.4 3.5m, 90-deg bend, 15.9 mm ID

The abo dev dels for FSP for each of the tests. The models 

are not descri nted he similar, conceptually, to the sample problem 

describe 7

 The el (called storage tank in these tests) and discharge 

piping were each modeled with PIPE components, with a VALVE component in between them, 

simulating the initiation of the discharge process. In modeling the discharge piping, junctions were 

located at the physical locations of area changes (contraction or expansion) and bends. Appropriate loss 

coefficients were entered to simulate the energy losses at these locations. Figure 8-45 shows the general 

FSP model used for these simulations. 

Figure 8-45. FSP Input Model. 

ve information was used to elop the input mo

bed in detail or prese re. They were very

d in detail in Tuzla et al. supply vess

Tmdpvol

500

Nitrogen Make-up 

Tank

Recovery Tank

Valve 405

Pipe 300

Valve 203 Dischar Pipe

Test Section

Pipe 203

Sngljun 301

snglvol

205

ge

Tmdpvol

500

Nitrogen Make-up 

Tank

Recovery Tank

Valve 405

Pipe 300

Valve 203 Dischar Pipe

Test Section

Pipe 203

Sngljun 301

snglvol

205

ge
790 Fluid Dispensing and Dispersion 

Time (s)

p (Pa)

These cases were all run 10-8 m. The discharge

coefficients at the xit w s 1.0, 0.8 and 0.8 for the subcooled, two-phase, and single

ph condi spectivel he value of Γ0 was set at tests. Figure 8-46,

Figu 7, Figure , and Fig -49 respectively d pressure

respo n the sup essel, for T -59, B-68, B-61, he pressure 

histories at various locations along the discharge piping. G the measured

pressure would increase sharply as scharge was initiated, and then decrease gradually as the fluid 

left t tem. Thi was picke by the code. Overall tative trends in

the pressure history he time fo plete discharge of th e at which the

pressure drops to its lowest value, th e seems to calcul . A better

agree between lation and bably b his has not

been pted here, primarily beca ere are inherent un s, and a code 

ser would normally vary these parameters in design calculations to get conservative results for design 

Figure 8-46. Comparison of 

Calculated and Measured Bottle 

Pressure for B-59. 

Figure 8-47. Comparison of 

Calculated and Measured Bottle 

Pressure for B-68. 

with the value of rc in the range of 7.5 × 10-9 m to 1.0 ×

system e ere chosen a

ase vapor tions, re y. T 10,000 for the

re 8-4 8-48 ure 8 show the calculated and measure

nses i ply v est B and B-60. Not shown here are t

enerally, at these locations,

the di

he sys s trend d up , the code picks up the quali

. If t r com e agent is taken as the tim

e cod ate this generally within about 25 %

ment calcu data could pro e obtained by varying rc and Γ0. T

attem use th certainties in these parameter

u

purposes. Generally, a higher value of Γ0 would release more dissolved gas earlier in the transient. This

would generally delay the complete discharge of the bottle slightly. Users can utilize this information to

develop conservative designs in applying the FSP code. 

Time (s)

p (Pa)
Fluid Transport Through Piping 791

ode Assessment Against Current Test Data 

In this section a detailed comparison of the computer code predictions and the experimental values for a

rapid transient discharge of a suppressant flow will be examined. To fully test the code, all aspects of an

actual suppressant discharge must be considered. For this reason, the current experimental data should be 

the benchm most extensive experimental data to date. This is due 

ures, void fraction, and mass flow rate which, were previously

 data for a number of different flow conditions and 

piping configurations have been obtained. 

When using the computer code to make predictions, it was necessary to determine a few operating 

parameters to represent the operating conditions of a specific run. Some of these parameters are 

straightforward and pertinent to the piping configuration, such as diameters, lengths, etc., and operating

conditions such as initial pressure, temperature, etc. However, some of these parameters are part of the 

modeling used in the code. One of these models is the gas dissolution model, as discussed above.

Figure 8-48. Comparison of 

Calculated and Measured Bottle 

Pressure for B-61. 

Figure 8-49. Comparison of 

Calculated and Measured Bottle 

Pressure for B-60. 

Time (s)

p (Pa)

Time (s)

p (Pa)

C

ark for comparison since it includes the 

to the fact that data for local temperat

unavailable, were measured. In addition, extensive
792 Fluid Dispensing and Dispersion 

Dependent on the fluid used during the discharge, the gas dissolution model requires two constants: the 

critical bubble radius when nitrogen is released from the fluid and the release rate of nitrogen. 

The critical radius can be found for a specific run by estimating when the release of nitrogen begins. This 

is the point near the beginning of the run when the pressure stops dropping rapidly, represented as a 

change in slope in the pressure trace. With this pressure and the surface tensi

radius can be calculated as described earlier. After examining th ), 

it was determined that the value was in the range of 5 nm to 20 f 

degassing, was found to fall in the range from 1000-10,000, depe he last parameter 

that needs to be defined as input to the code is the discharge coefficient for choked flow conditions. Since 

the default is 1.0, it is expected that the value must be relatively close to this value. 

For ease in use and consistency, it is desirable to choose one value for each of these parameters to run the 

computer code. To determine the appropriate values for these arameters, a sensitivity analysis of the 

effects of varying these parameters on the code’s output was performed, and the results were compared 

with experimental data. The experimental Run #4 was used for this purpose. This run was chosen ove

the others because it was one of the repeatability tests and was in the range of typical suppressant 

discharge applications. 

The first sensitivity study examined the effect of critical radius on the computer code output. To isolate 

the effect of changing this parameter, the values for the gas release rate and the discharge coefficients 

were kept constant at 1000 and 0.8, respectively. The calculations showed that a lower value for the 

critical the source vessel pressure trace to occur later. Therefore, this 

pa hen the gas begins to release from the liquid. By comparing the 

ca and 10 nm with the experimental results, as seen in Figure 8-50, 

a critical radius of 10 

The second sensitivity study was to identify a value for the rate of nitrogen gas release, with the discharge 

coefficient and the critical radius kept constant at 0.8 and 7.5 nm, respectively. This rate influences the 

speed at which the nitrogen gas is released once the process begins, thus changing the shape of the 

ressure-time history. As shown in Figure 8-51, the pressure trend remains straight and uniform at lower 

gas release rates; however, there is a pressure recovery or “bump” in the trace at higher release rates. 

is hard to determine the best value to use for this 

parameter so other output parameters from the calculations were examined. The void fraction results are 

on of the fluid, a critical

e first set of experimental Runs (#1-#7

 nm. The second parameter, the rate o

nding on the system. T

p

r 

 radius caused the slope change in

rameter is important for determining w

lculations using critical radii of 7.5 nm

nm was chosen. 

p

Based solely on the pressure-time history results, it 

shown in Figure 8-52, which indicates that average void fraction increases with the gas release rate 

parameter. This figure, the other does not, shows that a value just below 2500 kg/m3

 s appears to be 

appropriate. Based on the observations from the above two figures, a gas release rate value of 

2000 kg/m3

 s was chosen. 
Fluid Transport Through Piping 793

Figure 8-50. Comparison of Experimental and Predictive Source Vessel Pressure Data in 

Sensitivity Study on Critical Radius Value for Conditions of Run #4. 

Figure 8-51. Comparison of Experimental and Predictive Source Vessel Pressure Data in 

Sensitivity Study on Gas Release Rate Value for Conditions of Run #4. 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

r = 7.5 nm (blue)

r = 10 nm (red)

experimental (black)

Gas Release Rate = 1000 kg/m3/s

Discharge Coefficient = 0.8

Time (ms)

Pressure (kPa)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

r = 7.5 nm (blue)

r = 10 nm (red)

experimental (black)

Gas Release Rate = 1000 kg/m3/s

Discharge Coefficient = 0.8

Time (ms)

Pressure (kPa)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 300

Time [msec]

Pressure [kPa]

Gamma = 1000 kg/m3/s (blue)

Gamma = 2500 kg/m3/s (red)

Gamma = 5000 kg/m3/s (green)

Experimental

Critical Radius = 7.5 nm

Discharge Coefficient = 0.8

Time (ms)

Pressure (kPa)

3000
794 Fluid Dispensing and Dispersion 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 300

Time [msec]

Void Fraction

Gamma = 1000 kg/m3/s (blue)

Gamma = 2500 kg/m3/s (red)

Gamma = 5000 kg/m3/s (green)

Experimental

Critical Radius = 7.5 nm

Discharge Coefficient = 0.8

Time (ms)

V

oid Fr

a

ction

3000

Figure 8-52. Comparison of Experimental and Predictive Void Fraction Data in Sensitivity

Study on Gas Release Rate Value for Conditions of Run #4. 

The last sensi r influences 

were only 0.9 for the

discharge coe

With all of #4 was 

conducted. T 53

and Figure 8-

with an entire 

experim of time are

ents. The only 

 the different 

ately

1800 m e of discharge

time. 

tivity analysis was to pick a value for the discharge coefficient. This paramete

when and where choking occurs in the system. Values ranging from 0.75 to 1.15 were tried, and there 

 negligible differences in the output. Therefore, it was decided to use a value of

fficient. 

the operating parameters chosen, a final comparison with the experimental data of Run 

he calculations show good agreement with the experimental results, as shown in Figure 8-

54. 

In the following discussion, the focus is on comparing the computer code prediction 

ental run (Run #5). The results for cumulative mass in the source vessel as a function 

shown in Figure 8-55. The prediction agrees well with the experimental measurem

noticeable difference is the final mass value and the speed of the discharge represented by

slope gradients. Even with these differences, the prediction gives an end-of-liquid flow at approxim

s compared to a measured time of 1600 ms in the experiment, a very good estimat
Fluid Transport Through Piping 795

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3000

sure Data 

Figure 8-54. Comparison of Experimental (in black) and Predictive (in red) Void Fraction 

Data Using Final Values for Code Operating Parameters for Conditions of Run #4. 

Figure 8-53. Comparison of Experimental (in black) and Predictive (in red) Pres

Using Final Values for Code Operating Parameters for Conditions of Run #4. 

0.0

0.8

1.2

-500 0 500 1000 1500 2000 2500 300

1.0

0.2

0.4

0.6

0

Time [msec]

Void Fraction

Time (ms)

id Fr

a

ction

V

o

3000
796 Fluid Dispensing and Dispersion 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Cumulative Mass [kg]

Time (ms)

Cumulativ

e M

ass (kg)

3000

Figure 8-55. Comparison of Cumulative Mass for Experimental Run #5 (black) and 

Predictive Computer Code Data (red). 

The next comparison examined is the void fraction experienced at the end of the piping system before the

discharge reached the collection vessel. Again, the agreement between the prediction and experiment is

, as shown Figure 8-56. While the experiment was influenced by the local flow regime giving the

output a fluctuating appearance, the prediction has a smooth trace due to the fact that the void fraction

culated based on mass balance terms giving an average void fraction value for the am

liquid and vapor present in the system. A similar trend can be seen in both, a sudden drop as the pipe is

filled with liquid and then an increase as nitrogen comes out of solution and raises the average am

gas in the flow until the run ends with no more liquid flowing. The only glaring difference is in the fi

value reached at the end of the run. The prediction never goes back to an all-vapor reading of 

indicating that in the simulation there is still liquid present in the pipe. In a realistic situation, the liquid 

would eventually drain into the collection vessel since it is the lowest part of the system

prediction is finding this value through a mathematical simulation, so it may not account fo

Neglecting this problem, a good representation of the void fraction can be found using the prediction. 

good

was cal ount of 

ount of 

nal 

1.0,

, but the

r this. 
Fluid Transport Through Piping 797

Figure 8-56. Comparison of Void Fraction for Experimental Run #5 (black) and Predictive 

Computer Code Data (red). 

The most important comparison for this study is a comparison of the experimental and calculated pressure 

traces since pressure is what drives the discharge and delivers the suppressant to the fire. Figure 8-57, 

Figure 8-58, Figure 8-59, Figure 8-60, and Figure 8-61 show the prediction compared to the experiment 

for the pressures in the source vessel, at pipe position #1, at pipe position #2, at pipe position #3, and in 

the collection vessel, respectively. They all agree very well with the experimental data, with the only 

discrepancy being the final pressure at the end of the run. While the shape of the curves varies slightly, 

they all show the same trend and a similar slope as the pressure decreases during the discharge. This 

observation is most exciting since most of the experimental data available is in the form of pressure 

traces, allowing for the code to be more widely used in comparisons and in simulating the output of 

various system configurations. 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Void Fraction

Time (ms)

Void Fraction

3000
798 Fluid Dispensing and Dispersion 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 300

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3000

Figure 8-57. Comparison of Source Vessel Pressure for Experimental Run #5 (black) and 

Predictive Computer Code Data (red).

Figure 8-58. Comparison of Pipe Position #1 Pressure for Experimental Run #5 (black) 

and Predictive Computer Code Data (red). 

0

500

1000

1500

-500 0 500 1000 1500 2000 2500 300

2000

2500

3000

3500

4000

4500

0

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3000
Fluid Transport Through Piping 799

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3000

Figure 8-59. Comparison of Pipe Position #2 Pressure for Experimental Run #5 (black) 

and Predictive Computer Code Data (red).

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3000

Figure 8-60. Comparison of Pipe Position #3 Pressure for Experimental Run #5 (black) 

and Predictive Computer Code Data (red). 
800 Fluid Dispensing and Dispersion 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

k

P

a)

3000

Figure 8-61. Comparison of Collection Vessel Pressure for Experimental Run #5 (black)

and Predictive Computer Code Data (red). 

While also

special 

the friction 

throug ental 

d

e

es from 

stem.

erature 

f the system, it predicts a much lower temperature than the experimental measurements. The

co

largest temperature changes

these comparisons were available with all of the runs conducted in this study, there were 

measurements made in some cases. For instance, experimental measurements of the pressure drop 

across different pipe fittings were conducted. While the prediction used a literature value for 

loss factor associated with the fittings, comparison of the pressure drop across these fittings could still be

made. This provides an indication of whether the literature values are accurate for a two-phase flow 

h different pipe configurations. Figure 8-62, Figure 8-63, and Figure 8-64 show the experim

data for Run #9 compared to the predicted data for the pressure drop across a capped tee, 90° elbow, and 

connecting union, respectively. This run used the simpler of the two alternative piping configurations

(see Figure 8-19). The comparisons generally show reasonable agreement; however, the predicte

pressure starts to fall earlier than the measurement. The experimental pressure trace exhibits a sudden

drop when the liquid runs out at the initiation of the vapor/gas flow. Although the calculation does not

predict a sudden drop in pressure at the end of the liquid flow, it shows an end of the run in the sam

general vicinity as the experimental trace, implying that it is most likely at the end of the liquid flow. 

The last comparison made dealt with the temperature measurements. Since the predictive code does not 

consider heat transfer between the fluid and the piping, the only real temperature variation com

any phase change in the system or any compression or expansion of the contents of the sy

Specifically, degassing of the dissolved nitrogen and the adiabatic expansion of the nitrogen near the end 

of the run will be the main contributors. Because the code is not influenced by the ambient temp

o

mparisons in this analysis are for experimental Run #16, which used HFC-125 as a test fluid. The

were experienced for this fluid. 
Fluid Transport Through Piping 801

0

50

100

150

200

250

300

350

-500 0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3500

F

(bla d).

r Code Data (red). 

igure 8-62. Comparison of Pressure Drop across a Capped Tee for Experimental Run #9

ck) and Predictive Computer Code Data (re

100

150

200

250

300

350

Pressure [kPa] Pressure (

kPa)

0

50

-500 0 500 1000 1500 2000 2500 3000 350

Figure 8-63. Comparison of Pressure Drop across a 90° Elbow for Experimental Run #9 

(black) and Predictive Compute

0

Time [msec]

3500

Time (ms)
802 Fluid Dispensing and Dispersion 

0

20

40

60

80

100

120

140

160

180

200

-500 0 500 1000 1500 2000 2500 3000 3500

Time [msec]

Pressure [kPa]

Time (ms)

Pressure (

kPa)

3500

Figure 8-64. Comparison of Pressure Drop across a Union for Experimental Run #9 

(black) and Predictive Computer Code Data (red). 

In Figure 8-65, a comparison is made between the experimental measurements of the source vessel

perature using shielded thermocouple placed at the bottom of the vessel and immersed in the fluid and 

the fluid temperature predicted by the code. The trends in the predictions and measurements show good

qualitative agreements. Figure 8-66 illustrates a temperature comparison between predictions 

surements for the pipe position #1 in the piping system. In this case, the differences betw

calculated and measured values are more pronounced than in the source vessel comparison. As expected

the heat transfer coefficient in the pipe is greater than anywhere else in the system, and the short-com

of excluding fluid-to-pipe heat transfer in the code are most noticeable in this region. A comp

predicted and measured gas temperature in the collection vessel is shown in Figure 8-67. The initial 

perature drop is due to the fact that the liquid is evaporating to raise the pressure to its saturation

equilibrium value. This trend stops when the pressure rises high enough that there is no longer any

for the liquid to evaporate. Both the prediction and the experiment capture such trend in the temp

tem

and 

mea een 

,

ings 

arison of 

tem

 need 

erature

traces. 
Fluid Transport Through Piping 803

Fi 6

Figure 8-66. Comparison of Pipe Position #1 Fluid Temperature for Experimental Run 

#16 (black) and Predictive Computer Code Data (red). 

gure 8-65. Comparison of Source Vessel Fluid Temperature for Experimental Run #1

(black) and Predictive Computer Code Data (red). 

-15

-10

-5

0

5

10

15

20

25

-500 0 500 1000 1500 2000 2500 300

30

0

Time [msec]

Temperature [C]

Time (ms)

T

e

m

perat

ure (oC)

3000

-15

-10

-5

-500 0 500 1000 1500 2000 2500 30

0

5

10

15

20

25

30

Temperature [

C]

0

Time ( Time [mmsecs)]

Temp

erature (oC)

3000
804 Fluid Dispensing and Dispersion 

-20

-15

-10

-5

0

5

10

15

20

25

30

-500 0 500 1000 1500 2000 2500 3000

Time [msec]

Temperature [

C]

Time (ms)

T

e

m

perature (oC)

3000

Figure 8-67. Comparison of Collection Vessel Gas Temperature for Experimental Run 

#16 (black) and Predictive Computer Code Data (red).

8.3.8 

agree twocy.

s, it

mu

would n due to 

some

put.

the sim

cum

 to

8) were conducted with low downstream pressures so that flashing could occur in the pipe directly after 

 The code would not accept these conditions to run the 

si e

downstream pressure s of the test fluid in

Assessment of Fluid Transport Model 

Overall, comparisons between the predictions and the experimental runs generally show reasonable 

ments. In most cases, the prediction gives good estimation of the physical characteristics of a

phase flow in a model system. The code even handles two different test fluids with reasonable accura

It also predicted three different piping configurations well, demonstrating its versatility in modeling other

potential systems. While these points support the code’s robustness for use with suppressant system

st also be noted that there are a few limitations of the code. The most notable one is that the code

ot always work for some initial conditions for a specific test fluid. This is most likely

 limitation on the thermodynamics package. If this situation occurs, the user must slightly adjust the 

actual run condition in order to fall into a region of the thermodynamics package that will yield an out

For example, an error occurred before the program could complete the simulation for the experimental 

Run #5. However, changing the ambient temperature from 31 oC to 30 oC in the initial conditions enabled 

ulation to completion. This was only a minor change, but it still made the simulation a bit

bersome.

Another area that caused problems was to simulate low-pressure runs (2000 kPa to 2500 kPa, initial 

source vessel pressure). There were two problems which arose during these tests. The first was similar

the problem stated previously due to the thermodynamics package. These experimental runs (Runs #1 & 

#

the start of the run and the actuation of the valve. 

mulation due to the fact that it identified a non-equilibrium condition in the downstream areas. Th

had to be raised to a pressure closer to the saturation condition
Dyamics of Fluid Transport in Cluttered Spaces 805

order for the code to run. The other problem associated with these low-pressure test runs was the high fill 

level used in the source vessel. In experimental Runs #1, #8, #11, #14, and #18, a fill level of 80 % to 

% was used to try and to reduce the amount of nitrogen present in the system. The hope was to keep 

stem pressure low enough to facilitate flashing of the suppressant during discharge. While t

initial conditions did not cause the code to stop running with an error, it did provide unexpect

mple, in Run #1, the total mass of test fluid (HFC-227ea) placed in the source vessel

g of the run was about 4.9 kg. However, the code prediction never approached that va

the predicted discharge; it reached a final value of about 3.1 kg. It is unclear at this time why the code ran 

reasonably well with a fill level of about 60 %, instead of the test fill level of about 85 %. This problem 

it the applicability of the code to moderately fill conditions. 

The last problem encountered executing the code was the high-pressure runs (4750 kPa to 5000 kPa, 

initial source vessel pressure). Once again, it was believed that the problem was caused by the properties 

package. The only way to get the code to run using these initial conditions was to lower the source vessel

erature considerably, while keeping the downstream temperature around the ambient value. Even

then, the desired operating pressure could not always be reached. For example, in Run #6, 

vessel temperature was dropped from 31 oC to 2 oC with an initial source vessel pressure of 4860 

place of 4910 kPa. In addition, the code tends to under-predict the total duration of discharge due 

 to the temperature dropping below the range of the thermodynamics package. Despite these 

90 

the sy he 

ed results. 

For exa at the

beginnin lue during

would lim

temp

the source 

kPa in 

most

likely

bserved problems, the code did a reasonable job in predicting the parameters (e.g., void fraction, mass 

inventor

le

The FSP code can, in principle, be extended to include other candidate fluids that exhibit transient two-

 in Tuzla et al.7

 for the incorporation of halon 1301,

itional chemical (and the accordant larger storage bottle, piping, etc.) would be needed, an 

undesirable outcome. In particular, high boiling suppressants (which tend to have high heat extraction

o

y, etc.) for most runs with initial source vessel pressures from 3000 kPa to 4500 kPa and a fill 

vel of about 65 %.

phase flow in piping system. The procedure outlined

CO2, HFC-227ea, and HFC-125 into FSP should be followed. In addition, a computational 

thermodynamic tool similar to REPROP or PROFISSY is needed to predict fluid properties for 

performing FSP calculations. Estimation of other input parameters like critical bubble radius and release

rate of dissolved gas for the fluid of interest can be made through sensitivity analysis of these parameters 

in FSP calculations and comparison to experimental data. 

8.4 DYNAMICS OF FLUID TRANSPORT IN CLUTTERED SPACES 

8.4.1 Spray Transport Past Generic Clutter Elements 

As discussed in Chapter 7, the NGP examined a wide range of potential candidates as alternatives to

halon 1301. Should the transport of a chemical from the distribution plumbing to the fire site be

inefficient, add

capacity) would be discharged in a liquid state, breaking into liquid droplets, and be entrained within the

flow passing through the nacelle, impinging on various objects prior to reaching the fire zone. Since 

halon 1301 was so efficient, research into understanding the engine nacelle airflow offered little

advantage. Today, however, a better understanding of the nacelle airflow and how it influences the 

spread of fires and fire extinguishing agents can have a large impact on the effectiveness of a halon 

replacement system. NGP research expanded the fundamental knowledge of spray interactions with 
806 Fluid Dispensing and Dispersion 

clutter (e.g., obstacles representing fuel and hydraulic lines, electrical wire bundles, etc.) to learn how 

well agents of low volatility might reach an unspecified downstream fire location. 

Disimile and coworkers conducted experiments focusing on the ability of sprays to pass through a series 

of cylindrical obstacles, representing generic clutter, while moving in a turbulent coflow.31 Since only 

transport, and not flame extinguishment, was to be studied, water was used as the test fluid. A low-speed 

flow facility, with the test section air speed ranging up to 12.0 m/s, was modified for the current program. 

The major components of this facility include an inlet contraction, turbulence generator, test section, 

clutter section, and the return and separation plenum (Figure 8-68). The flow is from left to right. They 

collected three-dimensional velocity and diameter data at two locations downstream for nine 

combinations of clutter spacing and coflow airspeed. 

A large grid consisting of several 25.4 mm wide, 6.4 mm thick, sharp-edged flat steel slats, spanning the 

e in a checkerboard pattern with open cell 

dimension between the slats of 51 mm × 51 mm. This grid is also visible in Figure 8-68. Velocity 

test section. These elements were cylindrical segments made from PVC. The elements had an outer 

Figure 8-68. Zone A of the Test Section. 

cross-s ctional area of Zone A of the test section, was assembled

surveys using constant temperature anemometry were acquired downstream of the turbulence generator, 

at x = 711.2 mm ± 0.8 mm. A wave-like distribution of the streamwise component of the mean velocity 

was observed, with velocities ranging from approximately 3.7 m/s to 5.0 m/s. Although general 

symmetry was observed, it appeared that the lower portion of the test section had a greater degree of 

unsteadiness. It is believed that the additional unsteadiness was a result of smoke generation supply tubes 

positioned at the entrance of the inlet contraction. In a similar manner, turbulent intensities were recorded 

and ranged between 10 % and 14 %. 

The clutter package used in the current test series can be seen installed within Zone A of the test section 

(Figure 8-68). The clutter package consisted of 16 two-dimensional elements, spanning the width of the 
Dyamics of Fluid Transport in Cluttered Spaces 807

diameter D of 50.8 mm ± 0.8 mm and were assembled to form three separate arrays with equally spaced 

rows of 5, 6, and 5 tube elements, separated vertically by 0.94 D between each cylindrical element. The

streamwise spacing between each clutter array was variable, ranging in terms of element diameter, from 

A three-dimensional phase Doppler interferometer (PDI) was used to simultaneously acquire velocity

com

 and 

diam

diam

nozzle 

eter 

f

clutter 

elem with

y.

se 

y and air speed, 13 air speeds were investigated ranging from 0.5 m/s to 6.5 m/s 

increments of 0.5 m/s. To measure the volume of water passing through the clutter configuration

accurately, a repeatable proc as followed. This included 

the water supply tanks being filled to the same initial starting volume of 303 L, the air speed and the 

ir speed. In fact, above 4.5 m/s less than 5 % of the liquid was 

captured, and the differences between the five clutter densities converged. However, with the air speed 

0.25 D to 2.00 D with an uncertainty of ± 0.06 D. 

The clutter arrangement was selected based on its geometric similarity to common elements found within 

aircraft engine nacelles. Many cylindrical elements fill the nacelle environment with various local

densities. With the capability of varying the streamwise distance between each array of clutter elements 

in the chosen clutter package, the clutter densities found within larger aircraft engine nacelles was 

simulated. 

ponents and the diameter of the liquid drops exiting the suppressant spray nozzle. Water and air are 

mixed by the dual fluid nozzle and travel toward the leading edge of the clutter package. The droplets not 

captured by the clutter package proceeded downstream, where their three-dimensional velocity

eters were measured. The measurement volume of the PDI system was located at 2.0 and 5.5 clutter 

eters downstream of the trailing edge of the clutter. 

The spray nozzle water flow was set and maintained at (17.1 ± 0.4) L/min, with a corresponding 

water pressure of (158 ± 14) kPa. The water flow was monitored using a turbine type flowm

positioned directly upstream of a pressure gage. The incoming air was regulated to a pressure o

(172 ± 3) kPa. The test matrix consisted of 18 experimental conditions. This included 13 air speeds, five 

clutter densities, and two downstream measurement locations. Clutter package densities were varied by 

changes in the streamwise spacing between individual clutter arrays. Since the leading edge of the clutter 

package was fixed, changing the array spacing affected the location of the trailing edge of the last 

ent. Therefore, to maintain a fixed downstream location of the PDI measurement volume

respect to the trailing edge of the clutter, the PDI measurement volume had to be moved correspondingl

To determine the volume of water transmitted through the clutter array as a function of the streamwi

spacing of the clutter arra

in

edure for measuring the liquid water volume w

nozzle air pressure set. A clock was then energized when the water pump was powered on such that the

water flow through the nozzle was set to (17.1 ± 0.4) L/min. Water drops that wetted the clutter pooled

on the individual elements and dripped down to a collection pan located beneath the clutter. Water

droplets that passed through the clutter into Zone B were deposited within the return plenum. The volume

of water collected directly under the clutter package was carefully measured, as was the water collected in 

the return plenum by using graduated containers. 

Figure 8-69 shows the percentage of water recovered directly under the clutter package as a function of 

element spacing and air speed. The general trend of the data suggests that the volume of the liquid 

collected decreased with increasing a

set to 0.5 m/s, the amount of water collected under the clutter ranged from 61.25 % (at 0.25 D spacing) to

37.50 % (at 2.0 D). As the spacing between the individual clutter rows was reduced, the amount of water
808 Fluid Dispensing and Dispersion 

captured increased. Specifically, as the streamwise spacing was reduced from 2.0 D to 0.25 D, the 

captured water increased to over 50 %. 

Figure 8-69. Clutter Recovery vs. Airspeed. 

Likewise, Figure 8-70 indicates the amount of water collected in the return plenum as percent of the 

initial volume. All five clutter densities are represented in this figure. The volume collected in the 

plenum increases as the air speed increases. It can be seen that the volume recovered in the plenum 

approaches 100 % as the air speed increases. 

Figure 8-70. Plenum Recovery vs. Airspeed. 

Coflow Airspeed (m/s)
Dyamics of Fluid Transport in Cluttered Spaces 809

During the test evaluation of five clutter spacings and 13 air speeds, the percent of unaccounted water 

volume was determined. In all cases, the difference was random and less than 4 %. As a measure of

repeatability, no less than 96 % of the total supply volume was recovered in the combined clutter and 

ele ining 

f

8.4.2 

wellrest

The to 

mass of liquid agent impinging on the obstacle, the mass that dripped off the

bstacle, and the mass transported past the obstacle. This geometry also prevented liquid droplets

downstream of the obstacle . 

ato

sy -

 by

lacing a square layer of wire mesh screen downstream of the honeycomb. For these experiments, the

incoming air was directed entirely through a distributor plate with steel wool, circular cross-sectional area

plenum return recovery tanks. 

The results of these experiments clearly show the effect of cylindrical clutter elements on the transport of 

liquid droplets and provide benchmark data to develop first-generation computer models to aid in the 

design of fire suppression systems for aircraft engine nacelles. Although this work only addresses round 

ments of uniform size and distribution, it provides a framework to generate a database for exam

the effects of different size, geometry, and density of clutter elements as well as different levels o

turbulence on droplet transport for nacelle applications. 

Spray Interaction with Unheated and Heated Clutter Elements 

For the next level of understanding, Presser and coworkers injected liquid fire suppressants into a 

characterized, homogenous, turbulent flow field, and investigated the droplet transport processes under a 

variety of conditions, as well as the interaction of the spray with different obstacles.32 Also of inte

was determining whether droplets rebounded and/or shattered off the surface of an obstacle. 

experimental arrangement is shown in Figure 8-71. The experiment was oriented horizontally

enable estimating the 

o

from falling back upstream into the oncoming stream

Figure 8-71. Heated 

Cylinder Test Section. 

The initial agent was water and was supplied to the flow field with a 60o hollow-cone pressure-jet

mizer. In the octagon-shaped PMMA chamber, the front face supported the inlet passages for the 

liquid agent and air, and the back face supported the exhaust passage, which served to form a closed

stem with defined boundaries. A honeycomb layer was used to straighten the air flow, which was co

positioned around an injector for the agent. Grid-generated turbulence was imposed on the air stream

p
810 Fluid Dispensing and Dispersion 

of the honeycomb, and the m of the honeycomb), as 

shown in Figure 8-71. The face of the liquid atomizer was placed flush with the upstream side of the grid, 

ain spatial and temporal profiles of the size and velocity distributions), and 

visualization of the flow field. Measurements in the spray and flow field were carried out upstream and 

The cylinder had a diameter of 32 mm (305 mm in length), which was chosen because its diameter was 

 study the effects of a 

surface. A hole 

tance along 

the surface of 6.4 mm, with the thermocouple junctions placed about 3.2 mm of the surface with bored 

n through wire mesh screen (placed 25 mm downstrea

and centered within one mesh cell so that the liquid spray would be unimpeded by the grid. The steppermotor-driven traversing system translated the entire assembly, and permitted measurements of the flow 

field properties at selected locations downstream of the injector. Measurements included particle image 

velocimetry (PIV), PDI (to obt

downstream of the obstacles. 

Measurements were carried out with two obstacles, an aluminum cylinder and a more complex bodycentered cube (BCC) arrangement of wooden spheres and connecting posts. (See Figure 8-72 and 

Figure 8-73, respectively.) 

larger than the integral length scale of turbulence. The cylinder was heated to

heated surface on droplet vaporization and transport, as a droplet approached the heated 

was bored through the center for placement of a 250 W cartridge heater. The rod was also cut into two 

halves and 1 mm deep channels bored along one segment for placement of five K-type thermocouples. 

The thermocouples had an inconel sheath, ungrounded, and 0.8 mm in diameter (305 mm long). The 

thermocouples were placed in a cross pattern in the center of the rod (each separated by a dis

holes at each location). The central thermocouple was used for temperature control of the heater, which 

was positioned behind the thermocouples. 

Figure 8-72. Heated Cylinder. (A) Schematic and (B) Front View. 

Thermocouple for set point 

temperature
Dyamics of Fluid Transport in Cluttered Spaces 811

The BCC was composed of nine wooden spheres with a nominal diameter of 28 mm, all interconnected

with posts, as shown in Figure 8-73. The blockage ratio, or obstructed cross-sectional area for an

equivalent area encompassing a face of the BCC, was about 64 %. The obstacles were placed nominally

182 mm downstream of the honeycomb, and centered with the atomizer centerline. 

Figure 8-73. Body-centered Cube of 

Spheres. 

r layer region between the recirculation zone and free stream.

Surface cooling that resulted from spray impingement was around 50 % of the preset cylinder

64 %), there was both transport of droplets and 

as significantly more liquid accumulation and 

rded with a digital movie camera at 9 frames/s.

s are shown in Figure 8-74 for (a) seeded 

linder, and (c) combined droplet and seeded flow over 

flow field (see Figure 8-74A) and a relatively high 

behind the cylinder. On the other hand, the droplets

the surface of the cylinder while those droplets at 

linder with an increased radial component of

ved behind the cylinder in its wake. Droplets that

a rate of approximately one drop every 5 s. The

transport of droplets through the BCC (see Figure 8-74C) was interesting in that both the spheres and

connecting rods (that simulate cylinders) block the droplets, while the flow field traversing through the

obstacle provided an unobstructed path for the entrained droplets. Dripping was observed from each

sphere at a rate of approximately 1 droplet/s. If one assumes that droplets fall off each sphere at this rate,

one can determine that this liquid represents approximately 4.5 % of the inlet water flow (assuming a

28 mm

24 mm

28 mm

24 mm

PIV measurements were carried out in the droplet-laden, homogeneous turbulent flow over both the 

unheated and heated cylinder, and body-centered cube arrangement of spheres. Transport of both water 

droplets and seed particles was characterized upstream and downstream of these obstacles. Data were

recorded for the cylinder at ambient temperature and after being heated to 150 °C to estimate the effects

of the hot cylinder surface on droplet transport. The results indicated that smaller droplets were entrained

into the recirculation region behind the cylinder while the larger droplets impacted the cylinder surface, 

accumulated and dripped off, and/or rebounded off the surface and dispersed radially outward into the

free stream. The Weber number was too low to lead to droplet shattering. Significant spray cooling of 

the surface was observed for the heated cylinder, in addition to the presence of a vapor stream

downstream of the cylinder along the shea

temperature. For the BCC (with a blockage ratio of about 

seed particles around and through the BCC, as well 

dripping than for the cylinder. 

