NIST Technical Note 1933
 

Intelligent Building Agents 

Laboratory: Hydronic System Design 

Dr. Amanda J. Pertzborn 

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NIST Technical Note 1933
 

Intelligent Building Agents 

Laboratory: Hydronic System Design 

Dr. Amanda J. Pertzborn 

Energy and Environment Division

Engineering Laboratory

This publication is available free of charge from: 

http://dx.doi.org/10.6028/NIST.TN.1933 

September 2016 

U.S. Department of Commerce 

Penny Pritzker, Secretary 

National Institute of Standards and Technology 

Willie May, Under Secretary of Commerce for Standards and Technology and Director 
 

 

 

 

 

 

Certain commercial entities, equipment, or materials may be identified in this 

document in order to describe an experimental procedure or concept adequately. 

Such identification is not intended to imply recommendation or endorsement by the 

National Institute of Standards and Technology, nor is it intended to imply that the 

entities, materials, or equipment are necessarily the best available for the purpose. 

National Institute of Standards and Technology Technical Note 1933 Natl. Inst. 


Stand. Technol. Tech. Note 1933, 83 pages (September 2016)
 

CODEN: NTNOEF 


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Abstract 

Achieving national goals of net zero energy buildings requires substantial reduction in the 

energy consumption of commercial building systems. In 2015, commercial buildings 

consumed 18 % of the total energy consumed in the U.S. [1]. Although significant progress 

has been made in the integration of building control systems through the development of 

standard communication protocols, such as BACnet and BACnet/IP, little progress has been 

made in making them “intelligent” about optimizing building system-level performance. 

The purpose of this project is to demonstrate the potential for distributed, intelligent software 

agents to perform this optimization and to develop a research infrastructure suitable for 

development and testing of advanced agent-based optimization techniques that can improve 

the energy and comfort performance of building systems. Towards that goal, the Intelligent 

Building Agents Laboratory (IBAL) has been constructed to act as a testbed for these 

intelligent control algorithms. This note describes the design of a portion of that facility. 

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Acknowledgements 

The wiring, instrumentation, and data rack design of the laboratory are primarily the efforts 

of Glen Glaeser. Glen has been instrumental in bringing the laboratory online. Dan Veronica 

was the main in-house designer of the laboratory and has been a key consultant regarding its 

operation. Cynthia Hudson oversaw the construction and helped us through some 

miscommunications with the contractor regarding the design. I would also like to thank 

former SURF students Nusrat Molla and Philip Hoddinott for the work they were able to 

complete during the summers of 2015 and 2016, respectively. Harrison Skye assisted with 

brainstorming parts of the LabVIEW code and was a sounding board for uncertainty 

calculations, as was James Yen. Greg Cala also consulted on the design of the LabVIEW 

code. Farhad Omar, Vance Payne, and Mark Kedzierski have all provided assistance in 

solving problems that arose during commissioning. John Wamsley, Art Ellison, and Luis 

Luyo have all assisted at various points installing instrumentation and wiring in the lab. 

Finally, I would like to thank the reviewers of this document, Steve Bushby, Ashwinkumar 

Patel, and Greg Linteris for their feedback and suggestions. 

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TABLE OF CONTENTS
 

Abstract..................................................................................................................................... i
 

Acknowledgements ................................................................................................................. ii
 

Table of Figures....................................................................................................................... v
 

Table of Tables ...................................................................................................................... vii
 

Nomenclature ....................................................................................................................... viii
 

Introduction ..................................................................................................................... 1
 

Background on Local Loop Control in the IBAL......................................................... 2
 

Description of the IBAL.................................................................................................. 6
 

3.1. Overview ..................................................................................................................... 6
 

3.2. Condensing Loop ........................................................................................................ 8
 

3.3. Primary Loop............................................................................................................. 13
 

3.4. Secondary Loop......................................................................................................... 15
 

3.5. Zone Simulators ........................................................................................................ 17
 

3.6. Chillers ...................................................................................................................... 19
 

3.7. Thermal Storage Tank ............................................................................................... 21
 

3.8. Heat Exchangers........................................................................................................ 23
 

3.9. Pumps ........................................................................................................................ 24
 

3.10. Support Equipment.................................................................................................... 26
 

3.11. Fluid Properties ......................................................................................................... 28
 

Data Collection and Operation..................................................................................... 29
 

4.1. Signals ....................................................................................................................... 29
 

4.2. Data Acquisition System Hardware .......................................................................... 30
 

4.3. Data Collection.......................................................................................................... 35
 

4.3.1. Metadata .............................................................................................................. 35
 

4.3.2. Experiment Tags.................................................................................................. 36
 

4.3.3. Time Varying Data.............................................................................................. 37
 

4.3.4. Database .............................................................................................................. 37
 

4.4. Architecture of the LabVIEW Control Program ....................................................... 37
 

Measurement Uncertainty Calculations...................................................................... 38
 

5.1. Overview ................................................................................................................... 38
 

5.2. Uncertainty of Calibration Curve Fit......................................................................... 39
 

5.2.1. Example of Calibration Uncertainty Calculation ................................................ 41
 

5.3. Flow Meter Uncertainty ............................................................................................ 45
 

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5.4. RTD Uncertainty ....................................................................................................... 47
 

5.5. Power Measurement Uncertainty .............................................................................. 47
 

5.6. Uncertainties of Derived Quantities .......................................................................... 50
 

Future Work .................................................................................................................. 52
 

References....................................................................................................................... 52
 

Appendix: Additional Calibration Data...................................................................... 54
 

8.1. Hydronic Pressure Transducer Calibration ............................................................... 54
 

8.2. Hydronic Differential Pressure Transducer Calibration............................................ 62
 

8.3. Hydronic Flow Meter Calibration ............................................................................. 64
 

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Table of Figures 

Figure 1. Example of a local control loop between a temperature and control valve.............. 3
 

Figure 10. The black tanks hold water for the thermal mass coils in the zone simulators.
 

Above the tanks are the red circulating pumps that move the water through the TMCs. The
 

Figure 13. The two process chillers in the IBAL. Chiller 1 is on the left and Chiller 2 is on
 

Figure 19. The PG reservoir is the white tank with yellow liquid and the expansion tank is
 

Figure 23. The Cat5e cables are placed in cable trays that run throughout the IBAL and then
 

Figure 24. In one style, cables are wired to terminal blocks (left), which are then connected
 

Figure 25. In C2, all of the cables connect to breakout boxes that are separate from the
 

Figure 29. A technician adjusts the pressure in the deadweight tester to just balance the
 

Figure 2. Possible temperature profiles under PI control......................................................... 4
 

Figure 3. Schematic of the hydronic system as built. .............................................................. 7
 

Figure 4. Legend for the loop schematics. .............................................................................. 9
 

Figure 5. Schematic of the condensing loop. ......................................................................... 10
 

Figure 6. Illustration of the function of the bridge system..................................................... 11
 

Figure 7. Schematic of the primary loop................................................................................ 14
 

Figure 8. Schematic of the secondary loop. ........................................................................... 16
 

Figure 9. Zone Simulator 2. ................................................................................................... 17
 

flow rate is determined by manually setting a valve............................................................... 19
 

Figure 11. Chiller capacity as a function of leaving fluid temperature.................................. 20
 

Figure 12. Chiller efficiency as a function of leaving fluid temperature............................... 20
 

the right. HX2 is just visible on the far right. ......................................................................... 21
 

Figure 14. Thermal storage tank. ........................................................................................... 22
 

Figure 15. Interior of the thermal storage tank. The small tubes contain PG. ....................... 22
 

Figure 16. Left: HX3 and HX1; HX3 is the larger heat exchanger on the left. Right: HX2. 23
 

Figure 17. Pump 3. The other in-line pumps have the same appearance............................... 25
 

Figure 18. Circulating pumps for the zone simulator thermal mass coils.............................. 25
 

the red object in the front of the picture.................................................................................. 27
 

Figure 20. Chemical feeder.................................................................................................... 27
 

Figure 21. Air separator (covered by insulation) and air vent (red object at the top)............ 28
 

Figure 22. Left: Back of the two data racks. C1 and C2 are on the top shelf of the right and
 

left data racks, respectively. Right: Front of the two data racks. The cables terminate in a
 

shielded RJ45 connector that plugs into a shielded RJ45 coupler. ......................................... 31
 

connect to the data racks. ........................................................................................................ 32
 

to the DAQ cards that are installed in C1 (right). ................................................................... 32
 

chassis. The cables shown in this picture run from C2 to the breakout boxes. ...................... 33
 

Figure 26. Left: Close up of the front of the data rack. Right: Two breakout boxes are
 

mounted to a shelf................................................................................................................... 34
 

Figure 27. Left: Cat5e cables connected to the breakout box. Right: Close up of the wiring in
 

the breakout box...................................................................................................................... 34
 

Figure 28. Architecture of the LabVIEW RT program.......................................................... 38
 

weight on the piston. There is a stack of calibrated plates in the background........................ 41
 

Figure 30. Channel 19 calibration data. ................................................................................. 43
 

Figure 31. RTD uncertainty with and without the DAQ uncertainty..................................... 47
 

Figure 32. Watt transducer for the fan in AHU1. .................................................................. 48
 

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Figure 33. Current transformers for Chiller 2. There is one CT for each phase and each CT
 

has 3 wraps.............................................................................................................................. 49
 

Figure 34. Relative uncertainty of specific heat (ucp,rel) and density (uρ,rel) with respect to
 

propylene glycol concentration............................................................................................... 51
 

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Table of Tables 

Table 1. Loads for Case 1: open office space. ....................................................................... 18
 

Table 11. Uncertainties of temperature, voltage, and current measurements of NI hardware.
 

Table 14. Calibration uncertainty results for pressure transducers. n = 25 measurements, ν =
 

Table 15. Calibration uncertainty results for ultrasonic flow meters. n = 10 measurements, ν
 

Table 19. Calibration uncertainty results for pressure transducers. n = 25 measurements, ν =
 

Table 20. Calibration data for a 344.5 kPa (50 psi) differential pressure sensor (S/N
 

Table 21. Calibration data for a 172.25 kPa (25 psi) differential pressure sensor (S/N
 

Table 23. Calibration uncertainty results for ultrasonic flow meters. n = 10 measurements, ν
 

Table 2. Loads for Case 2: conference room. ........................................................................ 18
 

Table 3. Design data for the chillers. ..................................................................................... 20
 

Table 4. Specifications of HX2. ............................................................................................. 23
 

Table 5. Specifications of the WSE (HX3). ........................................................................... 24
 

Table 6. Specifications of HX1. ............................................................................................. 24
 

Table 7. Key specifications for the in-line pumps in the IBAL. ............................................ 25
 

Table 8. Specifications of DAQ cards.................................................................................... 30
 

Table 9. List of the metadata collected for each signal.......................................................... 36
 

Table 10. List of experiment tags written to file. ................................................................... 36
 

................................................................................................................................................. 39
 

Table 12. Calibration data for Channel 19 hydronic pressure transducer.............................. 42
 

Table 13. Calibration uncertainty calculation results for Channel 19.................................... 43
 

23 degrees of freedom............................................................................................................. 44
 

= 8 degrees of freedom. .......................................................................................................... 46
 

Table 16. Power meter information for components that do not require a CT. ..................... 49
 

Table 17. Power meter information for components that do require a CT. ........................... 50
 

Table 18. Pressure transducer raw calibration data................................................................ 54
 

23 degrees of freedom............................................................................................................. 61
 

6600605). ................................................................................................................................ 62
 

6600603). ................................................................................................................................ 62
 

Table 22. Calibration uncertainty results for differential pressure transducers. .................... 63
 

= 8 degrees of freedom. .......................................................................................................... 65
 

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Nomenclature PG Propylene glycol 

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ρ Density 

Δ Difference 

mv Mass flow rate 

Qv Heat transfer 

∀v Volumetric flow rate 

cp Specific heat 

dt Time step 

t Value of the t-distribution 

for a given number of 

samples 

u Local control signal 

A Control direction: 1 – 

direct, -1 – reverse 

AHU Air handling unit 

AOM Advanced optimization 

method 

AS Air separator 

B Position feedback 

CF Chemical feeder 

CHWR Chilled water return 

CHWS Chilled water supply 

CL Condensing loop 

CWR Condenser water return 

CWRV Condenser water regulating 

valve 

CWS Condensing water supply 

DAQ Data acquisition 

DP Differential pressure 

E Control error 

EU Engineering unit 

F Flow 

GUI Graphical user interface 

HVAC Heating, ventilating, and air 

conditioning 

HX Heat exchanger 

IBAL Intelligent Building Agents 

Laboratory 

K PID gain coefficient 

O On/off 

OS Operating system 

P Pressure 

PI Proportional integral 

PID Proportional integral 

derivative 

PL Primary loop 

PV Process variable 

Q Power 

RT Real-time 

S Speed 

SCHW Site chilled water 

SCR Silicon controlled rectifier 

SHW Site hot water 

SL Secondary loop 

S/N Serial number 

SOM Simple optimization 

method 

SP Set point 

T Temperature 

TMC Thermal mass coil 

TS Thermal storage 

V Valve 

VAV Variable air volume 

WSE Water side economizer 

ZS Zone simulator 

Subscripts 

accum Accumulated 

high High level 

low Low level 

rate Rate 

P Proportional 

I Integral 

d derivative 

bias Bias 

min Minimum 

max Maximum 

Superscripts 

- Previous time step 

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Introduction 

Achieving national goals of net zero energy buildings requires substantial reduction in the 

energy consumption of commercial building systems. In 2015, commercial buildings 

consumed 18 % of the total energy consumed in the U.S. [1]. Although significant progress 

has been made in the integration of building control systems through the development of 

standard communication protocols, such as BACnet and BACnet/IP, little progress has been 

made in making them “intelligent” about optimizing building system-level performance. The 

focus of this project is to demonstrate the potential for distributed, intelligent software agents 

to perform this optimization and to develop a research infrastructure suitable for development 

and testing of advanced agent-based optimization techniques that can improve the energy and 

comfort performance of building systems. 

An intelligent agent can take many forms, but the basic concept is that it acquires information 

about the state of the system, makes an optimal or near-optimal control decision, and 

communicates that decision to another agent or to an actuator that executes the decision. The 

agent can represent a piece of heating, ventilating, and air conditioning (HVAC) equipment 

such as a chiller, and learn how that chiller operates over time in order to produce an optimal 

or near-optimal operating point given the current or forecast system conditions. An HVAC 

system would contain a number of agents that communicate in order to make choreographed 

control decisions that lead to optimal or near-optimal operation of the overall system. In this 

way the decision making process is distributed. 

Kelly and Bushby [2] completed a feasibility study to determine if intelligent agent 

technology could lead to significant savings in HVAC energy consumption. Their study was 

comprised of 17 agents: 

• 8 – VAV (variable air volume) box agents 

• 2 – AHU (air handling unit) agents 

• 2 – Chiller agents 

• 2 – Cooling tower agents 

• 1 – Agent to coordinate the actions of the other agents 

• 1 – Agent to quantify the operating cost of the system 

• 1 – Agent to control the simulation 

In order to simulate the learning that an agent would have to do in the real world to 

understand how a given piece of equipment operates, models of each HVAC component 

were developed and used to provide data to the agent under a variety of conditions. 

