Hot Water Distribution 

System Model 

Enhancements

M. Hoeschele and E. Weitzel

Alliance for Residential Building Innovation (ARBI)

November 2012
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Hot Water Distribution System Model Enhancements

Prepared for:

The National Renewable Energy Laboratory 

On behalf of the U.S. Department of Energy’s Building America Program

Office of Energy Efficiency and Renewable Energy

15013 Denver West Parkway

Golden, CO 80401

NREL Contract No. DE-AC36-08GO28308

Prepared by: 

M. Hoeschele and E. Weitzel

Alliance for Residential Building Innovation (ARBI)

Davis Energy Group, Team Lead

123 C Street

Davis, California 95616

NREL Technical Monitor: Cheryn Metzger

Prepared under Subcontract No. KNDJ-0-40340-00

November 2012
iv

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v

Contents

List of Figures ............................................................................................................................................ vi

List of Tables .............................................................................................................................................. vi

Definitions.................................................................................................................................................. vii

Executive Summary................................................................................................................................. viii

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

1.1 Background and Motivation ................................................................................................1

1.1.1 HWSIM Background ...............................................................................................2

1.2 Research Questions..............................................................................................................3

2 Methodology ......................................................................................................................................... 4

2.1 Modeling Methodology .......................................................................................................4

3 Results................................................................................................................................................... 5

4 Conclusions and Recommendations ................................................................................................. 9

References................................................................................................................................................. 11
vi

List of Figures

Figure 1. Comparison of lab and simulated uninsulated pipe UAs ....................................................... 7

Figure 2. Insulated pipe UAs as a function of insulation conductivity ................................................. 8

Figure 3. Comparison of lab and simulated insulated pipe UAs............................................................ 9

Unless otherwise noted, all figures were created by the ARBI team.

List of Tables

Table 1. HWSIM Required Inputs for Combined Convective/Radiant Heat Transfer Modeling .......... 4

Table 2. Combined Convective/Radiant Heat Transfer Modeling Algorithms ...................................... 5

Table 3. Comparison of Lab and Simulated Plastic Pipe Outlet Temperatures and UAs.................... 6

Table 4. Comparison of Lab and Simulated Copper Pipe Outlet Temperatures and UAs................... 6

Unless otherwise noted, all tables were created by the ARBI team.
vii

Definitions

ARBI Alliance for Residential Building Innovation

ARIES Advanced Residential Integrated Energy Solutions

AET Applied Energy Technology

CARB Consortium for Advanced Residential Buildings

CEC California Energy Commission

CU University of Colorado

CPVC Chlorinated Polyvinyl Chloride

DEG Davis Energy Group

k Thermal conductivity

LBNL Lawrence Berkeley National Laboratory

PIER Public Interest Energy Research

PEX Cross-linked Polyethylene

UA Product of overall heat transfer coefficient (U) and pipe 

surface area (A)
viii

Executive Summary

Hot water distribution systems deliver heated water from the heat source to the use points 

throughout the house. As house size and number of fixtures has increased in recent years, the 

impact of distribution systems on overall performance has become more significant. Inefficient 

distribution systems contribute to unnecessary energy and water waste, as well as excessive hot 

water wait time.

This project involves enhancement of the HWSIM distribution system model to more accurately 

model pipe heat transfer. Recent laboratory testing efforts have indicated that the modeling of 

radiant heat transfer effects is needed to accurately characterize piping heat loss. An analytical 

methodology for integrating radiant heat transfer was implemented with HWSIM. Laboratory 

test data collected in another project was then used to validate the model for a variety of 

uninsulated and insulated pipe cases (copper, PEX, and CPVC). Results appear favorable, with 

typical deviations from lab results less than 8%. Improving the modeling capabilities of 

distribution system models is a critical step in improving the accuracy of projecting hot water 

distribution system performance. Future efforts should include using detailed field data from the 

National Renewable Energy Laboratory’s (NREL) Solar Row project (Barley et al 2010) to 

further validate the HWSIM model, as well as a recently developed TRNSYS model.
1

1 Introduction

1.1 Background and Motivation

The delivery characteristics of hot water distribution systems are a critical factor affecting 

overall water heating system performance in terms of both energy and water use (and waste). 