The droplet-laden flow field over each obstacle was reco

Examples of the observed droplet/particle transport processe

only and (b) droplet only flow over the unheated cy

the BCC. The seed was entrained in the turbulent 

concentration of particles was observed in the wake 

in the center of the spray were found to impinge on 

larger radial positions were transported around or past the cy

velocity (see Figure 8-74B). Few droplets were obser

impinged and wetted the cylinder surface dripped off at 
812 Fluid Dispensing and Dispersion 

dripped drople from digital

movies). Althoug of the spray

was still able 

Fields 

B: Heated 

-centered Cube 

 Direction is 

The above-mentioned laser sheet images indicated that dispersion of droplets/particles around the obstacle 

was dependent on its size. Comparison of the PIV velocity fields obtained with water droplets from the 

pressure-jet atomizer and 1 μm size seed particles formed from the fogging device also supported this 

finding. For example, the three components of droplet velocity for the flow over the unheated cylinder 

are presented in Figure 8-75. In this figure, three cases are presented that represent the flow with the seed

only, both seed and spray, and spray only. The black circle represents the position and size of the 

cylinder. The black contour lines represent stream traces (i.e., direction) of the in-plain velocity vectors.

t diameter of 8.5 mm, which was an estimated largest droplet size observed 

h the BCC had more dripping of liquid than the cylinder, the major portion

to traverse the obstacle. 

Figure 8-74. Photographs of 

Seed/droplet-laden Flow

around Obstacles. 

A: Unheated Cylinder; 

Cylinder; C: Body

of Spheres. Flow

from Right to Left. 

Comparison of the two cases with spray to the seed-only case indicated that the recirculation zone was 

somewhat larger for the spray cases. Larger size droplets required a longer distance to interact with the 

turbulent flow field, reduce their higher momentum, and be entrained into the recirculation zone, if at all. 

The stream trace (contour lines) also showed an unexpected pattern behind the cylinder near the

stagnation point. Instead of presenting closed loops that indicate a time-integrated recirculating pattern, 
Dyamics of Fluid Transport in Cluttered Spaces 813

the contours appear to emanate from the stagnation region. One possible explanation is that there is a 

strong spanwise flow along the length of the cylinder. It appeared to be generated by the cylinder and 

may be related to the finite cylinder length (with an aspect ratio of about 10:1). 

Figure 8-75. Variation of the Mean Streamwise and Cross-stream Velocities with 

Downstream Distance for the Unheated Cylinder. Contours are the Stream Traces of the 

In-plane Vectors Obtained from the Axial and Radial Components of Velocity. 

Figure 8-76 presents the velocity field around the BCC for the combined spray/seed case. Although the 

configuration was more complicated, there were still similar f tures to the cylinder case. The flow 

accelerated around the spheres and there was reverse flow in the wake region. In addition, the presence of 

a cross-stream component of the flow was evident around the sph res. This cross flow may be a result of 

ea

e
814 Fluid Dispensing and Dispersion 

the three-dimensional nature of the spheres and flow field, and the transport of entrained droplets and 

aerosol particles through convoluted pathways of this obstacle. 

Figure 8-76. Variation of the Mean Streamwise and Cross-stream Velocities with 

Downstream Distance for the Body-centered Cube of Spheres. Contours are the Stream 

Traces of the In-plane Vectors Obtained from the Axial and Radial Components of 

Velocity. 

Droplet Size and Velocity Distributions 

The aforementioned results indicated that droplet surface impact, vaporization, and transport behind the 

cylinder were dependent on droplet size. Measurements of spatially and temporally resolved droplet size 

and velocity distributions in the upstream and downstream vicinity of the cylinder, using PDI, were 

needed. Three agents with different boiling points were examined: water (with a boiling point of 100 °C), 

HFE-7100 (with a boiling point of 61 °C) and HFE-7000 (with a boiling point of 34 °C). Several 

strategies may be used to detect size dependent effects in regions where droplets rebound or vaporize. 

For example, a droplet near the upstream surface of the cylinder with a negative streamwise velocity 
Dyamics of Fluid Transport in Cluttered Spaces 815

(i.e., a droplet transported against the flow) would be indicative of a droplet rebounding off of the 

cylin tion

n

l

strategies were used in interpretation of the measurements. 

 of the droplet. For a droplet with known 

refractive index, the size and velocity can be determined by analyzing the scattered light collected with

several photomultiplier tubes (PMT). The PDI is a single-point (or spatially resolved) diagnostic

instrument in that it obtains information about the spray at a single point in space. The PDI is also a 

single-particle instrument in that information is obtained for only one droplet at a time. This offers 

advantages over integrating techniques because the characteristics of a particular droplet (size, velocity, 

etc.) can be recorded and the data can be separated into classes (size classes, velocity classes) to further

characterize the spray system. 

e 

e 

der surface, and thus PDI would be used to obtain the associated droplet size. If the size distribu

ear the heated cylinder surface is devoid of relatively smaller size droplets, as compared to other

ocations away from the cylinder, then this result may be indicative of the effects of vaporization. These

Phase Doppler techniques involve creating an interference pattern in the region where two laser beams 

intersect, and results in a region consisting of alternating light and dark fringes. The region where the

laser beams intersect is called the probe volume or sample volume. Due to the interference pattern, a 

droplet passing through the probe volume scatters light that exhibits an angular intensity distribution, 

which is characteristic of the size, refractive index, and velocity

The experiments were conducted using a two-component phase Doppler interferometer with a Real-tim

Signal Analyzer (RSA) available from TSI, Inc. A 5 W argon ion laser, operating in multi-line mode, was 

used as the illumination source. The blue (wavelength = 488 nm) and green (wavelength = 514.5 nm) 

lines of the argon ion laser were separated by beam conditioning optics, and focused by the transmitting

optics to intersect and form the probe volume. The transmitting optics were coupled to the beam 

conditioning optics, using fiber optic cables to permit the transmitter to be located near the experiment. 

The front lens on the transmitter had a focal length of 500 mm. The green and blue beams had a beam

separation distance of 39.9 mm and 40.2 mm, fringe spacing of 6.45 mm and 6.07 mm, and beam waist of

164 mm and 155 mm, respectively. Frequency shifting was set at 40 MHz. The receiver was located at a

scattering angle of 30° measured from the direction of propagation of the laser beams. To accommodate

the horizontal orientation of the experimental apparatus, the transmitter and receiver were positioned in a 

vertical plane, as shown in Figure 8-77. Due to the large size of the receiver, the transmitter was 

positioned with the laser beams angled at 30° to the cylinder, which required correction of the crossstream velocity. The front lens on the receiver had a focal length of 1000 mm. The spacing for the three

PMT detectors (A, B, and C) that were used to carry out the sizing measurements was 34.8 mm for

detectors A and B, and 101 mm for detectors A and C. A 150 mm slit aperture was located within the

receiver to limit the length of the probe volume. 

The measurements were carried out at several radial (R, cross-stream) positions and over a range of axial 

(Z, streamwise) positions upstream and downstream of the cylinder. Figure 8-78 illustrates th

measurement grid that was used and the location of the cylinder relative to the grid mesh. Measurements

were carried out from approximately 50 mm upstream of the cylinder to a downstream position of

100 mm. An increment of 2.5 mm was used for -25.4 mm < Z < 38.1 mm, and an increment of 12.7 mm 

for all other axial positions. In the radial direction, measurements were carried out in increments of 5 mm 

from 0 mm to 20 mm in the upper hemisphere (i.e., in the positive radial direction). Data were not

obtained immediately downstream of the cylinder (i.e., for ≈ 25 mm < Z < 14.6 mm) because the signals 

were too low to detect any droplets. 
816 Fluid Dispensing and Dispersion 

Figure 8-77. View and Schematic of the Experimental Arrangement with the Laser from

the Phase Doppler Interferometry System. 

Figure 8-78. Schematic of the 

Measurement Grid around the 

Cylinder. 
Dyamics of Fluid Transport in Cluttered Spaces 817

The droplet-laden flow field over both the unheated and heated obstacle was recorded with a highresolution digital camera (providing both still-images and movies at 9 frames/s). Droplets were observed

in the center of the spray impinging on the surface of the cylinder and dripping off at the bottom of the 

cylinder, while those droplets at larger radial positions were transported around the cylinder. Movies 

cylinder surface may influence locally the transport of droplets behind the

cylinder by vaporizing the smaller size droplets, and thus was a focus of this segment of the investigation. 

nder. The gap in the data for the radial positions R = 0, 

r. For Figure 8-79A, the general trends were:

ent. There is an increase in the droplet streamwise velocity over the

cylinder for R = 15 mm, and 20 mm, which is also characteristic of the accelerated flow over the cylinder, 

as described earlier. At locations near the upstream surface of the cylinder, negative values for the

obtained with a high-speed digital camera at 1000 frames per second indicated that many impinging 

droplets rebounded off the surface and into the free stream. More rebounding droplets were observed

when the air velocity was zero. Few larger size droplets were observed behind the cylinder in its wake,

but were abundant with the smaller size aerosol seeds that were introduced to the flow through the air

stream. There was no evidence of secondary breakup of the droplets, which was expected because the 

Weber number was much smaller than the critical value for droplet shattering. 

When the cylinder was heated to 150 °C (i.e., well above the boiling point of water), the droplet-laden 

flow over the cylinder appeared to be similar to the unheated case except along the shear layer 

downstream of the cylinder. In this region, as mentioned earlier, a vapor layer formed which was 

presumed to be the result of vaporization of the liquid that wets the hot surface. It was expected that

vaporization of liquid near the

A solid-cone nozzle was used to increase the number of droplets impinging on the cylinder surface

(a hollow-cone atomizer was used earlier with PIV measurements). It was observed that drippings off the 

cylinder occurred at a rate of approximately 6.5 mL/min for the unheated cylinder, while there was no

dripping for the heated cylinder due to droplet vaporization. It was also observed by the PDI laser beam

intensity that the concentration of droplets behind the cylinder was significantly reduced. For the heated 

cylinder, the cylinder surface temperature varied significantly with time after the spray was introduced to 

the flow field. However, it is unknown at this time whether these changes are attributable to time-varying 

changes in the response time of the cylinder heater during droplet impingement, or to some other systemic 

issue. 

The PDI was used to provide information on: (1) droplets rebounding off the upstream face of the 

cylinder, (2) vaporization of droplets near the heated cylinder, (3) droplet sizes entrained into the

recirculation region behind the cylinder, and (4) the effect of agent boiling point on droplet transport. The 

unheated cylinder results for the Sauter mean diameter (D32) and droplet mean streamwise component of 

velocity (U) are presented in Figure 8-79. The rectangle located on the abscissa at an axial position of

Z ≅ ± 14.6 mm represents the location of the cyli

5 mm, and 10 mm indicates the presence of the cylinde

(1) a decrease in mean size on the downstream side of the cylinder, as compared to the upstream side, and 

(2) an increase in mean size with increasing radial distance from the central plane of the cylinder. The

latter was indicative of the presence of more smaller size droplets near the center of the spray, as 

exemplified by the results obtained at the upstream axial position of Z = -50 mm, which was attributed to

the design characteristics of the atomizer. For the droplet mean streamwise velocity (Figure 8-79B), the 

values increased with decreasing radial position at the upstream position of Z = -50 mm. These higher 

velocities correlate with the smaller droplet mean size near the center of the spray. As droplets approach

the upstream surface of the cylinder, there is a decrease in the streamwise velocity component and an 

increase in the cross-stream compon
818 Fluid Dispensing and Dispersion 

streamwise velocity ng off

the surface. 

indicates that these i an angle that 

maintains their m e symbols in 

Figure 8-80 are sized ac

n

Streamwise

Figure 8-80. Variation of the Streamwise Velocity with Ti

Cylinder at Z = –15 mm and along the Centerline. 

 are detected (see Figure 8-80), which may be indicative of droplets reboundi

 However, positive values of velocity are obtained for the abundance of droplets, which

mpinging droplets either adhere to the cylinder surface or rebound at 

omentum in the downstream direction over the cylinder. Note that th

cording to the actual droplet diameter. 

Figure 8-79. Variation of Water Droplet (A) Sauter Mean Diameter and (B) Mea

 Velocity with Streamwise Position at Different Cross-stream Positions for the 

Unheated Cylinder. 

me upstream of the Unheated 
Dyamics of Fluid Transport in Cluttered Spaces 819

The droplet streamwise velocities decrease and become negative values for R = 0, 5 mm, and 10 mm on 

the downstream side of the cylinder, which is indicative of the presence of a recirculation zone and the 

entrainment of these droplets into this zone. Although the magnitude of the droplet mean streamwise 

velocity downstream of the cylinder is negative, indicating the presence of a recirculation region, it is 

clear that the mean is representative of a distribution of velocities and associated droplet sizes. This point 

is highlighted in Figure 8-81, which presents the droplet streamwise velocity with respect to droplet 

interarrival time into the probe volume at two points downstream of the cylinder within the recirculation 

region. One measurement location along the centerline, at Z = 25 mm (see Figure 8-81A), represents a 

measurement close to the cylinder, while the other, at Z = 76 mm (see Figure 8-81B), represents a 

location near the downstream edge of the recirculation pattern. The results for Z = 25 mm indicate that 

many droplets are recirculated upstream toward the cylinder (because U < 0), as expected, but also 

transported in the downstream direction at this point (i.e., for U > 0). However, a few droplets are 

indicate that several droplets at this location are transported in the downstream direction (i.e., U > 0). 

One can speculate that these latter droplets either originate in the recirculation zone or are transported 

around the cylinder surface and penetrate directly into the recirculation region. In addition, the droplet 

size does not provide additional information since the size for these droplets varies between 5 μm and 

30 μm, and this range is similar to that for the size distribution for the entire population for this 

measurement. In a similar vane, the results in Figure 8-81B indicate that the abundance of droplets are 

entrained into the recirculation region (i.e., for U < 0). 

Figure 8-81. Variation of the Streamwise Velocity with Time at Two Streamwise Positions 

of (A) Z = 25 mm and (B) Z = 76 mm along the Centerline, downstream of the Unheated 

Cylinder within the Recirculation Region. 

Comparison of results for the unheated and heated cylinders indicates consistently that the value of D32

are smaller for the heated case as the droplets are transported past the cylinder surface. The droplet 

streamwise and cross-stream components of velocity are also lower for the heated case. The unheated 

and heated results are compared in Figure 8-82 for D32 and U at R = 20 mm. The decrease in the values 

of both D32 and U for the heated case indicates that droplet vaporization does not result in the complete 

removal of the smaller size droplets from the distribution, but instead a decrease in the size of all droplets 
820 Fluid Dispensing and Dispersion 

(which results in an overall decrease in both the mean size and velocity). In fact, the droplet size

distributions illustrate clearly the shift of the entire distribution to smaller sizes for the heated cylinder. 

Figure 8-82. Variation of Water Droplet (A) Sauter Mean Diameter and (B) Mean

Streamwise Velocity for the Unheated (22 °C)and Heated (150 °C) Cylinders. 

more readily, resulting in vaporization hing the obstacle, and the absence of

dripping off the cy

increases and velocity comparison 

of the droplet me

R = 20 mm. sizes for increasing agent

boiling point. 

Figure 8-83. Comparison of the Droplet (A) Mean Size and (B) Streamwise Velocity for 

the Three Agents. 

Droplets with lower boiling points (i.e., the HFE agents as compared to water) were observed to vaporize

of droplets before reac

linder surface. Comparison of results for the three agents indicates that droplet size 

decreases with increasing agent boiling point. Figure 8-83 presents a 

an size and streamwise velocity with streamwise position for the three agents at

The size distribution for each agent is also found to shift to larger 
Dyamics of Fluid Transport in Cluttered Spaces 821

This study shows the effects of agent thermophysical properties on droplet transport processes through 

clutter elements. Other parameters, such as initial droplet size and velocity distributions, initial droplet

number density, clutter surface temperature, and geometry of clutter elements, also govern droplet 

interaction with clutter elements and droplet transport through the elements. All these factors together

with the nacelle airflow and potential fire location need to be considered when designing a fire

suppression system using a liquid fire suppressant for nacelle applications. 

8.4.3 Transport around Clutter and Recirculation Zones 

There is a dearth of data of flow around basic bluff-body shapes immersed in the low speed, turbulent free 

streams characteristic of engine nacelles. Therefore, wind tunnel models of basic shapes were 

manufactured and tested in a high-turbulence, low-speed wind tunnel.33 The data were analyzed to obtain 

mean velocities, turbulence intensities, and drag coefficients. In addition, the data time history was 

analyzed to gage the Strouhal number of the bluff-body wake. The data from these tests were used to

develop and validate a sub-grid-scale CFD model to account for the effects of small objects in the engine

bay that are difficult to resolve using a CFD mesh. 

Circular cylinders (single and in tandem), spheres (single and tandem), a simulated wire bundle, a

of 0.03 m/s at a velocity of 9.87 m/s. The turbulence

structural rib, and a cubic arrangement of spheres with cylindrical connectors were tested from 1 m/s to

10 m/s in a free-stream turbulence intensity of approximately 10 %. A circular cylinder was also tested in

intensity across the “clean” test section averaged 

0.58 %.

p

six model diameters downst shaped models were tested. 

laminar flow at a turbulence intensity of 0.6 % for comparison with published data. Drag measurements 

were estimated using a momentum deficit approach. 

Experimental Setup 

The tests were conducted in the low-speed, high-turbulence wind tunnel located at the United States 

Naval Academy (USNA). The test facility is an open jet wind tunnel powered by three 3.73 kW motors 

and has a speed range from 0 m/s to 18 m/s. A turbulence grid, consisting of 5 cm (2 inch) PVC

plumbing pipe, was installed at the jet exit and a 0.99 m long by 0.69 m high by 0.18 m wide extension 

was added to condition the flow downstream of the turbulence grid. Empty test section tests found that

the flow had average turbulence intensities across the test section of 9.78 %, 9.32 %, and 9.65 %. Test 

section flow non-uniformities of 0.16 m/s, 0.08 m/s, and 0.02 m/s were measured at average free stream 

velocities of 10.21 m/s, 5.08 m/s, and 1.19 m/s, respectively. The wind tunnel free stream velocity was 

analyzed in the absence of the turbulence grid also and found to have a test section flow non-uniformity 

The clutter models were placed at the jet exit (Figure 8-84 and Figure 8-85), and a thermal anemometry

robe was traversed upstream one model diameter from the leading edge of the model and one, three, and

ream from the trailing edge of the model. Various

Table 8-6 gives details of the models and test conditions. The cylinder models were manufactured from 

PVC or copper pipe. Representative surfaces of the pipe material were measured and found to have a 

surface finish 0.4 μm, rms.
822 Fluid Dispensing and Dispersion 

Model

Hot-wire probe

3-Component Traverse

Pitot-static probe

Figure 8-84. USNA Wind Tunnel Schematic. 

Figure 8-85. Low-speed, High-turbulence, Open Jet USNA Wind Tunnel. 

V∞

Turbulence grid

Wind tunnel nozzle

Wind tunnel extension

Model

Hot-wire probe

3-Component Traverse

Pitot-static probe

Turbulence grid

V∞

Wind tunnel nozzle

Wind tunnel extension
Dyamics of Fluid Transport in Cluttered Spaces 823

Table 8-6. Model Geometry and Test Conditions. 

Type 

Diameter 

(mm) 

Velocity 

(m/s) 

Reynolds 

Number Material Laminar Turbulent Spacing 

Model 

Location 

from 

Ceiling 

(mm) 

Empty 

TS 

N/A 10, 5, 1 NA N/A × (10 

m/s) 

× 306.8 

(297.3 

laminar) 

Cylinder 48.4 10 32600 PVC ×

5 16200 

× 297.3 

1 3250 

Cylinder 28.8 10 19550 Copper × 318.4 

5 

1 

9800 

2200 

Cylinder 9.6 10 

5 

1 

6400 

3200 

760 

Copper × 323.9 

Tandem 

cylinder 28.8 5 9800 Copper × 1 d 277.8 

Sphere 50.8 5 16900 Wood × 342.9 

(CL) 

Tandem 

sphere 50.8 5 16900 Wood × 1 d 342.9 

(CL) 

Rib 38.1 5 12800 Aluminum × Tunnel 

floor 

Wire 47.6 W

bundle (9.5 mm 10 32000 

ire 

around 

PVC 

× 306.4 

wire) 

Cube 63.5 

(25.4 mm 

spheres) 

5 12800 Wood × (CL) 

342.9 

Wire Bundle Model 

This model was created using approximately 1.3 cm diameter wires secured around a 2.54 cm PVC pipe, 

see Figure 8-86. The outer diameter of the wire bundle is roughly equivalent to the large cylinder model. 

The mean velocity and turbulence intensity data were little affected by a 1 in 24 rotation of the wire 

bundle model. In comparison to the large cylinder data, the wake of the wire bundle model had a greater 

velocity deficit and an increase in the turbulence intensity. 

Tandem Medium Cylinder Model 

higher than the medium cylinder model turbulence intensity. Tandem cylinder drag (and 

correspondingly, the shed wake) is very much dependent upon the spacing between the cylinders. The 

The tandem cylinder model, seen in Figure 8-87, was tested, and the results were compared to those from 

the medium cylinder model at 5 m/s. The tandem medium cylinder model had a significantly wider wake 

and more of a velocity decrement. The turbulence intensity of the tandem medium cylinder model was 
824 Fluid Dispensing and Dispersion 

data depicted is for a cylinder spacing of one diameter. New data may prove to be markedly different for 

another cylinder spacing. 

Figure 8-86. Photograph of the Wire 

Bundle Model. 

Figure 8-87. Photograph of the Tandem 

Medium Cylinder Model. 

Sphere Model 

To obtain an accurate assessment of the drag coefficient, horizontal traverses were accomplished for all of 

the three-dimensional models (sphere, tandem sphere, and cube). For each location, six traverses (three 

horizontal and three vertical) were obtained. In general, the sphere exhibited a smaller wake with less 

turbulence intensity as compared to a similar sized two-dimensional cylinder at a similar Reynolds 

number. The effect of the model wake on the flow quickly dissipated downstream of the model, 

approaching the free stream tunnel conditions. 

Tandem Sphere Model 

This model was compared to the sphere model; the tandem sphere model had a wider wake but less of a 

velocity deficit immediately behind the model. However, the tandem sphere model had a slightly greater 

velocity deficit farther downstream. Turbulence intensity levels were less than the single sphere model 

immediately downstream but were slightly more at the farther downstream location. 
Dyamics of Fluid Transport in Cluttered Spaces 825

Cube Model 

A cube arrangement of spheres with connecting rods, as shown in Figure 8-88 was meant to simu

many porous, three-dimensional objects found in an engine bay. The mean velocity and

intensity were measured at different upstream and downstream traverse locations at a free stream

of 5 m/s. Unlike the sphere data, the wake of the cube was not seen to dissipate as quickly at the 

downstream traverse locations. In addition, the wake immediately downstream was wider but with a 

smaller velocity deficit than seen for the sphere. Turbulence intensity immediately aft of the cube w

noticeably less than that of the sphere. However, the turbulence intensity of the cube far downstrea

noticeably higher than the sphere’s. 

Rib Model 

A representative aircraft rib, affixed to a flat plate was tested to determine mean velocity and turbulence 

intensity data. Limited data were also obtained on the flat plate alone. As expected, there is a size

velocity deficit seen near the flat plate and behind the rib. Recovery to the free stream velocity is dela

as the vertical traverse location moves downstream. The turbulence intensity data is chaotic near the flat

late the

 turbulence

 velocity

as

m was

able

yed 

late and behind the rib. Recovery to the free stream turbulence intensity is delayed. 

data and takes

ndaries, and 

milar

e

34

 based on a 

ount of 

f 13.2 % at 95 % confidence. 

p

Figure 8-88. Photograph of the Cube 

Model. 

Drag Estimates 

The drag coefficient estimates are presented in Table 8-7 along with the uncertainty estimates. In general,

the models in a turbulent free stream had lower values of drag coefficient compared to the published 

values for similar models in a low-turbulence free stream. The analysis used the velocity

into account the wind tunnel velocity jet dissipation, effects of the walls and jet bou

momentum losses vertically as well as horizontally. The present tests and historical data yielded si

drag coefficient values for a cylinder in low turbulence flow (1.23 for the present test, 1.20 from th

literature). The estimate for the tandem sphere data in a “clean” flow field was estimated from Hoerner

assuming the models to be flat disks. The estimate for the cube in a “clean” flow field was

porous model composed of spheres and rods, weighted by area. Analyzing data with a similar am

scatter35, 36 for a circular cylinder and applying the same uncertainty/bias estimates yielded an uncertainty 

o
826 Fluid Dispensing and Dispersion 

Table 8-7. Summary of Drag Coefficients. 

Model Type

CD

(present 

test) 

Velocity

(

95 %

Confidence 

(%)

CD

(published; 

low 

turbulence) 

Reynolds 

Number 

S

m/s)

ize

(mm)

Large

r

555 9.54 20 30812 4

cylinde

0. 0 8.4 1. 8.41

Large

cylinder 0.792 4.731 11.3 1.20 15279 48.41

Large

cylinder 1.130 1.012 10.8 1.00 3268 48.41 

Cylinder 

turbulence 

low 1.228 9.534 7.1 1.20 30793 48.41

Medium 1.040 9.2 1.20 17611 2

cylinder

37 8.2 8.80

Medium

cylinder 0.858 4.618 8.6 1.06 8804 28.80 

Medium

cylinder

1.084 1.089 12.6 1.00 2077 28.80

Tandem

medium

r

939 4.6 1.06 8826 28

cylinde

0. 30 11.3 .80

Small 

cylinder

0.368 9.556 8.4 1.04 6089 9.55

Small 

er

0.444 4.825 1.00 3074 9.

cylind 9.0 55

Small

cylinder 0.635 1.128 9.5 1.30 719 9.55 

Sphere 0.467 4.950 26.8 0.47 16775 50.80

Tandem

sphere 0.703 4.907 8.9 0.71 16633 50.80

Rib 0.921 5.086 15.9 1.30 12930 38.10 

Wire bundle 1.039 9.334 8.6 1.14 29662 47.63 

Cube 0.242 4.531 15.9 0.28 19195 63.50

Generally, for a given Reynolds number, the smaller the size of the model, the lower the drag coefficient. 

For the small cylinder, the drag coefficient was found to be significantly lower than for the large and

medium cylinders at a roughly equivalent Reynolds number. Although the length of the wind tunnel 

extension was thought sufficient to ensure that the generated turbulence was well-mixed, perhaps the 

5.08 cm diameter turbulence grids causes differences in the local flow

violation in the similarity parameter. 

nature of the eddies created by the

field around the various models, thus causing a 

The wire bundle model was seen to have significantly higher drag (approaching the drag coefficient of the

cylinder in low turbulence flow field) compared to a similar sized cylinder. This is a different trend than 

seen in a similar model in a low turbulence flow field. A wire bundle in a low turbulence flow field has 

been shown to decrease the drag coefficient compared to a smooth cylinder of the same diameter. 
Dyamics of Fluid Transport in Cluttered Spaces 827

The tandem sphere had nearly double the drag coefficient of the single sphere model. For each estimate, 

the same frontal area was used in the drag coefficient calculations. In a similar manner, the same frontal 

area was used for estimating the drag coefficients for the medium cylinder and tandem medium cylinder. 

Strouhal Number 

The algorithm to determine the power spectrum densi .

37 The 

data were segmented into windows to allow eight av , and a 

Hanning filter was used with a window length the sa ments. The mean was 

eliminated from the PSD calculations and a 95 % as used to gage the PSD 

assessment. 

Table 8-8 gives the frequency and Strouhal number resolution. The Strouhal number is a dimensionless 

characteristic of vortex-shedding off bluff bodies, suc vortices downstream 

affects the mixing of agent into the recirculation regions as well as the major downstream flows. In cases 

where a comparison of models needed to be consistent (e.g., a medium cylinder model and the tandem 

medium cylinder model), the analysis was performed over the same data record length. 

Table 8-8. Frequency and Strouhal Number Resolution. 

ty (PSD) was based on the method by Welch

erages. No data overlapping was employed

me size as the data seg

confidence criterion w

h as clutter. This shedding of 

Model Type Reynolds Number Velo ty (m/s) ci ∆f (Hz) ∆St 

Large cylinder 32,605 10.0126 8.492 0.041 

Large cylinder 16,208 4.9936 4.069 0.039 

Large cylinder 3,253 1.0000 1.424 0.069 

Medium cylinder 19,553 1 157 0.0 10.851 0.031 

Medium cylinder 9,826 4.9664 21.701 0.126 

Medium cylinder 2,175 1 70 .10 3.255 0.085 

Small cylinder 6,395 9.9710 13.021 0.012 

Small cylinder 3,193 4.9840 13.021 0.025 

Cylinder-low 

turbulence 32,338 10.0126 11.182 0.054 

Tandem medium 

cylinder 9,435 4.8953 21.701 0.128 

Sphere 16,917 4.9866 8.492 0.087 

Tandem sphere 17,426 5.0994 8.492 0.085 

Wire bundle 32,019 10.0131 8.492 0.040 

Cube 21,585 5.0647 4.069 0.051 

To gage the coherence, the empty test section data were analyzed to determine the pulse frequency peaks 

in the tunnel. This was used as a guide to cull non-model frequencies from the spectrum. The Strouhal 

number corresponding to the dominant frequency is plotted against Reynolds number in Figure 8-89. It 

was found that the Strouhal number of the cylinder model in a low-turbulence flow field was lower, than 

that reported in the literature, 0.13 versus 0.19, (see Schlichting36). 
828 Fluid Dispensing and Dispersion 

ynolds Number for the Various Te

ons. 

Figure 8-89. Strouhal Number versus Re sted 

Configurati

It should be noted that model size had an effect on the Strouhal number. That is, the large circular 

cylinder at 1 m/s has the approximate Reynolds number of the small circular cylinder at 5 m/s. However, 

the Strouhal number was significantly different: 1.2 for the large cylinder at 1 m/s and 0.2 for the small 

cylinder at 5 m/s. 

The fundamental frequency of the empty test section data was: 25.8 Hz (St = 0.125, 0.074, and 0.025 based 

upon the large, medium, and small cylinder diameter, respectively) at 10 m/s, 17.3 Hz (St = 0.167, 0.100, and 

0.033 based upon the large, medium, and small cylinder diameter, respectively) at 5 m/s, and 8.7 Hz 

(St = 0.419, 0.249, and 0.083 based upon the large, medium, and small cylinder diameter, respectively) at 

0 m/s. The different flow fields most likely caused the differences in Strouhal numbers and drag 

oefficients. 

ers of the sphere and tandem sphere models were equal. However, there was a notable 

difference between the medium cylinder and tandem medium cylinder models. The wire bundle model 

 in low-turbulence flow. Turbulence intensity increased with decreasing 

Reynolds number. The drag coefficient estimates were generally lower than those obtained in low1

c

The Strouhal numb

was found to have a similar Strouhal number as the similarly sized cylinder. No dominant frequency was 

noted for the rib model. In general, the Strouhal number was higher for cylinders in a turbulent flow field 

compared to cylinders in low turbulence. 

Summary and Implications 

Fundamental measurements of mean velocity, turbulence intensity distributions, drag coefficient 

estimates, and wake shedding frequency were obtained for basic aerodynamic shapes. A limited 

comparison to data obtained for a circular cylinder in a low-turbulence flow field was also conducted. 

The results show that the wake structure behind a circular cylinder in a turbulent flow field was smaller 

compared to the same cylinder

0

0 5000 10000 15000 20000 25000 30000 35000

Reynolds Number

0.2

0.4

0.6

0.8

1

1.2

1.4

Strouhal Number

1.6 Large Cylinder

Large Cylinder - Low Turbulence

Wire Bundle

Medium Cylinder

Tandem Medium Cylinder

Small Cylinder

Sphere

Tandem Sphere

Cube

Low Turbulence Cylinder - Reference 6
Dyamics of Fluid Transport in Cluttered Spaces 829

turbulence flow fields. St was generally higher for 

cylinders in a turbulent flow field, when compared to cylinders in low-turbulence. Model size was seen 

to affect the similarit rameters of the Strouhal r and mber due to differences in the 

shedding characte the e gr ind tu The o sho her 

tu nsity d the blu y when c red to nfig a lam ow 

field. Also, the drag coefficients fo ame confi tion were o be low those in nar 

flow. These latter two points imply that the clutter impedes the flow of agent and air less (proportionally) 

in a turbulent flow than in a lam ne and th e mixing of agent into the flow as a result of 

interacting with the clutter is less sensitive to Reynolds number than was expected. Subsequent testing, 

described below, indicates that clutter usually facilitates the mixin gent in th cted spa

8.4.4 w Temp re Effec Agent D rsion 

Introduction 

Sho suppre e disch nto a suff tly cold e nacelle o bay, it is expected 

that the chemical will condense on the cold surfaces. Gravity would then lead to puddling of the 

condensate at a low point in the vo and the a would th latilize at a rate determined by its 

vapor pressure at the local temperature and the local air flow. This behavior would necessitate the storage 

and distribution of a al suppr which w result in i ed storag ht and v , as 

wel ger time to fire extinguishment. The cold temperature release finds its applications in the 

cold an engi cold env nt or in h ltitude cruising condition

Yang and coworkers ducted a of tests in mulated engine nacelle to this phenomenon 

and to estimate the magnitude of its impact. In these tests, the key variable was the difference between 

the boiling point of the suppressant and the ambie mperature nacelle. The temperature of the 

suppressant storage bottle was also treat

For the NGP, a crit or low t ture appl ons for a ppressan et at -4 To 

study ect of lo to identify a surrogate agent that 

has a norm higher t °C m um temperature criterion. Trifluoroiod ane 

(C has b posed a ent for halon 1301 in ai ngine n and 

y b protecti lications eets this on and w ected as a surrogate for the study. 

F3Br.2

rouhal number variation with Reynolds number

y pa numbe

id in the w

Reynolds nu

nnel.

 the same co

ristics of 

behin

turbulenc results als w hig

rbulence inte ff bod ompa uration in inar fl

r the s gura seen t er than a lami

inar o at th

g of a e prote ce. 

Lo eratu ts on ispe

uld a fire ssant b arged i icien ngine r dry 

 some of 

lume, gent en vo

ddition essant, ould ncreas e weig olume

l as a lon

start of ne in a ironme igh-a s. 