Regression models were developed based on the data and these models were incorporated 

into the agents in order to predict equipment performance. With the agents now capable of 

estimating the performance of their equipment, the next step was to develop a method to 

optimize system performance. 

Kelly and Bushby tested two methods, a simple optimization method (SOM) and an 

advanced optimization method (AOM). Only the SOM will be presented here because the 

AOM was more complicated and did not lead to a significant increase in savings relative to 

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SOM. In SOM, each of the HVAC agents takes turns optimizing the operation of their 

equipment. It should be noted that often the optimal operation of one piece of equipment is in 

conflict with the optimal operation of another piece of equipment. For example, the AHU 

may have optimal performance when the chiller provides it with water at 1.7 °C (35 °F), but 

the chiller may have better performance producing water at 12.8 °C (55 °F). In each time 

step, one agent determines how it would like to operate its equipment, calculates the cost of 

that operation, and communicates with the other agents to determine what the impact of that 

operation is on the other equipment in the system and the overall system cost. The agent can 

then decide if, given the overall impact on the system, it should change its set point as 

proposed. In the next time step, a different agent leads this process. 

In a simulation of a single day of operation, the cost savings over a reference case without 

optimization was 21 %. Although the authors note that these savings are dependent on the 

details of the reference case, this proof of concept study was promising enough to justify 

constructing a laboratory to test the concept using actual HVAC equipment. The Intelligent 

Building Agents Laboratory (IBAL) is the culmination of that effort. The IBAL contains an 

air system that emulates a building and a hydronic system that emulates the plant. The air 

system is located on a mezzanine and the hydronic system is located underneath the 

mezzanine. There is an AHU dedicated to conditioning outdoor air to produce repeatable test 

conditions and zone simulators to emulate building loads. All of the equipment are monitored 

and controlled from a central data acquisition (DAQ) system. This technical note will 

describe the design and construction of the hydronic system and a future technical note will 

describe the air system in detail. 

Section 2 is a high level review of some of the control concepts that are deployed in the 

IBAL, Section 3 is a description of the design of and equipment in the IBAL, Section 4 is a 

description of the data collection and operation, and Section 5 details the instrumentation and 

uncertainty of the measurements in the IBAL. Section 6 is a look towards the future 

operations of the IBAL. 

Background on Local Loop Control in the IBAL 

Control systems can be thought of as having two levels, local and supervisory. Supervisory 

control is the level that makes big picture decisions, such as which of two chillers to use to 

meet the current building load and what the set point temperature of the water from the 

chiller should be. Local control is used to control a single action based on the system 

conditions. In a typical application, for example, a valve, V, modulates to control a 

temperature, T, to a set point temperature calculated by the supervisory level. Numerous 

local control loops are used throughout the IBAL. The intelligent agent technique described 

in the introduction will be applied to the supervisory level while the local control will use 

traditional proportional-integral-derivative (PID) control. This report will not address the 

supervisory level in detail, leaving that topic to future publications, but PID control will be 

presented in some detail. 

The local control loop has four parts [3]: 

1) a measurement of the state of the system (process variable or PV), 

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2) a controller that makes a control decision based on the state of the system and the 

desired state of the system (set point or SP), 

3) an actuator that executes the control decision, and 

4) a process that is being controlled. 

Figure 1 is an example of a typical local control loop in the IBAL. A temperature sensor 

provides a measurement of the state of the system, a PID controller compares that 

measurement to the SP, provided by the supervisory level, and determines the control action 

that needs to be taken by the control valve in order to bring the process closer to the set point. 

The disturbance in the process could be a change in chiller operation or pump speed, for 

example, which will cause the temperature in the loop to change, which will require the 

control valve to respond. 

Control valve, V 

Disturbance 

+-

Set point = SP 

Control action 

Tin Temperature, T = PV 

Figure 1. Example of a local control loop between a temperature and control valve. 

In the IBAL local controllers use proportional-integral (PI) control, though derivative control 

is programmed into the software and can be added if necessary. For proportional control, the 

error between PV and SP is calculated and the control action is determined by multiplying 

the error by the proportional gain, hence the control action is proportional to the error. The 

problem with using proportional control by itself is that the error can reach a steady non-zero 

value, so although the system is stable, it is stable at the wrong set point. When this is the 

case, integral control, in which the integrated or accumulated error is multiplied by the 

integral gain, is added to proportional control in order to move the system closer to the set 

point. If the error is currently at a steady state, the proportional term is constant, but if it has 

been changing over time then the integral term will nudge the control action towards the set 

point. Derivative control is added to provide stability. The error rate is multiplied by the 

derivative gain; the derivative term anticipates the change in the system. Derivative gain has 

the significant disadvantage of being very sensitive to noise in the system [4]. In most 

temperature control applications derivative gain is not used. 

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The proportional, integral, and derivative gains are free parameters that must be determined 

for each system. The process of determining these values is called tuning. Although in some 

cases the values can be theoretically estimated, in most cases there are too many variables in 

the real system to capture in a model and the only way to set these values is to tune the 

system in operation. Tuning can be more of an art than a science, but one approach is to start 

by setting the integral and derivative gains to zero and the proportional gain to a large 

number, such as 100. This will likely cause the system to be unstable and oscillate around the 

set point. The proportional gain is decreased until the system no longer oscillates. At this 

point, however, the PV is usually offset from the SP, so the integral gain is slowly increased 

until the offset is removed. If the integral gain is too large, oscillations can again occur. 

Figure 2 shows some temperature profiles that can be encountered during tuning. The 

horizontal line indicates the set point temperature. Oscillation is generally an indicator that 

the proportional gain is too high – the system is too responsive to the error. The figure shows 

two cases of overshoot, one that overshoots the SP, oscillates around the SP a couple of 

times, and slowly settles to the SP and one that overshoots the SP and then slowly settles to 

the SP. Both of these situations indicate that proportional gain is too high, but not so high 

that the system will never stabilize. The fourth profile shows the temperature increase to the 

SP without over or undershooting. Of all the profiles in this figure, this is the “best” case 

because it reaches the SP in the least time. However, depending on the situation, it may take 

too long for even this case to reach SP. In such a situation it may be better to increase the 

gain to overshoot the SP, but then stabilize to the SP more quickly after the overshoot. 

Time 

PV 

Oscillation 

Overshoot 

No over- or under-shoot 

SP 

Figure 2. Possible temperature profiles under PI control. 

The details of the implementation of PID in the IBAL are shown in Eqs. ( 1 ) through ( 5 ). 

Eq. ( 1 ) is the error calculation, where E is the error, SPhigh is the largest value of the SP and 

SPlow is the lowest value. The various loops throughout the IBAL have SPs and PVs of 

different magnitudes, so by normalizing the error by the range of SP values, the magnitude of 

the gains will be similar even though the loops are very different. 

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PV − -P 

E = ( 1 ) -Phigh − -P1aw 

The accumulated error, Eaccum, is defined in Eq. ( 2 ), where dt is the control time step (10 s ; typical) and Eaccum is the accumulated error at the start of the time step. The error rate, Erate, 

is defined in Eq. ( 3 ), where E − E; is the difference between the error of the current time 

step and the error of the previous time step. 

; Eaccum = E + Eaccum ( 2 ) 

E − E;

E a = ( 3 ) 

The control signal, uraw, is calculated as shown in Eq. ( 4 ), where Kp, KI, and Kd are the 

proportional, integral, and derivative gains, respectively. A is used to indicate if the control 

loop is direct (+1) or reverse acting (-1). Direct acting means that in order to increase 

temperature, the control action increases; reverse acting means that in order to increase 

temperature, the control action decreases. For example, looking back at Figure 1, if Tin < T, 

then in order to increase T, V needs to close, so the loop is reverse acting (A = -1). If, on the 

other hand Tin > T, V needs to open to increase T and the loop is direct acting (A = 1). The 

IBAL contains both direct and indirect control loops. ubias is a bias control term that is used to 

provide coarse control on the system while the rest of the equation provides fine control – the 

bias term quickly brings the system near the SP and the PI terms refine the control action to 

bring the system to SP. In practice the bias term can be different for different operating 

conditions. 

Eq. ( 5 ) is used to scale the raw signal to the engineering units required by the actuator. For 

example, the valves modulate from 2 to 10 V, but the control action from Eq. ( 4 ) outputs a 

value from umin = 0 to umax = 1. The control action has to be scaled to instead take a value 

between EUhigh (10 V, for example) and EUlow (2 V, for example). This scaled value is the 

one that is written out by the DAQ system. 

aw = ia − E + Eaccum + E a ( 4 ) 

E high − E 1aw = aw − ma + E high ( 5 ) 

ma − mi 

The PI loops in the IBAL are continually being refined. As more tests are run additional 

complexity, such as adding feedforward control to anticipate the change in the control action 

based on something occurring elsewhere in the system, may have to be added to the 

calculation in order to bring the system under tighter control. 

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Description of the IBAL 

The intent of the IBAL is to emulate a small office building in terms of the magnitude of 

building loads and the type of HVAC equipment that would typically be present. Since the 

primary purpose of the facility is to test the performance of different control algorithms, the 

equipment selection was designed to provide as many control options as possible. For 

example, rather than meeting all of the cooling load via a single chiller, the IBAL includes 

two chillers with different capacities, a water side economizer, an air side economizer, and 

thermal storage in the form of an ice tank. The control algorithm will have to determine 

which equipment or combination of equipment to use under the given the conditions. This 

section will describe the mechanical design of the hydronic system of the IBAL in detail and 

will touch on components of the air system as needed. The air system will be described in 

more detail in a future technical note. 

3.1. Overview 

The IBAL contains the following equipment: 

• Air system 

o 4 – Zone simulators (see Section 3.5) 

o 4 – Variable air volume terminals 

o 2 – Air handling units 

o 2 – Exhaust fans 

o 1 – Outdoor air simulation unit 

• Hydronic system 

o 2 – Chillers (see Section 3.6) 

o 1 – Thermal storage tank (see Section 3.7) 

o 3 – Heat exchangers (see Section 3.8) 

This technical note will focus on the hydronic system (aka chilled water plant), but there is a 

section about the zone simulators because the hydronic system ultimately is required to meet 

the loads generated in the zone simulators. In the IBAL, the hydronic system is on the lower 

level and the air system is on a mezzanine above the hydronic system. The entire laboratory 

is controlled from a central DAQ system. 

Figure 3 shows the system as it was built. The hydronic system contains three main loops, the 

condensing loop (CL), the primary loop (PL), and the secondary loop (SL). Each loop is 

described in more detail in the following sections. 

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HX 1 

HX2 

Site Hot Water 

Condensing Loop 

Chiller1 Chiller2 

Thermal 

Storage 

Primary Loop S

Site Chilled 

Water 

V4 

V3 

V5 

V6 V7 V1 

V9 

V8 

V10 

V

Pump2 Pump1 

Pump5 

Pump3 

Pump4 

Figure 3. Schematic of the hydronic system as built. 

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3.2. Condensing Loop 

The CL provides a heat sink to the chillers. In a real commercial building, this loop would 

include a cooling tower, but in the case of the IBAL the heat sink is chilled water produced 

by the NIST plant facility (SCHW). The CL in the IBAL includes the SCHW, a three way 

mixing control valve (V3), a pump (Pump 4), the condenser for Chiller 2 and Chiller 1, and a 

heat exchanger (HX3) that serves as the water side economizer (WSE). The CL is shown in 

Figure 5; the legend for this schematic and the other loop schematics is in Figure 4. The 

figure shows the channel numbers associated with measurements at different locations (e.g., 

C356AO is a control signal for a valve and is identified by channel number 356AO). 

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V – valve

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Three-way mixing valve with actuator 

Two-way valve with actuator 

Symbols 

Pump 

Manual two-way valve 

Prefix Signal 

Identifier 

B – position 

feedback 

C – control 

DP – differential 

pressure 

F – flow 

O – on/off 

P – pressure 

Q – power 

S – speed 

T – temperature 

Abbreviations 

AS – Air separator 

CF – Chemical feeder 

CHWR – Chilled water return 

CHWS – Chilled water supply 

CWS – Condenser water supply 

CWR – Condenser water return 

HX – Heat exchanger 

SCHW – Site chilled water 

SHW – Site hot water 

TS – Thermal storage 

WSE – Water side economizer 

Figure 4. Legend for the loop schematics. 

Suffix Signal Identifier 

AO – analog output: in some cases, 

both analog output and input signals 

run in the same cable, so the channel 

number is the same and AO is used to 

distinguish between signals 

bw, ow, gw, brw – blue and blue white; 

orange and orange white; green and 

green white; brown and brown white: 

in the case of pump and fan on/off 

control, all connections are made in a 

single location so a single cable carries 

up to four distinct control signals, all 

designated with the same channel 

number, and the color of the individual 

wires is used to distinguish between the 

signals 

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V3: C215 B358 

P31 P32 

HX2 

V5: C356AO B356 

T133 

SHW 

V4: C355AO B355 

T132 

T131 

SCHW 

V6: C408 B377 

F196 

T157 

V7: C409 B378 

T158 

F194 

CWR 

CWS 

Chiller 1 

T154 

Chiller 2 

Pump 4: Q57 S448 O396bw 

T136 

F214 

Bridge 

Q53 C443 O444 

Q52 C441 O442 

Figure 5. Schematic of the condensing loop. 

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At the far left of the CL is a bridge system that serves two purposes: 1) control temperature 

T136 and 2) hydraulically separate the SCHW loop from the lab CL. This system is shown in 

more detail in Figure 6. In Case 1, V3 is 50 % open, so there is partial flow through the 

bypass and through the common pipe. T136, which is the condenser water supply (CWS) 

temperature, TCWS, is calculated as shown in Eq. ( 6 ). In Case 2, V3 is 0 % open, so all of the 

SCHW goes through the bypass and T136 is equal to the condenser water return (CWR) 

temperature, TCWR. In Case 3, V3 is 100 % open, so no SCHW flows through the bypass and 

T136 is again calculated from Eq. ( 6 ). In this case, the flow through the common pipe, mv , 

is simply mv − mv . If mv mv , mv 0, and if mv = mv , mv = 0. The 

position of V3 is set to achieve the desired T136 via an automated control loop. 

mv + mv 136 = 

mv ( 6 ) 

SCHW CW 

m m 

T136 

m 

m m 

Common Pipe Bypass V3 

Figure 6. Illustration of the function of the bridge system. 

HX2 (Figure 5) is a plate heat exchanger between the site hot water (SHW) and the CL. It is 

not currently being used, but it has two possible purposes. First, it can be used to set a 

predetermined loop temperature at T136 prior to activating the chillers; second, it can be 

used to apply an additional load to the CL if the load from the chillers or WSE are 

insufficient for the purposes of a test. 

When Chiller 2 is operating, control valve V6 is fully open, allowing flow through the 

chiller. When Chiller 1 is operating, control valve V7 is fully open. The chiller control 

system consists of two parts, an internal controller provided by the manufacturer and the 

IBAL external controller. The internal controller determines how the compressor operates 

and protects the chiller components from damage by modifying the operation to keep 

pressure, for example, within specified limits. The external controller determines the set 

point temperature and when the chiller should be on or off. The internal chiller control 

includes a condenser water regulating valve (CWRV) that controls the discharge pressure. If 

the heat exchange in the condenser is such that the refrigerant is being overcooled by the CL, 

the discharge pressure will drop below the set point and the water flow through the condenser 

11 
 

 

 

 

 

 

 

 

 

 

 

 

will be throttled back by the CWRV, potentially to the point of completely shutting off flow. 