Accurate simulation tools, such as the HWSIM distribution system model and recent modeling 

work completed by CU Boulder and NREL (Maquire et al 2011), are needed to quantify the 

impacts of distribution system performance, which is the first step in identifying cost-effective 

improvement options that will contribute to Building America’s goal of 30%-50% energy 

savings.

Little data currently exists in quantifying distribution losses, especially in terms of understanding 

how climate, plumbing practices (i.e. pipe layout and house vintage), hot water usage patterns, 

and user behavior affect overall losses. A variety of factors contribute to this poor understanding 

of distribution system performance, including the following:

• Detailed monitoring of water heater energy and water flows to use points is challenging 

and expensive, since remote temperature sensors and individual flow meters are required. 

Few studies have been completed that accurately assess distribution losses in single 

family homes.

• Modeling tools have historically been limited in their predictive capability, especially 

given the uncertainties of typical piping layouts, hot water usage patterns, and how pipe 

(surrounding) environment temperatures affect thermal losses. The short duration of 

typical residential water heating loads (typically 20-60 minutes of hot water flow per 

day), results in hourly simulation tools being largely ineffective at accurately modeling 

these high resolution events.

• For many homes and apartments, much of the distribution piping is largely hidden from 

view, making accurate quantification of pipe routing, and pipe lengths and diameters 

difficult. Without knowledge of the pipe layout, it is challenging to understand the system 

interactions.

• Hot water loads, usage patterns, and user behavior varies widely among households and 

vary significantly from day to day. How loads are imposed on a system can significantly 

affect distribution system performance in terms of heat loss and water waste. Addressing 

all of these issues is critical in developing a better understanding of distribution system 

performance. Work is proceeding in some of the identified gap areas, but additional effort 

is needed to generate the input data and improve tools required to properly assess 

distribution system performance. Jim Lutz of Lawrence Berkeley National Laboratory 

(LBNL) has been working for several years on developing a database for archiving high 

resolution hot water use data from field monitoring studies1

. The Building America team, 

Advanced Residential Integrated Energy Solutions (ARIES), is starting a field effort to 

assess the impact of water heater and distribution system upgrades at three or more 

existing homes in central New York. Davis Energy Group (DEG), who leads the ARBI 

team, is currently completing simulation enhancements to HWSIM (focused on 

integrating both gas storage and gas tankless water heater models with the distribution 

 1 http://www.aceee.org/files/pdf/conferences/hwf/2010/3D_Jim_Lutz.pdf
2

model), as part of a California Energy Commission (CEC) Public Interest Energy 

Research (PIER) sponsored advanced water heating project being led by the Gas 

Technology Institute. The PIER simulation enhancement work complements the work 

presented in this report.

1.1.1 HWSIM Background

In 2004, working under funding from the Building America team Consortium for Advanced 

Residential Buildings (CARB), DEG began an extensive enhancement of the HWSIM 

distribution system model. (The model was originally developed in a simplistic BASIC coded 

form for use in DEG’s development of the 1990 detailed California Title 24 water heating 

methodology.) The 2004 Building America funding was designed to increase the analytical rigor 

and flexibility of the modeling tool, improve the user interface, and develop a user’s manual for 

the public domain software tool.

HWSIM was originally designed to model in detail the energy and water use (and waste) effects 

associated with residential-scale hot water distribution systems. Impacts of pipe heat loss both 

during draws and between draws are modeled. The software requires the user to specify a water 

heater setpoint temperature, a plumbing network (separated into elements of various lengths, 

with each pipe element characterized by pipe material, pipe diameter, insulation, and pipe 

environment temperature), plumbing environment temperatures, and hot water end use points. 