38 con series a si verify

nt te in the

ed as an independent variable. 

erion f empera icati fire su t was s 0 °C. 

 the eff w temperature on agent dispersion, it was necessary

al boiling point inim

F3I), which 

han the -40 ometh

een pro s a potential replacem rcraft e acelle 

dr

C

ay fire on app ,

4,39 m criteri as sel

F3I has a normal boiling point of -22 oC, which is almost 20 °C higher than the -40 °C minimum 

temperature criterion. The dispersion of CF3I into air at temperatures down to -40 °C may not be as 

effective as halon 1301, which has a normal boiling point of -57.8 oC. In addition, CF3I can be detected 

using UV absorption spectrometer, which was the available method for measuring temporal CF3I 

concentration in this study. Table 8-9 lists some of the physical properties of CF3I and CF3Br. 

Table 8-9. Selected Thermophysical Properties of CF3I and C

Agent 

Molecular Weight 

(kg/mol) 

Tb 

(oC) 

Tc

(oC) 

Pc

(MPa) 

ρc

(kg/m3) 

∆Hv

(kJ/kg) 

CF3I 0.196 −22.0 122.0 4.04 871 106 

CF3Br 0.149 −57.8 67.0 4.02 745 111 

Tb is the normal boiling point; Tc is the critical temperature; Pc is the critical pressure; ρc is the critical density; ∆Hv is the latent 

heat of vaporization at Tb. 
830 Fluid Dispensing and Dispersion 

Although the release of CF3I (at room temperature or chilled to about -40 °C) into a fire compartment and 

an engine nacelle simulator at ambient room temperature has been examined,2,40 the discharge of cold 

CF3I into a cold ambience has not been performed, or at least has not been documented in open literature. 

There is only one corporate internal report,41 which describes a study of the release of cold CF3I into a 

sure with no airflow. Careful examination of the data indicated some deterioration 

in the distribution of CF3I within the enclosure when compared to room temperature conditions. To 

well-mixed cold enclo

assure that there is no substantial deterioration in dispersion performance under cold temperature 

applications, discharge tests in an aircraft engine nacelle at temperatures below the agent boiling point are 

needed. The temperature of -40 °C was selected in this study because it was below the normal boiling 

point of CF3I and was the lowest operating temperature for some of the equipment used in the 

experiments.

Experimental Apparatus (ELEFANT) 

The experimental apparatus (called Extremely Low-temperature Environment For Aircraft Nacelle 

Testing) consisted of a simulated engine nacelle with baffles, an agent release port, four observation 

windows, and two measurement ports. Figure 8-90 is a schematic of the simulator. The annulus of the 

simulator had an inside 

area of 0.35 m2

. T between the agent 

injec the d a ty ine nacel affle height was 0.075 m. 

The sed to m omplicated f for the agen the case of a real nacelle. 

Two longitudinal ribs with t height as th s were placed on the outer surface inner 

core between t r forward and les. The ribs sed as barriers agent 

flowing circumferentially. T lator was fab f 3.2 mm thick stainless-steel shee . 

Figure 8-90. Schematic of the Test Fixture (ELEFANT). 

diameter of 0.6 m and an outside diameter of 0.9 m, resulting in a cross-sectional

he length (2 m) of the simulator was comparable to the distance 

tion port and ownstream end of pical small eng le. The b

 baffles were u imic a c low path t as in

he same e baffle of the

 of the nacelle he inne aft baff were u to the

he simu ricated o t metal

To exhaust

Video camera

Baffle

Air from blower

Observation window

2 m

60 cm

Pitot tube

15 cm

Agent bottle

Fiber-optic probes (UV s eter) pectrom

Agent release location

Simulated

engine core 1

2

3 4

Horizontal rib
Dyamics of Fluid Transport in Cluttered Spaces 831

A bottle with an internal volume of 2.36 L was used to store CF3I for discharge. A fast-response static 

pressure transducer (uncertainty ± 10 kPa specified by the manufacturer) was mounted on the receiver

bottle to monitor the pressure inside the bottle during filling and discharge. A K-type thermo

(uncertainty ± 1 °C) was inserted into the bottle to record the temperature of the liquid ag

discharge. A quick-acting solenoid valve was used to release the agent. To tailor the agent discharge 

time (≈ 0.5 s), a reducer was placed at the valve exit. The agent was released through a vertical tee at the 

end of a short stainless-steel tubing (i.d. = 15.9 mm, o.d. = 19.1 mm) connected to the reducer. Four CCD 

cameras (30 frames/s) were used to observe the agent discharge behavior at the release port (Cam

a location in the bottom of the simulator to observe any pooling of agent (Camera 2), and at th

concentration measurement locations (Cameras 3 and 4). A frequency-controlled, variable-speed blower 

provided airflow through the nacelle simulator. The maximum air speed at room temperature in the 

annulus, measured using a pitot tube, can reach 9.2 m/s. 

To achieve an operating temperature of –40 °C, the entire facility was placed inside the U.S. Ar

environmental test chamber at Ft. Belvoir, and the cold discharge experiments were conducted inside the 

chamber. The chamber has an interior dimension of 2.74 m (H) × 3.35 m (W) × 3.66 m (L) and a 

couple 

ent before 

era 1), at

e two

my

.83 m × 1.83 m sliding door. The lowest temperature attainable in the environmental test chamber is

−54 ° h the

refrige

ssure to facilitate the transfer of CF3I vapor to the receiver bottle. When the 

For cold temperature conditions, the environmental test chamber and the receiver bottle were

cooled down to approximately −40 °C before a test was commenced. Two contact K-type thermocouples 

irflow, the amount of agent required for a fixed injection period

(< 0.5 s for typical nacelle applications) was estimated using the generic nacelle modeling results 

agent bottle was charged with ≈ 1 kg of CF3I and then pressurized with 

(4.21 MPa) at room temperature. Table 8-10 lists the experimental

1

C. Discharge experiments in room temperature were also conducted inside the chamber wit

ration unit turned off to establish baselines for comparisons. 

The experimental procedure involved the following steps. The receiver bottle was first immersed in dry

ice and connected to the CF3I supply bottle, which was placed on an electronic balance (uncertainty of

± 1 g) to monitor the amount of agent transferred to the receiver bottle. The dry ice was used to condense 

the CF3I vapor in the receiver bottle. The supply bottle was slightly warmed using two 120 V floodlights

to increase the vapor pre

amount of agent in the receiver bottle reached the target mass, the bottle was then removed from the dry ice, 

warmed back to room temperature, and weighed on the electronic balance to determine the actual mass in

the bottle. The receiver bottle was then pressurized with nitrogen to 4.12 MPa. Shaking the bottle

intermittently and vigorously was required before the final equilibrium pressure was attained. The amount 

of nitrogen added was obtained by weighing the filled bottle. The bottle was now ready for the discharge

experiments.

were attached on the front and aft of the simulator external skin to monitor the ambient temperature of the 

chamber. In addition, a bare-beaded K-type thermocouple was placed in the annulus to measure the 

airflow temperature through the nacelle. 

Given the simulated nacelle volume and a

discussed in Hamins et al.66 The

nitrogen to the desired pressure

matrix. The airflow through the simulator was maintained at 1.5 kg/s ± 0.1 kg/s (mean ± standard

deviation). 
832 Fluid Dispensing and Dispersion 

Table 8-10. Experimental Matrix. 

Nominal Initial 

Conditions of Vessel 

Nominal Conditions of Vessel 

Before Discharge Nominal Conditions in the Simulator 

22 °C and 4.12 MPa −40 °C at prevailing P −40 °C 

22 °C and 4.12 MPa 22 °C and 4.12 MPa 22 °C (baseline) 

22 °C and 4.12 MPa 22 °C and 4.12 MPa −40 °C 

The dispersion effectiveness of CF3I was assessed based upon concentration measurements at the two

locations inside the engine nacelle simulator (see Figure 8-90). The number of measurement locations

could be easily increased; however, the intent of this work was not to address the certification process,

which requires twelve measurement locations. The measurements were made using two Ocean Optics

nents consisted of a deuterium/tungsten 

source, four (UV grade quartz) collimating lenses, and 300 μm diameter optical fibers. These were

ide two measurement locations (coincident with Cameras 3 and 4) approximately 0.75 m 

apart along the direction of the airflow in the engine nacelle testing apparatus. A bifurcated fiber (1 m in

onfiguration, it was able to achieve 

a data acquisition rate of approximately 12 single scan spectra (6 at each location) per second to capture 

a plot of

absorbance (A) against concentration (C, molecules cm ), is shown in Figure 8-92. 

The Bouguer- is exp ed as

S2000 UV/VIS fiber-optic spectrometers. The optical compo

arranged to prov

length, coupled with a 5 m extension) was used to connect the source to a pair of collimating lenses 

secured by brackets to the Plexiglas® viewing windows located on the top of the apparatus. The source 

radiation emanating from each lens was transmitted over a 0.038 m optical path (perpendicular to the

airflow) to an opposing set of collimating lenses connected by independent optical fibers (5 m in length) 

to the master and slave spectrometers. Although the manual indicated that these optical components

should have a spectral range from 200 nm to 850 nm, very little throughput at wavelengths shorter than 

250 nm was found. 

The spectrometer settings used for the measurements in the nacelle testing apparatus were as follows. 

The spectrometers were triggered by an electronic timer. The integration time (analogous to the shutter 

speed) was set at 30 ms, and the pixel resolution of the analogue to digital converter (ADC) was set at 10, 

which amounts to a spectral resolution of only about 3 nm. With this c

the time dependent details of the agent discharge. An estimate of the uncertainty (one standard deviation)

of the measurements was obtained by comparing results at these settings to more accurate values obtained 

after signal averaging 100 scans at the full resolution of the spectrometer (≈ 0.3 nm). Based on this 

analysis, the CF3I partial pressures reported in this paper are accurate to ± 15 %. 

The UV spectrometer was calibrated at 295 K using a quartz cell with an optical path length of 0.075 m.

The cell was first evacuated to 1.33 Pa. Then, a fixed amount of CF3I vapor was metered into the cell by

monitoring the cell pressure. Spectra were taken using an integration time of 30 ms and a pixel resolution 

of 10. Figure 8-91 shows a typical CF3I absorption spectrum at 295 K. Note that the peak absorbance for 

CF3I centers around 270 nm. The calibration curve (at λ = 300 nm and 22 °C), which is

-3

Beer-Lambert law ress

( ) ( ( ) ( ))

303

λ, λ log T L

I

I A

o

⎢ =

⎣

⎡ −40) 2.

Cσ

λ ⎥

⎦

λ ⎤ = − (8
Dyamics of Fluid Transport in Cluttered Spaces 833

where I(λ) and Io(λ) are the incident and transmitted intensities through the cell respectively, σ(λ,T) is the 

absorption cross section (cm2

), L is the optical path length (cm), T is the temperature, and λ is the

wavelength. Note that the absorption cross-section is a function of wavelength and temperature. Using

the ideal gas law, Equation 8−41 gives the relationship between C and the partial pressure p (Pa) at 22 °C. 

C p

14 = 2.44×10 (8−41)

2

.

1.5

2.6 kPa CF3

I

0

0.5

1

250 300 350 400

Absorbance

Wavelength (nm)

Figure 8-91. Absorption Spectrum of CF3I. 

From Equation 8−40, the absorption cross section can be obtained from the slope of the calibration curve

A linear regression line is fitted through the data points in Figure 8-92, and the absorption cross-section of 

CF3I is 8.1×10-20

 cm2, which is comparable to the value of 8.9×10-20 cm2 at λ = 300 nm and 22 °C to 

27 °C in the literature.42 Since the calibration was performed at 22 °C, a correction for the temperature

effect on the absorption cross section is necessary to obtain the CF3I partial pressure at other prevailing

temperature, using the following equation:42

σ( ) λ, σ(λ,25 C) exp[ (λ)( 25)] 63 C 27 C o o o T = B T − − < T < (8−42)

The concentration C of CF3I at any temperature was calculated from the absorbance measurement using

Equations 8−40 and 8−42. At 300 nm, B = 4.876×10-3 °C-1 from DeMore et al.

42 The partial pressure of 

CF3I was then obtained using the ideal gas law at the prevailing temperature. However, the temperature

effect on the absorption cross section was found to be negligible in the concentration calculations. 

An electronic timer was used to coordinate the experimental sequence of events. At t = 0 s, a signal was

sent from the timer to trigger the data acquisition system to record the pressure of the discharge bottle and 

the pitot tube output at a sampling rate of 200 Hz. At t = 1 s, the timer initiated the two UV 

pectrometers, and at t = 2 s, the solenoid valve was activated to discharge the CF3I/nitrogen mixture from 

e bottle into the engine nacelle simulator. 

s

th
834 Fluid Dispensing and Dispersion 

Figure 8-92. Calibration Curve at 

300 nm. 

Results and Discussion 

Figure 8-93 shows the temporal variation of pressure inside the bottle during a typical discharge. The 

initial time (t = 0) corresponds to the time when the solenoid valve was opened. In the figure, the 

prevailing bottle pressure before discharge at ≈ -40 oC is much lower than that at room temperature. Due

to the reduction in the initial bottle pressure, the discharge time (≈ 0.24 s) of the cold liquid agent is much

longer than that (≈ 0.16 s) of the baseline case; the liquid discharge time corresponds to the transition 

point in the pressure vs. time curve.43 The observations from Camera 1 also showed that the agent 

discharge time at ≈ -40 oC was longer than that at room temperature. 

Figure 8-93. Variation of Bottle Pressure 

during Discharge at Room and Cold 

Temperatures. 

0.4

0.6

0.8

1

1.2

at λ = 300 nm

Absorbance

0

0.2

0 0.5 1 1.5 2 2.5 3 3.5 4

 (molecules / cm

3

) x 10-18 C

Time (s)

0.0 0.2 0.4 0.6 0.8

Pressure (MPa)

0

1

2

3

4

5

Cold temperature

Room temperature
Dyamics of Fluid Transport in Cluttered Spaces 835

When CF3I was discharged at room temperature, the observations obtained from Camera 2 showed that a 

small pooled in pon release, and the liquid CF3I boiled off

within 66 ms. When CF3I was disch significan e

botto on release. orated slowly and remained for many seconds 

(> 60 evaporation from Cameras 3 an a cloud of

CF3I field of vi after agent discharge. The observations from 

ameras 3 and 4 were qualitatively similar for the discharge of CF3I at room temperature and -40 °C. 

id Fraction of CF3I/N2 Mixture after Isentropic Expansion to 0.101 MPa. 

amount of CF3I the bottom of the simulator u

arged at -40 oC, a t amount of liquid CF3I pooled at th

m of the nacelle up The liquid CF3I evap

s) before complete . The observations d 4 showed that

passed through the ew of the cameras

C

The difference in pooling tendency described above can be explained as follows. Consider a 2.36 L

container with 1 kg of CF3I pressurized with nitrogen to 4.12 MPa at 22 oC. If the container is cooled

down to -40 oC before release, the final pressure of the container is estimated to be 2.8 MPa using the 

computer code (PROFISSY).2,6 The code is based on the calculations of vapor-liquid phase equilibria

using the extended corresponding-states principle. Assuming the discharge of the liquid agent from the 

container is an isentropic process from the initial container pressure to atmospheric pressure, the final

states of the agent can be calculated using the computer code (FISSYCS)2

, which is a modified version of 

PROFISSY. Table 8-11 tabulates the calculated results for the two conditions. The liquid mole fraction

(the percent of agent/nitrogen mixture still remaining in the liquid phase after the isentropic expansion 

process) is substantially higher at -40 oC than at 22 oC. Such a high liquid fraction should result in

significant pooling upon agent release from the bottle. The combined effects of liquid pooling and slow 

evaporation at -40 oC will have an adverse impact on the subsequent dispersion of the agent/nitrogen 

mixture in the nacelle. 

Table 8-11. Liqu

Initial Conditions Liquid Fraction (%) 

22 °C at 4.12 MPa 70 

−40 °C at 2.8 MPa 90 

Although full CF3I spectra were obtained in each test, a common practice used is to base concentration

measurements on the wavelengths at the peak absorbance or its vicinity. The absorbance at 300 nm was 

used to obtain the CF3I concentration because saturation of the detector at ≈ 280 nm was observed under 

certain test conditions. The concentration of CF3I thus obtained is shown for both the room and cold 

temperature releases in Figure 8-94 and Figure 8-95 for the two measurement locations, respectively. The 

on of the agent release. Although three runs 

se the off-resonance

spectral measurement at 500 nm also showed a peak at the same time. The two-phase flow was the result

rt into droplets. The off-resonance extinction at 500 nm 

indicated that liquid CF3I droplets were present for only a short period of time (< 2 s) immediately

llowing the discharge. Therefore, it can be argued that the concentration measurements after the initial

spike in Figure 8-94 was due largely to the CF3I vapor, with minimal or negligible contribution f

initial time (t = 0) in the figures corresponds to the initiati

were performed at each condition with similar observations, only a single run for each condition is shown

in the figure for clarity. The arrival times of the agent at the two measurement locations were clearly 

captured in the figures. Some salient features are noted in the two figures. 

For the room temperature release, an initial spike was observed at the forward measurement location. 

This was due to the presence of a two-phase (liquid droplet-laden) flow becau

of break-up of the liquid core at the discharge po

fo

rom the

droplets. 
836 Fluid Dispensing and Dispersion 

Figure 8-94. CF3I 

Concentration Profiles at the 

Forward Port. 

Figure 8-95. CF3I 

Concentration Profiles at the 

Aft Port. 

0

5

10

15

0 5 10 15 20 25 30

20

Room temperature release, forward port

Heated agent / cold air release, forward port

Cold temperature release, forward port

Volume fraction (%)

Time (s)

0

0 5 10 15 20 25 30

5

10

20

15 Room temperature release, aft port

Heated agent / cold air release, aft port

(%)

Cold temperature release, aft port

Volume fraction 

Time (s)
Dyamics of Fluid Transport in Cluttered Spaces 837

The off-resonance spectral measurement at 500 nm in the aft loca

present. The absence of the droplets and the much lower CF3

indicated that the current nacelle simulator had indeed created a very

dispersion, a condition which is generally true for a real engine nacelle. Furthe

model66 provided a reasonable estimate of the amoun

tion indicated that no droplets were

I concentration (Figure 8-95) at this location

 challenging environment for agent

rmore, the generic nacelle 

extinguishing concentration at two measurement locations in the current nacelle. Halon 1301 and CF3I 

have similar heptane cup-burner extinguishing values, a volume fraction of 0.032 from Grosshandler et 

al.4

 Assuming that the military specification for halon 130 nts in

Figure 8-94 and Figure 8-95 suggest that a volume fraction

in both locations at room temperature. 

For cold temperature release, the off-resonance spectral measurements at 500 nm did not indicate the 

initial presence of droplets at both forward and aft measurement locations. The absence of the droplets 

was due partly to the reduction in the initial bottle pressure (≈ 3 MPa vs. ≈ 4.1 MPa at room temperature),

which would impart less momentum to the droplets upon the release of the agent. Droplets with less 

momentum were less likely to be transported to the two measurement locations. The combined effect of 

low bottle pressure and large liquid fraction in cold tem ature release (see discussion above) might 

generate larger droplets as a result of poor atomization of the liquid core, thus hindering the ability of the 

droplets to follow the airflow. Similar to the room temperature release, the concentration at the forward 

location was higher than that at the aft. However, the difference was not as significant as in the case of 

he most important finding from this study was that there was a significant

reduction in the agent concentration in the cold temperature release. At the forward measurement

rough the nacelle was maintained at

≈ –40 oC. The concentration levels obtained under this condition were still much lower than those at 

room temperature; however, some improvement wa clearly noted when compared to the results at cold 

temperature. 

To further illustrate the potential of this approach, thermodynamic calculations were performed using

PROFISSY, FISSYCS, and the same initial bottle ons at room temperature. (1 kg of CF3I in a 

2.36 L bottle, pressurized with nitrogen to 4.12 MP the 

following analysis, the heat transfer between the f not

considered. The calculations were performed as fo

using PROFISSY to simulate heating or cooling of the bottle. The state was then used as input for

FISSYCS to obtain the amount of liquid fraction r ulting from an isentropic process taking the fluid 

from the prevailing pressure to 0.101 MPa. 

Figure 8-96 shows the calculated liquid fraction as a function of temperature. The liquid fraction

decreases with increasing bottle temperature. However, there is a discontinuity at about 94 °C. At 

temperatures below the discontinuity temperature, the initial state is liquid-phase, the isentropic process 

sults in a liquid-vapor system. 

t of agent needed to achieve the required

1 can be applied to CF3I, the measureme

of 0.06 can be attained over a duration of 0.5 s 

per

room temperature release. T

location, a reduction of a factor of almost 3 was observed at the peak concentration. At both locations,

the agent concentration measurements were always below a volume fraction of 0.06. 

One operational strategy to mitigate the poor dispersion of CF3I for cold temperature applications has

been proposed, namely, warming the bottle before being released into the cold ambience. Figure 8-94 

and Figure 8-95 illustrate, respectively, the concentration measurements at the two locations in the nacelle

simulator when the agent was released at ≈ 20 °C and the airflow th

s

conditi

a at 22 °C, see discussion above.) Note that in

lashing spray and the nacelle surroundings was

llows. First, a final state of the bottle was obtained 

es

re
838 Fluid Dispensing and Dispersion 

Figure 8-96. Calculated Liquid 

Fraction as a Function of Bottle 

Temperature. 

At temperatures above the discontinuity temperature, PROFISSY predicted a single-phase gaseous state 

before the isentropic process. The discontinuity is the result of the occurrence of a two-phase system due 

to the isentropic process. If the strategy is to decrease the liquid fraction, heating the bottle up to a 

te

bottle above perature appears to be a better choice from the figure, a dichotomy 

exists. On the one hand, the resulting liquid fraction is much lower than that at any temperature below the 

discontinuity the other hand, the isentropic process inadvertently transforms a gaseous 

hase, which persion of the agent, back to a liquid-vapor phase, which may hinder agent 

not very effective and there is 

mperature before the discontinuity temperature is reached seems to be an option. Although heating the

 the discontinuity tem

 temperature. On

p facilitates the dis

transport through cluttered space in the nacelle. However, system constraints (e.g., bottle operating 

pressure and space) on a specific aircraft platform may ultimately limit the implementation of either 

approach because the bottle pressure is a function of temperature. Although the above argument provides 

some thermodynamic basis for examining the feasibility of heating the bottle to improve dispersion for 

cold temperature applications, the interaction of a flashing spray with cold nacelle surfaces may also play 

an important role in determining subsequent agent dispersion. Further experiments are needed to validate 

the concept. 

The results from the two measurement locations in the nacelle have shown that the dispersion of CF3I 

under this condition with the equipment and the discharge nozzle used is 

substantial deterioration in agent concentration. If the military specification for halon 1301 extinguishing 

concentration can be applied to CF3I (volume fraction of 0.06 for 0.5 s), the concentration levels at the 

two measurement locations in the nacelle never exceed the extinguishing concentration requirement. The 

situation worsens at the location further away from the agent injection port. If the extinguishing 

concentration for the nacelle is designed based on room-temperature test data, the measurements indicate 

that the dispersion and performance of the agent are likely to deteriorate when the agent is used at a 

temperature below its normal boiling point. 

Temperature (oC)

-50 0 50 100 150

Liquid fraction (%)

0

10

20

30

40

50

60

70

80

90

100
Modeling of Fluid Dispersion in a Nacelle 839

Implications 

This study using CF3I as a surrogate shows that the agent’s no

and nacelle conditions are critical to the agent disp

Halon 1301 and HFC-125, with their respective normal boiling 

efficiently. The benefit of a more efficient suppressant chem

readily offset by the poor dispersion performance (pudd

agent is expected to be used at temperatures below its norm

before agent discharge could improve agent dispersion 

high normal boiling points, nacelle fire suppression system

dispersion performance data obtained at room temper

also be conducted. 

8.5 MODELING OF FLUID DISPERSION IN A NACELLE 

8.5.1 Background 

rmal boiling point and the prevailing bottle 

ersion processes for low temperature applications. 

points lower than -40 °C, will disperse 

ical with a high normal boiling point will be

ling and slow evaporation) in a nacelle when the 

al boiling point. Heating the storage bottle

performance at low temperatures. For agents with

 design should not be solely based on the agent

ature, and low-temperature dispersion tests should 

The focus of this research was to develop engineering models of flow, fire, and fire suppression and 

extinguishment in cluttered environments These models will advance the fundamental knowledge of fire

dynamics and suppression and provide a foundation for optimizing the distribution of suppressants for 

newly designed or retrofit fire safety systems in aircraft engine nacelles. This work was carried out in a 

joint, iterative computational/experimental approach to develop engineering subgrid models for use in

integral CFD and fire field sim lations. Models were developed using detailed CFD calculations 

performed at Sandia National Laboratories and discovery and validation experiments performed at Air 

Force and Naval laboratories. Only gaseous agents were investigated initially. The end goal was to 

provide computational tools to im livery and develop guidance to system designers. 

8.5.2 CFD Models 

During the course of the NGP, several CFD codes, which include VULCAN, CFD-ACE, Fire Prediction 

Model (FPM), and Fire Dynamics Simulator (FDS), have been assessed for use in modeling of fluid 

dispersion and fire suppression in aircraft engine nacelle environment. The simulation effort in this 

project focus e of VULCAN because of its many newly developed sub-models

le applications. 

Basic Features of VULCAN 

VULCAN has been developed at Sandia National Laboratories (SNL) in collaboration with the SINTEF 

Foundation and the Norwegian University of Science and Technology. VULCAN is derived from the 

KAMELEON Fire model44, 45 and uses an extension of the SIMPLEC method of Patankar and Spalding46

to solve the conservation equations on a structured, staggered, three-dimensional Cartesian, finitedifference grid. The brick mesh is employed to facilitate rapid solutions of radiative heat transfer. The 

ability to resolve the geometry of t e system is only limited by the ability to construct the appropriate grid 

with the Cartesian grid generator available in VULCAN. First- and second-order upwind schemes can be 

used for the convective terms. Turbulence is modeled using a standard two-equation k-ε model. The 

u

prove suppressant de

ed mainly on the us

specifically for aircraft engine nacel

h
840 Fluid Dispensing and Dispersion 

VULCAN code has the capability of performing fire simulations, and the combustion simulation is based 

on Magnussen’s Eddy Dissipation Concept (EDC) assuming infinitely fast combustion.47 Models of soot 

generation and oxidation are also included. 

The wide range of length-scales in reacting flows presents a significant modeling challenge. Where air 

flows are high enough that the flow is turbulent (as is typical in most terrestrial fire environments), fluidmixing length-scales may span several decades from the geometric scale down to the Kolmogorov scales. 

Chemical length-scales may be even smaller, typically less than a millimeter. Because it is not possible to 

resolve the full range of dimensions, models of subgrid-scale processes are employed. Within the 

VULCAN fire-field model, the k-ε model is employed to predict the effect of turbulent fluctuations on the 

flow, and the EDC model predicts the chemical evolution using a collection of perfectly stirred reactors 

 mixing), then 

pletion. This 

mbers smaller than a critical value, the flame will be extinguished. The critical Damköhler 

number that relates τK and the extinction time is not known a priori and is determined empirically by 

ts then depend strongly on heat flux through walls, a quantity 

that is not well known for the experimental configurations. Two neglected thermal effects are of 

ux through the wall, which is unknown. Estimates indicate that heat 

losses to obstructions are significant here and tend to increase the chemical time scale. 

(PSR). 

Modeling Fire Suppression 

Combustion in VULCAN is modeled using the EDC that can be thought of as a distribution of PSRs that 

relate the fuel-consumption rate to the fluid-mixing rate, the latter obtained from turbulent time scales. 

The submodels within VULCAN assume that the fuel-air mixing rates scale with the inverse of the 

Kolmogorov time scale (τK). The actual mass rate of reactant mixing is proportional to τK and is also a 

function of the local mass fractions of reactants. In high-fidelity modeling of turbulent diffusion flames, 

the fluid time scales corresponding to extinction are found to be very close to the Kolmogorov time 

scales.48 Conversion of reactants to products and the associated heat release occur at a rate determined by 

either the mixing rate or some maximum chemical rate that is a function of the composition. Fires are 

typically limited by mixing, but if the ratio of time scales is sufficiently small (fast

conversion of reactants to products and the associated heat release cannot proceed to com

results in a reduction in temperature leading to a reduction in chemical rates. Continued reduction in the 

mixing time relative to the chemical time leads to a state where no combustion is possible, and the flame 

is extinguished. The ratio between fluid and chemical mixing times is generally referred to as the 

Damköhler number. A suitable chemical time relevant to flame extinction can be defined as the value of 

PSR extinction time corresponding to a switch from combustion occurring to combustion being 

impossible, which is the chemical time scale representing the fastest possible chemical reaction rates. For 

Damköhler nu

matching blow-off criteria for an ethane jet flame.49 The suppression model takes advantage of this 

Damköhler number criterion by determining values corresponding to extinction from detailed chemicalkinetic calculations in the PSR configuration. 

The chemical time scale is a function of the reactant mass or mole fractions, enthalpy, and pressure, 

assuming these reactants originate at ambient pressures and temperatures, neglecting enthalpy changes. 

While it is straightforward to make the chemical time scale a function of the enthalpy (and this has been 

done with the suppression model), the resul

moderate significance: For JP-8 pool fires, the initial fuel vapor temperature is somewhat greater than 

ambient; this tends to reduce the chemical time scale. Radiative thermal losses and losses to the walls, 

while included in VULCAN, are neglected in the suppression model because the magnitude of these 

losses is dependent on the heat fl
Modeling of Fluid Dispersion in a Nacelle 841

Within VULCAN, chemical reactions are greatly simplified, reflecting the predominance of mixing 

processes in fires. This simplified treatment of kinetics is not necessarily sufficient for suppression 

predictions, and chemical time scales corresponding to the addition of suppressant are calculated off-line. 

These off-line calculations use the CHEMKIN PSR capability50 with a detailed chemical mechanisms for 

iso-octane from Curran et al.,51 coupled with a mechanism logenated suppressants from Babushok 

et al.52 Chemical time scales have been obtained for iso- 25, N2, 

H2O, CO2 and CF3Br, although only results with the first su al time 

scales relevant to suppression are obtained by conducti shorter 

residence times until combustion is extinguished, thereby defini

CFD simulations, values for the extinction time are fitted to a suitable functional form as a function of the 

mole fraction of HFC-125 added to the inlet air. For iso-octane, the selected surrogate for JP-8, the curve 

fit is inverted to express the magnitude required to extinguish the mixture. Given the chemical time scale 

as a function of the fluid cell composition and the mixing rate based on the dissipation rate and viscosity 

(through the Kolmogorov time scale), the magnitude of the Damköhler number in that cell determines 

whether combustion takes place in that cell or not. In the numerical implementation, given τK in a fluid 

cell, the time required to extinguish the flame is obtained using a comparison with the HFC-125 mole 

fraction in the fluid cell to indicate whether suppression occurs. A similar approach was used by 

Byggstoyl and Magnussen for local quenching in the absence of suppressants.53 A detailed description of 

or flame attachment or for local extinction depending on the local time scales of the heat 

ous media literature. The second class of problems was a 

linder in cross-flow for which both detailed experimental measurements and detailed CFD calculations 

f velocity deficit and kinetic energy profiles were available. Results from the experimental 

 for ha

octane combustion in air with HFC-1

ppressant are described here. Chemic

ng PSR simulations at successively 

ng the extinction time. To facilitate use in

the fire suppression model can be found in Hewson et al.54

Subgrid Scale Clutter Model 

The release and transport of an agent into an engine nacelle is sensitive to local geometrical features or 

“clutter” that is difficult to resolve numerically without using an excessively large CFD grid. Examples 

include wire bundles or hydraulic lines. Capturing these features in a grid will result in extremely small 

time steps for accurate numerical simulations of agent release and subsequent fire suppression. An 

alternative is to use a sub-grid scale (SGS) model to represent the macroscopic effects of these small 

features using reasonably sized CFD grid-cells. For agent dispersal in a cold flow environment, the 

macroscopic flow effects of sub-grid clutter cells must have two main effects. The first is to provide a 

momentum sink due to viscous and pressure drag forces. The second is to either increase or decrease the 

turbulent kinetic energy, depending on the local clutter size relative to the characteristic length-scale of 

turbulence. In general, if the size of the clutter is smaller than the turbulent length-scale, the turbulent 

kinetic energy will decrease, and vice versa. Regarding flame suppression, the clutter serves as either a 

mechanism f

transfer to the clutter and chemical kinetics for ignition. 

Specifically, the effects of subgrid scale (SGS) clutter on the momentum and turbulent kinetic energy 

transport were developed with application to engine nacelles.55, 56 The modeling methodology was based 

on a two-phase averaging procedure introducing expressions that required SGS modeling. The SGS 

models were formulated using a combination of well-established constitutive relations borrowed from the 

porous media literature and classical relations for drag on bluff bodies. The modeling methodology was 

exercised for two classes of problems. The first was flow in a porous media for which the obstructions 

were relatively dense. For this problem, predictions using the SGS clutter model were compared to 

established correlations taken from the por

cy

o
842 Fluid Dispensing and Dispersion 

measurements r

coefficient. C

evealed that the effect of upstream turbulence had a significant effect on the drag 

omparisons of the detailed CFD predictions to experimental measurements showed 

cheme in which the assembled equations for each dependent variable are solved 

sequentially and repeatedly to reduce errors to acceptably low values. 

us verning equations were solved 

until a steady-state solution was reached. Heat transfer was not modeled. The code was applied using the 

th a single fluid (air) and the k-ε turbulence model of Launder and Spalding59

with wall functions. In addition, the k-ω turbulence model of Wilcox60 and the Low Reynolds number k-ε

e 

principal processes involved the initiation and sustainment of fires, or ullage explosions in a dry bay. The 

omputers, and queries the user for specific information about the conditions to 

principles which are supplemented by empirical data 

as needed. Study conditions that can be examined by the FPM are grouped into 9 categories and briefly 

reasonable agreement for the mean and RMS streamwise velocity indicating that extracting phaseaveraged quantities from the detailed computations, as part of future efforts, was a sound approach for 

determining unknown clutter model constants in a bluff body drag limit. 

Basic Features of CFD-ACE 

CFD-ACE, a commercial computational fluid dynamics model with a body-fitted coordinate grid, is a 

pressure-based commercial code57,58 that solves the Farve-averaged Navier-Stokes equations. The code 

uses a cell-centered control volume approach to discretizing the governing equations. It employs an 

iterative solution s

Vario modeling options are available. In the present calculations, the go

incompressible option wi

turbulence model of Chien and Smith61 were used in sensitivity calculations. First-order upwind spatial 

differencing was used for the turbulence quantities and 90 % second-order upwind spatial differencing 

(with 10 % first order blend) was used for the velocity and density. The structured grid utilized a bodyfitted coordinate system with multiple domains. 

Basic Features of FPM 

The Fire Prediction Model (FPM)62 simulates the events occurring during the penetration of a single 

ballistic threat into an aircraft and subsequent penetration of a fuel tank. The model describes th

model runs on personal c

be analyzed. No off-line computations by the user are required; the model contains pre-determined threat, 

fluid, and target material data encompassing a wide range of conditions of interest. The FPM was 

designed specifically to provide a tool to examine dry bay fires and ullage explosions over a wide range 

of conditions rapidly and apply directly to the needs for live-fire testing predictions, planning, and posttest analysis; vulnerability estimates (probability of kill given a hit, Pk/h); and aircraft design guidelines. 