This can occur if the water flow rate is too high and/or the temperature of the water is too 

cold given the magnitude of the load being met. In order to avoid excessive modulation of 

the flow through the condenser, the set point for T136 is no less than 24 °C (75 °F) and the 

speed of Pump 4 is set to produce only the necessary flow. 

When the WSE is operating, control valve V1 is open. The WSE, aka HX3, is a plate heat 

exchanger that sits between the CL and the PL. It is plumbed in parallel with the chillers, 

which means that it will likely only be used when it can meet the full building load. 

For more information about: 

• Chillers – see Section 3.6, 

• WSE – see Section 3.8, 

• Pump 4 – see Section 3.9. 

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3.3. Primary Loop 

The primary loop produces the cold fluid in order to meet the building load in the SL and is 

shown in Figure 7. In this system the fluid is a 30 % propylene glycol (PG) solution because 

the minimum temperature for making ice is approximately -6.7 °C (20 °F). Although this 

loop contains PG, it is referred to as the chilled water loop by convention. As shown in the 

figure, the “water” from the PL to the SL is referred to as the chilled water supply (CHWS) 

and the water returning to the PL is the chilled water return (CHWR). 

The PL contains Chiller 2, Chiller 1, and the WSE all in parallel, while a thermal ice storage 

tank (TS) is plumbed in series. Each chiller and the WSE have a dedicated pump. The pumps 

typically operate as single speed, but all of the pumps in the IBAL are operated from variable 

frequency drives (VFDs), so the PL can be variable speed. When not in use, the TS can be 

bypassed by closing control valve V8. AS is the air separator and is just downstream of the 

TS. CF is a chemical feeder that is plumbed between the PL and the SL. 

This portion of the system presents a number of challenges to a control system. The control 

algorithm has to determine when to use which chiller, whether to use one or both, whether to 

use the WSE, when to charge and discharge the TS, etc. 

For more information about: 

• Chillers – see Section 3.6, 

• TS – see Section 3.7, 

• WSE – see Section 3.8, 

• Pump 1, 2, and 5 – see Section 3.9, 

• AS and CF – see Section 3.10. 

13 
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Chiller 2 Chiller 1 WSE 

TS 

A

P27 

V18: C518AO B518 

Pump 1: Q54 S445 O395brw 

P20 

T122 

F193 

P19 

V20: C458 B520 

Pump 5: Q58 S449 O396gw 

P34 

T134 

F211 

P33 

T121 

T160 

T126 

V8: C456 B381 

T127 

F199 

T159 

Figure 7. Schematic of the primary loop. 

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3.4. Secondary Loop 

The secondary loop is where the hydronic system connects to the “building” through the 

cooling coils in the air handling units (AHUs) and is shown in Figure 8. The PL connects to 

the SL at another bridge like the one in the CL. This bridge serves the same purpose as that 

one; control valve V9 controls temperature T135 and there is a common pipe to allow the PL 

and SL to have different flow rates. 

The SL contains HX1 and the cooling coils for AHU2 and AHU1. The cooling coils in 

AHU2 and AHU1 each have a control valve (V13 and V12, respectively) that can operate as 

either a three-way valve or, by closing off the bypass, a two-way valve. These valves will be 

controlled from the air system in order to deliver the right flow rate of chilled water to meet 

the air set point temperature and/or dehumidification needs. HX1 connects between the SL 

and the SHW. This heat exchanger will be used to place a cooling load on the SL either 

independently of the cooling coils or in addition to the coils. 

If the cooling coils need less chilled water either because the building load is low or the 

water temperature is cold, control valves V13 and V12 will close down. This will lead to an 

increase in flow resistance, which is seen as an increase in the head that the pump must 

deliver. If the pump was constant speed, it would respond by simply moving along its pump 

curve to a higher head – lower flow point, but the SL pump is variable speed, so instead it 

can respond by decreasing its speed and thereby reducing its power consumption (which is 

proportional to the cube of the speed). In order to automate this process, a control loop is 

established between the pump speed and the pressure drop in the system. 

The best location to measure the pressure drop in the SL is across the most distant significant 

load in the system [5] because the measurement will be sensitive to small changes in cooling 

coil valve position and the pump energy savings will be maximized. AHU2 is the most 

distant load in the system, but its pipes are located right next to those for AHU1, so one 

differential pressure (DP) sensor, DP493, measures the pressure drop across both AHU 

cooling coils. A separate DP sensor, DP362, was installed to measure the total pressure drop 

across the SL. This sensor can be used when the AHU cooling coils are not in use and HX1 is 

providing the entire system load. As of writing, DP362 is a 25 psi sensor and DP493 is a 

10 psi sensor, but the final sensor selection will have to be determined at a future date once 

enough data has been collected to decide the optimal DP range for each location. 

Prior to commissioning of the air system, HX1 will provide the entire load so that the 

hydronic system can be commissioned independent of the air system. When in use, control 

valve V10 is opened and control valve V11 modulates to produce the desired temperature 

T128. HX1 is designed to provide a load to the system, so a load set point, QSP, is requested 

and the temperature set point, T128SP, is calculated from that load by use of Eq. ( 7 ). 

cp [kJ/kg-K] is the specific heat of the PG, ρ [kg/m3] is the density, ∀v [m3/s] is the flow rate 

in the SL, and T135 is the temperature of the PG into the SL. QSP is, therefore, the total 

“building load.” 

Cp∀p

1285p = + T135 Q5p ( 7 ) 

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HX1 AHU1 

V10: C379AO B379 

T130 

CHWS 

SHW 

V11: C380AO B380 

T129 

CHWR 

F208 

F207 

CF 

T128 

DP362 DP493 

T124 

F197 

V12: C412 B383 

T125 

F198 

To PL 

Figure 8. Schematic of the secondary loop. 

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3.5. Zone Simulators 

Building HVAC systems are designed based on the expected building loads. The IBAL does 

not include an actual building or rooms due to space constraints, but zone simulators (ZSs) 

were designed to provide a load to be met by the HVAC system. There are four ZSs, each 

containing an electric heating element, a steam spray humidifier, a cooling coil, and a 

thermal mass coil. The electric heating element provides the sensible cooling load, the steam 

spray humidifier supplies the latent cooling load, the cooling coil provides a heating load, 

and the thermal mass coil (TMC) provides a source of thermal mass. Note that the focus of 

the IBAL is to study control systems to meet cooling loads with the underlying belief that the 

developed methodologies can be adapted to heating loads, so the cooling coil is not currently 

used. 

The four ZSs are stacked one above the other at one end of the mezzanine; Figure 9 shows 

one ZS. Beginning at the far left and moving right are an electric heater, a steam spray 

humidifier, an access door, a cooling coil, and a TMC (the copper pipe runs from the TMC to 

a water tank). The zone temperature and humidity are measured at the outlet of the ZS. 

Electric Heater 

Steam Humidifier 

Access Door 

Cooling Coil 

TMC 

Steam Valve Cooling Coil Valve 

Figure 9. Zone Simulator 2. 

Each ZS represents a 65 m2 (700 ft2) room in an office building and the equipment within the 

ZS was sized to provide the loads defined by each of two cases: (1) open office space and (2) 

conference room. The design engineer based the magnitude of the loads on the tables in the 

ASHRAE Handbook Fundamentals [6]. For Case 1, there are 6 occupants, each performing 

office work. The room has a 32.5 m2 (350 ft2) exterior wall with 7 m2 (75 ft2) of glass that 

faces southwest and the magnitude of the heat gain through the envelope is based on 

conditions in Maryland. A summary of the loads for this zone is provided in Table 1. 

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Table 1. Loads for Case 1: open office space. 

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Source Type of Load Load Total Load 

Person Sensible heat 72 W (245 BTU/hr) 430 W (1470 BTU/hr) 

Latent heat load 60 W (205 BTU/hr) 360.5 W (1230 BTU/hr) 

Equipment Workstation 175 W (597 BTU/hr) 1050 W (3583 BTU/hr) 

Lighting Lighting 11.8 W/m2 (1.1 W/ft2) 770 W (2627 BTU/hr) 

Envelope Heat gain 2344 W (8000 BTU/hr) 2344 W (8000 BTU/hr) 

Total 4955 W (16,910 BTU/hr) 

For Case 2 (see Table 2) there are 18 people performing office work in the conference room. 

There is one projector and one workstation and the envelope is the same as in Case 1. 

Table 2. Loads for Case 2: conference room. 

Source Type of Load Load Total Load 

Person Sensible heat 72 W (245 BTU/hr) 1292 W (4410 BTU/hr) 

Latent heat load 60 W (205 BTU/hr) 1081 W (3690 BTU/hr) 

Equipment Workstation + projector 500 W (1706 BTU/hr) 500 W (1706 BTU/hr) 

Lighting 11.8 W/m2 (1.1 W/ft2

) 770 W (2627 BTU/hr) 

Envelope Heat gain 2344 W (8000 BTU/hr) 2344 W (8000 BTU/hr) 

Total 5987 W (20,433 BTU/hr) 

The latent load is provided by a steam spray humidifier that is connected to the site steam 

supply. For Case 1, the design steam flow rate is 0.6 kg/hr (1.25 lbs/hr) and for Case 2 the 

design steam flow rate is 1.8 kg/hr (4 lbs/hr). 

The electric heater and steam spray humidifier were selected to meet either of these two 

scenarios as a minimum, but the ZS operation will not be limited to these scenarios. The 

electric heater is a 5 W open coil heater with a minimum air flow requirement of 187 m3/hr 

(110 SCFM). The amount of heat generated by the unit is controlled with a silicon controlled 

rectifier, or SCR. The steam spray humidifier can deliver up to 1.8 kg/hr (4 lbs/hr). 

The electric heater and steam spray humidifier will provide a means to simulate the cooling 

loads in a zone, but a real zone also has thermal mass that acts to damp out changes in the 

temperature of the zone. For example, in a real room if an additional person (additional load) 

enters the room, the room temperature does not immediately increase. If there is no 

equivalent thermal mass in the zone simulator, an increase in the heater level will lead to an 

immediate change in temperature. The TMC is designed to provide the zone simulator with a 

means to damp out temperature changes. It was sized to mimic the effect of adding an 

occupant and workstation to the zone such that the temperature of the room would rise by 

0.56 °C (1 °F) in 120 seconds. The volume of water required to achieve this effect is 

calculated as shown in Eq. ( 8 ), where Q = 72 + 175 = 247 W, t = 120 s, cp = 4.18 kJ/kg-K, 

ΔT = 0.56 K, and ρ = 998 kg/m3. In order to achieve the desired effect, a water volume of 

0.013 m3 (3.35 gallons) is required. 

Q [kW] [s] Vol me [m3] = ( 8 ) 

Cp[k] ⁄kg − K] ∆T [K] p [kg ⁄m3] 

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Rather than just placing a container of water in each ZS that will heat up over time, fluid 

circulates through the TMC so that at any given moment there is a volume of water in the 

TMC, but since it is not stagnant it has an opportunity to release heat outside of the ZS. Each 

TMC is independently supplied by a 76 L (20-gallon) water tank with a dedicated circulating 

pump. The flow rate of the water through the coil will be adjusted in order to achieve the 

desired effect. Figure 10 shows the water tanks and circulating pumps that supply the TMC. 

Figure 10. The black tanks hold water for the thermal mass coils in the 

zone simulators. Above the tanks are the red circulating pumps that 

move the water through the TMCs. The flow rate is determined by 

manually setting a valve. 

The four zone simulators together can generate a sensible load of 20 kW (5.7 ton) and a 

latent load of approximately 4.3 kW (1.2 ton), for a total load of 24 kW (6.9 ton). 

3.6. Chillers 

The chillers are AC Series water-cooled process chillers from Precise Cooling Solutions and 

use digital scroll compressors from Copeland. The Chiller 2 compressor is ZP120KCE-TFD250 and has a nominal cooling capacity of 10.25 tons and the Chiller 1 compressor is 

ZP90KCE-TFD-250 and has a nominal cooling capacity of 7.5 tons. Table 3 contains design 

data for the chillers. Note that when the chillers are used to charge the TS, the capacity is derated because the temperature they are required to deliver is so low. 

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Table 3. Design data for the chillers. 

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Chiller 1 Chiller 2 

Refrigerant R-410A 

Nominal capacity [kW] (ton) 26.4 (7.5) 36 (10.25) 

De-rated capacity during TS charging [kW] (ton) 16.2 (4.6) 22 (6.2) 

Condenser water flow [m3/hr] (gpm) 5 (22) 6.8 (30) 

Condenser supply temperature [°C] (°F) 29.4 (85) 

Leaving fluid temperature range [°C] (°F) -6.7 to 26.7 (20 to 80) 

Chiller flow [m3/hr] (gpm) 4 (18) 5 (22) 

Figure 11 shows the manufacturer data for nominal capacity as a function of leaving fluid 

temperature, assuming that the condenser supply temperature is 29.4 °C (85 °F). Figure 12 

shows the corresponding EER for each chiller. 

Figure 11. Chiller capacity as a function of leaving fluid temperature. 

Figure 12. Chiller efficiency as a function of leaving fluid temperature. 

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The chillers have remote start/stop and remote temperature reset, so they can be activated and 

the temperature set point can be changed from the control program on the DAQ. The 

operation of the chiller itself is controlled internally and is described in detail in the users’ 

manual [7]. The chiller has two controls that impact the rest of the system. The condenser 

water regulating valve (CWRV) was discussed earlier. If the CL temperature and flow rate 

are not appropriately adjusted, there will be excessive oscillation of the CWRV, which will 

lead to oscillation in the flow rate through the condenser and the return temperature from the 

condenser, which makes it more difficult to control the supply temperature to the condenser 

(T136). By keeping the flow rate in the CL well matched to the chiller and maintaining T136 

above 24 °C (75 °F), the oscillations are less likely to occur. 

The second control is the hot gas bypass, which is affected by the CWRV; if the CWRV is 

fluctuating the hot gas bypass typically does as well. Under conditions of partial loading, the 

hot gas bypass will open so that the load on the compressor remains relatively constant. This 

prevents excessive cycling of the compressor [7]. The intent is to operate the CL so that 

CWRV and hot gas bypass are of limited use and therefore the system is more stable overall. 

Figure 13. The two process chillers in the IBAL. Chiller 1 is on the left 

and Chiller 2 is on the right. HX2 is just visible on the far right. 

3.7. Thermal Storage Tank 

The thermal storage tank (TS) is Calmac part number 1082A. It is specified to discharge 

274 kWh (78 ton-hours) of ice over an eight-hour period with an inlet temperature of 10 °C 

(50 °F). The tank contains 3105 L of water (820 gallons) and is located outside of the lab as 

shown in Figure 14. Figure 15 shows the interior of the TS. The heat exchanger is spiral 

wound polyethylene tube and is filled with 295 L (78 gallons) of PG. The tank was designed 

to be fully charged during a single 8-hour off-peak period with a flow rate of 9.5 m3/hr 

(42 gpm) and charge temperature of -3.9 °C (25 °F). However, in operation the flow through 

the TS is provided only by the chiller pumps and/or WSE pump and these pumps do not 

provide that level of flow. In order to maximize the amount of ice that can be made during a 

given charging period, the charging temperature has been dropped to -6.7 °C (20 °F). The 

time required to fully freeze the tank as well as the amount of the tank frozen in 8 hours will 

be determined during future experiments. 