The piping network serves individual use points such as showers, tubs, sinks, and appliances. A

full weekly schedule of hot water draws is then input to characterize the various demands of hot 

water through the course of a day. Seasonal effects are captured by varying monthly cold water 

inlet temperatures and the temperatures of the pipe heat loss environments, which can vary both 

monthly and hourly. Draws are characterized by start time, flow rate, volume or energy content 

desired, and minimum use temperature (in the case of showers or other draws where a comfort 

threshold applies). The representative week of draws is scaled to develop monthly, and 

ultimately, annual summaries of piping energy waste, hot and cold water wasted, and water 

heater energy consumption (Springer et al 2008). 

Each unique pipe element is comprised of a series of nodes of discrete volume (dV) to improve 

the resolution of the heat transfer calculations. Typical node size is 0.075 gallons, although the 

user has the ability to increase or decrease with resulting implications on both computing time 

and resolution. Heat transfer from the pipe to the environment is calculated continuously as each 

dV flows through the piping network towards the use point. As the piping network moves from 

the water heater to the use points, the pipe environment and pipe diameter may change, varying 

the calculated heat loss. During periods between draws, the distribution piping undergoes a 

thermal decay based on material properties, presence of insulation, and the hourly surrounding 

environment temperature.

As part of the CEC PIER project currently underway, the following program enhancements are 

being implemented:

• Integrate the center flue storage water heater simulation program TANK (originally 

developed by Batelle in the early 1990’s) with HWSIM to more accurately simulate 

system performance by recognizing the interactions between the water heater and the 

distribution system.
3

• Integrate the single node tankless water heater model used in TRNSYS (Type 940 model) 

to evaluate tankless water heater performance in terms of efficiency, hot water delivery 

characteristics, and water waste.

• Utilize test data on pipe heat loss performance developed by Applied Energy Technology 

(AET) to validate the HWSIM model.

The AET laboratory testing led to the conclusion that integrating radiant heat transfer was 

needed to accurately model pipe heat transfer. During lab testing of plastic piping, it was 

observed that uninsulated 3⁄4 in. PEX piping exhibited considerably higher heat loss per foot than 

uninsulated 3⁄4 in. copper pipe, while the addition of identical pipe insulation to each resulted in 

roughly comparable heat loss between PEX and copper pipes (Hiller 2005; 2006; 2008; 2011). 

Further investigation indicated that the surface emissivity of PEX (and other plastic pipes) is 

equal to 0.91, while copper piping has a much lower emissivity, depending upon the level of 

oxidation on the pipe surface. An extreme case for highly polished copper suggests an emissivity 

of 0.02, although any level of oxidation will quickly increase the surface emissivity2. 

This laboratory finding suggested the need for radiant heat transfer integration within HWSIM. 

Integrating radiant heat transfer is just the first step of the process, since now an assumption must 

be made for the mean radiant temperature for each pipe environment that is being modeled. 

Specification of the air temperature is challenging enough for many applications such as attics or 

garages, where conditions can vary significantly, especially in summer months. With input from 

AET, we have simplified the assumption that pipe radiant environment temperature is equal to 

the surrounding air temperature. Future monitoring and model validation efforts will provide 

insights to the validity of this assumption.

1.2 Research Questions

The work presented here represents a key step in the development of the tools needed to assess 

the performance of distribution systems. A better understanding of distribution systems, hot 

water usage magnitude and patterns, and use behavior, are all critical building blocks to 

accurately assessing the overall performance of existing and alternative hot water systems, and 

identifying cost-effective strategies leading to the Building America goal of 30%-50% whole 

house energy savings. The enhancement of the HWSIM program is an important step in 

improving understanding of system performance. The following research questions have been 

identified for this technical report:

• What analytical method should be used to accurately model pipe heat transfer?

• How well does the model predict performance relative to detailed laboratory 

measurements?