The simulation principally relies on basic physical 

described below. 

Flammable Liquid Container Type The user can select an integral or non-integral tank or a liquid line. 

Run Setup The run setup option allows the user to tailor the run to their needs. The user can select 

single-shot or parametric runs, specify the flow field cell size, and modify the time step to increase speed 

or accuracy. 

Target Vehicle The FPM allows the user to specify either an air or ground target vehicle. Selections of 

threats, liquids, and target materials are restricted based on the vehicle selected. 
Modeling of Fluid Dispersion in a Nacelle 843

Ignition Source The FPM simulates spray ignition by either a ballistic threat, hot surface, or electrical 

spark. Ignition by a hot surface can occur directly by sprayed droplet impinging directly onto the hot 

surface or indirectly as liquid vapor previously released into the bay is carried past the hot surface. 

-5606 and MIL-H-83282) are available. In addition, the user is given the option to describe the 

characteristics of some liquid of interest, other than what is available. 

Encounter Conditions The user may define a wide range of environmental conditions under which the 

velocity, threat approach direction, and point of impact on the target’s surface. In addition, the model can 

, and an Eulerian 

Ballistic Threat Four types of ballistic threats can be simulated by the FPM: Armor-Piercing Incendiary 

(API) projectiles, High Explosive Incendiary (HEI) projectiles, warhead or bomblet fragments, or shaped 

charges. Because the functioning of an API projectile can vary depending on impact conditions, four 

types of function can be simulated: complete, partial, slow burn, or delayed. 

Flammable Liquid Seven flammable liquids can be selected by the user. Three military jet fuels (JP-4, 

JP-5, or JP-8, two different flash points) a diesel fuel (DF-2), or two military hydraulic fluids 

(MIL-H

simulation is to be run, including target altitude, fuel and ambient air temperatures, ventilation air 

velocity, external pressure, and target velocity. For altitudes above sea level, the model will compute 

ambient conditions using the standard atmosphere. External air pressures will be computed by the model 

based on the target surface and location impacted and orientation of the damage-hole to airflow. 

Dry Bay Description The FPM provides the user with a large number of options and features to describe 

the dry bay. First, the dry bay dimensions and location are defined. The dry bay is assumed to be a 

rectangular parallelepiped. Other items needed to define the bay include wall material and thickness; 

internal clutter locations and dimensions; structural barrier locations, dimensions, and orientation; 

ventilation flow areas and locations; and the presence of an ECS duct. As part of the dry bay description, 

a fire-suppression system can be specified. The user has a wide range of options to describe the firesuppression system. Ten agents can be selected, including both cooling and reactive agents. Next, the 

number, location, and type of injector can be specified. The type can be spherical (agent injected radially 

from location) or directional (agent injected in a specified direction). The duration of the agent injection 

and mass-rate of injection are also needed. Finally, the injection can be activated by an IR sensor or 

manually, at the user's discretion. The clutter option is sufficiently general to allow the user to shape the 

bay into various shapes and/or multiple compartments. If a hot surface is present within the bay, the 

clutter is used as the hot component, and the user can describe the hot surface by its location and 

temperature. 

Impact Condition The FPM requires a description of the impact conditions, including threat impact 

simulate the threat function to be on the dry-bay surface or internal to the bay. 

As part of this effort, the FPM was modified to allow ignition of a spray fire with a user-described 

ignition source, bypassing the ballistic-impact routines of the model. The approach used by the FPM to 

simulate a spray fire is known as a separated-flow (two phase) model. This approach treats the finite rates 

of exchange of mass, momentum, and energy between the liquid and gas phases. In general, there are 

three approaches to separated flow models, reflecting differences in simulating evaporating and 

combusting sprays. The FPM uses the discrete-droplet approach. In this approach, the entire spray is 

divided into many representative samples of discrete drops whose motion and transport through the flowfield are found using a Lagrangian formulation in determining the drop’s history
844 Fluid Dispensing and Dispersion 

formulation is used to solve the governing equations for the gas phase. It is assumed that the spray is

dilute; i.e., although the droplets interact with the gas phase, they do not interact with each other. Thus, 

droplet collisions are ignored and empirical correlations for single droplets can be employed for 

interphase transport rates. 

In two-phase models, the liquid droplet flow is divided into a finite number of classifications: Each drop 

class is assigned an initial diameter, velocity, direction, temperature, concentration, position, and time of

injection. The temporal evolution of each class is then determined throughout the flow. 

The FPM uses this approach, adapting it to the FPM dry-bay flow-field. In effect, the FPM tracks the

position of each class of droplet, computing the vaporization for each class dependent on the droplet

location and bay conditions at that location, and the model's flow-field computes the conservation

equations. The position of a given group is calculated from:

∫

∫

∫

= +

= +

= +

z z v dt

y y v dt

x x v dt

o z

o y

o x

p p p

p p p

p p p

(8−43)

The instantaneous velocity is determined by the solution of the equation of motion. 

C AV mg dt d 2

The standard drag coefficient for solid spheres is employed for sprays. 

dV

m = − +2 / 1ρ (8−44)

⎪

⎪

⎪

⎩

⎪

⎪

⎪

⎨

⎧

>

<

⎥

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎢

⎣

⎡

+ =

0.44 Re 1000

Re 1000

6

3

2

Re

1

Re

24

p

r

p

d

d

p

D d

for

for

d

C (8−45)

The Reynolds number is defined as: 

v

d p Re =

The simulation of the transport properties involved in fire involves the application of the conservation 

equations of mass, momentum, energy, and species for that system. These equations simply describe a

balance of the net rate of inflow and outflow of some particular parameter, its rate of storage, and its rate

of production and destruction within a volume. The FPM describes the motion of the fluid within the bay 

by the Eulerian approach where the composition, velocity, and state of the fluid everywhere in the bay 

occupied by the fluid at all instants are determined. To derive the Eulerian equations of motion, a 

stationary coordinate system is chosen and fluid is observed entering and exiting a volume of arbitrary

shape and size. This control volume is found within the fluid and is at rest with respect to the coordinate 

system. In the FPM, the volume is a cube whose length is specified by the user. 

v p p − (8−46)d v
Modeling of Fluid Dispersion in a Nacelle 845

The FPM uses a staggered grid concept where the scalar properties of pressure, temperature, mass, and

species mass are determined at the cell center and fluid velocities are established at each cell edge in each 

coordinate direction. 

Solutions are obtained on a numerical grid of elementary control volumes which fill the entire dry bay. 

This approach ensures local balances in the many small control volumes, subject only to the particular 

computational efficiency and reduce model run-time, the FPM utilizes 

stem; a diffusion and convection grid. Within the diffusion 

(8−47)

boundary conditions. To improve

a multi-cell, three-dimensional dual grid sy

grid, the simulation of fire is performed by the solution of the conservation equations of mass, 

momentum, species, and energy. Because convective currents work over much larger scales than the 

processes of diffusion and combustion, the conservation of momentum (the convective mass and energy 

flow) is performed in the convective grid and results superimposed into the diffusion grid by the prorating

the flow. 

The mass-rate of change of chemical fire suppressant can occur by convection, depletion by chemical

reaction, or injection into the bay. The FPM simulates both chemical and "cooling" types of agents. 

Cooling agents such as CO2 and H2O extinguish flame by the rapid introduction of mass into the

combustion zone, which absorbs heat through changes of heat capacity and the heat of vaporization as

described above. Chemical agents extinguish fires by the removal of free radicals throughout the 

combustion process, precluding complete combustion as well as providing some cooling effect. 

The FPM treats the chemical reaction of fuel vapor, oxygen, and suppressant as a one-step, third-order 

reaction, as shown below.

products

k

F +O+ S →

where k is the specific reaction rate constant and follows the Arrhenius law 

⎟

⎠

⎞ ⎜

⎝

⎛ = RT

E k Aexp (8−48)

Basic Features of FDS 

Fire Dynamics Simulator (FDS), developed by NIST, is a CFD model of fire-driven fluid flow. The 

formulation of the equations and the numerical algorithm and a user’s guide can be found in McGrattan 

et al.63,64 In conjunction with FDS, an OpenGL graphics program called Smokeview was also developed

by NIST to visualize the numerical output generated by FDS. Smokeview performs this visualization by

nd

stems and sprinkler/detector activation studies. The other half consists of

 providing a tool to study

presenting animated, traced, particle flow, animated contour slices of computed gas variables, a

animated surface data. Smokeview also presents contours and vector plots of static data anywhere within 

a scene at a fixed time. A detailed description of Smokeview can be found in Forney and McGrattan.65

Since its first release in February 2000, about half of the applications of FDS have been for design of 

smoke-handling sy

reconstructing residential and industrial fires. Throughout its development, FDS has been aimed at 

solving practical problems in fire-protection engineering, while at the same time
846 Fluid Dispensing and Dispersion 

fundamental fire-dynamics and combustion. Some of the major components and sub-models used in FDS 

are briefly described below. 

Hydrodynamic Model FDS solves numerically a form of the Navier-Stokes equations appropriate for 

 enough. LES is the default 

mode of operation. 

 derived 

from a combination of simplified analysis and measurement. 

about the burning behavior of the material. Usually, material properties are stored in a database and 

low-speed, thermally driven flow with an emphasis on smoke and heat transport from fires. The core 

algorithm is an explicit predictor-corrector scheme, second order accurate in space and time. Turbulence 

is treated by means of the Smagorinsky form of Large Eddy Simulation (LES). It is possible to perform a 

Direct Numerical Simulation (DNS) if the underlying numerical grid is fine

Multi-blocking This is a term used to describe the use of more than one rectangular mesh in a calculation. 

FDS calculations can prescribe more than one rectangular mesh to handle cases where the computational 

domain is not easily embedded within a single block. 

Combustion Model For most applications, FDS uses a mixture-fraction model for combustion. The 

mixture fraction is a conserved scalar quantity that is defined as the fraction of gas at a given point in the 

flow-field that originated as fuel. The model assumes that combustion is controlled by mixing, and that 

the reaction of fuel and oxygen is infinitely fast. The mass-fractions of all of the major reactants and their 

products can be derived from the mixture by means of “state relations,” empirical expressions

Radiation Radiative heat transfer is included in the model via the solution of the radiation equation for a 

nonscattering gray gas, in some limited cases using a wide-band model. The equation is solved using a 

technique similar to finite-volume methods for convective transport, thus the name given to it is the 

“Finite Volume Method” (FVM). Using approximately 100 discrete angles, the finite-volume solver 

requires about 15 % of the total CPU time of a calculation, a modest cost given the complexity of 

radiative heat transfer. Water droplets absorb thermal radiation. This is important in cases involving mist 

sprinklers, but it also plays a role in all sprinkler cases. The absorption coefficients are based on Mie 

theory. 

Geometry FDS approximates the governing equations on a rectilinear grid. The user prescribes 

rectangular obstructions that are forced to conform with the underlying grid. 

Boundary Conditions All solid surfaces are assigned thermal boundary conditions, plus information 

invoked by name. Heat and mass transfer to and from solid surfaces is usually handled with empirical 

correlations, although it is possible to compute directly the heat and mass transfer when performing a 

Direct Numerical Simulation (DNS). 

Heat-Conduction through a Wall In early versions, heat that was conducted into a wall was lost to an 

infinite void. Now it is possible to transfer the heat from one room to another through a one-cell-thick 

wall. 

Thin Walls It is possible to prescribe a thin sheet barrier to impede the flow. This is particularly useful 

when the underlying grid is coarse, or when the barrier is indeed very thin, like a window. However, FDS 

will reject obstructions that are too small relative to the numerical grid. 
Modeling of Fluid Dispersion in a Nacelle 847

Suppression The suppression algorithm is a necessary adjustment to the mixture-fraction model of that 

prevents combustion from occurring in cool, oxygen-depleted environments. Recall that the basic 

mixture-fraction model assumes that fuel and oxygen burn when mixed. This is a good assumption in 

many fire scenarios, but when compartments become under-ventilated, or when agents are injected, the 

“mixed is burnt” model is not appropriate. 

nt flow-field can 

be prescribed. 

tability for highly-cluttered engine nacelle 

applications, an initial exploratory effort was to investigate the flow field in a simplified, quarter-scale 

nacelle of typical shape. Calculations were performed using both the CFD-ACE and VULCAN codes. 

ons examined correspond to the same Reynolds numbers as test data from the full-scale 

acelle simulator used by the 46th Test Wing of the United States Air Force (USAF). The

conditions were examined using both models prior to fabrication of a test fixture. Based on the pre-test 

 have been performed 

for comparison to the experimental results obtained from the quarter-scale test fixture. Because of 

eometric complexities, efforts to characterize the flow field in engine nacelles using computational fluid 

dynamics have been limited to simplified cases. Calculations performed to date include the analysis 

med in the Aircraft 

Engine Nacelle (AEN) test facility for the Halon Alternatives Research Program for Aircraft Engine 

Nacelles and Dry Bays. Marginal agreement between calculation results and experimental data was 

obtained. In some cases, opposite trends were observed in the calculations and experimental results. 

Additional calculations were performed by Lopez et al.67 of a typical fighter nacelle geometry simulating 

ent release via solid propellant gas generator. 

Quarter-scale experiments (to allow access of appropriate diagnostics guided by pre-test calculations) 

were performed at WPAFB.68 Flow conditions were scaled to match the Reynolds numbers in the 

ed in the AEN facility as part of the Halon Alternatives Program. 

mpared with experimental data at multiple cross sections within the 

flow field. The pre-test calculations assisted in the design and execution of the experiments required to 

ain the necessary knowledge for these kinds of flows. Then the post-test simulations, using bot

ACE and VULCAN, and the exact geometry and boundary conditions from the experiments compared 

 fire-suppression effects, 

Initial Conditions It is possible to prescribe some non-trivial initial conditions. For example, certain 

parts of the domain can have temperatures different from ambient, and an initially consta

8.5.3 Code Assessment Using Quarter-Scale Nacelle Tests and Simulations 

To evaluate the fidelity of these CFD codes and their sui

Flow conditi

n se flow 

simulations, a quarter-scale test fixture was designed and fabricated for the purpose of obtaining spatially 

resolved measurements of velocity and turbulence intensity. Post-test calculations

g

performed by Hamins et al.66 of agent transport for the extensive set of tests perfor

ag

extensive set of experiments perform

Calculations were performed and co

g h CFDCFD results with the experimental results.

The primary flow-field calculations used the CFD-ACE code because of its body-fitted coordinate 

features to represent smooth circular geometries. Although capable of simulating reacting flows, the 

CFD-ACE code does not contain models for radiative heat transfer, turbulent combustion, and soot 

production needed to simulate fires. These fire-physics models are included in VULCAN; however, the 

VULCAN model approximates the geometry by using a rectangular brick grid to facilitate the solution for 

radiation. Although many nacelle fire cases can be addressed without modeling the fire-physics, it is 

ultimately desirable to be able to represent the heat transfer from the fire and the
848 Fluid Dispensing and Dispersion 

such as the influence of turbulent flame strain combined with fuel/air mixtures. Both models have been 

applied in the pre-test and post-test calculations. The flow solution yielded by the approximate mesh used 

in the VULCAN code is compared with the results provided by the CFD-ACE modeling to quantify the 

effect of the Cartesian VULCAN mesh. 

lity with LDV apparatus. 

Simplified Nacelle Tests and Simulations 

A photograph of the experimental test fixture is shown in Figure 8-97. The fuselage stations where 

experimental velocity data were obtained are shown in Figure 8-98. 

Figure 8-97. Photograph of the Quarter-Scale Nacelle Test Faci

Figure 8-98. Measurement Stations in the Quarter-Scale Nacelle. 
Modeling of Fluid Dispersion in a Nacelle 849

The CFD codes modeled the nacelle geometry starting at measurement station #1 (MS-1), where 

experimental data were used as an exact initial and boundary condition. The modeled geometry ended 

10 pipe diameters downstream of the core region. 

In the present simulator, the cone half-angle was machined at 10 degrees. As a result of the cone angle 

face boundary. 

(based on diameter) between the full-scale and quarter-scale nacelle simulators, for a specified 

mass flow. Air within the test range at ambient temperature and pressure was used to supply the flow 

ensity, a mass flow for the 

quarter-scale nacelle was determined to be approximately 0.344 kg/s. Assuming uniform flow, the 

e traverses were obtained to confirm that the air supplied to the 

simulator using an external blower was adequately conditioned. Verification of the flow conditioning 

s were obtained by horizontally traversing across the tube diameter. Each velocity traverse 

consisted of measurements at 38 locations across the tube diameter. At each spatial location, 

V were initiated, which locations 

Upon entering the quarter scale nacelle, the flow undergoes a change from a pipe flow to an annular flow. 

This change in flow geometry is induced by a fluoropolymer cone, with a sharp leading edge centered 

within the nacelle. The cone is approximately 432 mm long and 149 mm at its base. The base of the cone 

is attached to the 149 mm teflon core which resides within the nacelle proper. 

and transition duct wall offset, the flow is redirected away from the simulator centerline. This 

geometrical change occurs abruptly at the interface between the air supply duct and nacelle, and is 

therefore considered to be a sharp or discontinuous sur

Further, this divergence increases the flow cross-sectional area by a factor of approximately three. After 

passage through this transition duct the flow is abruptly redirected towards the simulator centerline by 

10°. This occurs at a second discontinuity on both the inner surface (simulating the engine core) and 

outer surface. This next element, referred to as the nacelle proper is configured as an annular channel of 

constant spacing, H, between inner and outer surfaces − 74.7 mm. The nacelle proper extends 

downstream 1.22 m, approximately 16 H. 

Exiting the nacelle proper the flow is redirected toward the simulator centerline through another 

10-degree offset. This offset occurs at the entrance of a second cone, designated as the Exit Transition 

Duct (ETD). At the entrance of the ETD, the inner core of the nacelle proper undergoes a discrete 

transition back to a conical surface with a sharp trailing edge, thereby producing a transition from a 

converging annular channel back into a pipe flow. 

Flow conditions upstream of the quarter-scale engine nacelle were determined by matching the Reynolds 

number 

facility in all tests. Supply air density was computed using the local temperature and pressure of the 

surrounding air resulted in a computed density of 1.2 kg/m3

. From this d

average velocity within the 152.4 mm air supply tube was computed and estimated to be 15.7 m/s. Under 

these conditions the Reynolds number based on tube diameter, ReD was estimated to be 172,000. 

Velocity measurements were accomplished using both hot-wire anemometry and laser-Doppler 

velocimetry (LDV). Several hot-wir

section consisted of the acquisition of velocity data at the exit of the inlet supply tube with a typical hotwire, nominally 4 microns in diameter and 1.25 mm-long, positioned normal to the mean flow. Velocity 

profile

5000 samples were acquired from which a mean velocity and turbulence fluctuation level were computed. 

Once the supply airflow was considered to represent a fully-developed pipe flow, the simulator was 

attached to the inlet supply tube, and velocity traverses utilizing an LD
850 Fluid Dispensing and Dispersion 

or measurement stations were determined from prior simulations conducted by Sandia National 

Laboratories (SNL). 

For VULCAN, the extreme length of the geometry created a grid with many computational cells 

(Figure 8-99). The final Cartesian grid consisted of 196 (X-direction) by 45 (Y-direction) by 

45 (Z-direction) grid points for a total of 396,900 cells in the simulation. The cells in the cross-section 

 was approximately 5 days utilizing a 250 MHz processor. The solution was converged 

such that all residuals were reduced 5 orders of magnitude. 

 the annulus. Circumferential spacing was constant at 

were 0.007 × 0.007 m2

, while the minimum cell length in the axial direction was 0.0085 m and varied 

along the pipe (refined in transition regions and stretched in the exit pipe and other straight sections). The 

simulation time

Figure 8-99. VULCAN Gridding for the Quarter-Scale Nacelle. 

The computational grid used by CFD-ACE consisted of 301 axial (primary flow direction) points, 

25 radial points, and 48 circumferential points, for a total of 361,200 grid points. Example slices from the 

grid are shown in Figure 8-100. Axial grid spacing in the annular (nacelle/core) region varied from 

0.6 cm near the corners of the expansion/contraction regions to 1.8 cm in the middle section. Radial 

spacing was approximately 0.2 cm throughout

7.5 degrees, which relates to arc dimensions of 2.0 cm at the maximum nacelle diameter to 1.0 cm at the 

maximum core diameter. In addition to the fine three-dimensional solution, a coarser mesh solution was 

obtained. The coarse mesh was generated by extracting every other grid point in all three directions from 

the fine mesh. The coarse mesh contained 151 axial points, 13 radial points, and 24 circumferential 

points, for a total of 47,112 grid points. In both cases, convergence was obtained such that all residuals of 

interest (velocity, pressure, turbulence) were reduced by more than 5 orders of magnitude. The fine mesh 

solution required 400 Mbytes of memory, 2200 iterations and 15 days computing time on a 250 MHz 

processor. 

The boundary conditions used in the CFD simulations were carefully applied to represent the 

experimental conditions. In some cases, a slight deviation from the experimental conditions was 

necessary. The boundary conditions are fully discussed in Black et al.69
Modeling of Fluid Dispersion in a Nacelle 851

CFD-ACE Grid Used in the 

onl

Figure 8-100. Section of the 

Simulation. 

The data measured at the inlet (MS-1) showed a slight asymmetry in the velocity profile. It was not 

possible to use this asymmetric velocity profile as an inlet boundary condition in the calculations since 

y a radial profile was required. Instead, a logarithmic symmetrical profile was used to fit the data. 

0.12

max

⎟

⎠

⎞ ⎜

⎝

⎛ = R

y

u

u (8−

The agreement with measured inlet profile is shown in Figure 8-101. In both cases, the maxim

49)

um 

lence intensity was also asymmetric.

he simulations used a symmetric inlet turbulence intensity based on a parabolic curve fit of experimental

ata. This was accomplished by splitting the experimental data set at the midpoint, mirroring both sides 

a

for the inlet turbulence intensity is shown on the plot as the solid curve. 

Figure 8-101. Inlet Velocity Profile. 

velocity is 20.07 m/s. Similar to the inlet velocity, the inlet turbu

T

d

cross the centerline, and fitting a parabolic curve to these data in Figure 8-102. The resulting equation
852 Fluid Dispensing and Dispersion 

omparison with Experimental Data 

At the outlet o nt conditions 

of 98,700 Pa and 293 K. The outlet was located 10 pipe diameters downstream from the nacelle’s core.

ly larger than the CFD-ACE predictions and show 

oscillations near the nacelle wall and core wall (Figure 8-103). The VULCAN velocity predictions show 

deviate near the walls.

ity Profiles at Measurement Station 4. 

Figure 8-102. Inlet Turbulence Intensity Profile. 

C

f the nacelle geometry, constant pressure was specified using standard ambie

Along the surfaces of the core there was no surface roughness, and the temperature was likewise 293 K. 

The experimental velocities at MS-4 are slight

a very narrow band of high velocity flow with rapid decreases in velocity away from the center of the 

channel because the VULCAN grid is not smooth along the angled walls and is blocking more of the 

flow. The experimental data shows poorer resolution near the walls. The experimental turbulence

intensity values agree with the CFD predictions in the center of the channel but

Figure 8-103. Velocity and Turbulence Intens
Modeling of Fluid Dispersion in a Nacelle 853

The velocity predictions at MS-7 are in very good agreement with the experimental data, and the CFD

predictions of turbulence intensities also show good agreement, with the data showing slightly larger 

turbulence intensity. It should be noted that the experimental data does not span the entire distance to the 

core (Figure 8-104). 

Figure 8-104. Velocity and Turbulence Intensity Profiles at Mid-nacelle. 

Figure 8-105. Comparison of Simulation and Experimental Data at the Exit Cone. 

The CFD-ACE velocity predictions shown in Figure 8-105 are in very good agreement with the

experimental data, whereas, the VULCAN predictions show the flow slowing down near both the nacelle 

wall and the core wall and increasing in the center of the channel. This is caused by the stair-stepped grid 

along the angled walls which tend to squeeze the flow into center of the channel. Both CFD-ACE and

VULCAN predict ~10 % lower turbulence intensity values than the experimental data, similar to the 

previous measurement plane (MS-8). 
854 Fluid Dispensing and Dispersion 

At the final measurement plane, MS-11, in the outlet pipe the predicted velocity profiles show the wake

diminishing with increasing distance from the core, as shown in Figure 8-106. In addition, the measured

turbulence intensity is considerably higher than CFD-ACE predicted, which is a constant turbulence 

intensity below 10 % for the majority of the flow across the pipe. 

 

Figure 8-106. Velocity and Turbulence Intensity Pr files Flow in the Exit Pipe. 

The comparisons of the numerical predictions with the experimental data, in general, showed good

agreement with the velocity, and the turbulence intensity predictio s also showed good agreement in the 

inlet pipe section and in the inlet transition section. However, the numerical predictions showed larger 

turbulence intensity near the corner region between the inlet transition duct and straight core section.

Then, downstream the data consistently showed larger turbulence intensity at the remaining measurement 

planes, although the trends were similar. In addition, there were some differences between VULCAN and

CFD-ACE results due to the Cartesian grid structure used by th nces

mainly occurred in the inlet transition duct and the outlet transiti oothly 

angled, but the grid is stepped. Also, the experimental data tend orer resolution near the

walls of the transition ducts because of the physical difficulties in measuring near these surfaces. 

8.5.4 Assessment of VULCAN Fire Suppression Sub-model 

The optimization of fire suppression systems in aircraft engine nacelle applications is made more

challenging by the fact that clutter in the form of structural supports, wiring, piping, machinery and 

een

identified as some of the most challenging to suppress.

low obstructions can act as flame holders, stabilizing flames and making suppression difficult. 

Stabilization is aided by creating a recirculation region with relatively low dissipation rates, and thus large 

τκ, and hot products. Suppression is made more difficult because it takes significantly more time for

o

n

e VULCAN code. These differe

on duct where the walls are sm

ed to show po

similar items can adversely affect the suppressant flow. Furthermore, recirculation zones that form on the

downstream sides of clutter have been identified as favorable for flame stabilization.70,71,72 Of the various

stabilized fires, liquid pool fires established behind obstructions such as structural ribs have b

70,71,72

F
Modeling of Fluid Dispersion in a Nacelle 855

suppressant to penetrate the recirculation zone than it takes for the suppressant to pass over an

unobstructed flame. Hamins et al. and others66,75,73 have taken advantage of a simple mixing model in the

form of the conservation equations for an unsteady PSR that predicts the suppression delay associated

with the delay in mixing suppressant into a recirculation zone.50 The model predicts that the mole

fraction of suppressant in the recirculation zone varies as 

[ ( )] recirc mix X = X 1 − exp − t /τ ∞ (8−50)

where X∞ is the suppressant mole fraction outside the recirculation region and τmix ∝ h / u* is the mixing 

time, proportional to the quotient of the velocity past the recirculation zone and the recirculation zone 

thickness, here taken to be the step height, h. Takahashi et al.74 measured the proportionality constant for

their configuration to be τmix = 34.7(h / u*) where u* is explicitly given as the average of the mean flow

velocity over the step and the mean flow without the step. 

In this section, the efficacy of the VULCAN fire suppression s

stabilized behind obstructions was assessed. The suppression model was evaluated using measurements 

of the agent required to suppress a fire stabilized behind a rearward-facing step.75 The CFD code was 

then used to indicate ways in which the arrangement of clutter within an environment resembling an 

aircraft engine nacelle may change suppressant requirem ts, suggesting potential design practices that 

might be confirmed with further experimental measurements. 

For a CFD model to adequately predict suppression in the presence of obstructions, it will be important

that the model can reasonably predict (1) the suppressant required to extinguish flames at a given fluid 

mixing rate, and (2) the rate of suppressant mixing into recirculation regions. To address these questions,

simulations using the suppression model described above were conducted for JP-8 pool fires stabilized 

behind a backwards-facing step, and results are compared with measurements of Takahashi et al.75 Those 

simulations for which there are experimental data available and that are involved in model evaluation are 

referred to as Case A1; see Table 8-12. All simulations denoted as Case A are conducted in a 154 mm by

154 mm square wind tunnel, 770 mm long, with a 64 mm tall backwards-facing step placed in front of a 

150 mm by 150 mm JP-8 pool. Airflow through the wind tunnel was 10100 standard L/min, the 

turbulence level at the entrance was set to 6 % and the turbulent length scale, used to calculate the initial

dissipation rate was set to 3 mm based on the turbulence generators employed in the experiments. 

Table 8-12. Description of Simulations of Pool Fires Stabilized behind a Backwardsfacing Step. 

sub-model for the suppression of pool fire

en

Case Description τmix

A1* As in Takahashi et al.

75 with the fuel being JP-8 and the suppressant being HFC-125. 0.23 s 

A3 As in A1 but with a 42 mm rib on the upper wall collocated with the backwards-facing step. 0.15 s 

A5 As in A1 but with a 42 mm rib on the upper wall 84 mm behind the backwards-facing step. 0.24 s 

B1 22.5 cm high, 180 cm wide, and 180 cm long wind tunnel with 5 cm rib located 60 cm from

entrance. A 45 cm long by 30 cm wide JP-8 pool was centered on the lower surface. 

0.30 s 

B2 As in B1 but with two 5 cm high longitudinal ribs each located 20 cm from the centerline. 0.30 s 

C1 As in B1 but with the tunnel height reduced to 10 cm. 0.23 s 

C2 As in B2 but with the tunnel height reduced to 10 cm. 0.23 s 

*Used in model validation.
856 Fluid Dispensing and Dispersion 

Figure 8-107 ame behind 

the step. Sim suppressant was 

injected, thor

provides an overview of the simulation geometry, showing the location of the fl

ulations were brought to a steady state with fires established, after which 

oughly mixed with the incoming air. 

 

 

Figure 8-107. Ray Tracing Image of Case A1 before Agent Injection (top left) and 0.2 s 

after Injection of 10% HFC-125 (top right). Images of Case A3 (lower left) and A5 (lower 

right) before Agent Injection. The air/suppressant inlet is light blue, the pool is purple, 

the suppressant is deep blue, and the flame is orange to yellow.

Figure 8-108 shows the state along the wind tunnel centerline just prior to agent injection with the high

y 

ove the flame 

t

for Case A1. 

temperature flame mainly located at the edge of the recirculation zone between the fuel and air. Fuel 

vaporization is determined by the rate of heat flux to the pool surface, moderated by an estimate of heat

losses, for example to the porous plate through which the fuel passes. The flame location relative to the 

edge of the recirculation zone is somewhat sensitive to these heat losses. It was assumed that 40 % of the

heat flux to the pool resulted in fuel vaporization. Greater heat losses result in reduced fuel vaporization, 

bringing the flame closer to the pool. This effect tends to increase the heat flux to the pool, partiall

offsetting the heat losses. The sensitivity to heat loss is not very large, but it is enough to m

in and out of the recirculation zone given 80 % to zero heat losses. Also shown in Figure 8-108 is a

cross-section of the computational mesh, showing grid points clustered around the step to capture relevant 

details of the boundary layer in these regions. Grid sensitivity studies are in process, although refinemen

in regions around the step to date has not resulted in measurable differences in the results 

Injection of suppressant is conducted by keeping the air mass flow rate through the domain constant and

increasing the total mass flow rate as required to inject the desired quantity of suppressant. 
Modeling of Fluid Dispersion in a Nacelle 857

Figure 8-108. Centerline Contour Plots Showing (from top to bottom) the Temperature, 

Oxygen Mass Fraction, Fuel Mass Fraction and the Computational Grid for Case A1. 

Rather than conduct a number of simulations for each suppressant mole fraction to determine the 

minimum injection time, as was done in the experiments, the suppressant was continually injected and the 

time to suppression was measured. Suppression was defined as the time at which the maximum 

temperature throughout the domain dropped below 1000 K. Figure 8-109(a) shows the evolution of the

maximum temperature for various suppressant mole fractions. The selection of 1000 K as the 

temperature corresponding to suppression seems justified since the temperature rapidly drops around this 

point, and there is no evidence of tendency to reignite for temperatures below 1200 K. It is evident that 

an HFC-125 mole fraction of 0.075 is insufficient to suppress this flame, while 0.08 is sufficient. 
858 Fluid Dispensing and Dispersion 

Successively greater mole fractions lead to a monotonic reduction in the time required to suppress the

flame. These results are summarized in Figure 8-109(b) where they are also compared with the results of

Takahashi et al.75

Figure 8-109. (a) Evolution of the Maximum Fluid Cell Temperature in the Domain for 

Case A1 for Various HFC-125 Mole Fractions. (b) Suppression Times as a Function of 

Added HFC-125 for Cases A1, A3 and A5. (c) Mass Fraction and Temperature Evolution in 

the Recirculation Zone (8 mm above pool and 8 mm behind step) for Case A1 with 10 %

HFC-125 by Volume Injected at 5 s. 

The maximum temperature shown in Figure 8-109(a) fluctuates greatly during the transient suppression 

process because of a combination of the refined grid and the delta-function nature of the EDC model: at 

certain instants of time the model treats a particular cell as almost entirely stoichiometric flame. This

behavior occurs as the flame moves through the finely gridded region behind the step during the

ppressant injection. While this behavior would not be observed when averaging over integral time or

lengt the

Kolm del 

(a) (b)

(c)

74

(a) (b)

(c)

74

(a) (b)

(c)

74

(a) (b)

(c)

74

su

h scales, this can occur in the context of the EDC model when the cell thickness is comparable to

ogorov scale as it is in the present grid at some locations. In fact, for better EDC mo
Modeling of Fluid Dispersion in a Nacelle 859

applicability, it is desirable to coarsen the mesh, but high levels of grid refinement are used to reduce 

reliance on log-linear wall models in regions of adverse pressure gradients. 

Figure 8-109(c) shows the local smoothness of the temperature evolution deep in the recirculation region 

along with major species. This figure and Figure 8-110 show key aspects of the suppression dynamics for 

the particular case A1 with 0.1 HFC-125 mole fraction. The suppressant rapidly flows over the top of the 

recirculation zone, but dilatation associated with combustion initially reduces recirculation behind the 

step. As the upper portions of the flame are suppressed (within the first 0.1 s) recirculation gradually 

increases, bringing suppressant in to extinguish regions that are still burning. As the fire suppression 

progresses, the flame is observed in Figure 8-109(c) and Figure 8-110 to move deeper into the 

recirculation zone as fuel vaporization is reduced and oxygen moves into the recirculation zone with the 

suppressant. It is found that an inner, secondary recirculation zone forms in the corner between the pool 

and the step into which some air is entrained, primarily from the sides, but into which suppressant 

penetration is exceedingly slow. With wall heat losses treated in the suppression model, this region is 

generally the last to be suppressed. 

Figure 8-110. 

Centerline Contour 

Plots of Temperature 

and HFC-125 Mass 

Fraction at 0.1 s and 

0.2 s after 

Suppressant 

Injection for Case A1 

with 0.1 HFC-125 

Mole Fraction 

Injected. 