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Figure 14. Thermal storage tank. 

Figure 15. Interior of the thermal storage tank. The small tubes contain PG. 

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3.8. Heat Exchangers 

There are three brazed plate heat exchangers in the IBAL. The plate material is 316L 

stainless steel and the brazing material is copper. All three heat exchangers are shown in 

Figure 16. 

Figure 16. Left: HX3 and HX1; HX3 is the larger heat exchanger on the left. Right: HX2. 

HX2 acts as an additional load on the CL and can be used to pre-heat the temperature in the 

CL before the rest of the system runs. HX2 has 50 plates and one side of the heat exchanger 

is hot water while the other side is CL water. Some key specifications are provided in Table 

4. 

Table 4. Specifications of HX2. 

Hot Water Water 

# of Passes * channels 1*24 1*25 

Internal Volume [L] (ft3) 2.5 (0.08758) 2.58 (0.09123) 

Flow [m3/hr] (gpm) 5.1 (22.5) 6.8 (30) 

Inlet Temperature [°C] (°F) 82.2 (180) 7.2 (45) 

Outlet Temperature [°C] (°F) 71.1 (160) 15.3 (59.59) 

LMTD [°C] (°F) 65.38 (117.68) 

Overall Heat Transfer Coefficient, Clean/Dirty [kW/m2-K] 

(BTU/hr-ft2

-F) 

3.60 (1142.26) 

Overall Heat Transfer Coefficient, Service [kW/m2-K] 

(BTU/hr-ft2

-F) 

0.22 (68.70) 

Effective Surface Area [m2] (ft2) 2.52 (27.17) 

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The WSE is HX3, which has 70 plates. One side of the heat exchanger is PG and the other 

side is CL water. Some key specifications are provided in Table 5. 

Table 5. Specifications of the WSE (HX3). 

PG Water 

# of Passes * channels 1*34 1*35 

Internal Volume [L] (ft3) 9.06 (0.31997) 9.327 (0.32938) 

Flow [m3/hr] (gpm) 5.45 (24) 5.45 (24) 

Inlet Temperature [°C] (°F) 15.6 (60) 7.2 (45) 

Outlet Temperature [°C] (°F) 10 (50) 12.5 (54.54) 

LMTD [°C] (°F) 2.91 (5.23) 

Overall Heat Transfer Coefficient, Clean/Dirty [kW/m2-K] 

(BTU/hr-ft2

-F) 

0.96 (304.53) 

Overall Heat Transfer Coefficient, Service [kW/m2-K] 

(BTU/hr-ft2

-F) 

0.96 (304.26) 

Effective Surface Area [m2] (ft2) 6.72 (72.28) 

HX1 is used to simulate a building load and has 30 plates. One side of the heat exchanger is 

hot water and the other side is PG. Some key specifications are provided in Table 6. 

Table 6. Specifications of HX1. 

Hot Water PG 

# of Passes * channels 1*14 1*15 

Internal Volume [L] (ft3) 3.73 (0.13175) 4.00 (0.14116) 

Flow [m3/hr] (gpm) 4.54 (20) 9.54 (42) 

Inlet Temperature [°C] (°F) 82.2 (180) 7.2 (45) 

Outlet Temperature [°C] (°F) 71.1 (160) 12.6 (54.70) 

LMTD [°C] (°F) 66.7 (120.08) 

Overall Heat Transfer Coefficient, Clean/Dirty [kW/m2-K] 

(BTU/hr-ft2

-F) 

2.45 (776.71) 

Overall Heat Transfer Coefficient, Service [kW/m2-K] 

(BTU/hr-ft2

-F) 

0.17 (54.63) 

Effective Surface Area [m2] (ft2) 2.77 (29.76) 

3.9. Pumps 

There are nine Bell & Gossett centrifugal pumps in the IBAL. Four of the pumps are small 

circulation pumps for the zone simulator TMCs and the other five pumps are in-line process 

pumps. 

Pump 1 is the pump dedicated to Chiller 1, Pump 2 is the pump dedicated to Chiller 2, and 

Pump 5 is the pump dedicated to the WSE. All three of these pumps are plumbed in parallel 

in the PL, and therefore pump PG. Pump 3 pumps PG in the secondary loop and Pump 4 

pumps water in the CL. Figure 17 shows Pump 3 installed in the SL; the other four pumps 

have the same appearance, though they are slightly different sizes. Table 7 contains the key 

specifications for these five pumps. Although the table contains the pump speed in RPM, all 

of these pumps are powered by a variable frequency drive (VFD), which outputs power at 15 

to 60 Hz, and can therefore be operated at speeds determined by the control program. 

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Figure 17. Pump 3. The other in-line pumps have the same appearance.
 

Table 7. Key specifications for the in-line pumps in the IBAL.
 

Pump 1 Pump 2 Pump 3 Pump 4 Pump 5 

P/N 90 1-1/2A 90 1AA 90 1-1/2A 80 1-1/2x1-1/2x9-1/2 90 1-1/2A 

Flow [m3/hr] (gpm) 4.1 (18) 5.45 (24) 9.5 (42) 11.8 (52) 5.45 (24) 

Head [kPa] (ft of head) 167.4 (56) 167.4 (56) 119.6 (40) 224.2 (75) 119.6 (40) 

Motor size [kW] (hp) 1.1 (1.5) 1.1 (1.5) 1.1 (1.5) 2.2 (3) 0.75 (1) 

RPM [rpm] 1725 3450 1725 1750 1725 

Max flow [m3/hr] (gpm) 13.4 (59) 11.1 (49) 13 (57) 23.2 (102) 12 (53) 

Impeller diameter [cm] (in) 17.8 (7) 10.8 (4.25) 16.8 (6.625) 21.9 (8.625) 15.9 (6.25) 

Fluid PG PG PG Water PG 

The four circulating pumps for the TMCs in the zone simulators are shown in Figure 18. 

They are constant speed, but, as can be seen in Figure 18, the flow rate can be varied by 

partially closing one of the red handled valves. These pumps currently are operated manually 

and are not connected to the DAQ. The pumps are capable of producing 

0 - 9 m3/hr (0 - 40 gpm) at 120 - 0 kPa (40 - 0 ftH2O). The design calls for 0.45 m3/hr 

(2 gpm), which corresponds to a head pressure of approximately 105 kPa (35 ft H2O). 

Figure 18. Circulating pumps for the zone simulator thermal mass coils. 

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3.10. Support Equipment 

There are several other important pieces of supporting equipment that are not part of any 

experiment, but allow the system to operate. This section will briefly introduce the support 

equipment in the hydronic system. 

In order to add additional PG into the system or change the concentration of PG, a 189 L 

(50 gallon) reservoir is placed in the PL. When work needs to be performed on a section of 

the system that requires draining pipe, the PG can be drained directly into the reservoir and, 

when the system later needs to be refilled, PG is pulled from the bottom of the reservoir by a 

dedicated pump and pumped back into the system. 

The entire hydronic system is a closed loop, so an expansion tank is necessary to allow for 

changes in PG volume over the wide temperature range that will be used in the IBAL. The 

lowest temperatures will occur when the TS is being charged, -6.7 °C (20 °F), and the highest 

temperatures will occur in the SL at high loads. In theory, the SL temperature could reach the 

temperature of the site hot water, 82.2 °C (180 °F), due to the connection via HX1, though it 

is unlikely that this will be an intentional operating point. Based on estimates of the length of 

pipe in the IBAL, there is approximately 757 to 946 L (200 to 250 gallons) of PG in the 

system. In a worst case scenario where the temperature does range from -6.7 °C to 82.2 °C 

and the system volume is 946 L, the volume of PG would change by 45 L (12 gallons). The 

expansion tank has a volume of 200 L (53 gallons), so it is more than capable of 

compensating for the volume change. The system pressure can be set by adding compressed 

air to the expansion tank. Figure 19 shows both the PG reservoir and the expansion tank. The 

current system pressure is approximately 193 kPa (28 psi). 

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Figure 19. The PG reservoir is the white tank with yellow liquid and 

the expansion tank is the red object in the front of the picture. 

A chemical feeder is included in the PL/SL in order to allow chemical treatment to be added 

to the PG as needed to avoid corrosion. This feeder is 19 L (5 gallons) and contains a 

replaceable filter bag. Figure 20 is a picture of the chemical feeder. 

Figure 20. Chemical feeder. 

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In order to remove air from the system, an air separator and air vent, pictured in Figure 21, 

are incorporated into the PL just downstream of the TS. The air vent is the red device at the 

top. A copper pipe runs from the top of the air vent to the PG reservoir so that when the vent 

opens any PG that passes through has somewhere to go. The air separator, which is just 

below the air vent and covered with insulation, is designed with tangential inlet and outlet 

openings. This creates a vortex pattern in the flow, which allows the air to more readily 

separate from the fluid. The air is then purged from the system via the air vent. Some 

additional small air vents were added to other points in the system in order to enable more 

localized venting. 

Figure 21. Air separator (covered by insulation) and air vent (red object 

at the top). 

3.11. Fluid Properties 

The hydronic system contains water in the condensing loop and a nominally 30 % PG 

solution in the primary and secondary loops. The density, ρ, and specific heat, cp, of PG are 

required to calculate items such as mass flow rate and heat transfer. Eq. ( 9 ) and Eq. ( 10 ) 

and used for these calculations; { is the concentration of PG and T is the fluid temperature in 

K [8]. 

kg p [

m3] = 508.41109 − 182.40820 { + 965.76507

273

T

.15 

+ 280.29104 {

273

T

.15 

( 9 ) − 472.22510 (

273

T

.15 )

2 

Cp [

kg

k]

K] = 4.47642 + 0.60863 { − 0.71497

273

T

.15 − 1.93855 {273

T

.15 

+ 0.47873 (

273

T

.15 )

2 

( 10 ) 

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The freezing temperature of 30 % PG is -13.3 °C (8 °F) and the burst point is -27.5 °C 

(-18 °F). At the freezing temperature, the PG is a slush, but at the burst point the fluid will 

freeze solid and can potentially burst pipes. 

Data Collection and Operation 

Commercial HVAC equipment typically arrives from the manufacturer with controllers that 

can be linked to a central control system. The IBAL, however, is designed to study different 

control algorithms and as such does not contain any proprietary manufacturer control systems 

on the major equipment (exceptions: the AHU that conditions outdoor air and the internal 

chiller controls). Instead, the IBAL is fully controlled from a LabVIEW program on an 

embedded computer system. 

This section will describe the types of signals used in the IBAL, the data acquisition (DAQ) 

system, the database, and the architecture of the control software. 

4.1. Signals 

When completed, the IBAL will contain nearly 300 unique measurement and control signals, 

roughly split equally between the air and hydronic systems. This section will describe the 

types of signals that exist in the hydronic system. Other sections will discuss the details of 

how those signals are acquired or output. 

There are 6 general categories of signal: pressure, control valve, power, temperature, flow, 

and control. The pressure devices output a 4 – 20 mA signal that is converted to a voltage at 

the DAQ by measuring the voltage drop across a 249 Ohm resistor (note: this method is used 

for all sensors that output current and are read by a DAQ device that measures voltage). The 

reason for using a current signal is that it is less susceptible to noise from other electrical 

equipment in the IBAL. The control valves have both a control signal and a position 

feedback signal. In both cases these signals are typically voltage because most of the valves 

use voltage by default. There are a couple of instances where the control signal for the 

control valve is generated by a DAQ card that only outputs current because of the limited 

availability of analog output (AO) channels that generate voltage. In those cases, the current 

is converted to a voltage at the valve via a 500 Ohm resistor (4 mA = 2 V, 20 mA = 10 V). 

The watt transducers that are used to measure power produce 4 – 20 mA signals that are 

converted to voltage at the DAQ. The temperature measurements all use 4-wire RTDs and 

are read by a DAQ card that is designed to read RTDs. The 4-wire design is used in order to 

minimize the effect of noise on the measurement. The flow meters output current and are 

read by a current reading DAQ card, so no conversion to voltage is necessary. Finally, there 

are a multitude of control signals (other than valve control) throughout the laboratory. For 

example, each pump is operated by a VFD. The VFD is operated remotely by sending 1) a 

digital signal to a relay that turns the VFD on or off and 2) a voltage signal that sets the 

frequency between 15 and 60 Hz and thereby sets the pump speed. The control signals are a 

mixture of voltage, current, and digital. 

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4.2. Data Acquisition System Hardware 

The DAQ system uses the PXI and PXIe (PXI Express) standards for data acquisition and all 

of the hardware is from National Instruments. The system contains 2 PXI chassis: PXIe-1075 

(C1) and PXIe-1082 (C2). C1 is the controlling chassis; it contains an embedded computer, 

PXIe-8135, which fills two of the 18 slots in C1. The 8135 is a 2.3 GHz quad-core Intel Core 

i7-3610QE computer that can be booted into the Windows 10 operating system (OS) or 

LabVIEW Real-Time OS (RTOS). Another slot in C1 contains a card that connects C1 to C2 

in a master-slave type arrangement. Fourteen of the remaining slots in C1 contain DAQ cards 

and there is one open slot for future expansion. C2 is smaller than C1, containing only 8 

slots. One slot contains the card that communicates with C1, and the remaining slots contain 

DAQ cards. 

Table 8 is a list of the DAQ cards that are currently installed in C1 and C2. In this table AI is 

analog input, AO is analog output, DI is digital input, DO is digital output, and DIO is digital 

input or output (the functionality of the channel is software selectable). The 4300 is only 

capable of measuring voltage (± 10 V), while the 4357 is specifically designed to measure 

RTDs and the 6238 is designed to measure and output current (0 – 20 mA). The 6363 

measures and outputs voltage (± 10 V), while half of the channels on the 6704 output voltage 

(± 10 V) and the other half output current (0 – 20 mA). The 6345 measures and outputs 

voltage (± 10 V). The digital channels output voltage in the range of 3 to 5.5 V when the 

channel is on and 0 when it is off. 

For the cards that measure voltage, the sensors can be wired as either differential or singleended. The differential configuration requires two wires for every sensor, whereas the singleended configuration only requires one wire and the ground is shared. The advantage of the 

single-ended configuration is that twice as many channels are available; in this configuration, 

the 4300 would have 16 AI channels rather than 8. However, this configuration is more 

susceptible to noise, so all of the sensors in the IBAL are wired in the differential 

configuration. 

Table 8. Specifications of DAQ cards. 