• What are the limitations of the model?

• What should be the next step in the model validation process?

 2 Standard heat transfer reference texts present typical emissivity values for copper ranging from 0.02 for highly 

polished, 0.04-0.05 for “polished”, 0.07 for “scraped, shiny”, 0.15 for “slightly polished”, to 0.78 for “black 

oxidized”. 
4

2 Methodology

2.1 Modeling Methodology

The development of the combined convective/radiant pipe heat transfer relied on calculating a 

combined surface heat transfer coefficient based on the input parameters shown in Table 1.

Table 1. HWSIM Required Inputs for Combined Convective/Radiant Heat Transfer Modeling

Variable Description Equation (or value)

INPUTS

Tw, water temperature (deg F)

Te, environment temperature (deg F)

Tr, Mean radiant temperature (deg F)

F, flow rate (gpm)

kp, pipe conductivity (Btu/hr-ft-degF)

ki, insulation conductivity (Btu/hr-ft-degF)

Li, insulation thickness (inches)

S, Stephan-Boltzmann constant (Btu/hr-ft^2-degR^4) 1.714 x 10−9

e, surface emissivity (non-dimensional)

Ri, inside pipe radius (ft)

Ro, outside pipe radius (ft)

Rs, outer surface radius (ft) Ro+Li/12

Tsi, initial surface temperature estimate (deg F) (Tw+Te)/2

The calculation methodology, outlined in Table 2, is based on standard heat transfer calculations 

for free convection and radiation (Kreith 1973). The calculation process involves first 

determining an exterior surface coefficient based on an initial estimate of surface temperature 

equal to the average of the pipe element water temperature and the surrounding environment 

temperature. The initial coefficient was calculated using standard pipe heat transfer modeling for 

horizontal cylinders at moderate surface temperatures. The interior coefficient is then calculated 

based on the pipe fluid velocity. The methodology utilizes Newton’s method to iterate in 

estimating a final surface temperature to be used for determination of the combined convective 

and radiant heat transfer. This technique is then used for each dV of the piping network where 

water is flowing, accommodating changes in fluid temperature (from one dV to the next), 

environment air and mean radiant temperature, and fluid velocity (as pipe diameters change).
5

Table 2. Combined Convective/Radiant Heat Transfer Modeling Algorithms

Variable Description Equation

CALCULATIONS

hoi, initial surface air film estimate (Btu/hr-ft^2-degF)

V, fluid velocity (ft/sec)

hi, inside film coefficient estimate (Btu/hr-ft^2-degF)

Ui, inside total U-value (Btu/hr-ft^2-degF)

f, Ts written as a function

f

/

, derivative of f

Tsf, final surface temperature (deg F)

ho, final surface air film (Btu/hr-ft^2-degF) 

Q/l, heat flow to environment (Btu/hr-ft)

UA, overall pipe UA (Btu/ft-degF) Q / (Tw - Te)

3 Results

Upon implementation of the heat transfer calculation methodology outlined in Table 2, a series 

of runs were completed to compare results to the laboratory data collected by AET over the past 

several years. Tables 3 and 4 summarize the findings for various uninsulated pipe cases with 

plastic pipes listed in Table 3 and copper in Table 4. The surface emissivity of plastic and copper 

pipe was assumed to be 0.91 and 0.40, respectively. Hot water inlet temperature, air and radiant 

environment temperature (assumed equal), and fluid flow rates were all specified to match the 

reported test conditions for horizontal pipes in air. Outlet water temperatures were calculated 

based on the lab-reported UAs, inlet hot water temperature, and environment (air and radiant) 

temperatures. These input conditions were also fed into the model to simulate a 100-foot long 

pipe section. A 20-gal draw was imposed and the end of draw outlet temperature (reported in the 

Tables) was used to calculate the steady state “UA per foot” listed under HWSIM Results.
6

Table 3. Comparison of Lab and Simulated Plastic Pipe Outlet Temperatures and UAs