Using the same basic configuration as the experiments conducted by Takahashi et al.,75 simulations were 

conducted to investigate the effect of additional clutter, in the form of a small rib on the upper wall, 

opposite the backwards-facing step behind which the fire is stabilized. Specifically, a rib protruding from 

the upper surface with a height of 42 mm is located either directly above the end of the backward facing 
860 Fluid Dispensing and Dispersion 

step or two rib heights behind the back of the step; these configurations are denoted A3 and A5; the 

simulations are otherwise similar to those in A1. These scenarios reflect the existence of additional 

clutter on the side of a passage opposite the flame-stabilizing obstruction. Additional obstructions result 

in the acceleration of the flow over the step and past the fire. The correlation between flow velocities 

over obstructions and suppressant mixing rates66,73,74,75

 would suggest that collocated obstructions would 

result in accelerated suppression. In Figure 8-109(b), suppression times are plotted for cases A3 and A5

with 10% HFC-125 suppressant in the free stream along with the results for Case A1 where there is no 

additional obstruction. The results are not completely intuitive: there is a strong reduction in suppression 

time for case A5 but no reduction and possibly an increase in suppression time for case A3. This trend 

goes against a simple implementation of Equation 8−50 that would suggest reduced suppression times in 

accordance with the changes of τmix in Table 8-12. Equation 8−50 would imply that case A3 should have 

the shortest suppression time while it is observed to have the longest. 

The results for cases A3 and A5, relative to A1, can be explained by consideration of the pressure field, 

shown in Figure 8-111, that determines the extent of the recirculation regions. 

Figure 8-111. Centerline Pressure Contours and Velocity Vectors for Cases A1, A3 and 

A5 prior to Suppressant Injection. (Contour levels are equal for all panes and space at 

2 x 106 Pa intervals. Solid lines represent streamline traces from just behind the corner 

of the step.) 
Modeling of Fluid Dispersion in a Nacelle 861

Also shown in Figure 8-111 are velocity vectors and streamline traces from behind the corner of the step 

to provide rough indications of recirculation zone sizes. In case A3, flow past a flat plate oriented against 

the flow results in a greater pressure loss than flow over the backwards-facing step. The greater pressure 

loss tends to pull the mean flow upward, reducing the mixing in the lower recirculation zone where the 

fire is stabilized. Shifting the upper obstruction past the step results in significant reductions in the 

suppression time. This result occurs because the high-pressure region in front of the upper rib is 

incident with the low-pressure region behind the backwards-facing step, accelerating the flo 

ownward and increasing suppressant mixing into the recirculation zone. Thus, despite the fact 

circulation zone thickness. Given this, 

t the k-ε model is known to have limited 

success in adverse pressure-gradients, but the conclusions reached here are not dependent on the validity 

ls with 

heights on the order of 10 cm to 30 cm. The resulting series of simulations, cases B1, B2, C1 and C2 are 

sum ce 

intensity was 10 % and the turbulent length 5 m. Significantly, pool sizes are narrow 

relative to the channel width. Simulations in ilatation from a pool fire behind a rib 

s ar verse to th . 

O va into n 

p ns d cl e 

o ved long l 

(streamw (Cases B1 and C1 

b in al ribs do not 

p nt Figure 8-112. Mass fraction profile e 

re ula do affect the flow because rate of transport of 

a s for Case B2 relative to B1 and for Case C2 relative to C1, shown in Figure 

-113(a). Further, the time to suppress the fire is reduced as shown in Figure 8-113(b). The result that 

co

d

w

that the 

area available for flow past the lower recirculation zone is greater and the velocity u* correspondingly 

lower in Case A5 relative to Case A3, the suppression time is reduced because the flow is directed into 

the recirculation zone, thereby increasing mixing in the recirculation zone. The key result is that the 

suppression time is strongly dependent on recirculation zone size, and that multiple factors affect the 

recirculation zone size. Given a single obstruction, recirculation zone mixing is primarily dependent on 

h/u*, but pressure gradients can change the effective re

recirculation region mixing times should be a function of h*/u*, where h* = h*(h, ∇p), indicating the 

dependence of the effective recirculation zone length scale on the pressure gradient. As is typical for 

separated flows, favorable (accelerating) pressure gradients reduce recirculation zone length scales while 

adverse pressure gradients have the opposite effect. Pressure drop past obstructions is related to the drag 

coefficient, and there is extensive literature on the subject that may be useful in identifying the magnitude 

of pressure changes across obstructions. It is noted here tha

of the k-ε model. Rather, the conclusions depend on the relevance of pressure gradients in directing fluid 

flow, and on the result from dimensional analysis that mixing times can be related to μ

* 

and the 

characteristic scale of the recirculation zone. 

The model validation experiments described above and others for studying fire suppression of 

obstruction-stabilized flames66,75 were conducted in roughly square wind tunnels. In certain applications 

such as aircraft engine nacelles, the width to height aspect ratio tends to be large. In preparation for 

studies of actual engine nacelle environments and to plan an additional series of experiments to be 

conducted at WPAFB by the USAF 46th Test Wing, a series of simulations using dimensions 

characteristic of the wind tunnel available at WPAFB and an F-18 engine nacelle were conducted. The 

characteristic dimensions identified are obstruction heights on the order of 5 cm in wide channe

marized in Table 8-12. In each of these simulations, the inlet velocity was 5 m/s, the turbulen

 scale was 0.02

dicate that d induces 

econd y recirculation regions that sweep the fire outward and along the rib trans e flow

bser tion of these flow fields indicates that they may reduce the suppressant penetration certai

ortio of the flame-stabilization region. However, within aircraft, structural supports an utter ar

bser to be oriented in both transverse and longitudinal directions. The consequences of

ise) ribs are examined by adding longitudinal ribs just outside of the pool 

itudina

ecom g Cases B2 and C2). It is observed that for both Cases B2 and C2 the longitudin

reve spread of the fire beyond the ribs, as shown in s in th

circ tion zone indicate, however, that longitudinal ribs

gent is greater with rib

8
862 Fluid Dispensing and Dispersion 

longitudinal ribs reduce the time required to suppress a fire suggest a series of experiments in high aspect

ratio wind tunnels to evaluate their validity. If the experiments are consistent with the simulation results, 

then both the potential reduced suppression ability due to dilatation and the possibility that longitudinal 

clutter ameliorates it are considerations in system design. 

 

Figure 8-112. Raytracing images of Cases B1 (left) and B2 (right). (Colors as in Figure 

8-107. Simulations take advantage of symmetry, and only the calculated half of the 

domain is shown.) 

(a) (b)

Figure 8-113. (a) Temporal Evolution of HFC-125 Mass Fraction in the Recirculation Zone 

at a Point 0.012 m above the Lower Surface and 0.05 m behind the Rib along the 

Centerline. (b) Suppression Times as a Function of HFC-125 Mole Fraction for Cases B1, 

B2, C1, and C2. 
Modeling of Fluid Dispersion in a Nacelle 863

8.5.5 Assessment of VULCAN in Suppressant Distribution in a Full-Scale Nacelle 

The flow inside an engine nacelle ground test simulator was studied for the purpose of understanding and 

optimizing the distribution of suppressant.76, 77 One objective of the study was to identify conditions for 

which suppression would or would not be successful in order to test the ability of VULCAN to 

discriminate between various scenarios and to provide input on experimental design for full-scale nacelle 

fire tests. To accomplish this, the distribution of fire suppressant during cold flow (without a fire) was 

first examined to identify regions of low concentration using VULCAN. 

The overall nacelle geometry used in the VULCAN simulations was based on the “Iron Bird” full-scale 

nacelle simulator (to be described in detail below), which was a mock up of a port engine nacelle. In the 

absence of fires and suppressant flow, the flow field in the nacelle was dominated by flow through an 

inlet air scoop located near the front of the nacelle coming up through the nacelle bottom. The inlet air 

flowed from the inlet across the engine toward the upper aft of the nacelle. For the purposes of the 

simulations, an air mass flow rate of 1.0 kg/s was used. The inlet air mass flow rates determined the air 

exchange times, the time over which the mass of air entering and leaving the nacelle equaled the mass of 

air in the nacelle. For the simulation, the internal volume of the nacelle, neglecting clutter objects, was 

just over 1.4 m3

. This volume gave an air-exchange time of 1.6 s. The inlet cross section was 

approximately 0.008 m2 _and the inlet airflow velocity was approximately 150 m/s. This resulted in an 

inlet Reynolds number of 9 × 105 resulting in strong turbulence even without the clutter-enhanced mixing. 

The ground simulator was outfitted with a set of four suppressant discharge nozzles that were found to be 

sufficient to suppress a fire when 3.2 kg of fire suppressant was discharged. 78 These are denoted by the 

numbers 1 through 4 with higher numbers corresponding to nozzles that are located toward the rear of the 

nacelle (Figure 8-114). Numerical simulations were conducted for suppressant injection through these 

nozzles into the nacelle in the absence of a fire to obtain information on the distribution through the 

nacelle.76 The suppressant was assumed to enter the nacelle in the vapor phase or to vaporize fast relative 

to other time scales. The suppressant mass flux for each nozzle was assumed to be proportional to the 

nozzle area. 

Figure 8-114. Locations of the 

Suppressant Nozzles and the Pools in 

the Nacelle Simulator. 

AFT

FRONT

1

2

3

4

STARBOARD

PORT

FRONT VIEW

TOP VIEW

B1

B2

B3C3

B5C5

1

2

3

4

(not to scale)

AFT

FRONT

1

2

3

4

STARBOARD

PORT

FRONT VIEW

TOP VIEW

B1

B2

B3C3

B5C5

1

2

3

4

(not to scale)
864 Fluid Dispensing and Dispersion 

The mass fraction of HFC-125 in vertical planes near the nacelle center and near the starboard and port

sides are shown in Figure 8-115 at the end of the 3 s suppressant injection period. 

Figure 8-115. Contour Plots of C2HF5 at 3.0 s after Start of Suppression Injection in 

Vertical Planes near Starboard Side (top), near Nacelle Centerline (center), and near Port 

Side (bottom). (Airflow is 1.0 kg/s, and suppressant flow is 3.2 kg/s over 3 s.) 
Modeling of Fluid Dispersion in a Nacelle 865

In these contour plots the computational cells representing the nacelle, the engine, and the clutter are 

blanked (white). The mass fractions are colored in such a manner that blue and green (cool) colors 

indicate likely suppression and red (hot) colors indicate that suppression is unlikely. The critical mass 

second and third ribs, on the upper starboard side of the engine. Suppressant flo

45° angle upward across the top of the engine, and the majority of suppressant follows the mean flow 

forward along the upper nacelle. Nozzle 4 is located on the port side of the engine near the aft of the 

nacelle just behind the fifth rib. The suppressant is directed downward along the side of the engine in a 

direction that is counter to the general upward flow toward the upper diamond vent; this recirculation 

results in oscillations as the injecting gases are turned around by the mean flow. 

Distribution of Suppressant throughout the Nacelle 

As a measure of sufficient distribution in the nacelle, the portion of the nacelle volume for which the 

suppressant mass fraction exceeds 30 % has been used for characterization. Even with low-intensity 

mixing, this amount is generally sufficient for suppression and represents a f 

suppressibility. Figure 8-116 shows this fraction when the airflow is 1.0 kg/s with varying rates of 

injection (same mass over different durations). The mass of suppressant to at 

3.2 kg, and the period over which it was released varied from 2 s to 6 s. Shorter injection periods 

correspond to higher bottle pressures. To the extent that suppressant vaporizat

period of injection increases. Figure 8-116 shows that the entire volume is ess r at least 

one second for injection durations of 3 s or less. For longer periods of injection

with high concentrations (> 30 %) because suppressant is continually advected out the various vents. The 

failure to fill the nacelle completely does not indicate that suppression will not occur, but rather reduces 

the confidence in suppression. 

The average peak mass fractions for the simulations shown in this figure are 0 51, 0.44 and 0.35. 

Smaller mass fractions correspond to the longer injection duration. If the turbulent mixing in the nacelle 

were sufficient to create homogeneity, the mass fraction throughout the nacelle would exceed 0.3 for all 

of these scenarios. Clearly, inhomogeneities arising from imperfect mixing are significant. This indicates 

that the CFD analysis can provide significant information on the degree of inhom geneity. Specifically it 

can provide an estimate of the volume that fails to meet a criteria such as the one indicated here 

(suppressant mass fractions exceeding 0.3).

fraction for suppression in the absence of intense mixing is somewhat less than 0.3 (closer to 0.25, so that 

this is a conservative estimate), and so the dividing line for likely suppression can be taken to be the 

dividing line between yellow-green and green. Depending on the turbulent mixing rates, suppression may 

occur for lower mass fractions of HFC-125. Velocity vectors are also provided in Figure 8-115 to 

indicate the general flow direction. 

Nozzle 1 is located on the starboard side of the nacelle in the forward section and is directed upward. The 

suppressant from Nozzle 1 fills the upper forward nacelle and is advected into the lower forward nacelle. 

Nozzle 2 is located near Nozzle 1 on the starboard side of the nacelle and directed towards the port side 

beneath the engine and across the top of the inlet airflow. Suppressant from nozzle 2 is dispersed aftward 

by the inlet jet along the nacelle. Nozzle 3 is located just past the mid-point of the nacelle, in between the 

w is directed at roughly a 

conservative estimate o

be injected was fixed

ion is slow, the effective 

entially filled fo

, the volume is not filled 

.59, 0.

o
866 Fluid Dispensing and Dispersion 

Figure 8-116. Simulation Results of Various Injection Periods. 

Influence of Nozzles on Distribution of Agent 

ulations were conducted to ascertain the effect of removing a single suppressant nozzle, whil

keeping the overall mass of injected suppressant constant at 3.2 kg injected uniformly over 3 s. For th

conditions, the nacelle volume in which the fraction exceeds 0.3 is evaluated. These results wer

mpared to those shown for all four nozzles functioning; the nacelle was completely filled, according to 

this criterion, for the range of flows considered. 

In conducting simulations with specific nozzles removed, the mass flow out of the remaining nozzles was 

kept at the same values used in the previous simulations. This corresponds to an assumption that the 

pressure driving the suppressant is not affected by the removal of a nozzle and that the nozzle crosssections have not changed. The duration is thus increased to allow release of the full 3.2 kg of HFC-125. 

The volume fraction of the nacelle where the suppressant mass fraction exceeds 0.3 is indicated in 

Figure 8-117 for an airflow of 1.0 kg/s. In these and other scenarios, it appears that removing Nozzle 3 

has no detrimental effect, since the complete volume is indicated as filled, and the duration for which it is 

filled is increased because of the slightly slower rate of injection using three nozzles. Based on the 

criteria shown in Figure 8-117, removing Nozzle 4 also has little effect on the sufficient distribution of the

suppressant. Note that the lower diamond vent in the nacelle simulator is modeled as essentially blocked, 

Sim e 

ese 

e

co

 blocked on similar fleet

aircraft, the removal of suppressant in the aft region may be substantially faster, making the retention of 

ozzle 4 highly desirable. On the other hand, the additional vent in the aft region would mean that a 

greater portion of the suppressant injected through Nozzle 4 would leave the nacelle rapidly.

based on observations of the test simulator. Assuming that this vent is not

N
Modeling of Fluid Dispersion in a Nacelle 867

Figure 8-117. Simulation Results Showing the Effect of Nozzles on Agent Distribution. 

The removal of Nozzles 1 or 2 does appear to have a significant effect on the distribution of suppressant 

throughout the nacelle. Suppressant from these nozzles is entrained in the inflow; this entrainment by the 

air significantly helps distribute suppressant throughout the nacelle.67 The distribution of suppressant 

along the centerline is shown in Figure 8-118 with Nozzle 2 assumed to be capped; this can be compared 

with the distribution using 4 nozzles. Nozzle 2 is located in the forward starboard area of the nacelle and 

directed across the lower nacelle outboard. Without Nozzle 2 present, the inlet air jet entrains relatively 

little suppressant, and this results in little suppressant along the lower nacelle where pool fires might 

exist. It is clear that Nozzle 2 plays a key role in distributing the suppressant throughout the nacelle as it 

mixes with the air inlet. 

Figure 8-118. Simulated Agent Distribution along the Nacelle Centerline. 
868 Fluid Dispensing and Dispersion 

8.5.6 Assessment of VULCAN in Pool Fire Suppression in a Full-Scale Nacelle 

Pool fires stabilized behind obstructions have been identified as among the most challenging fires to 

suppress. 71,72 Obstructions such as structural ribs provide a region of recirculating flow where hot 

products help stabilize the flame that suppressant is relatively slow to penetrate. In certain scenarios, such 

as those described in References 54, 66, and 75, the suppressant concentration must be maintained at an 

elevated level in the flow past the stabilization region for a substantial period of time to ensure that 

adequate suppressant penetrates the stabilization region. 

The approximate locations of the pools used for VULCAN are shown in Figure 8-114. These sections are 

delineated from the forward to the aft end with increasing numbers as each rib is passed. The letter “B” is 

applied as a prefix to the pool location to indicate that the pool is located between the two central 

longerons. These are the only locations where substantial quantities of fuel can be collected. To augment 

the quantity of fuel, the basin just to the port of that indicated by “B” is sometimes assumed to hold some 

fuel also; this basin is denoted with the prefix “C”. The pool located at B1 is between the forward end of 

the nacelle and the first rib. That denoted B2 is located just aft of the first rib; the inlet air flows partially 

over this pool. The pool denoted B3 is located behind the second rib. The pool denoted B5C5 is located 

between the fourth and fifth ribs; these are the two larger ribs. The simulations indicate that pool fires at 

locations B4 and B6 are difficult to stabilize because of the particular predicted circulation. The surface 

areas of the largest possible pools in each section were measured in the ground-test simulator. Similar 

pool areas have been used in the simulations; the p reas are indicated in Table 8-13. 

T . 

In e 

partially advected beyond the pools by th he nacelle. It is particularly difficult to 

determine the evaporation rates without measurements. The uncertainty of the evaporation rate may be as 

high as 50 %. As a measure of the degree to which fires in different sections spread throughout the 

nacelle, Table 8-13 also shows the volume over which combustion is occurring and high temperatures 

exist. Heat release from pool fires B2 and B3C3 is substantially distributed throughout the nacelle by the 

main air inlet that passes over the fires in these regions. 

Table 8-13. Pool Characteristics. 

ool a

he pools are assumed to be filled with JP-8, and the evaporation rate based on heat feedback to the pool

 general, it is difficult to predict the thermal feedback to a pool from a fire, because these fires ar

e convective flows in t

Pool 

Area 

(m2) 

Predicted Evaporation Rate 

(kg/s) 

Volume of Combustion 

(%) 

Volume where 

T > 700 K (%) 

B1 0.084 0.0089 5.9 4.6 

B2 0.100 0.011 4.6 22 

B3C3 0.094 0.0082 5.5 37 

B5C5 0.043 0.0043 1.5 5.2 

Suppression Using Four nozzles 

uppression was predicted for all pool fires in the nacelle using the four-nozzle configuration and 3.2 kg 

mass was injected over 3 s or 4 s. Results of these tests are summarized in 

S

of suppressant when this 

Table 8-14. 
Modeling of Fluid Dispersion in a Nacelle 869

Table 8-14. Summary of Test Results with Four Nozzles. 

Pool 

Mass HFC-125 

(kg) 

Injection Rate 

(kg/s) Active Nozzles 

Suppression Time 

(s) 

B1 3.2 1.07 1,2,3,4 0.8 

B1 2.2 1.07 1,2,3,4 0.8 

B2 3.2 1.07 1,2,3,4 0.9 

B2 2.2 1.07 1,2,3,4 0.9 

B3C3 3.2 1.07 1,2,3,4 1.2 

B3C3 2.2 1.07 1,2,3,4 1.2 

B3C3 3.2 0.53 1,2,3,4 None 

B3C3 3.2 0.64 1,2,3,4 None 

B3C3 3.2 0.71 1,2,3,4 None 

B3C3 2.2 0.73 1,2,3,4 None 

B5C5 3.2 1.07 1,2,3,4 1.8 

B5C5 2.2 1.07 1,2,3,4 1.8 

To examine the effect of varying the mass of suppressant injected and the rate of injection, a series of 

additional simulations for fires in pool B3C3 were conducted. When the rate of suppressant injection is 

reduced to just below 0.75 kg/s, no suppression was predicted in the simulations, although sustained 

burning would certainly be described as tenuous for these conditions since the fire was restricted to a 

corner of the pool C3. As the rate of suppressant injection is reduced, the fire stability increases, and at 

0.53 kg/s the fire is clearly stabilized, at least near the corner of pool C3. The fire tends to stabilize in this 

location because the mixing rates are lower, as indicated in the following section. It is noteworthy that 

the mass of suppressant injected plays little role in determining the occurrence of suppression here. For 

the two cases with suppressant injection rates of 0.71 and 0.73, the resulting tenuous burning region is 

very similar. There will be a lower bound in terms of suppressant mass injected over a short period, 

although this has not been identified here. More significant in practice is the duration over which 

suppressant will act to inhibit reignition and allow cooling of heated surfaces. Thus the suppressant 

requirements are likely to be dictated by a combination of the rate required to flood the compartment with 

a high enough concentration and the mass required to maintain that concentration to inhibit potential 

reignition sources. 

There is one complication that arises with high-boiling point agents, however. For high boiling point 

agents, the relevant parameter will not be the rate at which liquid suppressant is injected, but rather the 

rate at which the liquid suppressant vaporizes. The physics of the evaporation process are not captured in 

the present simulations but will be considered in subsequent simulations. 

Though the detailed results are not presented here, suppression is sensitive to heat flux from the fire to the 

pool. If the heat flux and, hence, the fuel evaporation are reduced by 50 %, suppression is substantially 

easier for the cases considered in this section. For example, the reduced suppressant injection rates shown 

in Table 8-14 that fail to suppress the fire in pool B3C3 do s eat flux 

to the pool is reduced by 50 %. The fire can be completel

evaporation rates. Similar results are expected if the fuel tantial heat losses 

through the nacelle under the pool. While relatively high engine temperatures are expected during 

operations, temperatures during ground tests may be such that reduced evaporation is experienced. 

ucceed in suppressing the fire if the h

y separated from the fuel source with slower 

is cold or if there are subs
870 Fluid Dispensing and Dispersion 

Suppression with Individual Nozzles Capped 

he capping of various nozzles causes inhomogeneities that left certain regions with little suppressant. A 

series of simulations was conducted where one nozzle was assumed to remain capped. To examine the 

effects of these inhomgeneities for the majority of these simulations, the flow from each of the other 

nozzles was maintained at previous values when all nozzles were open, giving a reduced rate for the sum 

of the three remaining nozzles and an increased duration of injection. Results of these tests are 

summarized in Table 8-15. For fires in the extreme forward and aft pools, the removal of various nozzles 

did not alter the prediction of suppression. 

Table 8-15. Summary of Test Results with Individual Nozzles Capped. 

T

Pool 

Mass HFC-125 

(kg) 

Injection Rate 

(kg/s) Active Nozzles 

Suppression Time 

(s) 

B1 3.2 0.83 2,3,4 1.3 

B1 2.2 0.83 2,3,4 1.3 

B1 3.2 0.74 1,3,4 1.5 

B1 2.2 0.74 1,3,4 1.5 

B1 3.2 1.07 1,3,4 1.1 

B1 3.2 1.07 1,3,4 1.1 

B2 3.2 0.83 2,3,4 None 

B2 2.2 0.83 2,3,4 None 

B2 3.2 0.74 1,3,4 4.6 

B2 2.2 0.74 1,3,4 3.2 

B3C3 3.2 0.83 2,3,4 1.6 

B3C3 2.2 0.83 2,3,4 1.6 

B3C3 3.2 0.74 1,3,4 None 

B3C3 2.2 0.74 1,3,4 None 

B5C5 3.2 0.74 1,3,4 2.4 

B5C5 3.2 0.90 1,2,3 1.7 

For pool B1 the removal of either Nozzle 1 or Nozzle 2 has little effect beyond delaying the suppression. 

For pool B5C5, the removal of Nozzle 2 results in an increase in the suppression time because 

suppressant from Nozzle 2 is entrained in the air and carried back across the ribs surrounding the pool. 

Without Nozzle 2, the suppression is delayed until suppressant from other nozzles flows around the 

nacelle to be entrained by the air inlet. The removal of Nozzle 4, which is closest to pool B5C5 and 

injects suppressant around the aft section of the nacelle, has minimal effect on suppression of this pool 

because the major flow is under the engine aftward. 

For pool B3C3, the removal of Nozzle 1 has little effect other than to delay the suppression. Removing 

Nozzle 2, however, results in a failure to suppress fires in pool B3C3. As indicated in Figure 8-118, the 

removal of Nozzle 2 leaves a significant volume directly over the pool B3C3 with little suppressant. 

Thus, Nozzle 2 is necessary to suppress fires in this region. 

For a pool located at B2, Nozzle 1 is critical for suppression. Suppressant from Nozzle 1 is entrained 

across pool B2 by the air, and in the absence of that nozzle the suppressant’s concentrations just over the 
Full-Scale Nacelle Fire Suppression Tests 871

pool are too low. Capping Nozzle 2 also leaves a region deficient in suppressant there as well, but the air 

influx over this region (approaching 100 m/s) is sufficient to extinguish any fire in that region. 

As the rate of injection is reduced by a third or more, many volumetric regions of the nacelle do not have 

sufficient suppressant for all fires. This is caused by inhomogeneities in the concentration, since the 

average concentrations in the nacelle are sufficient to suppress all fires. Suppression also fails as the rate 

of injection is reduced by one third or more. The removal of Nozzles 1 and 2 causes substantial 

inhomogeneities in the distribution of agent. When Nozzle 3 is assumed to be capped, there is no 

apparent degradation in suppression. 

Sensitivity studies in these simulations have disclosed that the pool vaporization rate is very sensitive to 

fuel temperature, heat losses, details of the geometry, and the momentum associated with injection. 

8.6 FULL-SCALE NACELLE FIRE SUPPRESSION TESTS 

8.6.1 Experimental Design 

Results from the VULCAN pretest simulations (see above VULCAN assessment sections) and simplified 

analyses helped guide the design of the experimental test plan and matrix for fire suppression tests in a 

full-scale nacelle. These results estimated the overall concentration of suppressant in the nacelle, the 

duration of the transients as the concentrations rise and fall, and the magnitude of the distribution of 

suppressant. A simplified analysis of the relative masses of air and suppressant flowing into the nacelle 

can provide some guidance on the overall suppressant concentration and the transients. The suppressant 

mass-injection rate relative to the total injection rate provides a characteristic mean mass fraction within 

the nacelle, Yss. The injection must proceed for a long duration for the mean mass fraction to reach this 

characteristic steady-state value, but the mean mass fraction approaches this value in an exponential 

manner with an exponential time constant that is proportional to the total nacelle volume divided by the 

total volumetric influx. This time constant indicates the time scale for transients. In the tests conducted 

here, it was found that suppression was less sensitive to the total injected mass than it was to the rate of 

injection. 

The VULCAN predictions indicated, and the test results subsequently confirmed, that the overall or 

average mass fraction of suppressant resulting in fire suppression was substantially greater than the cup 

burner value, which was Ycb = 0.28.79 In general, the estimated average fraction required for suppression 

is on the order of 30 % to 40 % greater than the cup-burner value, according to the VULCAN simulations. 

A similar excess was required for the tests. The fact that a greater overall mass fraction is required 

indicates that inhomogeneities are significant. In other words, the suppressant’s mass fraction in certain 

regions of the flow is substantially less than the mean. It is noted that the high rates of mixing present in 

the nacelle tend to reduce the mass fraction required to suppress the fire. It has been found for HFC-125 

that strained laminar flames are indicated to be suppressed at mass fractions as low as 0.16.79

ne of the primary objectives of the study was to ascertain the predictive capabilities of VULCAN 

homogeneity in the nacelle. To this end, it was noted that predictions with 

V

recircu ading 

O

regarding the degree of in

ULCAN were very successful at reproducing extinction in a geometry where the suppressant was

introduced in a uniform manner and the only mixing processes were related to a fire-stabilizing 

lation zone.54 The nacelle simulator geometry was appreciably more complicated, and the le
872 Fluid Dispensing and Dispersion 

challenge was expected to be the transport of the suppressant rather than the well-established suppression 

model itself. In order to evaluate the mixing process for several scenarios, simulations and tests were 

conducted with different rates of injection and with different nozzle configurations. As an added variable, 

the air inflow was varied to simulate varying flight conditions. As indicated above, the ratio of the 

suppressant injection rate to the combined, total mass rates was indicative of the mean of the suppressant 

mass fractions in the nacelle. 

Based on the results of VULCAN model simulations of various test conditions, it was predicted that the 

suppression would be more sensitive to the rate of injection of agent than to the amount of suppressant, or 

he inboard side of the engine. The nacelle is roughly 3.18 m long. The 

width and height vary significantly along the length, but are contained within a region 1.45 m high and 

equivalently the duration of injection. Further, suppression was indicated to be sensitive to the 

distribution of nozzles about the nacelle. With these results, a test plan was generated in the form of a 

rule-based sequence of tests. The test sequence was initiated with an approximation of a scenario, which 

was expected to result in successful suppression. From this point, subsequent tests reduced the 

effectiveness of that system by either: 

• reducing the injection rate by reducing the bottle pressure so that the suppressant’s mass 

fraction was reduced, or 

• removing a nozzle so that the distribution of suppressant was less uniform, or 

• reducing the mass of suppressant injected for a given bottle pressure so that the peak mass 

fraction was reduced and held for a shorter duration. 

8.6.2 Test Facility 

The NAVAIR’s full-scale “Iron Bird” nacelle at Navel Air Station (NAS) Patuxent River, Maryland, 

which is typical of an advanced tactical aircraft, was used for this effort. Figure 8-119 shows the fire test 

simulator. The air inlet source is seen in the lower left coming up into the bottom of the nacelle. There 

are two vents in the top: a diamond-shaped vent in the aft, and a balance piston round vent about 1/3 aft of 

the face. On the front face, there are four exit holes simulating connections from the nacelle to the 

Airframe Mounted Accessory Drive (AMAD) bay and other parts of the aircraft. These four holes are 

arrayed around the engine as shown in Figure 8-120. 

The flow areas of the top vents, the diamond aft vent and the balance piston vent, are 248 cm2

 and 

22.8 cm2

 respectively. The ground test simulator is a mock up of a port engine nacelle. Therefore, the 

port side corresponds to the outboard side of the engine, where air is introduced in flight, and the 

starboard side corresponds to t

1.15 m wide. Coordinates are measured from a reference point on the top starboard side of the simulator 

test fixture so that all vertical coordinates are negative while other coordinates are positive. 
Full-Scale Nacelle Fire Suppression Tests 873

Figure 8-119. Ground Test Nacelle ‘Iron Bird’ Simulator. 

In conjunction with the rearward taper of the airframe, the nacelle is generally tallest and widest near the 

gine

sides and top with additional space for air circulation. The lower nacelle surface slopes smoothly up from

t end of the nacelle, the engine is uniformly 0.77 m in

diam

the forward end and primarily below the engine. The gearbox assembly is a collection of several 

forward end, narrowing towards the aft. At various sections, there are larger cavities around the en

the forward to the aft, crossed by five ribs of varying heights. There are roughly four longerons running 

along the lower nacelle surface. The two central longerons end about 0.6 m before the aft end. The 

engine, a hollow cylinder in the ground simulator, extends from the forward to the aft of the nacelle. The 

engine diameter is nominally 0.77 m with a slight narrowing over the front 0.61 m to a minimum 

diameter of 0.62 m. From 0.81 m aft to the af

eter. 

The outer surface of the engine is generally smooth, although various clutter items are attached as

described below. In addition to the ribs and longerons, the most significant clutter is located near the

forward end of the nacelle. It is dominated by a gearbox assembly located from 0.1 m to 0.75 m behind

parallelepiped and cylindrical objects of varying sizes that obstruct the flow in the large space between

the engine and the lower nacelle in the vicinity of the air inlet scoop. Additional large parallelepiped

clutter objects are located along the engine, particularly on the port side as far back as 1.5 m behind the 

forward end. Smaller clutter, primarily tubing and wire bundles, exists along the lower half of the engine 

across the length of the nacelle. Some of this smaller clutter has been identified as a potential relight 

surface because of the relatively low thermal capacity and rapid heating to very high temperatures. The

afterburner control vanes at the aft end of the nacelle have not been included in the computational model 

because the setup (initially) focused on fire scenarios near the forward end of the nacelle. 
874 Fluid Dispensing and Dispersion 

Air inlet pipe

Hole 4 (∅ 4.8 cm)

Hole 3 (∅ 5.3 cm)

Hole 2

(∅ 9.2 cm)

Hole 1

(∅ 5.3 cm)

(not to scale)

Air inlet pipe

Hole 4 (∅ 4.8 cm)

Hole 3 (∅ 5.3 cm)

Hole 2

(∅ 9.2 cm)

Hole 1

(∅ 5.3 cm)

(not to scale)

h number) at sea level. Given this restriction, three nominal flows were selected

to correspond to three major flight conditions: high-speed, high-altitude cruise, loiter, and precision 

approach. These flows are 0.96 kg/s, 0.68 kg/s, and 0.57 kg/s, respectively. The air is supplied from a 

centrifugal compressor driven by a gas turbine. The inlet flow is measured using a calibrated turbine 

meter. There is adequate straight pipe, according to ASME Standards,81 and a flow straightener between 

the compressor and the turbine meter. Likewise, there is adequate straight pipe downstream of the turbine

meter, and downstream of the 45° elbow, there is an Etoile swirl-removing conditioner in the straight pipe 

leading to the nacelle. The supply air pressure was measured with a water manometer immediately 

downstream of the turbine meter. The air effluxes were measured at each of the outlets separately under 

steady state. The air temperatures in the nacelles were measured with thermocouples at four locations, 

one on each side and near each end of the nacelle. The airflow out the aft diamond vent was measured

with a pitot rake. The airflow in the other outlets was measured with a calibrated vane anemometer and 

stopwatch. Air pressures in the nacelle were measured at three locations using an inclined water 

manometer. All airflow data were corrected to ambient conditions at the time of test in order to determine 

the mass balance. 

Figure 8-120. Drawing of Front Face of Ground Test Nacelle. 

In order to apply realistic boundary conditions for the VULCAN simulations, it was necessary to measure 

the inlet and outlet flows from the nacelle simulator under ambient conditions without fire. The openings 

shown in Figure 8-119 and Figure 8-120 are not the geometric ventilation paths. The various ventilation 

paths, such as the balance piston vent, aft diamond vents (both upper and lower), and AMAD bay

ventilation paths in the front, have been "sized" to provide the flow distributions predicted in the airflow

analysis conducted by Northrop-Grumman.80 The simulator is designed for testing at one flight condition,

traveling at 0.55 M (Mac
Full-Scale Nacelle Fire Suppression Tests 875

The nominal mass flow of air was set on the control console by setting the speed of the gas turbine 

driving the blower. There was some small variation in flow, less than 6 %, with a period of many seconds 

data output of its own, and the readout that was 

selected was that of volumetric flow at atmospheric conditions. Its period of observation was about 

d away from this 

vent by the interior ribs. The second was the rather large variation, proportionately speaking, in the 

mates. In retrospect, the 

only assumption which had any consequence was that of roughout the interior of the 

nacelle simulator. As mentione expected, and they contributed 

significantly to feren d ries a ted. 