P/N Quantity Chassis AI 

channels 

AO 

channels 

DI 

channels 

DO 

channels 

DIO 

channels 

PXIe-4300 7 C1 8 

PXIe-4357 5 C1 20 

PXI-6238 2 C1 8 2 6 4 

PXIe-6363 4 C2 16 4 48 

PXIe-6704 2 C2 32 8 

PXIe-6345 1 C2 40 2 24 

The system to connect the sensors and equipment to the DAQ was designed and constructed 

at NIST. The signals are all carried on 24 AWG, stranded and shielded Cat5e cable with four 

twisted pairs of wire for a total of eight wires per cable. These cables also contain a shield 

wire that runs along the shield for the entire length of the cable. For the pressure, flow, and 

control valve signals, the measurement device requires power, so two of the eight wires are 

used to send power to the sensor. Two of the remaining wires are used to acquire the 

measurement. For the control valves, which have both measurement and control signals, 

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where possible a single cable is used and therefore two more wires are used for the control 

signal, resulting in the use of six of the eight wires. However, in some cases the control and 

measurement signals cannot be acquired by the same card (note that the number of AO and 

AI channels are not equal for any of the cards), so only four of the eight wires are used and a 

separate cable is required for the other two wires. 

The DAQ hardware is all contained inside of two data racks, pictured in Figure 22 and Figure 

23. The color of the Cat5e cables designates the type of signal carried by that cable. Blue is 

pressure, purple is power, red is temperature, black is flow, and orange is control. The other 

colors visible in the pictures are for signals in the air system and will not be addressed here. 

At the bottom of the data racks as seen from the front are four DC power supplies for the 

equipment that require DC power. In the left image of Figure 22, at the bottom of the data 

rack on the left is a gray box. This box contains an AC transformer that provides 24 VAC for 

the equipment that require AC power. The Cat5e cables run from the equipment to the data 

rack along cable trays as shown in Figure 23. At the data rack, the cables terminate in an 

RJ45 connector, which then plugs into a RJ45 coupler that is mounted in a patch panel on the 

front of the data rack. 

Figure 22. Left: Back of the two data racks. C1 and C2 are on the top shelf 

of the right and left data racks, respectively. Right: Front of the two data racks. 

The cables terminate in a shielded RJ45 connector that plugs into a shielded 

RJ45 coupler. 

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Figure 23. The Cat5e cables are placed in cable trays that run 

throughout the IBAL and then connect to the data racks. 

Signals are connected to the DAQ cards via two different methods. Figure 24 shows the 

primary method used on C1. Cables are connected to the terminal blocks shown on the left 

and the terminal blocks are connected to the DAQ cards that are installed in C1 shown on the 

right. All of the connections in C2 use what are called breakout boxes. As can be seen in 

Figure 25, cables connect to the cards at C2. At the other end the cables connect to the 

breakout boxes visible in Figure 27. 

Figure 24. In one style, cables are wired to terminal blocks (left), which are then connected to 

the DAQ cards that are installed in C1 (right). 

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Figure 25. In C2, all of the cables connect to breakout boxes that are 

separate from the chassis. The cables shown in this picture run from C2 

to the breakout boxes. 

Figure 26 is a close up of the front of the data rack. Underneath the top row of cables, a black 

drawer handle is visible. In the image at right, the cables have been removed from the front 

of the patch panel and the drawer has been pulled out to reveal a shelf. The breakout boxes 

are screwed onto this shelf. Inside the data rack, cables connect the breakout box to the inside 

of the RJ45 couplers. Figure 27 is a picture of the same shelf with the cables on the shelf 

exposed. At the middle left of the left figure is a set of screw terminal blocks that are 

connected to AC and DC power. This is the point at which power is connected to the wires 

that will deliver power to the sensors that need it. The picture at the right shows the wiring 

inside of the breakout box. At the middle right of this figure, the shield wires for the Cat5e 

cables are connected to a common ground. The shield wire is not connected to the sensor at 

the other end in order to avoid establishing a ground loop. 

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Handle 

Figure 26. Left: Close up of the front of the data rack. Right: Two breakout 

boxes are mounted to a shelf. 

Figure 27. Left: Cat5e cables connected to the breakout box. Right: Close up 

of the wiring in the breakout box. 

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4.3. Data Collection 

All of the measured and generated signals, as well as other experimental information, need to 

be recorded for eventual storage in a database. The DAQ system software writes five distinct 

files: metadata, experiment tags, process data, raw data, and scaled data. The metadata and 

experiment tags are written once for each test because they contain data that do not change 

during a single test. Process, raw, and scaled data files are written at a pre-determined 

interval during a test (10 minutes, for example) so that multiple files are generated. The 

experiment tags are entered into a graphical user interface (GUI) prior to running a test. At 

the start of a test, a file containing a list of all of the relevant signals that will be measured or 

generated during the test is loaded into the software; this file contains all of the metadata. 

The following sections will describe the information presented in each file and briefly 

introduce the database structure. 

4.3.1. Metadata 

Table 9 is a list of the metadata collected for every signal measured or generated. Not only 

are these values written to a file and used in the database as an identifier of the signal, but 

some of them are also used throughout the control software. The “measurement_id” is used 

as a convenient method to identify the signal and its location within the IBAL. Here are some 

examples to illustrate the concept: 

• ch1_c_out_rtd = RTD measurement at the outlet of the condenser of Chiller 1 

• ch1_f_c = Flow in the condenser of Chiller 1 

• pump1_on = Digital output that turns Pump 1 on 

• pump3_p_down = Pressure measurement downstream of Pump 3 

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Table 9. List of the metadata collected for each signal. 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

measurement_id String identifier for the signal: Example - ch1_c_out_rtd 

card Number of the DAQ card used to make the measurement or generate 

the signal: Example - 4300 

physical_channel Channel used by the LabVIEW program to read/write to the DAQ 

channel: Example - PXI1Slot2/ai0 

channel_number Channel identifier for the signal: Example - 364 

measurement_type Type of signal: Example - temperature, flow 

signal_type Type of signal in terms of NI hardware: Example - RTD, AI, AO 

subsystem Identify what subsystem of the IBAL the signal belongs to: Example ­

chiller 1, condensing loop 

instrument_m_n Manufacturer part number if relevant 

instrument_s_n Device serial number if relevant 

calibration_date Calibration date for the device if relevant 

accuracy_scaled Accuracy of the device if relevant 

unit_raw Units of the raw signal: Example - V, A 

unit_scaled Units of the scaled signal: Example - gpm, W 

range_lo_raw Lowest allowable value of the signal 

range_hi_raw Highest allowable value of the signal 

startup Startup value of the signal if relevant (e.g., to ensure a damper is open, 

set the startup position to 1) 

shutdown Shutdown value of the signal if relevant (e.g., to ensure a damper is 

closed, set the shutdown position to 0) 

scaling_coeff_a0 Used to convert from raw to scaled – this is the intercept 

scaling_coeff_a1 Used to convert from raw to scaled – this is multiplied by the raw 

value 

scaling_coeff_a2 Used to convert from raw to scaled – this is multiplied by the raw 

value squared 

4.3.2. Experiment Tags 

The experiment tags, which are listed in Table 10, have two purposes. First, they can be used 

to identify information about the test itself. For example, the title tag could be “Summer Day, 

Control Algorithm 1.” Later, when looking for a specific data set, the title could be queried 

for this phrase. Many tests will be run more than once, so more than one test may have the 

title “Summer Day, Control Algorithm 1.” This leads to the second use of the experiment 

tags, differentiation of tests. The tags such as day, month, and year, can be used to 

distinguish one test from another. If multiple tests with the same title are run on the same 

day, then the run and start_time tags can be used to filter the data to find the test data that are 

needed. These tags allow the data and metadata to be linked to a specific test. 

Table 10. List of experiment tags written to file. 

title Title of the experiment 

run Run number in the event that multiple tests are conducted on the same day 

comments Any comments that the operator would like to have stored 

year Year of the test 

month Month of the test 

day Day of the test 

start_time Time at which the test began 

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4.3.3. Time Varying Data 

The process data, raw data, and scaled data files all store time varying data. Process data is 

information about the test operation that is not a signal. Values such as set point temperatures 

and control loop parameters (see Section 2) fall under this category. Raw data is the 

measured or generated signal value and scaled data is calculated by multiplying the raw data 

by the scaling coefficients listed in Table 9. The raw and scaled data can be the same, in 

which case scaling_coeff_a0 = scaling_coeff_a2 = 0 and scaling_coeff_a1 = 1. These data 

are saved at every time step, written to file at the specified writing interval (10 minutes is 

typical), and deleted from the program after being written to file. 

4.3.4. Database 

The back-end of the database uses InfluxDB and the front end of the database uses Grafana. 

InfluxDB [9] is an open source database designed for use with time-series data. Grafana [10] 

is an open source program that can be used to query and display data from a database. In the 

future a version of the database will be available for public access. 

4.4. Architecture of the LabVIEW Control Program 

LabVIEW is a graphical programming environment that is well suited to data acquisition and 

control applications. LabVIEW Real-Time (RT) was selected for the operation of the IBAL 

because it guarantees real-time operation. An OS such as Windows is not designed to 

guarantee real-time operation in which a section of code will finish within a required time. 

Real-time is also referred to as on time every time or deterministic operation. Real-time 

control is a key concern in control systems where decisions must be made at a specified time 

[11]. The control software is written in the LabVIEW RT software on a standard desktop 

computer called the host and deployed onto the embedded computer in chassis C1, which is 

booted into the LabVIEW RTOS and is called the target. 

The software is written by creating a new project that contains two levels. The top level 

contains LabVIEW codes that run on the host computer, which uses a Windows OS, and the 

lower level contains codes that run on the target computer, which uses the RTOS. The host 

computer has a graphical user interface (GUI). A user can enter commands into the GUI that 

are then transferred to the target as well as view data that are transferred from the target to 

the host. The target computer runs the code that reads and outputs signals, makes control 

decisions, writes data to file, etc. Figure 28 shows how the host and target are linked and 

what tasks take place on each computer. Note that the target contains non-deterministic and 

deterministic while loops. Processes such as data transfer and storage do not have to occur in 

real-time, so they are non-deterministic. Reading sensors and making control decisions are 

real-time processes and are therefore deterministic. A non-deterministic task can be 

interrupted when a deterministic task needs to execute, but not vice versa. 

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Figure 28. Architecture of the LabVIEW RT program. 

Measurement Uncertainty Calculations 

This section will provide an overview of the measurement uncertainty calculations performed 

to date for the sensors in the hydronic system of the IBAL. The same methodology will be 

applied to any new instrumentation added in the future. 

5.1. Overview 

According to the Guidelines for Evaluating and Expressing the Uncertainty of NIST 

Measurement Results [12], uncertainty can be categorized as one of two types, Type A or 

Type B. Type A uncertainties can be determined from a statistical evaluation of data, such as 

calculating standard deviation from a series of independent measurements. Uncertainty 

calculated from calibration data is an example of Type A. Type B uncertainties are based on 

scientific judgement and prior data, such as manufacturer specifications. In the following 

sections, the manufacturer specifications are referenced and included in the overall 

uncertainty measurement as necessary. When there is more than one source of uncertainty, 

they are summed in quadrature as shown in Eq. ( 11 ). 

= j f

2 + 22 + ⋯ + �

2 ( 11 ) o al 

Table 11 contains the measurement uncertainties of the NI hardware in the DAQ. In the 

following sections, where these values are sufficiently large relative to the other Type A and 

B uncertainties, they are included in the total uncertainty calculation. 

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Table 11. Uncertainties of temperature, voltage, and current measurements of NI hardware. 

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NI Card AI uncertainty Units AO uncertainty Units 

4357 0.126 °C 

4300 0.002460 V 

6238 0.0000188 A 0.0000523 A 

6363 0.00166 V 0.00189 V 

6704 0.00107 V 

0.000000448 A 

6345 0.001520 V 0.00189 V 

This section will present the measurement uncertainty calculations and summaries for the 

sensors in the hydronic system of the IBAL. Full sets of calibration data are in the Appendix. 

5.2. Uncertainty of Calibration Curve Fit 

This section contains the equations used to calculate the uncertainty of the curve fit derived 

from calibration data that relates the measured current or voltage signal to the engineering 

units of the sensor. In the case of pressure transducers, voltage is converted to psi and in the 

case of flow meters current is converted to gpm. For both sensor types the relationship 

between the measured signal and engineering units is linear. During calibration, pressure or 

flow is the independent x variable, while the voltage or current is the dependent y variable. 

Eq. ( 12 ) shows the relationship between the dependent and independent variables, where the 

slope m and intercept b are found from the calibration data as shown in Eqs. ( 13 ) and ( 14 ) 

[13]. 

Y = mx + b ( 12 ) 

 y m = ( 13 ) 

b = YY − mx̅ ( 14 ) 

∑i xi

x̅= =

 

f ( 15 )

− ∑ xi ∑ Yi y = xiYi = cxi − x̅) cYi − YY) ( 16 )

2 − c∑ xi)2

 = xi = cxi − x̅)2 

( 17 ) 

The standard error of the calibration is determined from the fit by first calculating the 

residual yr between the fit Yy and the measured y as shown in Eqs. ( 18 ) and ( 19 ). 

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Yy = mx + b ( 18 ) 

Y = Y − Yy ( 19 ) 

The standard error, se, is calculated by dividing the sum of the squares of the residuals, 

SSResid, by the number of degrees of freedom, ν, and taking the square root. The expanded 

standard error, see, which is the 95% confidence interval, is calculated by multiplying the se 

by the t statistic that corresponds to the degrees of freedom. See Eqs. ( 20 ) through ( 23 ). 

This final error is the calibration uncertainty. 

Resi = Y i

2 ( 20 ) 

i=f 

v = − 2 ( 21 ) 

 Resi

se = ( 22 ) 

v 

se = ∙ se ( 23 ) 

In order to apply the calibration curve fit to experimental data, in which voltage or current is 

now the independent variable, the relationship defined by Eq. ( 12 ) has to be rewritten as 

shown in Eq. ( 24 ) to solve for the engineering units. 

Y − b

x = ( 24 ) m 

The slope and intercept that are part of the metadata for each channel, a1 and a0, respectively, 

are derived from Eq. ( 24 ) and shown in Eq. ( 25 ). In the LabVIEW program, the measured 

voltage, for example, is converted to engineering units of psi for use in calculations and 

monitoring. 

ao = − m

b

, af = 1 ( 25 ) m 

The uncertainty also has to be scaled, but prior to scaling any additional measurement 

uncertainties, such as the DAQ measurement uncertainty from Table 11 and the uncertainty 

in the calibration standard, have to be included as shown in Eq. ( 26 ). The final scaled 

uncertainty is shown in Eq. ( 27 ). 

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us = jse 2 + o

2

h ( 26 ) 

cal = us ( 27 ) m 

5.2.1. Example of Calibration Uncertainty Calculation 

Ten hydronic pressure transducers were calibrated simultaneously using a pneumatic 

deadweight tester. Calibrated mass plates are set on a piston so as to establish a known 

pressure (force/area). Nitrogen gas, which is connected to both the deadweight tester and the 

sensor under test, is added to/removed from a bladder to perfectly balance the weight, 

thereby providing a known pressure to the sensor under test. Figure 29 is a picture of a 

technician operating the deadweight tester. Note that a new, more automated calibrator has 

been acquired and will be used in future calibrations. 

Twenty-four pressures were randomly selected from a calibration range of 69 kPa to 

1034 kPa (10 psi to 150 psi); the lower value was based on the limitations of the dead weight 

tester. Calibration was also performed at a pressure of 0 kPa by opening the pressure 

transducer to atmosphere for a total of 25 pressure measurements. The order in which the 25 

pressures were measured was randomized. 