It was predicted that half the flow w it from the top aft v n fact, closer t the 

flow exited at that location. Conseq the model predicted about 6.5 % more flow leaving via the 

Balance Piston Valve and 8.5 % m y the four AMAD vents in the front bulkhea The test 

pre s of th el as adjusted f ctual vent areas are shown in Table 8-16. 

 discussing the agreement between model and test in the total flow and average pressures, the test was a 

calibration of the nacelle simulator. In constructing the model, it was assumed that the balance piston 

arallel orifices and that the AMAD vents would behave more like 

nozzles. A weighted average of these coefficients of discharge was predicted to be 0.733. By actual test 

rrelates very well within the published data for the vent Reynolds number range, during test, 

of 1680 to 6800, for which the coefficient is 0.613 to 0.605, respectively.81

resulting from the gas turbine-mounted controls. During the test run at each rate, at least four readings 

were observed from each thermocouple and manometer. Considerably more data were recorded from the 

turbine meter. The vane anemometer, which was used for all air efflux measurements, except that from 

the aft diamond vent on top, was equipped with a mechanical totalizer. Consequently, a stopwatch was 

used to record the period of observation in order to obtain the average flow. The pitot rake and its 

converging ductwork came equipped with an electronic 

1 min, and two such observations were recorded for each test condition. All data were observed and 

recorded manually in view of the steady-state conditions. The automatic data acquisition system is 

designed for capturing transient fire events in the nacelle simulator and, therefore, would generate far 

more data than were required for this test. All data were averaged to provide a mean for each steady state. 

The observations could not be made simultaneously, and since there was some long-period variation in 

the flow, this introduced an additional uncertainty. 

The proportional distribution of air effluxes remained nearly constant throughout the range of inlet flows 

and, therefore, the actual mass flows are nearly proportional to the total inflow. There were several 

surprising observations during the tests. The first was that there was no perceptible flow in or out of the 

bottom aft vent. It could be that the very fine mesh screen (≈ 50 /cm) which covered this vent was 

clogged with soot and rust particles or that the flow pattern inside the nacelle was directe

average pressures measured inside the nacelle, the range being greater than the mean. The third 

observation was a highly asymmetric velocity profile across the top aft vent. Most of the flow was 

exiting from the port side of the diamond; the velocity out the starboard side was measured with the vane 

anemometer to be ≈ 20 % of that out the port side. The pitot rake apparatus was designed to observe an 

overall average of that efflux collected by the converging duct. 

The only corrections made to the pretest VULCAN model were the fact that no flow from the aft bottom 

vent and the actual, measured vent areas were used instead of their previous esti

a uniform pressure th

d above, these large variations were un

the dif ces between the actual flow istribution at the bounda nd those predic

ould ex ent. I o two-thirds of

uently, 

ore b d. 

diction e mod or the a

In

vent and aft top vent would behave as p

and calibration, it was determined that the effective coefficient of discharge equals 0.614. This value 

implies that all the vents behave essentially as sharp-edged orifices. This value of the coefficient of 

discharge co
876 Fluid Dispensing and Dispersion 

Table 8-16. Comparison of Predicted vs. Measured Pressures and Flows. 

Inflow 

(kg/s) 

Predicted Pitot 

Pressure 

(Pa) 

Measured Pitot 

Pressure 

(Pa) 

Measured 

Average 

Nacelle 

Pressure 

(Pa) 

Predicted 

Average 

Nacelle 

Pressure 

(Pa) B atio ias R

0.92 145.2 93.0 380.6 80.4 - 041 3 0.00

0.65 71.4 53.7 181.6 87.3 51 1 0.031

0.52 47.1 too small 118.2 23.6 70 1 0.045

8.6.3 atrices and Decision Tree 

The test plan and test matrices were made to co nd to VULCA ulations previ run to 

predict the test results. Twent e fire tests were he NA round nacelle

validate mulations. This simulator wa ipped with a four-nozzle suppressant distribution 

ystem. JP-8 considered in a variety of locations in the 

Test M

rrespo N sim ously 

y-fiv conducted in t VAIR g s lator to imu

 VULCAN si

 pool fires (see Table 8-13 for pool areas) were 

s equ

s

nacelle where the collection of fuel was likely, and both the suppressant flow and the overall air flow 

through the nacelle were varied to simulate a wide range of operating conditions. Tests were run also for 

reduced air flow. However, because of limitations on the rate of injection imposed by the HFC-125 vapor 

pressure, it was not possible to reach a condition where suppression failed at lower air flows. That was in 

agreement with the predictions that for lower airflows the overall mass fraction of agent for the attainable 

injection rates was always sufficient to extinguish the fires. The effects of varying the inhomogeneities 

were also investigated by capping individual nozzles. 

The planning for the tests and the computer simulations resulted in the following test matrices with 

decision tree: 

In test sequences 1 through 5, there are 11 to 14 tests indicated with no repeats. 

1. First sequence: Pools in B1, B2, and B3C3. Airflow: 1 kg/s. All nozzles. Vary the 

suppressant injection rate. (3 tests) 

a. Standard suppressant injection rate. 

e. If 1.a fails to suppress, 150 % injection rate. 

.” 

b. If 1.a. suppressed, 50 % injection rate. 

c. If 1.b suppressed, 25 % injection rate. End. 

d. If 1.b fails to suppress, 75 % injection rate. End 

f. If 1.e suppressed, 125 % injection rate. End. 

g. If 1.e fails to suppress, 200 % injection rate. End. 

h. General procedure: Given the results of a test, with the first test nominally at the standard 

injection rate, successful suppression will lead to a 50 % reduction in the rate of injection 

and failed suppression will lead to a 50 % increase. A possible sequence of injection 

rates (suppression results) would be “std” (suppress), “50 %” (fail), “75 %” (?). If the 

second test had resulted in suppression, then the final injection rate would be “25 %
Full-Scale Nacelle Fire Suppression Tests 877

2. Second sequence: Cap Nozzle 2. Airflow: 1 kg/s. (2 or 3 tests) 4 are listed 

3.

a. If 1.a. fails to suppress, try with pool B3C3 only. Standard injection rate. 

b. Pools in B1, B2, and B3C3. Standard injection rate. 

c. If 2.b. is suppressed, try reduction in suppressant injection for 2.b (only pool B3C3). 

Suggest intermediate injection rate from Sequence 1. 

d. If 2.a suppressed, try reduced suppressant rate for all pools that gave suppression in the 

first sequence. 

Third sequence: Cap Nozzle 1. Airflow: 1 kg/s. (2 or 3 tests) 

a. If 3.a. fails to suppress, try wi . Standard injection rate. 

Pools in B1, B2, and B3C3. Stand ection rat

. If 3.b. is sup sed, try reducti suppressant injection for 3.b (only ol B2). 

Suggest the in ediate injection rate from Sequence 1

. If 3.a suppressed, try reduced suppressant rate for all pools that gave suppression in the 

first sequence

4 ourth sequence

th pool B2 only

b. ard inj e. 

c pres on in po

term . 

d

. 

. F : Cap Nozzle 3. Air standard injection rate. (1 or 2 tests). Pools in B1, B2 

nd B3C3. Use lo t injection rate w suppression succeeded in the first sequence if this 

iffers from standard injection rate. 

. 75 % injection rate. 

50 % injection rate. 

th sequence

a wes here 

d

a

b.

5. Fif : Repeat first sequence irflow at 0.5 kg tests). This sequence might 

st be done before capping any nozzles to help map out the operation space. 

50 % injection rate. 

b. 75 % injection rate. 

w was reduced. When capping nozzles, the 

agent flow for a given bottle pressure was reduced somewhat. The bottle pressures led to suppression 

with a /s. (3 

be

a.

6. Repeat tests in all sequences that bracket suppression. 

7. Tests with reduced masses of agent (70 %, 43 %, and 32 %). Airflow: 1 kg/s. 

8. Tests with 100 % agent at reduced injection rate. Airflow: 0.75 kg/s. 

a. Minimum injection rate of agent. 

b. Slightly lower airflow; 0.73 kg/s. 

Suppressant injection rate was defined as “standard” for the standard rate of injection nominally used in 

the qualification tests, “50 %” for half that rate of injection, “75 %” for 3⁄4 that rate, etc. The procedure 

for changing the suppressant injection rate was to change the bottle pressure with a fixed suppressant 

mass. If any set of the pool fires were unstable, the air flo

without the inhomogeneities caused by removing nozzles. 
878 Fluid Dispensing and Dispersion 

8.6.4 Actual Test Program 

As the tests progressed through the decision tree and matrices, the sequence of tests was modified to 

adjust to the findings, in particular the seeming dependence of the success of extinguishments on the 

agent injection rate of the agent . As a result, the enumeration of Test Series 7 and 8 above were changed 

to Test Series 5 and 1 below. Series 8 was a repeat of certain tests in Series 1 (e.g., 8b = 1b). The actual 

path was: 

1. First sequence: Pools in B1, B2, and B3C3. Airflow: 1 kg/s. All nozzles. Vary the 

suppressant injection rate. (3 tests) 

d. Repeated b and c for replication assurance. 

a. Standard suppressant injection rate. 

b. If 1.a. suppressed, 5 0% injection rate. 

c. If 1.b fails to suppress, 75 % injection rate. 

2. Second sequence: Cap Nozzle 2. Air flow: 1 kg/s. 

a. Try with pool B3C3 only. 75 % injection rate. 

b. Pools in B1, B2, and B3C3. 75 % injection rate. 

c. If 2.b suppressed, 50 % suppressant rate for pool B3C3. 

d. Standard injection rate. 

3. Third sequence: Cap Nozzle 1. Air flow: 1 kg/s. 

a. Pools in B1, B2, and B3C3. 50 % injection rate. 

b. Pools in B1, B2, and B3C3. 75 % injection rate. 

c. Pools in B1, B2, and B3C3. 75 % injection rate and 0.75 kg/s air flow. 

d. Pool B3C3 only. 75 % injection rate. 

e. Pool B1 only. 75 % injection rate. 

4. Fourth sequence: Cap Nozzle 3. Air flow: 1 kg/s. 

a. Pools in B1, B2, and B3C3. 75 % injection rate. 

b. Pools in B1, B2, and B3C3. 50 % injection rate. 

5. Fifth sequence: Reduced mass of agent and airflow 1 kg/s. 

a. 50 % injection rate. 

b. 75 % injection rate. 

6. Repeat tests in all sequences that bracket suppression. 

7. Reduce agent mass. Airflow: 1 kg/s 

a. 69 % of agent and standard injection rate. 

b. 69 % of agent and 75 % injection rate. 
Full-Scale Nacelle Fire Suppression Tests 879

c. 43 % of agent and standard injection rate. 

d. 32 % of agent and 116 % standard bottle pressure. 

8. Test with 100 % agent at reduced injection rate. Airflow: 0.75 kg/s 

a. Minimum agent injection rate. 

8.6.5 Instrumentation 

Supply airflow measurement was made using a 15.24 cm turbine meter (Sponsler Co., Inc., Model SP6-

CB-PH7-C-4X, S/N 130619). When calibrated in water, the meter had an relative uncertainty of 

± 0.75 %. Temperature measurements were made using 21 type K thermocouples with an uncertainty of 

± 1 °C. Two digital stopwatches with an uncertainty of less than 0.1 s over 15 min period were used for 

time measurements. Fuel quantities for the pools were metered using graduated cylinders with an 

uncertainty of ± 5 mL. Four video cameras were used to record the existence of fire and its 

extinguishm

range of (0 to 71) MPa and an uncertainty of ± 0.02 MPa, a pressure gage from NoShok with a range of 

(0 to 7.1 age Co. with a 

range of (0 to

8.6.6 Test Procedure 

tinguishing JP-8 pool fires contained by structural ribs and longerons along the 

se this provided the strongest fire source. In several 

tle pressure to 

one of three values: 3.55 MPa, a rate roughly 75 % of standard design, 1.9 MPa, and a rate roughly 50 % 

of the standard 0.85 MPa. At these ambient temperatures the vapor pressure of HFC-125 was about 

0.85 MPa so that no nitrogen charge was added for the lowest pressure and rates. Nitrogen is somewhat 

soluble in this agent, and consequently the fire-suppression agent in these tests was a mixture of both 

HFC-125 and nitrogen; the latter was ignored in the VULCAN simulations. The suppressant bottle 

discharges downward so that the initial discharge is driven by the nitrogen pressure, which drops 

adiabatically as liquid agent is displaced from the bottle. At an intermediate pressure, the rate of pressure 

change slows; this is associated with agent discharge driven largely by the boiling of the agent or the 

ent inside the nacelle. Other instruments included a dead weight tester from Druck Co. with a 

) MPa and an uncertainty of ± 0.04 MPa, and a pressure transducer from Patriot G

 20.7) MPa and an uncertainty of ± 0.1 MPa. 

These tests focused on ex

lower nacelle surface. Prior to the testing, the bottom of the nacelle was lowered and the spaces between 

the ribs were sealed from their normal drain holes so that each could become a container for fuel. In the 

tests, three pools (Figure 8-114) were used: B1, B2 and B3 (or B3C3, indicating that the pool crossed one 

longeron). Prior to the tests, measured quantities of water were added to each pool, and the dimensions of 

the resulting pools were recorded to document the surface area of each pool as a function of liquid 

contained in the pool. 

In most of the tests, all three pools were ignited becau

tests, only the first or third pool was used in conjunction with fewer agent-distribution nozzles in order to 

assess the spatial distribution of the agent in both the VULCAN model and the real nacelle. The burning 

rate and the nacelle temperatures were observed to be substantially lower when a single pool was burned, 

as predicted in the VULCAN pretest simulations. 

The mass of agent to be used in each test was measured by the difference over the tare of the empty bottle 

on a calibrated scale. HFC-125 was the agent used in all tests. The rate of injection was controlled by the 

nitrogen pressure in this bottle, and three rates of injection were targeted by setting the bot
880 Fluid Dispensing and Dispersion 

dissolved nitrogen. For the lowest bottle pressure there is no nitrogen-driven stage. The last stage of the 

discharge is gaseous agent and nitrogen flowing from the bottle together. The pressure profiles from 

several tests, using all of the nozzles, are shown in Figure 8-121. The discharges from the two tests

denoted 1a(21) and 1a(25) are essentially the same conditions, as are the four tests denoted 1b(21), 

5d(25), 8a(26) and 1b(26). The scatter in these pressure profiles is indicative of uncertainties attributable

to, for example, ambient temperature changes that may heat the bottle during the few minutes that the test 

is being set up. Such uncertainties were estimated to be roughly ± 10 %.

Figure 8-121. Transient Bottle Pressure during Discharge for Various Initial Pressures 

with Nozzles Discharging a Total of 3.2 kg of HFC-125. 

according to the

turbine meter. This steady flow was maintained for about 15 s to 30 s before the agent was released. The 

elapsed period of burning was recorded with stopwatches as well as by the digital data acquisition system. 

Once the bottle was filled, it was installed into the distribution piping on the nacelle, and its manual safety 

valve was opened. Predetermined quantities of fuel were poured from graduated cylinders into the pools 

chosen for each test. At the end of each test, the remaining fuel was drained from each pool so that the

amount consumed could be accounted; these data, along with the elapsed time of the test, gave an 

estimate of the heat-release rate during the test. 

Igniting the pools of JP-8 fuel at ambient temperatures was challenging. The bottom of the nacelle was 

warmed with hot air to enhance the volatility of the fuel and to reduce heat losses. A minimum airflow 

from the blower at idle was established to provide sufficient air for combustion. An electric igniter was 

inserted over each pool in turn while a more volatile fuel, pure ethanol, was sprayed onto the pool. Once

the pool ignited, it required about 30 s to begin vigorously burning. After all pool flames had been 

established, the airflow was ramped up to the predetermined rate, either1 kg/s or 0.5 kg/s,
Full-Scale Nacelle Fire Suppression Tests 881

This system also recorded the signals from the array of 21 thermocouples in the nacelle. The indicated 

temperatures did not attain steady state over the duration of the fires. Four video cameras recorded the 

views inside and outside the nacelle, from which elapsed times for extinguishment were extracted. 

After each release of agent, a reduced airflow was maintained to cool the nacelle and remove potentially 

inflammable vapor. Then the remaining fuel was collected and measured in the graduated cylinders. 

For the tests in which a nozzle was removed by capping the end, the sequence was repeated also by 

lowering the bottle pressure until suppression failed. The general sequence for changing the injection rate 

was to reduce the injection rate by 50 % if the previous attempt succeeded and to increase the injection 

rate back to 75 % of the standard rate if the previous attempt failed to extinguish. The lowest attainable 

injection rate was 50 % of the nominal designed rate, so this process results in bracketing the suppression 

in proximity to 100 %, 75 %, and 50 % of normal injection rates. The nominal bottle pressures 

corresponding to these tests were 0.84 MPa, 1.9 MPa, and 3.55 MPa. While these were relatively wide 

margins, the available resources did not allow for additional tests to narrow these bands. The tests 

actually conducted are summarized in Table 8-17. 

Table 8-17. Summary of Full-Scale Tests Conducted. 

Test 

Indicator* 

Air 

Inflow 

(kg/s) Pools Nozzles 

Suppressant 

Mass 

(kg) 

Bottle Pressure 

(MPa) 

Target 

Suppressant 

Discharge Rate 

(kg/s) 

1a (25) 0.91 All All 3.18 3.55 1.1 

1a (21) 0.91 All All 3.18 3.55 1.1 

1b (21) 0.91 All All 3.18 0.84 0.5 

1d (25) 0.91 All All 3.18 1.83 0.8 

5b (25) 0.46 All All 3.18 1.83 0.8 

5d (25) 0.46 All All 3.18 0.84 0.5 

7a (26) 0.91 All All 2.20 3.16 1.1 

7d (26) 0.91 All All 2.20 1.86 0.8 

8b (26) 0.68 All All 3.18 0.83 0.5 

1b (26) 0.91 All All 3.18 0.9 0.5 

2d (27) 0.91 B3C3 No Nozzle 2 3.18 3.55 0.7 

2b (27) 0.91 All No Nozzle 2 3.18 1.9 0.6 

2d (27) 0.91 All No Nozzle 2 3.18 3.55 0.7 

2a (27) 0.91 B3C3 No Nozzle 2 3.18 1.9 0.6 

3d (27) 0.91 All No Nozzle 1 3.18 1.9 0.6 

3b (27) 0.91 All No Nozzle 1 3.18 3.55 0.8 

3c (28) 0.68 All No Nozzle 1 3.18 1.9 0.6 

3e (28) 0.91 B1 No Nozzle 1 3.18 1.9 0.6 

3d (28) 0.91 B3C3 No Nozzle 1 3.18 1.9 0.6 

4a (28) 0.91 All No Nozzle 3 3.18 1.9 0.6 

4b (28) 0.91 All No Nozzle 3 3.18 0.84 0.4 

7c (28) 0.91 All All 1.36 3.55 1.1 

7d (28) 0.91 All All 1.02 4.14 1.1 

Note: Variations from the baseline conditions, apart from bottle pressure, are indicted in bold face. 

* The alpha-numeric indicates the test conditions described in the Actual Test Program. The number in the parentheses is the 

date when the tests was conducted. 
882 Fluid Dispensing and Dispersion 

8.6.7 Test Results and Comparisons to Simulations 

The tests are enumerated in Table 8-18 in chronological order; these test numbers will be used in the 

discussion that follows. In addition to VULCAN, simulations were also performed using FDS and FPM 

to predict the results of the fire tests. Figure 8-122 and Figure 8-123 show the nacelle configurations used 

in the FDS and FPM simulations, respectively. The rectilinear shape of the nacelle simulator is the result 

of the Cartesian coordinate system used in FDS and FPM. 

Table 8-18. Comparison of Fire Test Results and Pretest Simulations. 

Test Plan Fire Test VULCAN FPM FDS 

Test 

Number 

Alphanumeric 

Designator 

Measured 

Time to 

Extinguish 

(s) 

Agent 

Injection, 

Rise Time 

(s) 

Predicted 

Time to 

Extinguish 

(s) 

Predicted 

Time to 

Extinguish 

(s) 

Predicted 

Time to 

Extinguish 

(s) 

2 1a Out in 1.3 s 6.8 1.1 (e) 2.0 2.0 

3 & 12 1c 10.0 Marginal out Not out Not out Accelerated 

burning 

5 1d Out in 5.2 s 7.0 1.9 (e) 2.0 to 3.0 2.6 

6 5d Out, no data No data 1.9 (e) 1.0 to 2.0 2.6 

7 5b Out in 4.4 s 9.5 Out 1.0 < 5.0 

8 5a Out >6.3 s 4.4 1.9 (e) < 3.0 1.9 

9 5b Out in 4.85 s 5.0 n/av 1.0 3.0 

10 & 11 8b Out in 2.3 s 9.6 n/av < 2.0 3.6 

13 2a Out in 11.2 s 6.5 Not out Not out 6.5 

14 2d Not out 10.4 Not out Not out > 4.0 

15 2b Out in 28.9 s 7.2 3.4 (e) Relight > .6 7.0 

16 2c Not out 9.3 Not Out 2.0 to 3.0 13.0 

17 3a Not out 10.8 Not out Not out Not out 

18 3b Out in 6.0 s 5.6 1.5 (e) 7.0 18.6 

23 4b Not out 13.8 n/av 2.0 19.5 

24 7a Out in 3.9 s 3.8 n/av 4.0 16.8 

25 7b Out in 1.8 s 2.4 n/av 3.0, relight 

@ 6.0 ? 18 

Table 8-18 also shows a condensation of all tests for which simulations were available. The primary 

observations therein include whether or not the fire was extinguished, the model predictions, the period of 

agent injection, and an estimate of the observed times-to-extinguish versus the predictions. These latter 

required interpretive judgment and the application of “rules of thumb” unique to each simulation program 

to decide when extinction was complete. Similarly, for the actual fire test data, while the injection period 

was acquired, the link between the recording video and the data-acquisition system had failed, 

unbeknownst to the test engineers. Consequently, the synchronization of the visual data to the agentinjection transient was not available during post-processing. The time of extinction was clearly 

observable with an uncertainty of ± 0.1 s, but the initiation of mixing the agent could be observed only by 

a sudden increase in the intensity of the fire. The uncertainty of this observation is estimated to be ± 2 s. 
Full-Scale Nacelle Fire Suppression Tests 883

Figure 8-12 celle 

onfigurat ed in FD

imulation

FPM S

2. Na

C ion Us S 

S s. 

Figure 8-123. Nacelle 

Configuration Used in 

imulations. 
884 Fluid Dispensing and Dispersion 

of agent, and all

the discharg . As expected

and predicte h

In Test 3, th a

pre-calculate t

later, as Test 12 g. At this lowest rate of injection, 

flames cam

video records and personal observations, it seemed that the injected agent only served to stir up the gases

in the n l ce, a much more intense fire 

resulted until 

The only di eplicate pair, was the order in which

the pools were filled. Normally (and in Test 5) they were filled from the front (B1) aft. In Test 6 they

were filled

of filling. The el disappeared from the middle

pool than fr

both during the e viewing the video records that the airflow in the nacelle blew the fuel 

out of the second pool (B

tests, th

In Test 7, a ated. Here, the injection rate was again set at about 50 %

of standard, educed by half. Even with the extended injection period, the fires 

were extinguished prom est, the concentration of agent in the ventilating airflow was 

identical to that of Test 2, and the obvious conclusion may be drawn. Following this test, the question 

arose w

the pool B3 table there, the

airflow was rate. The observed result was the most vigorous blow-torch seen,

and it was concluded that range of airflows in these tests were insufficient to “blow out” the fires. 

Test 8 w ent; the mass of agent was reduced to 

2.2 kg. Usin promptly, as in

Test 2. s in Test 5, the

fires ag more that sufficient to 

extinguish th

In Tests 10 ty was investigated further. In this replicate pair, the 

airflow was reduced to 75 % and the injection rate to 50 % (the minimum). In terms of agent 

ging the agent into the nacelle through the 

remaining three. In Tests 13 through 16, Nozzle 2, which discharged athwart near the front of the nacelle, 

was capped. In Tests 16 through 21, Nozzle 1, which discharged upwards at the same location as Nozzle 2,

Test 2 was the “standard” test arrangement. It used the full bottle pressure, the full mass

e nozzles and all the discharge locations that were used to qualify the system

d, t e fires were extinguished. 

e r te of injection was reduced to the minimum, which was the vapor pressure of HFC-125, 

d o be about 50 % of the standard rate. For replication, this test was repeated a few days

. What was observed seemed to be accelerated burnin

e shooting out of every opening in the test nacelle, and the fires did not go out. From the 

ace le in such a way as to promote better mixing. In consequen

the end of the injection period. 

fference between Tests 5 and 6, which were otherwise a r

front, back, and then middle last, in order to control for loss by evaporation during the period 

reason for this change was the observation that more fu

om the other two. There was no change in the test result, and this confirmed observations

test and from th

2) in visible drops toward the flame front over the pool B3C3. In both these 

e agent was injected at about 75 % of the standard rate; in both cases the fires were extinguished. 

proportionality question was investig

but the airflow also was r

ptly. In this t

hether or not the vigorous airflow itself was a major factor in “blowing out” the fires. In this test,

C3 was filled to the standard 2 L, and after the fire was established and s

increased to the standard

as the first to investigate the possibility of using less ag

g the standard airflow and injection rates, again the fires were extinguished

Test 9 was identical, except that the injection rate was reduced to about 75 %. A

ain were extinguished, proving that the “standard” mass of agent was

ese pool fires. 

and 11, the question of proportionali

concentration relative to airflow, these tests were similar to Test 5, and in the end the result was the same.

However, visual observations of the test showed that it took perceptibly longer to extinguish under these 

conditions, which indicated that the edge of the extinction envelope was near. 

In some tests, the standard, successful distribution system of four nozzles discharging the agent was

degraded by capping one nozzle at a time and dischar
Full-Scale Nacelle Fire Suppression Tests 885

was capped. In Tests 22 through 23, Nozzle 3 was capped. Nozzle 4 was so remote from the fires, 

toward the aft, outboard end of the nacelle, that it was never altered. 

on which was close to the edge of the extinction envelope. The injection rate was set at 75 % 

of stand ,

three wa

In Test 14, tion rate was reduced to about 50 %. The model 

predictions e ut this time the fires were not extinguished. This 

means that S 13, gave the only “wrong” result this time. In 

conclusion, outcomes, the edges of the actual extinction 

envelope ar

To illus ese tests were, Test 15 replicated Test 13, 

except that h tinguished. However, the elapsed time to 

extinction was abnormally mass of products of combustion acted to 

suppress the e

The varied ou only one pool, B3C3, was 

lit, and the i c about 50 %. In this case, all three models predicted extinction, 

and the s

In the next s ed with Nozzle 1 capped. As before, in 

Test 17 the j predicted the outcome. 

Likewise, in to 75 %. In this 

test also, all e

The next three te e not shown in Table 8-18. Test 19 established an 

airflow of 7 75 %, and even with Nozzle 1 capped the fires were 

extingu d ent to airflow as if both were standard. In 

Test 20, onl and a 75 % injection rate, that fire was 

extinguishe u to go out. This test was similar to Test 

13 except fo 1 was similar to Test 13 including that 

the fire o simulations of these tests were 

done. 

Nozzle 3 w 23; otherwise Test 22 was a replicate of Test 5, and Test 23 was a 

replicate of T tions, Nozzle 3 made no difference: the two tests in each pair had 

the sam the fires in Tests 3 and 23 did not. The 

injectio ny test. A simulation in VULCAN was not run; FPM 

predicted extinguishm which indicates 

that this tes o

Test 13 was conducted to verify fire-modeling predictions on the effect of poor distribution of agent. 

Nozzle 2 discharged athwart under the engine. It was predicted by two out of three simulations that this 

pool fire would not be extinguished, since the only pool fueled and enflamed was B3C3. This was a 

configurati

ard as in Test 5, except in this case the critical nozzle was capped, and only one pool instead of 

s used. In fact, the fire did finally go out, but it took more than 11 s to extinguish. 

 all three pools were lit, and the injec

wer the same for this case as for Test 13, b

FD , which predicted correctly for Test

it seems that when the models predict different

e nearby. 

trate how close to the edge of the extinction envelope th

all t ree pools were lit. In this case, the fires were ex

 long, almost 30 s. Perhaps the greater 

 fir s further. 

tcomes of the three prior tests led to conducting Test 16, in which

nje tion rate was reduced to

fire did indeed go out. 

eries of tests the original, logical sequence was follow

 in ection rate was set at 50 %, and all three models correctly

Test 18 the same configuration was set except that the injection rate was set

 thr e models correctly predicted the same outcome of extinguishment. 

sts, all with Nozzle 1 capped, ar

5 % of standard and an injection rate at

ishe . This one presented an equivalent proportion of ag

y pool B1 was enflamed, and with standard airflow 

d, b t with difficulty because it took several seconds 

r which pool was fueled. In the same manner, Test 2

was in pool B3C3 only, but in this case the fire did not go out. N

as capped in Tests 22 and

est 3. For these configura

e outcomes. The fires in Tests 5 and 22 were extinguished; 

n period of Test 23 was the longest of a

ent, as did FDS, but again note the elapsed time before extinction,

t als approached the edge of the envelope. 
886 Fluid Dispensing and Dispersion 

All the test o s c nducted with less agent were successful in extinguishing the fires in all three pools. 

Standard co were reported above for Tests 8 and 9. 

In Test 24, t m was at standard pressure. In Test 25, 

the mas to 4.14 MPa to increase 

the rate of i xtinguished. The most likely deduction may be that the 

rate of injection is the most important factor in extinguishing fires. 

o explore the edges of the extinguishment envelope for this ground nacelle 

tests in order to gain confidence in the results; 

in each replicate pair, the results were identical. Because of the vapor pressure of HFC-125 and the 

 fires in certain pools, some pretest VULCAN simulations could not be 

er, during the tests the discharge rate had to be estimated. For this purpose, 

 over the duration of the injection period, and the errors 

nditions were set for all these tests. The first instances 

he ass of agent was reduced to 1.36 kg, and the bottle

s of agent was reduced to 1.02 kg, and the bottle pressure was increased

njection. All fires were promptly e

The 25 tests were conducted t

simulator. Two of these tests were conducted to determine whether or not fires could be stabilized in 

individual pools (B1 and B3). It was demonstrated that these pools could sustain a fire, which agreed 

with VULCAN simulations, although the VULCAN simulations indicated that the stability of fires in 

individual pools was sensitive to heat losses. Specifically, if the heat losses associated with conduction 

through the pool to the nacelle were 50 % of the heat flux to the pool (essentially reducing the 

vaporization rate by 50 %), then certain pools, not employed in the present series of tests, could fail to 

sustain fires. In the test, it was necessary to apply heat sources (heat lamps) to the nacelle under the pools 

to minimize heat losses just to get the fires stabilized, and this lends support to the VULCAN 

observations. 

Of the remaining tests, two were replicates of the first two 

inability to light or stabilize

investigated. Consequently certain tests were run without pretest simulations. However, across a similar 

range of parameters, these results were in agreement with the trends of the VULCAN simulations. 

Ideally, the pressure data shown in Figure 8-121 could be used to determine the actual suppressant 

discharge rate to a level of accuracy similar to the accuracy of the inlet airflow meter. During the posttest data processing, this was done by calculating the adiabatic discharge of liquid agent from the bottle 

and assuming that the flashing and two-phase flow occurred at the throats of the nozzles, as reported in 

Smith et al.82 Howev

discharge rates identical to those in the VULCAN simulations were employed. Specifically, with all 

nozzles discharging, the 3.2 kg of HFC-125 was presumed to discharge uniformly over 3 s, 4.5 s, and 6 s 

for bottle pressures of 3.55 MPa, 1.9 MPa, and 0.85 MPa. The discharge rate was presumed to be 

reduced in accordance with the reduction in the total nozzle area when nozzles were capped. The 

assumption of constant discharge rates in the VULCAN model would be a source of disagreement with 

the test results. This uncertainty in the rates varies

in the estimates provided here are likely to be greatest in the earliest fraction of a second and during the 

latter periods. If the rate of suppressant injection were averaged over the significant few seconds, say the 

first 2 s to 3 s of the injection process, the uncertainties are on the order of ± 15 %. 

The results of the tests employing all nozzles are shown in Figure 8-124. Blue bars represent successful 

extinction, while red bars represent a failure to suppress the fire. In all of these cases, the VULCAN 

predictions were in agreement with the test results. 
Full-Scale Nacelle Fire Suppression Tests 887

7d(28)

7c(28) 7d(28)

7c(28)

7d(28)

7c(28) 7d(28)

7c(28)

Figure 8-124. Results of Tests with All Nozzles Used. 

The results of tests with labels starting in “1”, “5”, or “8” correspond to baseline cases using

approximately 3.2 kg of suppressant at varying bottle pressures and airflows. This series can be viewed 

as varying the ratio of the suppressant mass injection rate to the total (air + suppressant) mass influx. 

Suppression is observed to fail when this ratio is below (approximately) 0.4 ± 0.04. Where the airflow is

greatest and the bottle pressure is lowest, the total uncertainty is estimated to be ± 19 %. For reduced

irflows (0.68 kg/s) or increased bottle pressures (1.82 MPa), suppression was always successful. That

 exceeds the cup burner mass fraction4

 by a factor of 1.4 (0.4/0.28) probably 

in

ent, and these simulations agreed with the tests. No 

a

the ratio of injection rates

dicates the degree of inhomogeneous agent distribution in the system. 

In Figure 8-124, the four tests with labels starting “7” are where the mass of suppressant was reduced 

from 3.2 kg to 2.2 kg, 1.4 kg, and 1 kg. All of these tests resulted in successful suppression of the fire. In

each of these cases, the rate of injection was close to that for the designed conditions. It was estimated 

that the bulk of the suppressant was injected in 3 s for 3.2 kg, in 2 s for 2.2 kg, and in 1 s for 1 kg to 

1.7 kg, which reinforced the importance of the ratio of injection rates. The VULCAN simulations were 

conducted only with 3.2 kg and 2.2 kg of ag

VULCAN simulations were run for agent masses less than 2.2 kg. 

Figure 8-125 summarizes results for which one of the four nozzles was capped. Blue bars represent

successful extinction, while red bars represent a failure to suppress the fire. In all of these cases, the 

VULCAN predictions were in agreement with the test results. Green bars indicate cases where

suppression was successful in the tests but was indicated to fail in the VULCAN simulations. 
888 Fluid Dispensing and Dispersion 

gure 8 . Resu f Tests w ne Nozzle ped. 

Capping a nozzle has two effects. First, the total noz s reduce e 

pressure, the suppressant injection rate is reduced proportionally. The second effect of capping a nozzle 

is to increase the inhomogen f the distribution insid nacelle. Gre nhomogeneity a 

greater ratio of injection rates to achieve successful sup on. VULCA mulations predicted that 

h omoge ld result by capping either Nozzle 1 or Nozzle 2, but not Nozzle 3. 

The results of tests, with Nozzle 3 capped, are indicated by the labels with the prefix “4” at the top of 

Figure 8-125. The ratio where suppression fails trended toward lower values than with all nozzles. 

Whether or not the degree of inhomogeneous distribution actually decreased and performance of the 

s creased apping zzle t be ded based o

im y the tests. Nozzle 3 injected suppressant into the upper nacelle, om any of the pool fires. 

For this reason, a reduced concentration of suppressant in the upper nac ay not have influenced 

agent effectiveness at the loca s of unce ies in the sup ant injection r nd the 

lack of replicate tests do not allow definitive conclusions to be drawn. Test ere Nozzle 1 w apped 

are indicated with the prefix “3” in Figure 8-125. In som s only specific pools were ignited in order 

to e locations where fires failed to be extinguishe ble 8-17). T

ignited are 3b, 3d, and 3c. e c as a difference between N results and the 

tests. The VULCAN simula pred e to s ss the fire in

extinguished in the tests. (The VULCAN prediction lated.) 

Reducing the injection rate to a ratio 20 % less led to a successful prediction, as in case 3d. VULCAN 

tended to predict failure to suppress before it actually occurred. This ma because the mixing rate 

e 

cu count properly for enhanced mixing near the wall. Clutter models may 

Fi -125 lts o ith O Cap

zle area i d so that, for the same bottl

eity o e the ater i requires 

pressi N si

igher inh neity wou

ystem in by c No 3, should no conclu n the present results, even if

plied b far fr

elle m

tion the fires. The rtaint press ate a

s wh as c

e test

 find th d (Ta he tests where all pools were 

In thes ases, there w the VULCA

tions icted a failur uppre test 3b, although the fire was 

for 3c was not actually run, but extrapo

y be 

within the VULCAN simulation erred on the low side. In highly cluttered areas bounded by walls, th

rrent clutter model did not ac

3c(28)

3e(28)

3d(28)

3c(28)

3d(28)

3e(28) 3c(28)

3e(28)

3d(28)

3c(28)

3d(28)

3e(28)
Full-Scale Nacelle Fire Suppression Tests 889

improve these predictive capabilities, but the fact that the VULCAN predictions tended to be 

conservative, with a safety factor on the order of 20 %, is preferred and acceptable. In terms of the ratio 

uppression. The results indicate that low 

concentrations occur in t

simulations ry useful. 

The results of tests for which was ca re ind he la he p n 

Figure 8-125. As with the previous examples, AN s indic re to suppress at 

the njec ec duce eity of agent distribution. Test results showed 

tha re occurred at th ent in the in n rate, the e as when le 1 

was ca ed. This wise i 0 % sa factor rel the VUL simulations. The 

failure to suppress when eithe apped o at a ra on rat spanning 0.4, the 

same he tes ith al VULCA mulation ng Noz indicat ater 

inhom eneity in th re regi

The pretest VULC simula tly pred d the succ failure of extinction in nearly all 

cases. In only two cases wer eement ween the VULCAN predic and the tes ults. 

In b ese cas when e two for

fire uppress sing a ure 25 wer than the VULCAN s ns had p ted. 

This indicates that the VULC tions w omewhat conservative in their predictions of the 

mixing in the forwa acelle

8.7 PROVE TRANS OF WA TO FIR

8.7.1 ackgrou

As noted in Chapter 1, initially the N pons systems in 

which halon 1301 s ms had led. Wa s or m ere (and le alterna s for 

ome of those platforms. Accordingly, the NGP supported efforts aimed at improving the efficiency of 

temperatures much lower than those required for thermal ionization. In a normal flame, both positive and 

negative ions (primarily formed by electron attachment) are formed in addition to the electrons. The high 

mobility of the electrons results in the outer region of the flame being negatively charged by the electrons 

of the mass injection rates, the tests indicated a critical value between 0.4 and 0.45, a statistically 

insignificant increase over the 0.4 (± 15 %) found in tests employing all nozzles. The VULCAN 

predictions indicated that the critical ratio of mass injection rates was between 0.45 and 0.55. Tests 3e 

and 3d, in which only pools B1 and B3 were filled, were done to ascertain the regions of the 

inhomogeneous agent distribution that led to failed s

he vicinity of pool B1 but not pool B3, which agrees with the VULCAN 

. The ability of VULCAN to identify regions where fires cannot be suppressed is ve

 Nozzle 2 

ause of a re

pped a

 the VULC

icated by t

imulations 

bels with t

ated a failu

refix “2” i

 h i

t the failu

igher tion rates b

to suppress 

d homogen

e next decrem

ndicates a 2

jectio

ative to

 sam Nozz

pp like fety CAN

r nozzle is c ccurs tio of injecti es again

as in t ts w l nozzles. N si s cappi zle 2 did e gre

og e fi on. 

AN tions correc icte ess or 

e there disagr s bet t ions t res

oth of th

s w s

es, ither of the ward nozzles was capped, the test results found that the 

ere ed u bottle press

A la

% lo imulatio redic

N simu ere s

rd n region. 

IM D PORT TER ES 

 B nd 

GP research w

 been instal

as directed 

ter spray

at the full ra

ists w

nge of wea

yste are) viab tive

s

getting water sprays or mists to the fires. In particular, two techniques for improving water droplet 

transport to fires will be described and discussed: (1) electrically charged water mist and (2) a selfatomizing form of water. 

8.7.2 Electrically Charged Water Mist 

Background 

It is well known that hydrocarbon flames contain electrical charges because of the process of 

chemiionization.83 In chemiionization, flame radicals react to form electrons and positive ions at
890 Fluid Dispensing and Dispersion 

and the bulk of the flame region being positively charged by the preponderance of positive ions. Much of 

what is known about flame ionization has been learned from studies of premixed flames83,84,85,86 although 

some diffusion flame studies have been conducted.87

For real fuels and real fires (almost always diffusion flames) the are a number of considerations which 

could lead to either increases or decreases in the flame ionization, but

time. For example, real fuels contain impurities (e.g., meta n 

concentration. On the other hand the formation of soot particles sites to 

which electrons will attach. This keeps the negative charge clos ns of the fire than would 

occur if the electrons were free to diffuse away on their own. Thus, electron attachment may reduce the 

charge separation (at least in the fire plume) that normally makes flames appear to be positive. 

While it cannot be certain which effects will dominate in real fires, there is no doubt that diffusion flames 

in air behave as though they are positively charged since they are strongly pulled by negatively charged 

objects.88, 89

The application of an external electric field in the vicinity of the flame results in the motion of electrons 

nd negative ions towards the positive electrode and the motion of positive ions in the opposite direction 

towards the negative electrode. More momentum is generally exchanged by collisions between the 

ositive ions and the neutral gas molecules as compared to the momentum exchanged by collisions with 

the negative species dominated by electrons. This momentum exchange results in the production of an 

nic wind90 which is a flow towards the negative electrode. This ionic wind is responsible for the large 

e displacements reported above, and the effect has been used to control blowoff stability,89 which can 

e increased or decreased depending on the orientation of the electrodes that produce the electric field. 

hese effects can be produced with extremely low electrical power levels, on the order of 10-2 % of the 

 scenarios in which electric charging of the water mist droplets can interact 

atively charged droplet approaching the vicinity of the fire will repel electrons and 

negative ions, and there will be an attraction between the negatively charged droplets and positive ions. 

To distinguish whether the charged mist droplets move toward the flame or the flame moves towards the 

roplets, the overall mass of water mist per unit volume in a spray based on assumed droplet velocities 

was computed and compared it to the density of air under the assumption of a water application rate of 

(1 to 2) L/ (min-m2

), which is considered to be sufficient to extinguish a heptane pool fire.91 For example, 

the mass of the water mist droplets contained in a unit volume is 1.3 % of the mass of air in the same 

volume for a water flux of 1 L/ (min-m2

) and a droplet velocity of 1 m/s. The water density relative to air 

varies proportionately with the water flux and inversely with the droplet velocity. The effective mass per 

unit volume of the ions was taken as the density of the air since the ions pull the air or other flame gases 

along with them when they move. 

The mass of liquid water per unit volume can vary from a small to a moderate fraction of the mass of the 

flame gases per unit volume depending on the velocity of the droplets and the temperature of the gases. 

Of course, the actual droplet flux, and thus the liquid water mass, is decreased if the droplets are 

evaporating as they approach the flame. Thus, if the water flows are low and/or the droplets experience a 

great deal of evaporation near the flame, the droplet mass is low compared to that of the ions and the air 

that contains them so that the droplets can move towards the flame. 

re

 these cannot be quantified at this 

ls) which can greatly increase the io

 in cooler regions of a fire act as

er to these regio

a

p

io

flam

b

T

power released during combustion. 

There are several different

with real fires. A neg

d
Improved Transport of Water to Fires 891

Without a mechanism for charge removal, charge would build up and retard the attractive motion between

the negative mist and the positive flame gases. This removal can be accomplished if there is an electrical

ground in the vicinity of the fire. In many cases the circuit is closed by a conducting floor or wall in 

contact with the electrical ground. This would be the case for a fire on a ship deck or on metal shelving. 

The voltage drop, ∆V, across a surface is given by 

A

t I V ρ ∆ = (8−51)

where ρ is the volume resistivity of any insulating layer such as paint, t is the thickness of the insulating 

layer, I is the total electrical current and A is the total surface area available through which current passes

to ground. Because the currents involved in droplet charging are so small, and the surface area available 

ground near the base of the fire. 

egative

ions which are discharged through the electrical ground near the fire’s base. 

se droplets are redirected to lower velocity regions outside of the main plume,

then they might be pulled in closer to the base of the flame by the positive flame ions or the presence of a 

rogram two power supplies

were used: a high voltage (15 kV) unit which is not capable of delivering any significant current (200 μA) 

the high voltage electrodes be physically shielded to prevent direct contact with them. 

for current flow to ground through floors and walls is so large, the voltage drop caused by current flow 

through wall or deck paint should be small. For aircraft applications such as fire extinguishment in

engine nacelles, the surfaces are generally not painted so that there is no problem in obtaining a good

electrical ground. 

Even if the fire’s net positive charge is small, the fire can still be a relatively better electrical conductor

than the surrounding air due to the presence of charges in it. Thus, the droplets will still try to ground 

themselves through the fire, and the excess charge that they carry will eventually proceed to an earth

In addition to water droplets being individually drawn to the flame ions, the presence of a large number of 

charged droplets results in electrostatic repulsion between the droplets. An electrical ground allows a 

steady state current composed of the droplet charges to be established under the action of this selfrepulsion. The current path could be composed of droplets striking the floor or wall, droplets evaporating 

and the electrons they carry either passing directly to ground or attaching to a molecule which travels to 

ground under the influence of the charge induced electric field. Positive ions could move toward the 

droplets and neutralize them, leaving a net negative charge composed of the fire’s electrons and n

The presence of cooler soot particles in the upper regions of a fire plume may act as sites for flame 

electron attachment. Repulsion of the negatively charged droplets by the negatively charged soot

particles, could be beneficial from the point of view that those droplets might not be swept away by high

velocity plume gases. If tho

surface electrical ground. In any case there are a number of possible situations in which electrical

charging will cause water mist to come into closer contact with reacting flame gases. 

Safety considerations present only a small concern with the droplet charging method used in this work

because the currents involved in mist charging are extremely small. In this p

and a lower voltage (5 kV) unit which can deliver 10 mA. The first unit is safe and the second unit can be

made safe by installing current limiting resistors. While this is not life threatening in itself, any 

significant shock could be distracting or disorienting in an emergency situation. The only way such a

shock could occur is by direct contact with the charged electrode. For this reason it is recommended that 
892 Fluid Dispensing and Dispersion 

Two references of particular interest for the present study are those of Patterson et al.,91 performed at the 

New Mexico Engineering Research Institute (NMERI), and Gottuk et al.,

92 performed at Hughes 

Associates, Inc. Patterson et al.91 obtained a large database on uncharged mist extinguishment of heptane

ing a uniform 

water flux over their chamber and the absence of ventilation currents, their data exhibits a tremendous 

pool fires in a well-controlled test chamber environment. Gottuk et al.92 compared fire extinguishment of 

heptane pool fires with and without electric charging. 

Patterson et al.91 used water mist to extinguish 5.08 cm diameter heptane pool fires in a 1.07 m × 1.07 m ×

2.06 m chamber. Following establishment of the fire for 30 s, the chamber was closed so that there was

no further ventilation once the mist was turned on. In spite of their great care in achiev

amount of variability in extinguishment time as a function of water flux (Figure 8-126), especially for low 

values of the flux. The curve shown is a cubic fit to the extracted data. 

Water Flux (L/min-m

Ex me

nt Time (

s)

2)

tinguis

h

Water Flux (L/min-m2)

Ex me

ent occurred within 20 s after application of the water flow. They reported that this was a 

91 Their table shows three ranges of water mist

flux and the fraction of the tests in which a fire was extinguished for each flux. 

nt Time (

s) tinguis

h

Figure 8-126. Extinguishment of Heptane Pool Fires by Uncharged Water Mist.91 

Gottuk et al.92 studied the effects of electric charging of water mists on extinguishment of heptane fuel

fires. A single mist nozzle was used in an open environment to extinguish a heptane fire in a 10 cm 

diameter pan. Water was collected to determine the water flux in the same size pan as used for the fuel. 

Gottuk et al.

92 arbitrarily selected the criterion that a fire was considered to be extinguished if the 

extinguishm

useful criterion for their experiments on the basis that fires that were not extinguished in that time were 

never extinguished, except for one case with electrical charging in which extinguishment occurred in 34 s. 

Results were reported as groups of the number of cases in which a fire was extinguished out of the

number of tests within a range of water collection rates for a given voltage. 

Table 8-19 reproduces the fire extinguishment results that appear in Table 3 of the report of Gottuk 

et al.92 in the units of water flux used by Patterson et al.
Improved Transport of Water to Fires 893

Table 8-19. Effectiveness of Charged Water Mist Expressed as Percent of Successful 

Pool Fire Extinguishments.92

Water Application Rate (L/min-m2) 

5.0 to 5.9 6.0 to 6.4 6.5 to 7.0 

Uncharged (0) 0/0 6/13 (46 %) 9/10 

+ Charged 0/3 2/6 (33 %) 0/3 

− Charged 0/9 3/4 (75 %) 0/0 

For the lowest water flux range, no fires were extinguished by the charged sprays; thus no improvement 

from the charging could have been seen. For the highest water application rate, the positively charged 

spray was significantly less effective than the uncharged sprays. 

It is difficult to draw a conclusion for the middle range of water application rates. A change of a single 

test result for either type of charged spray gives results that are similar to the uncharged spray tests. It 

would take more extensive tests in this range to reveal a real effect. 

Gottuk et al.92 concluded that no significant increase in fire extinguishing capability resulted from 

charging the water sprays and that the most notable effect of charging the spray was spray divergence, 

sures 

wn in Figure 8-127. The chamber had a steel frame, 

polycarbonate walls, and a metal flame hood at its top that leads to a duct flow booster exhaust fan. The 

chamber plan view dimensions were 1.2 m × 1.2 m, and the viewable height through the Lexan window 

was about 1.8 m. The bottom of the chamber was open with a vertical height of at least 0.3 m, around the 

periphery of the bottom of the chamber for fresh air to enter. A horizontal beam located about 0.5 m 

resulting in lower water application rates to the fire. Gottuk et al.92 were also concerned with the safety of 

the electrical system. However, their observation that charging makes the mist spread out could actually 

be beneficial, since small uncharged droplets have short horizontal stopping distances which determine 

how far they can spread from the centerline of a spray nozzle. Charged droplets produce a force on each 

other that can disperse them to greater horizontal distances. Without charging, extremely high pres

would be needed, or there would have to be an array of a great number of nozzles to achieve a wide 

distribution of fine water mist spray. 

For the NGP, Berman and coworkers93 at AeroChem Research Laboratories carried out exploratory 

research to further assess whether electrical charging of water mist could substantially reduce both the 

time and the amount of water required to extinguish a small pool fire by taking advantage of the electrical 

properties of flames. The specific objectives of the study were to: 

• compare the motion of charged and uncharged water mist droplets near a flame 

• determine the reduced time for fire extinguishment due to electric charging of the water mist. 

The current program addressed ceiling sprinkler extinguishment of compartment fires, and 

the same principles should hold for aircraft engine nacelle fires. The main technical problem 

encountered was achieving a uniform distribution of water mist over a significant surface area 

both with and without charging. Promising results were obtained despite this difficulty, 

which may be correctable with additional work. 

Experimental Set-up 

The fire test chamber used for the experiment is sho
894 Fluid Dispensing and Dispersion 

above the bottom of the sidewalls was used to mount all of the burners and fuel pans. A translating beam 

located 0.13 m above the fuel pan held the water collection pans used to determine the water distribution. 

The translating beam was moved out of the way when fire extinguishment tests were performed. The 

booster fan was at its half point power position for all extinguishment tests. The chamber’s metal

structural elements, the flame hood, the spray nozzles, the water pipes, the fuel pans, and the water

collection pans were all electrically grounded. 

Water Droplet Motion Due to Charging 

The hypothesis of this project was that there is an attraction between the negatively charged droplets and

the positively charged flame. The first step was to verify that the droplets were being charged and to 

estimate the magnitude of the charging effect and the corresponding induced motion. Once this was 

established, tests were performed to detect additional motion of the charged droplets near the flame. 

Estimates of Electric Charging and Field Effects 

Initial tests were implemented to determine the electric forces on charged droplets in terms of their

motion near a grounded metal screen. A Cone Jet TX−1 hollow cone nozzle was chosen to observe the

attraction of the charged mist to grounded objects and fires. It was expected that the droplets dispersed in

the hollow cone pattern would be easier to track compared to a solid cone spray nozzle. The

characteristics of the TX−1 are given in Table 8-20. 

Table 8-20. Hollow Cone Nozzle Characteristics. 

TX−1 Hollow Cone Nozzle 

Pressure (kPa-g) 206 275 344 412 

Mean volume diameter (μm) 108 101 97 93

Flow rate (L/min) 0.056 0.063 na 0.095 

Total spray angle (degree) na 54 na na 

Charging was produced by an inductive principle in which an electric field is established between a 

positively charged ring and three grounded wire tips in a pitchfork configuration formed by three soft

copper wires that were twisted to form a single basic wire shaft (see Figure 8-128). The positive ring

to 15 kV with a Gamma High Voltage 

Research Inc. dc power supply. This power supply delivered 1 kV output for each 1 V input so that it

induces electron emission from these grounded wires, and these electrons attach to the droplets. The 

process is aided by the fact that the electric field also aligns polarized droplets so that the positive ends of 

droplets point toward the grounded wires. The proximity of a positive end of a nearby droplet produces 

extra field strength to remove additional electrons from the wire. From principles stated by Kelly,

94 the 

charges will distribute themselves among the available droplets. 

This electrode configuration was typically operated between 5 kV

could be operated with batteries or the low voltage dc normally found in fire control systems (typically

24 V). At 15 kV many droplets tended to head back toward the grounded nozzle body. The maximum 

effective spreading of the spray pattern occurred at around 10 kV. 
Improved Transport of Water to Fires 895

Figure 8-127. Schematic Sketch of Fire Test Chamber. Metal chamber structure, water 

nozzle, fuel pan, and water collection pans are all electrically grounded. 

Figure 8-128. Electron Induction Electrode. 
896 Fluid Dispensing and Dispersion 

The metal screen was positioned vertically and displaced about 13 cm away from the nozzle centerline 

(see Figure 8-129). Applications of 5 kV to 15 kV to a positive inductive electrode showed that the 

droplets from the TX−1 hollow cone nozzle were strongly attracted to the screen. Moving the grounded 

electrodes as a whole to different locations in the spray, e.g., directly underneath the nozzle or off to the

side, did not seem to make a big difference in the charging effect. Because the droplets traveled nearly 

horizontally towards the screen, the electrostatic force on them due to their charge and the electric field

generated by the bulk of the charged droplets greatly exceeded the net gravitational force on them. 

Estimate of the amount of droplet charging can be obtained by assuming that the ratio of the horizontal

component of the droplet velocity to its vertical component is the same as the ratio of the droplet’s 

horizontal electrical force to its gravitational force. 

vertical

horizontal

gravitational

electrical

V

V

F

F = (8−52)

This relation is valid if the droplet velocities are based on either of two extreme physical limits: (1) the 

two accelerating forces are equal to the corresponding component of the droplet drag force or (2) the drag 

is small compared to the accelerating forces. 

Figure 8-129. Attraction of Charged Droplets to Grounded Metal Screen. 

The ratio of the forces is 

R g

q E

Fgravitatio

Felectri

d d

d

nal

cal

π ρ = 3 4

3

(8−53)

lectrical charge on a droplet, Rd is the droplet diameter, E is the electric field strength, ρd

nsity, and g is the gravitational acceleration. An important characteristic droplet charge

where qd is the e

is the droplet de

value is the Rayleigh limit droplet charge qRayleigh

95, defined as 

2 3

0 64 Rayleigh Rd q = ε σπ (8−54)
Improved Transport of Water to Fires 897

where ε0 is the free space electrical permittivity constant and σ is the droplet’s surface tension. The

droplet will break up into smaller ones if the droplet charge exceeds qRayleigh. For this case, qRayleigh is 

around 4 × 107

 electrons per droplet. It is common practice to describe the actual droplet charge as a per 

cent of the Rayleigh limit charge. Thus, 1 % of the Rayleigh limit still corresponds to 4 × 105

electrons. 

Using Equation 8−52 to describe the force ratio and writing qd as a percent of the Rayleigh limit value, 

The electric field is determined by the distribution of all the charged droplets and the positioning of the 

high voltage electrode and all the grounded surfaces. Since the charge distribution is not known, it is not 

possible to determine E without making some important assumptions and additional computations.

However, the product of qdE can be estimated from Equation 8−53, and some possible combinations of qd

and E can be compared. 

the electric field vector in volts/meter is

horizontal Rayleigh

It is difficult to estimate the velocity ratio since it is so large, and it varies at different locations. If the 

ratio is arbitrarily set at 100 and the droplets are charged to 1 % of the Rayleigh limit, then

E = 7.197 × 106

 V/m, which is more than twice the breakdown voltage value for air of 3.0 × 106 V/m.

Thus, a droplet charging value of 3 % to 4% (with a correspondingly lower value of E) would not be

unreasonable. Gottuk et al.

92 estimated that the charging in their case was 4 % for a spray with a similar

droplet size. By rearranging Equation 8−55 to solve for percent of Rayleigh charge as a function of E, the

estimate for the percent charging increases if the electric field strength is lower and decreases if the

velocity ratio is lower. 

Attraction of Droplets to Flames 

vertical

V q

V E

%

1 = 71,970 (8−55)

).

mes weaker relative to the estimates

Tests were performed with the same positive inductive electrode and TX−1 hollow cone nozzle with 

flames positioned off to the side of the nozzle centerline instead of a metal screen. First, a small propane

diffusion flame was positioned a little over 0.30 m from the centerline of the nozzle (see Figure 8-130

Application of a 15 kV voltage changed the droplet trajectories from a vertically downward direction to a 

nearly horizontal orientation directed towards the base of the diffusion flame. 

Similar tests were instituted for pool fires in a 9 cm diameter pan using heptane in one case and methanol 

in a second. While there was a noticeable increase in the spray angle due to charging, the trajectories did 

not display the large horizontal motion observed for the propane diffusion flame and appeared to be more 

continuously vertical near the fire. Charging seemed to increase the amount of water reaching the pool

fire, but this may be due to the effect of self-repulsion which would increase the diameter of the region

covered by the spray.

There are indeed differences between the gas diffusion and pool flames. The heptane flame produces 

more soot particles which can attach electrons after the particles cool. The methanol flame is not 

expected to produce chemiions. 

Estimates can be made for the electric field and charging using the velocity ratio in Equation 8−55, 

typically on the order of 0.5. If the charging level is the same as in the case of attraction to a metal

ground, then the electric field will be on the order of a hundred ti
898 Fluid Dispensing and Dispersion 

made in the previous section. In making these estimates, one should be aware that air currents, which 

have not been accounted for, will also have an effect on the velocity components. 

Fire Extinguishment Tests 

Extinguishment time as a function of water flux with and without electric charging for a different nozzle

and nozzle arrangement, a different size fire, and a different chamber was obtained in the present study. 

he fire extinguishment study by Gottuk et al.92 in an open environment pointed out the importance of 

charging in changing the water flux. For this reason, almost all measurements of extinguishment time, 

1 m, ten times the diameter of the 10 cm diameter fuel pans to be used. A special 

consideration was that droplets carrying the same sign of electrical charge would tend to repel each other. 

T

both with and without charging, were either immediately preceded or followed by a measurement of the 

water collected at the location of the fuel pool pan. 

10 cm Diameter Pool Fire 

Much effort was needed to develop a spray system that would provide a uniform distribution of water 

over a diameter of

The effect of the self-repulsion would be to produce spreading of the droplets and reduce the water flow

per unit area. 

Propane flame Heptane or 

methanol pool fire

Propane flame Heptane or 

methanol pool fire

Propane flame Heptane or 

methanol pool fire

Propane flame Heptane or 

methanol pool fire

Figure 8-130. Motion of Charged Droplets near Fires. 

A single nozzle assembly called the 7N, recommended by Spraying Systems, Inc., was used for the 

experiments (see Figure 8-131). The 7N assembly, which held 7 individual hollow cone nozzles, had a 

single 2.54 cm water pipe connection which fed one central nozzle and six outer nozzles at a constant

radius from the center one. The axes of the outer nozzles were canted away from the centerline. The

manufacturer asserted without specific size measurements that the droplets from the individual nozzles 

crossed paths so that a somewhat uniform spray was produced. Following the manufacturer’s guidelines, 

the operating range was limited to between 687 kPa and 1031 kPa. A water feed system was designed
Improved Transport of Water to Fires 899

and assembled with the water pressurized by nitrogen from a regulated high pressure cylinder to cover the

range of pressures to be used with the 7N nozzles. 

It was expected that different sized nozzles might be needed to cover the range of conditions for the tests. 

Based on a preliminary test of fire extinguishment with a single nozzle, 0.095 L/min nozzles were

selected for the 7N assembly. The plan was to install the 7N assembly with 0.095 L/min nozzles, observe

zle flow capacity. 

its fire extinguishment performance with and without charging, and purchase one or more additional 7N

assemblies with the appropriate flow capacity nozzles to cover the range of testing. Thus, in all cases the 

overall geometry would remain unchanged whether or not the droplets were electrically charged or the

water flow rates were to be changed by replacement of the 7N assembly or individual nozzles. The water 

flow per unit area would be controlled by varying the water pressure and changing the nozzles. There

was little change in droplet diameter in going up or down one size in noz

Figure 8-131. 7N Seven Hollow Cone Nozzle Setup. 

Since extinguishment times with the 0.095 L/min nozzles were found to be short, a lower capacity 7N 

supplied with seven 0.063 L/min nozzles was obtained to cover the range of lower flow rates and longer 

extinguishment times. The characteristics of the 7N system with 0.095 L/min nozzles are given in 

Table 8-21 and those of the 0.063 L/min 7N system are given in Table 8-22. 

Table 8-21. High Flow Capacity Seven Nozzle Assembly.

7N – 1.5 Seven Hollow Cone Nozzle Assembly

Pressure (kPa-g) 687 859 1031

Mean volume diameter (μm) 69 62 59

Flow rate (L/min) 1.060 1.174 1.287 

Spray coverage diameter (m) 0.76 0.76 0.76 

Table 8-22. Low Flow Capacity Seven Nozzle Assembly.

7N – 1 Seven Hollow Cone Nozzle Assembly 

Pressure (kPa-g) 687 859 1031

Mean volume diameter (μm) 59 57 55 

Flow rate (L/min) 0.680 0.794 0.869 

Spray coverage diameter (m) 0.61 0.61 0.61 
900 Fluid Dispensing and Dispersion 

Ch o

each other. In a more typical setti parately to a number of individual

nozzles, rather than an assembly, it would b droplets from each nozzle

were charged using an individual charging electrode. For the 7N, a single circu diameter

charging electrode was positioned coaxially around the y.

A 3 strip of wire ning material was rol ircular hoop and fastened on the inside 

f an eter ring made of copper tubing (see Figure 8-132). The orientation of the screening

on the top and the same number on the 

me charged due to its proximity to

arging the spray from the 7N nozzles was challenging because of the close proximity of the nozzles t

ng in which water was supplied se

e relatively easy to assure that the

lar large

7N assembl

.8 cm wide

0.2 m diam

scree led into a c

o

material was vertical. It was hoped that this would decrease water collection on the screening and large 

droplet formation. This strip produced electron emission from both the top and bottom rows. 

The cut screen mesh provided approximately 250 sharp points

bottom of the electrode to charge the droplets from the outer set of six nozzles with the 7N grounded.

The question was if the center nozzle mist would become charged. The rationale was that since the outer

and central nozzle sprays crossed over, some charged outer nozzle spray would find its way to the center

of the system, and some inner nozzle spray would move out and beco

the charged outer nozzle droplets. In addition, earlier tests using the inductive approach with grounded 

wires as the electron source indicated that the ability to charge droplets was not strongly linked to the

position of those electrodes. 

High voltage power supply

7N seven hollow cone nozzle assembly

Spray pattern e

e

e

Electrons

Negatively charged ri

Electron emitting screen

ng

High voltage power supply

7N seven hollow cone nozzle assembly

Spray pattern e

e

e Negatively charged ri

Electron emitting screen

ng

Electrons

Figure 8-132. Spray Charging Set-up. 

One might think of an individual multiply-charged droplet near an uncharged droplet as an inductive 

source of electrons in the sense of inductive wire electrodes. Thus, an uncharged droplet will become 

polarized when it passes close to a charged droplet. The positive end of a polarized droplet will become 

aligned with the negatively charged droplet. The additional electric field strength associated with this

alignment will result in the transfer of electrons from the charged to the uncharged droplet. In this way, it

was hypothesized that a cascade effect could transfer electrons from regions of charged to regions of 

uncharged droplets. Despite precautions, some large drops formed on the strip electrode and dripped off, 

but they did not fall into the fuel pan and thus did not affect fire extinguishment. These larger drops were 

less susceptible to the effects of airflow induced by the ventilation fan or the fire plume. In a more
Improved Transport of Water to Fires 901

realistic environment with individual chargers for each nozzle, dripping would not be expected to be 

important. 

Water flux uniformity tests were made using nine 10 cm diameter pans to collect the water (these were

identical to the pan used to hold the fuel for the pool fire). These were placed side by side on a beam that

could be slid on a rail into position above the fuel pan, and then be moved easily out of the way when fire 

extinguishment tests were performed. This array of collection pans was about 13 cm above the plane of 

ed a distance of 0.9 m.

er in

ultiple nozzle design electrode ring was placed around

the nozzle, the spray pattern appeared to be more symmetric, but was still peaked. Dripping from the 

the fuel pan, and the entire array of pans spann

With all seven of the 0.095 L/min nozzles installed in the 7N, the flow was quite peaked with its

maximum off slightly from the centerline of the nozzle (Figure 8-133). Note that Spraying Systems, Inc.

asserted that the spray was uniform over a diameter of 0.75 m if the assembly was more than 0.9 m above 

the collection plane. Thus, the assembly did not operate as anticipated. It was unclear whether this

pattern was characteristic of all 7N assemblies or whether it was influenced by the particular chamb

which it was installed. When the 0.2 m diameter m

electrode contributed significantly to the water collected on either side of the main peak at ± 10 cm from 

the centerline. While these drops did have a major effect on the water collection, they did not appear to 

play any significant role relative to fire extinguishment because the water they carried did not interact

with the fire and did not splash the fuel surface. 

no electrode, 0.095 L/min center nozzle

electrode, 0.095 L/min center nozzle

electrode, 0.063 L/min center nozzle

no electrode, 0.095 L/min center nozzle

electrode, 0.095 L/min center nozzle

electrode, 0.063 L/min center nozzle

Figure 8-133. Effect of Center Nozzle Size on 7N Nozzles Water Flux. 

Plugging the center nozzle produced a fairly uniform water flow distribution. In this case, the spray

patterns of the 6 remaining nozzles appeared to project further out radially so that the walls of the 

chamber became wet at a greater height above floor than had been experienced before. It thus appeared 

that the central nozzle played an important role in determining the spray patterns of the other six nozzles. 
902 Fluid Dispensing and Dispersion 

Possibly, air entrained by the central nozzle affected the airflow environment that the other nozzle sprays

experienced. Unfortunately, the water flux without the center nozzle flow was too small to extinguish the 

fire being studied. For this reason, a compromise was reached to replace the center nozzle with a

0.063 L/min capacity nozzle and to retain the six other 0.095 L/min orifices in the 7N assembly. This did 

not produce any dramatic change in the water distribution (Figure 8-133), but it did allow a pressure to be 

set to provide extinguishment times in a good range for the measurements. 

The water flux distribution of the 7N nozzles with the 0.063 L/min center nozzle is shown in Figure 8-134

when the electrode is uncharged and at -5kV. Charging reduces the center water flux and increases that at

the edges of the spray pattern slightly. These changes are much less than those observed by Gottuk et

al.92 for a single nozzle. In the case of the 7N nozzles, charging of the outer portion of the spray makes

those droplets spread out in all directions, and the outer spray droplet charge density restricts the spread of

the inner charged spray. 

Experiments to determine the effect of mist droplet charging on the extinguishment of a heptane pool fire 

were performed in the test chamber. The water spray system consisted of an electrically grounded 7N

nozzle containing a central 0.063 L/min nozzle and six circumferential 0.095 L/min nozzles located 1.1 m 

above the pool fire. A 0.2 m diameter electron emission charging electrode, described previously, was 

placed coaxially around the water spray system centerline and located about 10 cm below the bottom of

the nozzle assembly.

-5 kV, 0.063 L/min center nozzle

0 kV, 0.063 L/min center nozzle

-5 kV, 0.063 L/min center nozzle

0 kV, 0.063 L/min center nozzle

Figure 8-134. Effect of Electrical Charging on Water Flux Distribution of the 7N Nozzles 

with the 0.063 L/min Center Nozzle. 

Heptane was poured into a lly grounded tin pan until

e fuel level was 0.8 cm from the open end. The fuel was ignited and the fire was allowed to burn for

3 min in order to develop a steady state structure. A water flow at pressures between 687 kPa and 

1031 kPa was supplied to the 7N nozzles immediately following the initial heating period. Measurements 

10 cm diameter, 2.8 cm tall seamless and electrica

th
Improved Transport of Water to Fires 903

of extinguishment time were made separately with and without dc electric field charging of the mist. 

Water flow measurements were made both with and without dc electric field mist charging by replacing 

the fuel pan with a water pan of the same size as the fuel pan and the nine pans used previously for water

distribution measurements. 