Figure 29. A technician adjusts the pressure in the deadweight tester 

to just balance the weight on the piston. There is a stack of calibrated 

plates in the background. 

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The pressure transducer returns a 4 to 20 mA signal, which is converted to a voltage at the 

DAQ by measuring the voltage drop produced by the current signal as it passes through a 

249 Ohm resistor. At each of the pressures, the DAQ acquired 12 measurements of voltage. 

The first and last data points were dropped and the mean of the remaining 10 voltages was 

used in the calculations. Table 12 shows the calibration data for Channel 19. The first column 

shows the 25 values of pressure that were selected and the order in which those pressures 

were applied and the last column shows the mean voltage for each pressure. Figure 30 shows 

a plot of the data. 

Table 12. Calibration data for Channel 19 hydronic pressure transducer. 

Pressure (kPa) Pressure (psi) Mean of 10 

measurements (V) 

xi xi yi 

627.4 91 3.40 

537.8 78 3.07 

406.8 59 2.57 

579.2 84 3.23 

137.9 20 1.53 

172.4 25 1.66 

441.3 64 2.71 

655 95 3.51 

0 0 0.99 

262 38 2.00 

682.6 99 3.64 

317.2 46 2.22 

358.5 52 2.39 

703.3 102 3.72 

289.6 42 2.12 

344.7 50 2.34 

82.74 12 1.31 

103.4 15 1.39 

510.2 74 2.96 

489.5 71 2.89 

365.4 53 2.41 

255.1 37 1.99 

689.5 100 3.66 

751.5 109 3.90 

627.4 29 1.77 

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Voltage [V] 

4 

3.5
 

3
 

2.5
 

2
 

1.5
 

1
 

0.5 

0 200 400 600 800 

Pressure [kPa] 

Figure 30. Channel 19 calibration data. 

The results of applying the uncertainty calculations are given in Table 13. For this sensor, the 

calibration uncertainty, which includes the uncertainty of the voltage measurement, is 

2.9 kPa (0.42 psi). The uncertainty of the calibration standard was neglected. Table 14 is a 

summary of the measurement uncertainty for all pressure transducers. 

Table 13. Calibration uncertainty calculation results for Channel 19. 

n 25 25 

ny 398.5 kPa 57.8 psi 

Xy 2.54 V 2.54 V 

Sxy 4412 kPa *V 639.91 psi*V 

Sxx 1.143e6 kPa2 24046 psi2 

m 0.0039 V/ kPa 0.027 V/psi 

b 0.997 V 0.997 V 

SSResid 0.00067 V2 0.00067 V2 

ν 23 23 

se 0.0054 V 0.0054 V 

t 2.069 2.069 

uus 0.011 V 0.011 V 

a0 -258.3 kPa -37.46 psi 

a1 259.1 kPa /V 37.58 psi/V 

ucal 2.9 kPa 0.42 psi 

43 
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Table 14. Calibration uncertainty results for pressure transducers. n = 25 measurements, 

ν = 23 

Channel S/N 

ny 

Xy 

Sxy 

Sxx m b SSResid se t uus 

kPa V kPa*V kPa2 V/kPa V 

V2 V V 

19 2058089.29 398.5 2.54 4412 1.143E+06 0.0039 0.997 0.00067 0.0054 2.07 0.011 

20 2058089.33 398.5 2.53 4402 1.143E+06 0.0039 0.991 0.0027 0.011 2.07 0.023 

27 2058089.32 398.5 2.54 4405 1.143E+06 0.0039 1.008 0.0012 0.0073 2.07 0.015 

28 2058089.31 398.5 2.54 4411 1.143E+06 0.0039 1.00 0.0014 0.0077 2.07 0.016 

29 2058089.25 398.5 2.53 4428 1.143E+06 0.0039 0.985 0.0010 0.0067 2.07 0.014 

30 071914D101 398.5 2.54 4402 1.143E+06 0.0039 1.004 0.00068 0.0054 2.07 0.011 

31 2058089.27 398.5 2.53 4399 1.143E+06 0.0039 0.997 0.00098 0.0065 2.07 0.014 

32 2058089.28 398.5 2.53 4404 1.143E+06 0.0039 0.995 0.00067 0.0054 2.07 0.011 

33 2058089.34 398.5 2.53 4430 1.143E+06 0.0039 0.986 0.0010 0.0066 2.07 0.014 

34 2058089.26 398.5 2.53 4405 1.143E+06 0.0039 0.998 0.00045 0.0044 2.07 0.0093 

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5.3. Flow Meter Uncertainty 

The IBAL uses two types of flow meters, 14 ultrasonic transducer (UT) meters and one 

magnetic flow meter. All of the meters were calibrated at an outside facility with water, 

although some of the meters are used to measure flow in 30 % propylene glycol. In addition, 

given the fact that temperature will differ from the calibration conditions during operation, an 

estimated uncertainty of 0.10 % is added to the calibration uncertainty in order to account for 

the difference in viscosity between the calibration and operation conditions [14]. 

The UT meters are transit time with transducers that are integral to the unit and a 

manufacturer specified accuracy of 1 % of reading for velocities greater than 0.3 m/s. The 

calibration summary for these meters is shown in Table 15. The error in the calibration 

standard (0.05 lpm) and the temperature error of 0.10 % make negligible contributions to the 

to the total error, which is dominated by the calibration curve fit error. 

The magnetic flow meter is used to measure the flow rate in the condensing loop. This meter 

was calibrated with a gravimetric standard that has an uncertainty of 0.10 %. The meter was 

brought to within the manufacturer specified accuracy of 0.30 % of reading by adjusting the 

calibration factor (coefficient Ka) in the meter to 1.9464. Incorporating the three 

uncertainties (temperature uncertainty, calibration standard uncertainty, meter uncertainty), 

the total uncertainty of this meter is 0.33 % of reading as calculated in Eq. ( 28 ). 

cal = �0.12 + 0.32 + 0.12 = 0.33 % ( 28 ) 

45 
 

Table 15. Calibration uncertainty results for ultrasonic flow meters. n = 10 measurements, 

ν = 8 

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Channel S/N 

ny 

Xy 

Sxy 

Sxx m b SSResid se t uus 

lpm mA lpm*mA lpm2 mA/lpm mA mA2 mA mA 

193 100718 55.02 5.07 104.02 5351.82 0.019 4.00 0.0024 0.017 2.306 0.044 

194 100716 51.38 5.02 85.13 4301.32 0.020 4.00 0.0020 0.016 2.306 0.041 

195 100725 94.76 5.01 172.42 17256.92 0.010 4.06 0.0218 0.052 2.306 0.12 196 100724 71.99 4.73 73.40 7368.61 0.010 4.01 0.0004 0.007 2.306 0.025 

197 100714 24.98 4.74 11.34 412.14 0.028 4.05 0.0003 0.006 2.306 0.023 

198 100713 25.00 4.70 12.21 416.88 0.029 3.96 0.0008 0.010 2.306 0.029 

199 100721 94.41 5.14 207.83 17198.41 0.012 4.00 0.0028 0.019 2.306 0.047 

200 100722 104.10 5.12 238.32 22655.11 0.011 4.03 0.0046 0.024 2.306 0.059 

207 100723 93.75 5.07 181.25 16645.96 0.011 4.05 0.0145 0.043 2.306 0.10 208 100720 54.98 5.08 103.02 5304.10 0.019 4.01 0.0024 0.017 2.306 0.044 

210 100717 52.44 5.01 90.50 4634.38 0.020 3.99 0.0022 0.016 2.306 0.042 

211 100715 47.55 4.96 67.58 3371.05 0.020 4.01 0.0027 0.018 2.306 0.046 

212 100719 43.98 4.85 51.00 2581.06 0.020 3.98 0.0048 0.024 2.306 0.059 

213 100727 71.89 4.83 85.59 7225.47 0.012 3.97 0.0016 0.014 2.306 0.038 

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5.4. RTD Uncertainty 

Temperature measurements in the IBAL hydronic system are made with four-wire 100 Ohm 

platinum RTDs (resistance temperature detector). The RTDs have class A accuracy, which is 

defined in Eq. ( 29 ), where T is the measured temperature in °C. 

RTD = c0.15 + 0.002 T) C ( 29 ) 

The RTDs are connected to National Instruments data acquisition card PXIe-4357. This card 

has a typical accuracy of 0.09 °C, however, the IBAL uses a faster data acquisition rate than 

normal, so an additional error of 0.036 °C must be added. These DAQ uncertainties, 

especially at low temperatures, are significant enough that they need to be considered in the 

evaluation of uncertainty as shown in Eq. ( 30 ). Figure 31 is a plot of the RTD uncertainty 

with and without the DAQ uncertainty as a function of temperature. 

0.35 

RTD, o al = j RTD

2 + c0.09 + 0.036)2 ( 30 ) 

0.3 

Uncertainty [°C] 0.25 

0.2 

0.15 

0 20 

Temperature [°C] 

40 60 80 

Figure 31. RTD uncertainty with and without the DAQ uncertainty. 

The RTDs are inserted at the approximate mid-point of the pipe and, given the small 

diameter of the pipes in the IBAL (5 cm or less), temperature variation through the crosssection is neglected. 

5.5. Power Measurement Uncertainty 

The power consumption of pumps, fans, electric heaters, and chillers are measured by Ohio 

Semitronics watt transducers. The AGW-006E watt transducer can measure up to 600 VAC 

at 5 A and the AGW-002E watt transducer can measure up to 300 VAC at 5 A; both 

uRTD 

uRTD,total 

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transducers have a manufacturer specified accuracy of 0.2 %. Some of the equipment draw 

greater than 5 A and therefore a current transformer (CT) is used to step the current down to 

a level that can be measured by the watt transducer. The CT’s have a manufacturer specified 

accuracy of 0.3 % and output a 4 – 20 mA signal that is converted to a voltage at the DAQ 

using a 249 Ohm resistor. Figure 32 is a picture of a watt transducer. 

Figure 32. Watt transducer for the fan in AHU1. 

Power is calculated from voltage by use of Eq. ( 31 ), where W is power in Watts, V is the 

measured signal in volts, a0 [W] is the intercept and a1 [W/V] is the slope. In Eq. ( 32 ), 

which is used to calculate the slope, WFS is the full scale power in [W] and the denominator is 

the difference between 20 and 4 mA multiplied by 249 Ohm. The intercept is calculated as 

shown in Eq. ( 33 ). 

W = ao + af V ( 31 ) 

Wp5 − 0

af = ( 32 ) c0.020 − 0.004) [A] ∗ 249[Ω] 

ao = Wp5 − afc0.020 [A]) ( 33 ) 

Table 16 contains information about the watt transducers for all of the power measurements 

that do not require a CT. All of these components are either fans or pumps. umeter is the 

uncertainty based on the manufacturer specified accuracy and utotal is the uncertainty 

accounting for the uncertainty in NI card 4300’s reading of the voltage. This uncertainty 

dominates the calculation. 

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Table 16. Power meter information for components that do not require a CT. 

Component P/N S/N WFS a0 a1 umeter utotal 

OSU Fan AGW-006E 14090243 4000 -1000 1004.016 0.2 % 0.00246 V 

AHU1 Fan AGW-006E 14090238 4000 -1000 1004.016 0.2 % 0.00246 V 

AHU2 Fan AGW-006E 14090246 4000 -1000 1004.016 0.2 % 0.00246 V 

EF1 AGW-006E 14090235 4000 -1000 1004.016 0.2 % 0.00246 V 

EF2 AGW-006E 14090236 4000 -1000 1004.016 0.2 % 0.00246 V 

P1 AGW-006E 14090248 4000 -1000 1004.016 0.2 % 0.00246 V 

P2 AGW-006E 14090245 4000 -1000 1004.016 0.2 % 0.00246 V 

P3 AGW-006E 14090237 4000 -1000 1004.016 0.2 % 0.00246 V 

P4 AGW-006E 14090244 4000 -1000 1004.016 0.2 % 0.00246 V 

P5 AGW-006E 14090242 4000 -1000 1004.016 0.2 % 0.00246 V 

WFS is 4000 W and 1000 W for the AGW-006E and AGW-002E, respectively. When CT’s 

are included WFS is scaled from these nominal values based on the number of wraps through 

the transducer. Figure 33 is a picture of the CT’s for Chiller 2. There is one CT for each 

phase and each CT has three turns (i.e., the wire carrying power is wound around the CT 

three times). Each CT has a current ratio of 100:5, so when a CT is used the nominal value of 

WFS is multiplied by a factor of 20 (100/5). This leads to new WFS of 80,000 W and 20,000 W 

for the AGW-006E and AGW-002E, respectively. The value of WFS is then divided by the 

number of wraps and this is the final value of WFS that is shown in Table 17. 

Figure 33. Current transformers for Chiller 2. There is one CT for each 

phase and each CT has 3 wraps. 

The error of the measurement takes into account the error of both the watt transducer and the 

current transformer by adding the individual errors as previously described. In the case that 

two CTs are used, the uncertainty of the CT is added in to the sum square error calculation 

twice. Even when the CT uncertainty is included, the uncertainty in the NI card reading 

dominates the calculation. 

49 
f f

f

f

f f

f f

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Table 17. Power meter information for components that do require a CT. 

Component P/N S/N Wraps WFS a0 a1 umeter utotal 

AHU 1 preheat AGW-006E 15040368 6 13333.33333 -3333.33 3346.72 0.47 % 0.00247 V 

AHU 2 preheat AGW-006E 15040369 6 13333.33333 -3333.33 3346.72 0.47 % 0.00247 V 

Chiller 1 AGW-006E 15040371 4 20000 -5000 5020.08 0.47 % 0.00247 V 

Chiller 2 AGW-006E 15040370 3 26666.66667 -6666.67 6693.44 0.47 % 0.00247 V 

VAV 1 reheat AGW-002E 15040501 13 1538.461538 -384.615 386.16 0.36 % 0.00247 V 

VAV 2 reheat AGW-002E 15040502 13 1538.461538 -384.615 386.16 0.36 % 0.00247 V 

VAV 3 reheat AGW-002E 15040500 13 1538.461538 -384.615 386.16 0.36 % 0.00247 V 

VAV 4 reheat AGW-002E 15040499 13 1538.461538 -384.615 386.16 0.36 % 0.00247 V 

Zone 1 heat AGW-006E 15040366 15 5333.333333 -1333.33 1338.688 0.47 % 0.00247 V 

Zone 2 heat AGW-006E 15040372 15 5333.333333 -1333.33 1338.688 0.47 % 0.00247 V 

Zone 3 heat AGW-006E 15040373 15 5333.333333 -1333.33 1338.688 0.47 % 0.00247 V 

Zone 4 heat AGW-006E 15040367 15 5333.333333 -1333.33 1338.688 0.47 % 0.00247 V 

5.6. Uncertainties of Derived Quantities 

The heat transfer at various points in the system will be calculated in order to 1) assess how 

well energy conservation is obeyed, thereby revealing hidden sources of uncertainty in the 

system, 2) understand how the system is operating (i.e., how much load is being met by 

different equipment), and 3) make control decisions such as when to bring a second chiller 

online. Eq. ( 34 ) shows the calculation of heat transfer, Qf, [kW], where ρ is the fluid density 

(kg/m3), ∀f is the volumetric flow rate (m3/s), cp [kJ/kg-K] is the specific heat, and ΔT [K] is 

the temperature change across the component. 