Since some previous tests had found large effects with low voltage charging, the tests began with voltages 

on the order of -1 kV and -2 kV at 1031 kPa. Measurements were then continued at -5 kV at this pressure

as well as at pressures of 687 kPa and 859 kPa. 

changing airflow patterns in the chamber or deposits 

found in the nozzle, in spite of the use of a 2 μm filter in the water line. 

xtinguishment time is plotted in Figure 8-135 as a function f water flux with and without electric 

charging. Because the voltage level at 1031 kPa did not produce a clear trend for values between -1 kV

er, electric charging did produce major improvements over 

the performance of uncharged droplets in the lower water flux range. As the flux was lowered without 

charging, a flow was reached where significantly greater times were needed to extinguish the fires. The 

curves can be interpreted as showing a decreased extinguishment time at constant water flux or reduced

water flux to achieve a given extinguishment time. This behavior would be beneficial in cases where the 

water supply for fire extinguishment is limited. It was speculated that the extinguishment time with

charging would also increase if the water flux were lowered much more. Data were not taken for smaller

fluxes with this nozzle because the water collection values were inconsistent for pressures below 687 kPa. 

Frequent water flow measurements were needed since it was clear that the water flux at a fixed nozzle 

pressure varied. These variations develop due to

E o

and -5 kV, all of the charged mist data is plotted together for these experiments. The voltage was 

maintained at -5 kV for all of the other droplet charging cases. At the higher flows, it does not appear that

there is an effect of electric charging. Howev

Water Flux (L/min-m2)

E Time (s)

xtinguishment

Water Flux (L/min-m2)

E Time (s)

Figure 8-135. Initial Data on Effect of Electrical Chargin for a 10 cm Diameter Hep

Pool Fire. 

xtinguishment

g tane
904 Fluid Dispensing and Dispersion 

The nozzle and electrode were removed, cleaned, and then reinstalled after the above initial set of data 

had been analyzed to obtain a second set of data. In the new tests, the water collected in the single pan

directly below the nozzle increased due to charging, which was different from other observations 

including the previously mentioned water flux distribution measurements recorded in Figure 8-134. 

These new data points were added to those previously displayed in Figure 8-135, and the total data set is

extinguishment times that are significantly higher, by a factor of nearly 2, than 

the charged case in the low water flux regime where extinguishment times are larger. The standard

ment due to charging, even though the validity of the additional

data was questionable because of the higher water collection. 

presented in Figure 8-136. The trend of rapidly growing extinguishment time with decreasing water flux 

is not as apparent for the uncharged case as in Figure 8-135. For this reason, linear fits to both the 

charged and uncharged data sets are displayed in Figure 8-136. Again, there is little difference in 

extinguishment time due to charging when that time is generally small at the higher water fluxes, but the

uncharged case still has

deviation of the uncharged data is nearly twice that of the charged results. Thus, the complete set of data

still indicates improvement in extinguish

E nguishment Time (s)

Water Flux (L/min-m2)

xti

Water Flux (L/min-m2)

E nguish

nozzle mist might not be receiving as much charging as the outer nozzle mist, it 

el pan was chosen to maintain the ratio of the spray diameter to the pan 

diameter much larger than unity. ment Time (s) xti

Figure 8-136. All Electrical Charging Data for a 10 cm Diameter Heptane Pool Fire. 

5 cm Diameter Pool Fire 

Because of difficulties in holding the 7N nozzle water flow constant in the water collection pan and the 

possibility that the center 

was decided to perform additional work with a single water mist nozzle and a smaller, 5 cm diameter, fuel

pan. More repeatable water collection rates and more effective charging of the mist were expected with

the single nozzle. The smaller fu

The lowest flow solid cone from Spraying Systems, Inc. nozzle was the TG−0.3 whose flow

characteristics are given in Table 8-23. A coverage area for the TG−0.3 nozzle was not given in the 
Improved Transport of Water to Fires 905

specifications. However, the spray visually appeared to be relatively uniform over a diameter of 0.25 m 

to 0.30 m at a distance of 0.7 m from the nozzle. Based on this observation, the ratio of the spray

diameter to pan diameter was between 5 and 6. 

screen with a 8.9 cm diameter circle cut out of its 

V.

ble 8-23. Solid Cone Nozzle Characteristics.

A new electrode for these tests consisted of a wire 

center. The cut inside edges of the screen formed the array of wires that emit electrons (Figure 8-137). 

This screen was positioned horizontally with its center point coincident with the spray nozzle centerline.

It was secured to the circular ring electrode that had been used in the positive inductive electrode system 

discussed previously (Figure 8-128). With the nozzle grounded, an easily visible spreading of the spray

pattern was observed with the application of -3 kV. This spreading was increased considerably when the

voltage was increased to the maximum value of -5 k

Ta

TG-0.3 Solid Cone Nozzle 

Pressure (kPa-g) 206 275 344 412 

Mean volume diameter (μm) 250 210 180 160

Flow rate (L/min) 0.195 0.233 N/A 0.277 

Total spray angle (degree) 51 54 N/A 59 

Figure 8-137. Schematic of Single Nozzle Electron Emission Electrode. 

eptane was poured into a 5 cm diameter, 1.6 cm tall seamless and electrically grounded tin pan until the

fuel was 0.6 cm from e study of Patterson

et al.91). The fuel was ignited, and the fire was allowed to stabilize for 1 minute. Water flow at pressures

measured as a function of the water flux collected in the 5 cm diameter pan at zero voltage and at -5kV. 

H

the open end (this is almost the same diameter as used in th

between 206 kPa and 412 kPa was supplied to the TG−0.3 nozzle immediately following the preheat 

period. Measurements of extinguishment time were made separately with and without dc electric field

charging of the mist. In most cases the extinguishment time measurements were followed by water flux 

measurements in a separate 5 cm diameter pan that was identical with the fuel pan and was placed in the 

holder that supported the fuel pan. 

The distance between the nozzle and the fuel pan was set as 0.7 m. Extinguishment time was then
906 Fluid Dispensing and Dispersion 

When the electrode was charged, there was a considerable decrease in the water flux collected in the pan 

because of mist spreading. Thus, the nozzle was operated at a higher pressure when charging was applied 

to obtain the same range of collected water flux rates that had been obtained at lower pressures without

charging. 

The results plotted in Figure 8-138 show that the expected rise in extinguishment time for the charged 

case occurred at a lower level of water flux than for the uncharged case. The solid line is a linear fit of 

the three water flux points for the charged case. A dashed line with the same slope is shifted to the right 

of the solid line to indicate the general upward trend for the uncharged case. This confirms the general

trend seen for the 10 cm diameter fuel pan fire, which also found improved extinguishment with charging. 

As it was noted for the 10 cm case, the extinguishment times were significantly shorter with charging for

the low water flux range in which the uncharged extinguishment times began to grow. 

Water Flux (L/min-m2)

E

xtinguishment Time (s)

Water Flux (L/min-m2)

E

xtinguishment Time (s)

8. Effect of Electric harging on Exting ment for a 5 cm eter

ptane Pool Fire.

D

The present results ottuk et al.

92 The

fitted curve results of Patterso 8-136, and the trend lines in

F lotted together in Fig -139. The experimen Gottuk et al.92 occu or water

fl n twice thos eated in current exper us outside of the range of 

F erson et al.91 did not er charging, and th ta show the general feature of the 

rise in extinguishment time as water flux is reduced beyond so oint and substantiat present

bservations of a rapid rise in extinguishment time for the case without charging. Note that the results of

the experiments using high water fluxes (small extinguishment time) closely follow the data of Patterson

Figure 8-13 al C uish Diam

He

iscussion of Results

are compared with other data obtained by Patterson et al.91 and G

n et al.,91 the fitted data shown in Figure

igure 8-138 are p ure 8 ts of rred f

ux rates that were more tha e tr iments and th

igure 8-139. Patt consid eir da

me p es the

o
Improved Transport of Water to Fires 907

et al.91 Although they were careful to establish uniform water flux, and they did not have additional air

motion due to ventilation, their extinguishment time data are at least as scattered as the present data. The 

apparent randomness appears to be inherent to this kind of problem, and it appears that the water flux is a

rational basis for comparing and interpreting extinguishment results when using water mists. 

E

xtinguishment Tim

e (s)

Water Flux (L/min-m2)

E

xtinguishment Tim

e (s)

Water Flux (L/min-m2)

Figure 8-139. AeroChem 5 cm and 10 cm and NMERI 5 cm Heptane Extinguishment Data. 

Hughes Associates, Inc. 10 cm tests ranged from (5 to 7) L/(min m2

). 

It was also found that charging the mist reduced the water flow directly under the single TG−0.3 nozzle to 

around 75 % of its value without charging. The data of Gottuk et al.92 show a reduction to around 85 %.

For the multiple nozzle configuration, the reduction of the water flux directly below the nozzle assembly

was much smaller, being about 95 % of the uncharged value. In addition, the increases due to charging at

large distances were also small as seen in Figure 8-134. 

Two possible reasons for the small reduction in water flux below the nozzle assembly compared to the

single nozzle case are that: (1) the repulsive forces due to charged droplets at larger diameters restrained 

e tendency of the smaller droplets to spread and (2) an insufficient amount of charge was available to 

the multiple nozzle spray, and o grossly affect its geometry. 

This is not a major concern, as ive charging electrode for the

th

in particular the central portion of the spray, t

it simply indicates the need for a more effect

7N nozzle. 

The current results confirm the conclusion of Gottuk et al.92 that charging produces a large amount of

spreading in the mist distribution for single nozzles. It is clear that charging applied to an array of single

nozzles will enable the use of greater spacing between the nozzles while achieving as uniform a spray

pattern as in the case without charging. This is of particular concern for small droplets which are hard to 

disperse transversely due to their high aerodynamic drag. The electrostatic forces help to spread them out

more evenly. 
908 Fluid Dispensing and Dispersion 

The present results clearly show that application of negative charging to water mist reduces the

extinguishment time when the water flux is at its lowest effective values. Within this range the water flux 

needed to attain a given extinguishment time is also reduced. This is true for both the 5 cm and 10 cm 

r, Q, per unit floor area needed to

extinguish a fire requires some further discussion. Q is equal to the product of the water flux, f, and the 

heptane fuel fires and two different nozzle and charging systems. For the 10 cm fire data in Figure 8-136,

the variability in extinguishment time, expressed as the standard deviation, was reduced at low values of 

water flux. 

The question of the effect of charging on the total amount of wate

extinguishment time text so that 

ext Q = f t (8−56)

and it has the dimensions of a length (or thickness). Patterson et al.91 refer to Q as the “de novo

thickness.” 

Ways in which reductions in Q can be categorized include: (1) a reduction in the flux, f, at constant 

extinguishment time, text, (2) a reduction in the extinguishment time, text, at a constant value of flux, f, and 

(3) an absolute maximum reduction of Q for some combination of text and f. The first two cases are

readily seen by comparing curves with and without charging in Figure 8-139 for either fixed f or text. 

To better understand the condition for an absolute maximum reduction in Q, note that the case of constant 

Q from Equation 8−56. corresponds to 

f

Q text = (8−57)

so that in a plot of extinguishment time vs. water flux, text → ∞ as f → 0 and text → 0 as f → ∞. Since the 

NMERI data in Figure 8-139 remains finite as f → 0, this data actually shows a trend of decreasing Q for 

small f, although the absolute minimum Q occurs for an intermediate value of f close to 1.5 L/min-m2

. 

The fitted curve of the NMERI data corresponds to increasing values of Q for large f since text levels out 

in that range. 

For the AeroChem data in the case of no charging, text appears to grow without limit in Figure 8-139 for 

both the 5 cm and 10 cm fires for finite f so that Q will become infinite as f decreases. Charging allows a

much smaller flux f of water to be used to achieve extinguishment in the same time. Here the reduction in

Q due to charging can be accomplished in a limited range of f at the same text (Figure 8-139). For the 

10 cm case, there is insufficient data to make any statement about how small a value of f can be used to 

minimize Q. 

92 argue that one can simply increase the flux f to achieve the same effect as charging. This

ay be a simple alternative in the single nozzle, well-ventilated case, but there are broader ranges of f in 

different pro significant

reductions in extinguishment time) is the wrong approach in a halon replacement program to minimize 

Gottuk et al.

m

blems over which electric charging has a beneficial effect. Increasing f (without

the weight of the fire suppressant. Therefore, work should focus on increasing the effectiveness of the 

technique so that smaller values of f will be capable of extinguishing a fire. 
Improved Transport of Water to Fires 909

Although the effects of ventilation and uniformity cannot be fully separated, a shift appears to be 

occurring in the AeroChem tests relative to the Hughes Associates, Inc. data to move the extinguishment 

time curves to lower water flux values and to reduce the magnitude of their slope. Because of this, it is 

anticipated that conditions such as those reported in Figure 8-126 for unventilated chambers and highly 

uniform water flux will yield significant reductions in extinguishment time text when charging is applied. 

In that case text would be greatly reduced for low f so that Q could be reduced both in the absolute case 

and for the same extinguishment time according to Equation 8−56. 

ment of this technique. Essentially, all those surfaces act as grounding plates. 

Background 

For the NGP, Lyon96 explored the potential use of gas hydrates as another approach to generating water 

mist and efficiently dispersing it throughout the space to be protected. The hydrate is a loosely bound 

complex of a host gas and a number of water molecules. It is only stable under high pressure. Thus, 

when released from its storage container, the ejected droplets of the complex would ideally travel some 

distance and violently break into water droplets and molecules of the host gas. These would then disperse 

rapidly from these numerous virtual sources. This is an analog to the flashing observed for halon 1301, 

HFC-125, and other low boiling point fluids. 

The hydrates can form in either of two structures. In both of these structures, the essential unit is a 

pentagonal dodecahedron of water molecules, the gas molecule occupying the space in the center of the 

dodecahedron. This structure owes its stability to the fact that each of the twenty apices is occupied by an 

oxygen atom bonded to four hydrogen atoms at close to tetrahedral angles, i.e. it maximizes hydrogen 

bonding. 

In the type I structure there are 2 smaller and 6 larger cavities for every 46 water molecules. For type II 

ere are 16 smaller cavities and 8 larger cavities for every 136 water molecules. The ty drate 

forms only

o

over a significant range. Furthe ifferent types of gas molecules 

Implications for Use 

Although there seems to be a potential benefit to electrically charged a water mist to extinguish a small 

pool fire, the locations of in-flight engine nacelle fires and the highly cluttered nature of an engine nacelle 

preclude further develop

Thus, one could expect that some fraction of the droplets will be attracted to the clutter and will pool on 

the surfaces. Furthermore, it is not clear whether a high voltage field would interfere with the aircraft 

avionics at a critical time when the pilot is undertaking emergency measures to fight the fire and perhaps 

to maintain readiness for survival. However, these limitations may not apply to other potential 

applications. 

8.7.3 A Self-Atomizing Form of Water 

th pe II hy

 with gas molecules that are too large for the cavities in the type I structure. While the number

f cavities has a definite stoichiometry, the extent to which gas molecules occupy those cavities can vary

rmore mixed hydrates with two or more d

filling the cavities can readily be formed. For the case of a mixed hydrate of a large molecule such as 

CHCl3 and a small molecule such as CO2, the large molecule occupies some of the large cavities and none 

of the small cavities while the small molecule occupies some of both. 
910 Fluid Dispensing and Dispersion 

At 0 °C, a pressure of 1.3 MPa is necessary to form the CO2 hydrate from pure water. With increasing 

temperature, the CO2 pressure needed to form the hydrate increases. At 9.9 °C, 4.39 MPa is needed and 

at greater temperatures, no hydrate can be formed by CO2 alone. Mixed hydrates containing substantial 

amounts of CO2 can, however, be formed at higher temperatures by using a second gas with a hydrate 

forming ability greater than CO . 

treme pressure can form 5 solid phases in addition to the 

familiar ice. One of these, ice III, is blue. While ice III is thermodynamically stable only at pressures in 

ct with anything warm. 

The goals of this project were to determine whether hydrates are capable of delayed self-atomization and 

that they are consequently potentially useful as replacements for halons in fire fighting. 

Experimental Procedures 

Sample Preparation 

0.5 L stainless steel sample bombs which were equipped with 0.635 cm ball valves were used to prepare 

CO2/water mixtures which were converted to hydrate. To prepare these mixtures, the sample bomb was 

weighed, distilled water was transferred into it, and it was reweighed. It was then attached to a vacuum 

line and evacuated briefly to remove air. The sample bomb valve was then closed, and the bomb was 

connected to a CO2 cylinder that was equipped with a dip leg. After liquid CO2 was added to the bomb, it 

was reweighed and placed in a refrigerator to convert the CO2/water mixture to hydrate. 

Video Camera Studies 

During tests the sample cylinders were held vertically with the valve pointed down. A lengt 35 cm 

D stainless steel tubing on the outlet of the ball valve bent to a right angle or to a U shape was attached 

t

upward. A video camera was used to record w During subsequent analysis of the videotape, 

the discharge time was measured with a stopwatch while playing the tape at slow speed. Playing speed 

2

There were no published reports as to what happens when a gas hydrate is suddenly depressurized. It is, 

however, interesting to note that water under ex

excess of 206 MPa, it can be cooled to liquid nitrogen temperature, and then be depressurized. At 

0.101 MPa and very low temperature, ice III is metastable. It can last for an extended period of time if 

kept cold, but it disintegrates into a fine powder of ordinary ice on conta

From a thermodynamic viewpoint, the decomposition of a CO2 hydrate offers two quite different cases. 

The heat of forming a CO2 hydrate from gaseous CO2 and liquid water is almost exactly the same as the 

heat for forming ice from the water. Thus, if a pure CO2 hydrate at an initial temperature below 0 °C 

were adiabatically depressurized, it would become unstable with respect to decomposition to ordinary ice 

and gaseous CO2 with very little temperature change occurring during this decomposition. This case 

would appear to be quite similar to the case of ice III in which considerable metastability was possible, 

i.e., both involve the conversion of one solid to another without the formation of a liquid phase. 

If, however, the initial temperature were greater than 0 °C, the hydrate would become unstable with 

respect to adiabatic decomposition to gaseous CO2 and a mixture of liquid water and ice, the temperature 

falling during the decomposition to 0 °C. Since the liquid water can act as a catalyst for the conversion of 

the solid hydrate to ordinary ice, the hydrate seems less likely to be metastable in this case. 

h of 0.6

O

o the outlet end of the ball valve. This allowed the discharge to be directed vertically downward or

hat occurred.
Improved Transport of Water to Fires 911

was measured by comparing stopwatch readings with time as recorded on the tape by the video camera’s 

clock. Distances were measured on the tape using a reference length. 

Candle in the Wind Experiments 

Figure 8-140 shows the experimental setup used in this series of tests. In this setup, a 2.22 cm diameter

candle was placed inside a transparent plastic tube, 61 cm long by 10.2 cm in diameter. The top of this

plastic tube was connected to a blower while the bottom was filled with vertical 10.2 cm long Pyrex

tubes, 6 mm OD and 4 mm ID. The blower was used to pull a flow of air through this tube at a rate of

3.54 L/s, i.e. at a velocity of 43.6 cm/s. The small Pyrex tubes served as flow straighteners. 

While the bulk of this airflow was vented, some of it was extracted by a sample pump and sent first

through a rotameter then to a Fuji NDIR CO2 meter, which monitored the CO2 content of the gases exiting 

the blower. For comparison experiments with halon 1211, the sample was passed through a bed of an

oxidation catalyst at 800 °C (CuO on high surface area alumina) to convert the halon to CO2. Previous 

studies have shown that this catalyst is quite efficient for oxidizing halons. 

Floor

4 cm gap

Blower

Recorder

CO2 meter

CuO catalyst

@ 800 oC

Transparent

plastic cylinder

Candle

Flow straightener

Sampling

pump

Vent

Extinguisher

discharge point

1.42 m

Floor

4 cm gap

Blower

Recorder

CO2 meter

CuO catalyst

@ 800 oC

Transparent

plastic cylinder

Candle

Flow straightener

Sampling

pump

Vent

Extinguisher

discharge point

1.42 m

Figure 8-140. Experimental Setup for Testing the Relative Effectiveness of Fire

Extinguishing Agents. 
912 Fluid Dispensing and Dispersion 

Test with an Obstructed Fire 

The experimental setup shown in Figure 8-141 was used in the extinguishment tests with an obstructed 

fire using a single burst discharge of the agent. The following procedure was used: a paper wick and 

Figure 8-141. Experimental 

Setup for Testing Agents Against 

an Obstructed Flame. 

75 cm3

 of diesel fuel were placed in the 6 cm cup. After igniting the wick, the fire was allowed to burn 

for 3 min, the ball valve was opened, and the result observed. 

Ambient Pressure Recovery of Hydrates 

To recover CO2 hydrate, a 2.54 cm OD stainless steel tube with fittings on its ends was used instead of the 

0.5 L sample bomb. Hydrate was prepared as above, but then the sample was cooled to −15 °C, 

depressurized, the fittings were undone, and the hydrate removed. To prepare and recover C3F8 hydrate, 

the same procedure was used, except that the preparation was done in a Fischer-Porter glass sample 

bomb. 

2.5 cm

10.2 cm

Sample

cylinder

2.5 cm × 2.5 cm

Aluminum plate

Unistrut

framework

Manual 0.6 cm ball valve

Air activated

0.6 cm ball valve

6 cm diameter

cup of diesel fuel 2.5 cm

10.2 cm

Sample

cylinder

2.5 cm × 2.5 cm

Aluminum plate

Unistrut

framework

Manual 0.6 cm ball valve

Air activated

0.6 cm ball valve

6 cm diameter

cup of diesel fuel
Improved Transport of Water to Fires 913

Discharge Characteristics of CO2 Hydrate 

Samples in which the ratio of CO2 to water was low enough to leave a significant portion of the water 

unconverted to hydrate had reasonably satisfactory discharge characteristics, i.e., when the ball valve was 

opened the hydrate/water mixture was discharged in a more or less continuous flow. Samples in which

000 cm3

 sample bombs pressurized with

time, 5 m tall and roughly 15 cm wide

ervable settling rate indicating that they

vior was observed with helium pressurizations at 

wever, the discharge resembled that of a 

with CO2 at ambient temperature and 

 tall and 50 cm wide. The droplets formed by 

ting that a desired fine mist was formed. 

rization of 1.51 MPa, the discharge was 

ized with helium to 1.57 MPa, but the

8-140 to determine the threshold for 

mists generated by CO2 hydrate/water

ixtures. The results in Figure 8-142 and Figure 8-143 show that these experiments gave a threshold for 

2 between 6.8 volume % and 7.1 volume % and a threshold for halon 1211 between 1.57 volume %

and ter

mixtures since under all conditions tested le to extinguish the candle flame. 

d laser beam was sent through the transparent plastic cylinder. Initially the

beam was invisible, but scattering from particles of Ca(OH) (20 μm to 40 μm size) in the plastic cylinder 

the ratio of CO2 to water was high enough to leave little or no water unconverted did not show

satisfactory discharge characteristics, i.e., when the ball valve was opened the hydrate was discharged in 

discontinuous spurts. 

Results 

Visual Observations 

A blank experiment was done with 400 mL samples of water in 1

He at 10.3 MPa. This produced a spray jet with a 0.35 s discharge 

at its peak. The droplets formed by this jet showed a readily obs

were relatively coarse. Qualitatively similar beha

6.87 MPa and 3.78 MPa. At 1.57 MPa helium pressurization, ho

common garden hose with little or no atomization. 

For a solution of 0.2 mass fraction of CaCl2 in water saturated 

5.81 MPa, the spray jet pattern was clearly different, 3 m

this jet did not show an observable settling rate, indica

For samples of CO2 hydrate/water mixture with an initial pressu

similar in length and width to that of the sample which was pressur

discharge produced a mist with no observable tendency to settle. 

Candle Flame Results 

Experiments were conducted using the setup illustrated in Figure 

extinguishing candle flames by CO2, halon 1211, and fine 

m

CO

1.74 volume %. No thresholds were determined for fine mists generated by the CO2 hydrate/wa

these mists were not ab

In another experiment, a re

2

made the beam evident. 

The Obstructed Flame Results 

Three tests were done with CO2 hydrate/water mixtures, and in all three tests the obstructed flame was not 

extinguished.
914 Fluid Dispensing and Dispersion 

Figure 8-142. Extinction of 

a Candle Flame by CO2. 

Figure 8-143. Extinction of a 

Candle Flame by Halon 1211. 

Stays lit Goes out

Cylinder cross section = 84 cm2

Updraft = 44 cm/s

Wt % CO2 in Air

Test Number

12345678

0

2

4

6

8

10

12

14

Stays lit Goes out

Cylinder cross section = 84 cm2

Updraft = 44 cm/s

Wt % CO2 in Air

Test Number

12345678

0

2

4

6

8

10

12

14

Stays lit Goes out

Cylinder cross section = 84 cm2

Updraft = 44 cm/s

Vol % halon 1211

Test Number

12345678

0.0

0.5

1.0

1.5

2.0

Stays lit Goes out

Cylinder cross section = 84 cm2

Updraft = 44 cm/s

Vol % halon 1211

Test Number

12345678

0.0

0.5

1.0

1.5

2.0
Improved Transport of Water to Fires 915

Observations on Hydrate Samples Recovered at Ambient Pressure

Samples of the CO2 hydrate looked very much like ice. When they were placed on the surface of a hot

plate (surface temperature of 260 °C), they acted much as did samples ice, i.e., they melted and boiled 

with little or no wetting of the surface. A sample of the CO2 hydrate placed on an ambient temperature

aluminum plate initially melted with bubbling but without producing mi

the explosion, some fragments of the sample remained on the alum

st, then suddenly exploded. After 

inum plate. They melted with

iscussion

y of Gas Hydrates

bject

to high shear. As that surface begins to convert to liquid water and gaseous carbon dioxide, any bubbles 

 rest, however, the situation is less clear. If the particle can store

sufficient strain energy for self-atomization, then it might do so. If the stored strain energy is not this

particle to explode into coarse fragments or make 

apping sounds as it melts. While the observations with the recovered hydrate samples are consistent 

y forming mechanisms exist when a liquid is discharged through a hole at various flow

rates. The spray regime map depends on the Ohnesorge and Weber numbers (see Faeth97). The results of

spraying presented in Faeth97 does not consider the possibility that the liquid being sprayed

may contain a dissolved gas. Given that helium is only very slightly soluble in water, it is not surprising 

bubbling but without further explosion. A sample of the C3F8 hydrate placed on an ambient temperature

aluminum plate melted without explosion or mist production but with bubbling and a continuous 

snapping sound. 

D

Metastabilit

As discussed above, gas hydrates might be effective firefighting agents if they were to undergo delayed

self-atomization, which in turn might occur if the hydrate were metastable at ambient pressure. One

might expect that metastability would or would not lead to self-atomization depending on the

circumstance. If a particle of hydrate is traveling through the air at a high velocity, its surface is su

forming will be broken into fine droplets. Thus for a hydrate particle in flight metastability seems likely

to lead to atomization. For a particle at

large, it could still be sufficient to cause the hydrate 

sn

with these expectations, the only thing they unambiguously show is that the hydrates are capable of

metastability. 

Analysis of Visual Observations 

Different spra

calculations for the experiments done with water pressurized with helium were consistent with the 

observation that samples with helium pressurizations of 10.31 MPa, 6.87 MPa, and 3.78 MPa atomized. 

Samples pressurized with helium to 1.57 MPa, which was observed not to atomize, were calculated to be

in the wind-induced range (Faeth97). 

The theory of

that the experiments with helium pressurized samples were quite consistent with this theory. The 

solubility of CO2, in water at 21 °C and 5.81 MPa is, however, 34 cm3

 STP gas per cm3 of liquid. The 

decrease in height, the increase in width and the fact that the droplets did not show observable settling are 

all consistent with the assumption that the discharge produced coarse droplets which the dissolved CO2

subsequently or concurrently atomized into fine mist.
916 Fluid Dispensing and Dispersion 

There is, however, the problem that droplets of fine mist are far more readily visible than an equal mass 

of coarse droplets. While the visual observations indicate that spray water saturated with CO2 at high 

pressure does indeed produce fine mist, they do not reveal how efficiently this happened. 

Since the discharged hydrate/water mixture occurred in the wind induced region, had a similar appearance 

to the helium pressurized discharge in this region, but still produced a mist that showed no observable 

settling, the indication of the visual observations is that after a delay the hydrate atomized itself into a fine 

mist. Here again, however, the data do not indicate how efficient the atomization was. 

 from the discharge of the hydrate so that mist from the hydrate arrived in the general 

vicinity of the flame, but without momentum from the discharge to carry it into the flame itself. Under 

t effective for extinguishing the flame. 

ns for this failure are not completely clear, two possibilities are obvious. The present 

results suggest that CO2 hydrate does undergo delayed self-atomization but they do not show the 

ether gas hydrates, especially CO2 hydrate, could undergo 

delayed self-atomization and whether this property would make them potentially useful replacements for 

• Fluid storage in a bottle determines the initial conditions for subsequent discharges into 

el to describe the physical system. 

Because of these characteristics, the code appears to be a viable tool for analysis or design of 

Fire Extinguishing Tests

In a previous research project, the ability of water saturated with CO2 at high pressure to extinguish fires 

was examined.98 While the results showed that this was indeed an effective way of extinguishing fires, 

the mechanism for extinguishing the fires was not clear. Perhaps the fine mist produced by the CO2

saturated water extinguished the flame by cooling it or perhaps the jet of CO2/mist was simply blowing 

out the flame. 

Both sets of experiments reported above were designed to avoid this ambiguity. In both cases the flame 

was protected

this condition, the mist from the hydrate was no

While the reaso

efficiency of this process. If the efficiency of mist production is poor, the hydrate will not be an effective 

extinguishing agent. Secondly, there is the question of the velocity at which the mist enters the flame. 

Droplets of mist have a diffusion coefficient that is very close to zero. For an ideal diffusion flame this 

would give them a near zero velocity of approaching the flame and for a real diffusion flame the velocity 

would be quite low. As the above analysis shown, fine mist might be ineffective in this situation. 

The goal of this research was to ascertain wh

the halons. While the data indicate the former, the latter now appears to be a remote possibility. 

Accordingly, further research along this line was not pursued. 

8.8 SUMMARY OF LESSONS LEARNED 

piping distribution systems. Fluid storage problems pertain to thermodynamic vapor-liquid 

phase equilibrium calculations, which in most cases are straightforward. 

• For multi-phase pipe flow calculations, the FSP code is capable of calculating the pressure 

history and discharge flow rates similar to the measured data. The code is able to pick up the 

qualitative behavior associated with the release of dissolved gas as the delivery system 

undergoes rapid depressurization during the discharge of the suppressant agent. The code is 

very flexible in being able to model different piping systems via user input, and it offers the 

user many options in developing an appropriate input mod
Summary of Lessons Learned 917

suppressant delivery systems. However, the code will only begin the computation if the 

initial thermodynamic state of the fluid is properly specified by the user. The uncertainties in 

the model predictions can be attributed to the constitutive relationships for interphase drag 

and wall heat transfer estimations, the inherent uncertainties in predicting the release rate of 

dissolved gas, the critical gas bubble radius, and the appropriate discharge coefficients to 

account for uncertainties in the critical flow model of the code and the geometry of the 

 possibly 

uired for 

 programs for 

ongly oscillatory flow and turbulence inside a typical nacelle, the initial 

 adverse effects of clutter on the penetration of suppressants into those 

ve been allayed. The “clutter” enhances the mixing of the suppressant into the flow. 

• In full-scale nacelle testing, almost all the predictions of “borderline” extinguishment 

ed of injection is more important than the total mass of agent deployed. Total 

rate of volumetric displacement by inflowing air plus suppressant determines the elapsed 

junction for subcooled liquid, two-phase liquid-vapor, and single-phase vapor. The user 

should plan to vary these parameters for a specific application and gain understanding of how 

this would affect the overall time of suppressant discharge. 

• Any of the fire simulation programs (VULCAN, FDS, and FPM) investigated in this effort 

can be used to help design a fire suppression system in practically any space inside an aircraft 

or ground vehicle. While their application to shipboard spaces was not investigated in this 

effort, there seems to be no conceptual impediment to such an application, except

that the allowable grid sizes might lengthen the computational periods significantly. Each of 

these software simulations incorporates a slightly different set of assumptions, so that using 

more than one of them will ameliorate unforeseen effects of the peculiar, embedded 

assumptions on any particular model. Of the three, only the FPM incorporates a threatevaluation subroutine which predicts whether or not a fire will be initiated by any of the 

weapons in its library. 

• Any of the fire simulation programs (VULCAN, FDS, and FPM) investigated in this effort 

can be used to optimize the design of qualification tests which may be req

acceptance of a fire-suppression system for an aircraft or ground vehicle. Such utility allows 

the planner of tests to focus on those cases for which these simulations show that extinction is 

marginal, thus reducing the number of tests required to ‘prove’ the system. 

• If two or more fire simulation programs agree in the outcome, the tests likely will confirm. If 

there be disagreement in the predicted outcome from different fire-simulation

the same case, then the conditions are approaching the edge of the extinguishment envelope. 

The simplified chemical analyses incorporated into these fire simulations do not account for 

nonhomogeneous mixing. 

• Because of the str

concerns about the

spaces ha

outcomes were, in fact, extinguished. In other words, the simulation programs used in this 

effort err on the ‘safe’ side. Simplified homogeneous analysis shows two critical parameters 

determine successful suppression in nacelles: 

1. Ratio of “suppressant” mass inflow rate to “suppressant plus air” mass inflow rate 

determines the maximum concentration attainable for “long” injection periods. This ratio 

should be greater than 0.41 for HFC-125. 

2. The spe

time scale to reach maximum concentrations. (For an F-18 nacelle, air flows are large, so 

that the time scale to reach maximum concentration is small (< 1 s)). Consequently, if a 

“wave”’ of sufficiently high concentration reaches all the potential zones of fire for even 

a fraction of a second, the fire will be extinguished. 
918 Fluid Dispensing and Dispersion 

• The temperatures of agent storage bottle, airflow, and nacelle surfaces all play important roles 

in agent dispersion performance at low temperature applications, especially when the 

prevailing temperature is below the normal boiling point of the agent. Care should be 

lating results from room temperature tests to evaluate agent dispersion 

performance at low temperatures. 

ation of system discharge,” in 

Gann, R.G., ed., Fire Suppression System Performance of Alternative Agents in Aircraft Engine and Dry 

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3. Walas, S.M., Phase Equilibrium in Chemical Engineering, Butterworth, Boston, 1985. 

4. Grosshandler W.L., Gann R.G., and Pitts W.M., eds., Evaluation of Alternative in-Flight Fire 

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6. Yang, J.C., Huber, M.L., Vázquez, I., Boyer, C.I., and Weber, L., “Measured and Predicted 

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7. Tuzla, K., Palmer, T., Chen, J.C., Sundaram, R.K., and Yeung, W.S., “Development of Computer 

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10. Elliott, D. G., Garrison, P. W., Klein, G. A., Moran, K. M., and Zydowicz, M. P., Nitrogenressurized Halon 1301 in Fire Extinguishing Systems, JPL Publication 84-62, Jet Propulsion Laboratory, 

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exercised when extrapo

• Neither electrically charged water mist systems nor the use of CO2 hydrates appear to be 

promising substitutes for halons. 

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