Q = p∀CpΔT ( 34 ) 

The uncertainty is determined from the Law of Propagation of Uncertainty [12], which is 

based on a Taylor series approximation of Eq. ( 34 ). The partial derivatives of the heat 

transfer rate with respect to each variable are provided in Eqs. ( 35 ) - ( 38 ). The total 

uncertainty is given in Eq. ( 39 ). 

aQ

a∀ 

= pCpΔT ( 35 ) 

aQ

aΔT = p∀Cp ( 36 ) 

aQ

ap = ∀CpΔT ( 37 ) 

aQ

aCp 

= p∀ΔT ( 38 ) 

50 
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f

f f

f f f 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ucp,rel

u

ρ

,rel

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2 2 2 2 

· = (

aQ

∀

2 + ( aQ 

2

2

T + (

aQ

�

2 + (

aQ) 2 ( 39 ) cP a∀

) aΔT) ap) aCp

The uncertainty associated with the temperature difference, Eq. ( 40 ), is 0.18°C as calculated 

in Eq. ( 41 ). 

ΔT = Tf − T2 ( 40 ) 

2 2 

( 41 ) 2T = (

aΔT

) 2

T1 + (

aΔT

) 2

T = jc1)2 2T1 + c−1)2 2T = √2 RTD = 0.18 °C aTf aT2

A similar analysis was completed for the density, Eq. ( 9 ), and specific heat, Eq. ( 10 ). That 

analysis showed that the uncertainty of the density and specific heat are dominated by the 

propylene glycol concentration, with the temperature contributing a very small amount to the 

specific heat and having almost no impact whatsoever on density. Figure 34 shows the 

relative uncertainty of specific heat, ucp,rel, and density, uρ,rel, as a function of propylene 

glycol concentration. It is unlikely that the concentration will stray far from 30 %, but in a 

worst case scenario values of ucp,rel = 1.8 % and uρ,rel = 0.5 % will be applied to the 

calculation of the uncertainty of Qf. 

1.84 

0.488 

0.49 

0.492 

0.494 

0.496 

0.498 

0.5 

u 

ρ , rel [%] 

ucp,rel 

u ,rel 1.82 

ucp,rel [%] 

1.8 

1.78 

1.76 

1.74 

1.72 

1.7 

20 25 30 35 40 

Concentration [%] 

Figure 34. Relative uncertainty of specific heat (ucp,rel) and density 

(uρ,rel) with respect to propylene glycol concentration. 

The uncertainty in volumetric flow rate was discussed in Section 5.3 and varies with each 

meter. Based on some preliminary data, the uncertainty of heat transfer is on the order of 

7 %. When the temperature change across the equipment is large, the uncertainty is 

dominated by the uncertainty of the flow meter reading, so improving the accuracy of the 

flow measurement would reduce the uncertainty of the heat transfer calculation. However, at 

low temperature differences, the temperature uncertainty dominates and although the flow 

meter uncertainty is not insignificant, improving that measurement will not have the same 

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impact. As more data are collected in the future the need to upgrade some of the sensors in 

order to reduce uncertainty will be evaluated. 

Future Work 

One of the major goals of the near term is to operate and more fully characterize the hydronic 

system by using HX1 to apply a variable building load. This will allow for the evaluation of 

the uncertainty and repeatability of system operation as well as the determination of what, if 

any, sensors need to be added or upgraded. The PI parameters and the sufficiency of the PI 

controllers to yield stable operation will be determined. System operating characteristics such 

as the time to fully charge/discharge the thermal storage, the amount of charge that can be 

achieved in an eight-hour charge period, will be established. In addition to further 

understanding the hydronic system, the air system will be commissioned, including 

integrating it into the control system. 

References 

[1]	 U.S. Energy Information Administration, "U.S. Energy Flow, 2015," 2016. [Online]. 

Available: http://www.eia.gov/totalenergy/data/monthly/pdf/flow/total_energy.pdf. 

[Accessed 29 August 2016]. 

[2]	 G. E. Kelly and S. T. Bushby, "Are Intelligent Agents the Key to Optimizing Building 

HVAC System Performance?," HVAC&R Research, vol. 18, no. 4, pp. 750-759, 2012. 

[3]	 W. Altmann and D. Macdonald, Practical Process Control for Engineers and 

Technicians, Amsterdam: Elsevier, 2005. 

[4] ASHRAE, 2013 ASHRAE Handbook Fundamentals, Atlanta: ASHRAE, 2013. 

[5]	 L. Tillack and J. B. Rishel, "Proper Control of HVAC Variable Speed Pumps," 

ASHRAE Journal, pp. 41-47, November 1998. 

[6] ASHRAE, 2009 ASHRAE Handbook Fundamentals, Atlanta: ASHRAE, 2009. 

[7] Precise Cooling Solutions, AC Series Portable Chillers, 2012. 

[8] M. Conde Engineering, "Thermophysical Properties of Brines Models," Zurich, 2011. 

[9]	 Influxdata, "Time-Series Data Storage," 2016. [Online]. Available: 

https://influxdata.com/time-series-platform/influxdb/. [Accessed 12 August 2016]. 

[10] Torkel Odegaard & Coding Instinct AB, "Grafana," 2015. [Online]. Available: 

http://grafana.org/. [Accessed 12 August 2016]. 

[11] National Instruments, LabVIEW Real-Time 1 Course Manual, Austin, TX, 2012. 

[12] B. N. Taylor and C. E. Kuyatt, "NIST Technical Note 1297: Guidlines for Evaluating 

and Expressing the Uncertainty of NIST Measurement Results," NIST, Gaithersburg, 

MD, 1994. 

[13] J. Devore and N. Farnum, Applied Statistics for Engineers and Scientists, Belmont, 

CA: Thomson Brooks/Cole, 2005. 

[14] J. Pope, Personal Communication, December 18, 2014. 

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[15] CFR Engineering Consultants, Inc., "Design and Installation of HVAC Research 

Laboratory," Gaithersburg, MD, 2013. 

[16] ASHRAE, ASHRAE Handbook Refrigeration, Atlanta: ASHRAE, 2014. 

[17] EPA, "End-Users of Electricity," 30 September 2015. [Online]. Available: 

https://www.epa.gov/energy/end-users-electricity#commercial. [Accessed 11 August 

2016]. 

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Appendix: Additional Calibration Data 

8.1. Hydronic Pressure Transducer Calibration 

The Kobold Sen 87 series pressure transducer uses an internal diaphragm and piezo-resistive 

ceramic sensing element to measure pressure. The manufacturer specifies an accuracy of 

0.5% of full scale, which is 0.5 % of 1034 kPa (150 psi) for these transducers, or 5.17 kPa 

(0.75 psi). The transducer outputs a 4 to 20 mA signal that is converted to a voltage by 

sending it across a 249 Ohm resistor at the DAQ. Channels 19-20, 27-29, and 31-34 use this 

transducer. Channel 30 uses the PX319 transducer from Omega. This transducer also outputs 

a 4 to 20 mA signal and uses an internal diaphragm, but the sensing element is a silicon strain 

gage. The manufacturer specifies an accuracy of 0.25 % full scale (2.59 kPa or 0.375 psi). 

Table 18 contains the raw data for the calibration of ten pressure transducer calibrations and 

Table 19 contains all of the calibration uncertainty calculations. 

Table 18. Pressure transducer raw calibration data. 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

627.4 91 19 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 

627.4 91 20 3.41 3.41 3.41 3.41 3.41 3.41 3.41 3.41 3.41 3.41 3.41 3.41 

627.4 91 27 3.43 3.43 3.43 3.43 3.43 3.43 3.43 3.43 3.43 3.43 3.43 3.43 

627.4 91 28 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

627.4 91 29 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

627.4 91 30 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

627.4 91 31 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

627.4 91 32 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.39 3.39 

627.4 91 33 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

627.4 91 34 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

537.8 78 19 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 20 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 27 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 28 3.08 3.08 3.08 3.08 3.08 3.08 3.08 3.08 3.08 3.08 3.08 3.08 

537.8 78 29 3.08 3.08 3.08 3.08 3.08 3.07 3.07 3.07 3.08 3.07 3.07 3.07 

537.8 78 30 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 31 3.06 3.06 3.06 3.06 3.06 3.06 3.06 3.06 3.06 3.06 3.06 3.06 

537.8 78 32 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 33 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 3.07 

537.8 78 34 3.07 3.07 3.07 3.07 3.07 3.06 3.06 3.07 3.07 3.07 3.07 3.06 

406.8 59 19 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 

406.8 59 20 2.53 2.53 2.53 2.53 2.53 2.53 2.53 2.53 2.53 2.53 2.53 2.53 

406.8 59 27 2.58 2.58 2.58 2.58 2.58 2.58 2.58 2.58 2.58 2.58 2.58 2.58 

406.8 59 28 2.57 2.57 2.58 2.58 2.58 2.58 2.57 2.57 2.57 2.58 2.58 2.57 

406.8 59 29 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 

54 
 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

406.8 59 30 2.58 2.58 2.58 2.58 2.58 2.58 2.57 2.57 2.57 2.57 2.57 2.57 

406.8 59 31 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 2.57 

406.8 59 32 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.56 2.57 2.57 2.57 2.56 

406.8 59 33 2.55 2.55 2.55 2.55 2.55 2.55 2.55 2.55 2.55 2.55 2.55 2.55 

406.8 59 34 2.56 2.56 2.57 2.57 2.56 2.57 2.57 2.57 2.57 2.57 2.57 2.57 

579.2 84 19 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 

579.2 84 20 3.21 3.21 3.21 3.21 3.21 3.21 3.21 3.21 3.21 3.21 3.21 3.21 

579.2 84 27 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 

579.2 84 28 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 

579.2 84 29 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 

579.2 84 30 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.21 3.21 3.22 3.22 

579.2 84 31 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 

579.2 84 32 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 3.23 

579.2 84 33 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 3.22 

579.2 84 34 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 3.24 

137.9 20 19 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 

137.9 20 20 1.51 1.51 1.51 1.51 1.51 1.51 1.51 1.51 1.51 1.51 1.51 1.51 

137.9 20 27 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 

137.9 20 28 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 

137.9 20 29 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 

137.9 20 30 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 

137.9 20 31 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 

137.9 20 32 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 

137.9 20 33 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.53 1.53 1.53 

137.9 20 34 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 1.53 

172.4 25 19 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 

172.4 25 20 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 

172.4 25 27 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 

172.4 25 28 1.68 1.67 1.67 1.67 1.67 1.68 1.68 1.68 1.68 1.68 1.67 1.68 

172.4 25 29 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 

172.4 25 30 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 1.67 

172.4 25 31 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 

172.4 25 32 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 

172.4 25 33 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 

172.4 25 34 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 1.66 

441.3 64 19 2.70 2.70 2.70 2.71 2.71 2.71 2.71 2.70 2.71 2.71 2.71 2.71 

441.3 64 20 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

441.3 64 27 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 

441.3 64 28 2.69 2.68 2.68 2.68 2.68 2.68 2.68 2.69 2.69 2.69 2.69 2.69 

441.3 64 29 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

55 
 

 

 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

441.3 64 30 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 2.71 

441.3 64 31 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

441.3 64 32 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

441.3 64 33 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

441.3 64 34 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 2.70 

655 95 19 3.50 3.50 3.51 3.51 3.51 3.51 3.52 3.52 3.52 3.52 3.52 3.52 

655 95 20 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 

655 95 27 3.55 3.55 3.55 3.55 3.55 3.55 3.55 3.54 3.54 3.54 3.54 3.54 

655 95 28 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 

655 95 29 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 

655 95 30 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.52 3.52 3.53 

655 95 31 3.53 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 

655 95 32 3.51 3.50 3.50 3.51 3.51 3.50 3.50 3.50 3.50 3.50 3.50 3.50 

655 95 33 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 3.53 

655 95 34 3.52 3.53 3.53 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 

0 0 19 1.00 0.99 0.99 0.99 0.99 0.99 1.00 0.99 1.00 1.00 0.99 1.00 

0 0 20 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 

0 0 27 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 

0 0 28 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 

0 0 29 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 

0 0 30 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 

0 0 31 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 

0 0 32 0.99 0.99 0.99 0.99 0.99 0.99 0.99 1.00 0.99 0.99 0.99 1.00 

0 0 33 0.98 0.98 0.98 0.98 0.98 0.98 0.98 0.98 0.98 0.98 0.98 0.98 

0 0 34 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 

262 38 19 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 

262 38 20 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 

262 38 27 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 

262 38 28 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 

262 38 29 1.98 1.98 1.99 1.99 1.99 1.99 1.99 2.00 2.00 2.00 2.00 2.00 

262 38 30 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 2.02 

262 38 31 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 

262 38 32 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 

262 38 33 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 

262 38 34 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 2.01 

682.6 99 19 3.64 3.64 3.64 3.64 3.64 3.63 3.64 3.64 3.64 3.64 3.64 3.64 

682.6 99 20 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

682.6 99 27 3.64 3.64 3.64 3.64 3.63 3.63 3.64 3.64 3.64 3.63 3.63 3.63 

682.6 99 28 3.64 3.64 3.64 3.63 3.64 3.64 3.64 3.64 3.64 3.64 3.64 3.64 

682.6 99 29 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

56 
 

 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

682.6 99 30 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

682.6 99 31 3.62 3.62 3.62 3.62 3.62 3.62 3.62 3.62 3.62 3.61 3.61 3.62 

682.6 99 32 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

682.6 99 33 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

682.6 99 34 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 3.63 

317.2 46 19 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 

317.2 46 20 2.22 2.21 2.21 2.21 2.22 2.22 2.22 2.22 2.21 2.22 2.22 2.22 

317.2 46 27 2.24 2.24 2.24 2.24 2.24 2.24 2.24 2.24 2.24 2.24 2.24 2.24 

317.2 46 28 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 

317.2 46 29 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 

317.2 46 30 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 

317.2 46 31 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 

317.2 46 32 2.21 2.21 2.21 2.21 2.21 2.21 2.21 2.21 2.21 2.21 2.21 2.21 

317.2 46 33 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 2.22 

317.2 46 34 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 2.23 

358.5 52 19 2.39 2.39 2.39 2.39 2.39 2.39 2.38 2.39 2.39 2.39 2.39 2.39 

358.5 52 20 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 

358.5 52 27 2.39 2.39 2.38 2.38 2.38 2.39 2.39 2.38 2.38 2.38 2.38 2.38 

358.5 52 28 2.38 2.38 2.38 2.38 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 

358.5 52 29 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 

358.5 52 30 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 

358.5 52 31 2.36 2.36 2.36 2.36 2.36 2.36 2.36 2.36 2.36 2.36 2.36 2.36 

358.5 52 32 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 

358.5 52 33 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 2.38 

358.5 52 34 2.37 2.37 2.37 2.37 2.37 2.37 2.37 2.37 2.37 2.37 2.37 2.37 

703.3 102 19 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 

703.3 102 20 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 

703.3 102 27 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 

703.3 102 28 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 

703.3 102 29 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 

703.3 102 30 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 

703.3 102 31 3.69 3.70 3.69 3.70 3.70 3.69 3.69 3.70 3.70 3.70 3.70 3.70 

703.3 102 32 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.70 3.71 3.71 

703.3 102 33 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 3.72 

703.3 102 34 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 3.71 

289.6 42 19 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 

289.6 42 20 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 

289.6 42 27 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 

289.6 42 28 2.12 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.12 

289.6 42 29 2.09 2.09 2.09 2.09 2.09 2.10 2.09 2.09 2.09 2.10 2.10 2.09 

57 
 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

289.6 42 30 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 

289.6 42 31 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 2.12 

289.6 42 32 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 

289.6 42 33 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 

289.6 42 34 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 2.11 

344.7 50 19 2.33 2.34 2.34 2.34 2.34 2.34 2.34 2.33 2.34 2.34 2.33 2.33 

344.7 50 20 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 

344.7 50 27 2.33 2.33 2.33 2.34 2.34 2.34 2.34 2.34 2.34 2.34 2.34 2.34 

344.7 50 28 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 

344.7 50 29 2.33 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.33 2.33 2.33 2.33 

344.7 50 30 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.34 2.34 2.33 

344.7 50 31 2.33 2.33 2.33 2.33 2.32 2.33 2.33 2.32 2.32 2.33 2.32 2.32 

344.7 50 32 2.33 2.32 2.32 2.33 2.33 2.33 2.33 2.33 2.32 2.32 2.33 2.33 

344.7 50 33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 2.33 

344.7 50 34 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 2.32 

82.74 12 19 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 

82.74 12 20 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 

82.74 12 27 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 

82.74 12 28 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 

82.74 12 29 1.31 1.31 1.30 1.30 1.30 1.30 1.30 1.31 1.30 1.30 1.30 1.30 

82.74 12 30 1.32 1.32 1.32 1.32 1.33 1.33 1.32 1.32 1.32 1.32 1.32 1.32 

82.74 12 31 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 

82.74 12 32 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 1.31 

82.74 12 33 1.30 1.30 1.30 1.30 1.30 1.30 1.30 1.30 1.30 1.30 1.30 1.30 

82.74 12 34 1.32 1.31 1.31 1.31 1.32 1.32 1.32 1.32 1.32 1.32 1.32 1.32 

103.4 15 19 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 

103.4 15 20 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 

103.4 15 27 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 

103.4 15 28 1.41 1.40 1.41 1.41 1.41 1.41 1.41 1.40 1.40 1.40 1.40 1.40 

103.4 15 29 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.39 1.38 1.38 1.38 

103.4 15 30 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 1.40 

103.4 15 31 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 

103.4 15 32 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 

103.4 15 33 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 

103.4 15 34 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 

510.2 74 19 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 

510.2 74 20 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 

510.2 74 27 2.98 2.98 2.98 2.98 2.98 2.98 2.98 2.98 2.98 2.98 2.98 2.98 

510.2 74 28 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 

510.2 74 29 2.94 2.94 2.95 2.94 2.94 2.94 2.94 2.95 2.94 2.94 2.94 2.94 

58 
 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

510.2 74 30 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 

510.2 74 31 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 

510.2 74 32 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.96 

510.2 74 33 2.96 2.96 2.96 2.96 2.96 2.96 2.96 2.97 2.96 2.96 2.96 2.96 

510.2 74 34 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 

489.5 71 19 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 

489.5 71 20 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 

489.5 71 27 2.89 2.89 2.90 2.90 2.90 2.90 2.90 2.90 2.90 2.90 2.90 2.90 

489.5 71 28 2.88 2.87 2.87 2.87 2.87 2.87 2.87 2.87 2.87 2.87 2.87 2.87 

489.5 71 29 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 

489.5 71 30 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 2.89 

489.5 71 31 2.87 2.87 2.88 2.88 2.88 2.87 2.88 2.88 2.88 2.88 2.88 2.87 

489.5 71 32 2.88 2.89 2.88 2.88 2.88 2.88 2.89 2.89 2.89 2.89 2.88 2.88 

489.5 71 33 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.89 2.89 2.89 2.88 2.88 

489.5 71 34 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 2.88 

365.4 53 19 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 

365.4 53 20 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 

365.4 53 27 2.42 2.42 2.42 2.42 2.42 2.42 2.42 2.42 2.42 2.42 2.42 2.42 

365.4 53 28 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 

365.4 53 29 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 2.39 

365.4 53 30 2.42 2.42 2.42 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 

365.4 53 31 2.41 2.41 2.40 2.40 2.40 2.40 2.40 2.40 2.41 2.41 2.40 2.40 

365.4 53 32 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 

365.4 53 33 2.39 2.39 2.39 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 2.40 

365.4 53 34 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 2.41 

255.1 37 19 1.98 1.98 1.99 1.99 1.99 1.98 1.98 1.99 1.99 1.99 1.98 1.98 

255.1 37 20 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 

255.1 37 27 1.98 1.98 1.98 1.98 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 

255.1 37 28 1.98 1.98 1.98 1.97 1.97 1.97 1.98 1.98 1.97 1.97 1.97 1.98 

255.1 37 29 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 

255.1 37 30 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 1.99 

255.1 37 31 1.97 1.97 1.97 1.97 1.97 1.97 1.97 1.97 1.97 1.97 1.97 1.97 

255.1 37 32 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 

255.1 37 33 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 

255.1 37 34 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 1.98 

689.5 100 19 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 

689.5 100 20 3.61 3.61 3.61 3.61 3.61 3.61 3.61 3.61 3.61 3.61 3.61 3.61 

689.5 100 27 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 

689.5 100 28 3.67 3.67 3.66 3.66 3.67 3.67 3.67 3.67 3.67 3.67 3.67 3.67 

689.5 100 29 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 

59 
 

 

Pressure 

(kPa) 

Pressure 

(psi) Channel Data (V) 

689.5 100 30 3.66 3.66 3.66 3.67 3.67 3.67 3.66 3.66 3.66 3.66 3.66 3.66 

689.5 100 31 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 

689.5 100 32 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 

689.5 100 33 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 3.65 

689.5 100 34 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 3.66 

751.5 109 19 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 

751.5 109 20 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 

751.5 109 27 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.87 3.87 3.87 

751.5 109 28 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 

751.5 109 29 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 

751.5 109 30 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 3.90 

751.5 109 31 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 3.88 

751.5 109 32 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 

751.5 109 33 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 

751.5 109 34 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 3.89 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

60 
 

Table 19. Calibration uncertainty results for pressure transducers. n = 25 measurements, 

ν = 23 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Channel S/N 

ny 

Xy 

Sxy 

Sxx m b SSResid se t uus 

psi V psi*V psi2 V/psi V 

V2 V V 

19 2058089.29 57.80 2.54 639.91 24046 0.027 0.997 0.00067 0.0054 2.07 0.011 

20 2058089.33 57.80 2.53 638.41 24046 0.027 0.991 0.0027 0.011 2.07 0.023 

27 2058089.32 57.80 2.54 638.93 24046 0.027 1.008 0.0012 0.0073 2.07 0.015 

28 2058089.31 57.80 2.54 639.69 24046 0.027 1.00 0.0014 0.0077 2.07 0.016 

29 2058089.25 57.80 2.53 642.16 24046 0.027 0.985 0.0010 0.0067 2.07 0.014 

30 071914D101 57.80 2.54 638.46 24046 0.027 1.004 0.00068 0.0054 2.07 0.011 

31 2058089.27 57.80 2.53 638.02 24046 0.027 0.997 0.00098 0.0065 2.07 0.014 

32 2058089.28 57.80 2.53 638.78 24046 0.027 0.995 0.00067 0.0054 2.07 0.011 

33 2058089.34 57.80 2.53 642.57 24046 0.027 0.986 0.0010 0.0066 2.07 0.014 

34 2058089.26 57.80 2.53 638.95 24046 0.027 0.998 0.00045 0.0044 2.07 0.0093 

61 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

8.2. Hydronic Differential Pressure Transducer Calibration 

Differential pressure (DP) transducers will be used at several locations in the laboratory for 

control and to provide secondary flow measurements. To date, two DP sensors have been 

calibrated, though the final use of these sensors is to be determined. The DP sensors are the 

PX2300 series from Omega. The manufacturer stated accuracy is 0.25 % of full scale. 

Table 20. Calibration data for a 344.5 kPa (50 psi) differential pressure sensor (S/N 6600605). 

Pressure 

(kPa) 

Pressure 

(psi) Data (V) 

254.93 37 3.92 3.92 3.92 3.92 3.92 3.92 3.92 3.92 3.92 3.92 3.92 3.92 

144.69 21 2.65 2.65 2.65 2.65 2.65 2.65 2.65 2.65 2.65 2.65 2.65 2.65 

323.83 47 4.71 4.71 4.71 4.71 4.71 4.71 4.71 4.71 4.71 4.71 4.71 4.71 

130.91 19 2.49 2.49 2.49 2.50 2.50 2.50 2.50 2.50 2.50 2.49 2.50 2.49 

103.35 15 2.18 2.18 2.18 2.18 2.18 2.18 2.18 2.18 2.18 2.18 2.18 2.18 

124.02 18 2.42 2.42 2.42 2.41 2.42 2.41 2.42 2.41 2.42 2.42 2.41 2.42 

234.26 34 3.68 3.68 3.68 3.68 3.68 3.68 3.68 3.68 3.68 3.68 3.68 3.68 

227.37 33 3.60 3.61 3.60 3.60 3.60 3.60 3.60 3.60 3.60 3.60 3.60 3.60 

75.79 11 1.86 1.86 1.86 1.86 1.86 1.86 1.86 1.86 1.86 1.86 1.86 1.86 

337.61 49 4.87 4.87 4.86 4.87 4.87 4.87 4.87 4.87 4.87 4.87 4.87 4.87 

206.7 30 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 

316.94 46 4.63 4.63 4.63 4.63 4.63 4.63 4.63 4.63 4.63 4.63 4.63 4.63 

172.25 25 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 2.97 

117.13 17 2.34 2.34 2.34 2.34 2.34 2.34 2.33 2.34 2.34 2.34 2.34 2.34 

48.23 7 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 

0 0 0.97 0.97 0.97 0.97 0.97 0.98 0.98 0.98 0.98 0.98 0.98 0.98 

Table 21. Calibration data for a 172.25 kPa (25 psi) differential pressure sensor (S/N 6600603). 

Pressure 

(kPa) 

Pressure 

(psi) Data (V) 

48.23 7 2.15 2.15 2.15 2.15 2.15 2.15 2.15 2.15 2.15 2.15 2.15 2.15 

62.01 9 2.47 2.47 2.47 2.47 2.47 2.47 2.47 2.47 2.47 2.47 2.47 2.47 

124.02 18 3.89 3.89 3.89 3.89 3.89 3.90 3.90 3.90 3.90 3.90 3.89 3.89 

82.68 12 2.94 2.95 2.94 2.94 2.94 2.94 2.95 2.94 2.95 2.95 2.95 2.94 

137.8 20 4.21 4.21 4.21 4.21 4.21 4.22 4.21 4.21 4.21 4.21 4.21 4.21 

117.13 17 3.73 3.73 3.74 3.74 3.74 3.74 3.74 3.74 3.74 3.74 3.74 3.74 

165.36 24 4.85 4.85 4.85 4.85 4.85 4.85 4.85 4.84 4.85 4.85 4.85 4.85 

55.12 8 2.31 2.31 2.31 2.31 2.31 2.31 2.31 2.31 2.31 2.31 2.31 2.31 

103.35 15 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 3.42 

130.91 19 4.05 4.05 4.05 4.05 4.06 4.06 4.05 4.05 4.05 4.05 4.05 4.05 

68.9 10 2.63 2.63 2.63 2.63 2.63 2.63 2.63 2.63 2.63 2.63 2.63 2.63 

110.24 16 3.58 3.58 3.58 3.58 3.58 3.58 3.58 3.58 3.58 3.58 3.58 3.58 

96.46 14 3.26 3.26 3.26 3.26 3.26 3.26 3.26 3.26 3.26 3.26 3.27 3.26 

144.69 21 4.37 4.37 4.37 4.37 4.37 4.37 4.37 4.37 4.37 4.37 4.37 4.37 

75.79 11 2.78 2.79 2.79 2.79 2.79 2.79 2.79 2.79 2.79 2.79 2.79 2.78 

172.25 25 5.01 5.01 5.01 5.00 5.01 5.00 5.00 5.00 5.00 5.01 5.01 5.01 

0 0 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.05 

62 
 

Table 22. Calibration uncertainty results for differential pressure transducer

S/N n 

ny 

Xy 

Sxy 

Sxx m b SSResid ν se t uus 

psi V psi*V psi2 V/psi V 

V2 V V 

6600605 16 25.56 3.01 255.09 3219.94 0.079 0.99 0.00023 14 0.0040 2.145 0.0090 

6600603 17 14.47 3.34 109.65 692.24 0.16 1.04 0.000030 15 0.0014 2.131 0.0039 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 63 
 

 

 

 

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

8.3. Hydronic Flow Meter Calibration 

The flow meters in the IBAL are described in more detail in Section 5.3. This section 

contains the calibration report for each flow meter. Table 23 is a summary of results in 

imperial units (see Table 15 for SI units). 

64 
 This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.TN.1933 

Table 23. Calibration uncertainty results for ultrasonic flow meters. n = 10 measurements, 

ν = 8 

Channel S/N 

ny 

Xy 

Sxy 

Sxx m b SSResid se t uus 

gpm mA gpm*mA gpm2 mA/gpm mA mA2 mA mA 

193 100718 14.54 5.07 27.48 374 0.074 4.00 0.0024 0.017 2.306 0.044 

194 100716 13.57 5.02 22.49 300 0.075 4.00 0.0020 0.016 2.306 0.041 

195 100725 25.04 5.01 45.55 1205 0.038 4.06 0.0218 0.052 2.306 0.12 

196 100724 19.02 4.73 19.39 514 0.038 4.01 0.0004 0.007 2.306 0.025 

197 100714 6.60 4.74 2.99 29 0.104 4.05 0.0003 0.006 2.306 0.023 

198 100713 6.60 4.70 3.23 29 0.111 3.96 0.0008 0.010 2.306 0.029 199 100721 24.94 5.14 54.91 1200 0.046 4.00 0.0028 0.019 2.306 0.047 200 100722 27.50 5.12 62.96 1581 0.040 4.03 0.0046 0.024 2.306 0.059 

207 100723 24.77 5.07 47.89 1162 0.041 4.05 0.0145 0.043 2.306 0.10 

208 100720 14.53 5.08 27.22 370 0.074 4.01 0.0024 0.017 2.306 0.044 

210 100717 13.85 5.01 23.91 323 0.074 3.99 0.0022 0.016 2.306 0.042 

211 100715 12.56 4.96 17.86 235 0.076 4.01 0.0027 0.018 2.306 0.046 

212 100719 11.62 4.85 13.48 180 0.075 3.98 0.0048 0.024 2.306 0.059 

213 100727 18.99 4.83 22.61 504 0.045 3.97 0.0016 0.014 2.306 0.038 

65 
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