Table 4. Comparison of Lab and Simulated Copper Pipe Outlet Temperatures and UAs

For the plastic pipe cases, HWSIM underpredicts the lab UAs by 0% to 10%. This falls within a 

reasonable range of accuracy given the expected experimental accuracy in the lab of utilizing 

immersion thermocouples. UA is highly sensitive to the accuracy in the entering and leaving 

water temperature measurements, which in some of the lab test cases varied by as little as 3°F 

from inlet water to outlet. For the copper pipe data shown in Table 4, the rigid piping simulated 

cases (with the 0.4 emissivity assumption) show good correlation with the lab data. The last four 

columns show a second 3⁄4 in. rolled copper tubing case tested in the lab. HWSIM results are 

shown for two cases (0.02 and 0.20 emissivity), in an attempt to approximate the actual “new 

Pipe 3/4PEX 3/4PEX 1/2PEX 1/2PEX 3/8PEX 3/8PEX 3/4CPVC 3/4CPVC

Pipe Insulation Level R-0 R-0 R-0 R-0 R-0 R-0 R-0 R-0

Insulation Conductivity Assumption 0 0 0 0 0 0 0 0

Assumed Surface Emissivity (e) 0.91 0.91 0.91 0.91 0.91 0.91 0.91 0.91

Hot Water Inlet Temperature (F) 135 135 136 136 135 135 137 137

Air and Radiant Environment Temp (F) 54 54 55 55 56 56 70 70

Flow Rate (gpm) 1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0

Lab Test Results

Pipe "UA per foot" target (Btu/hr-ft-F) 0.545 0.555 0.438 0.438 0.368 0.368 0.460 0.480

Calculate Outlet Temperature (F) 126.27 130.55 128.98 132.49 129.25 132.13 130.91 133.82

HWSIM RESULTS

Calculate Outlet Temperature (F) 127.00 130.86 129.53 132.68 129.88 132.39 130.97 133.90

Calculated Pipe "UA per foot" (Btu/hr-ft-F) 0.503 0.520 0.406 0.417 0.330 0.336 0.458 0.472

UA Difference vs. Lab Data (%) -7.7% -6.3% -7.2% -4.8% -10.3% -8.6% -0.5% -1.8%

Outlet Temperature Difference vs. Lab (F) 0.73 0.31 0.55 0.19 0.63 0.26 0.07 0.08

Pipe 1/2 Cu 1/2 Cu 3/4 Cu 3/4 Cu 3/4 Cu 3/4 Cu 3/4 Cu 3/4 Cu 

Rolled Rolled Rolled Rolled

Pipe Insulation Level R-0 R-0 R-0 R-0 R-0 R-0 R-0 R-0

Insulation Conductivity Assumption n/a n/a n/a n/a n/a n/a n/a n/a

Assumed Surface Emissivity (e) 0.4 0.4 0.4 0.4 0.02 0.02 0.2 0.2

Hot Water Inlet Temperature (F) 136 136 136 136 133 133 133 133

Air and Radiant Environment Temp (F) 65 65 58 58 56 56 56 56

Flow Rate (gpm) 1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0

Lab Test Results

Pipe "UA per foot" target (Btu/hr-ft-F) 0.345 0.360 0.417 0.421 0.334 0.334 0.334 0.334

Calculate Outlet Temperature (F) 131.16 133.47 129.57 132.75 127.91 130.46 127.91 130.46

HWSIM RESULTS

Calculate Outlet Temperature (F) 131.30 133.60 129.10 132.44 127.66 130.26 126.97 129.90

Calculated Pipe "UA per foot" (Btu/hr-ft-F) 0.335 0.342 0.447 0.461 0.351 0.359 0.396 0.407

UA Difference vs. Lab Data (%) -3.0% -5.0% 7.3% 9.6% 5.0% 7.6% 18.5% 21.8%

Outlet Temperature Difference vs. Lab (F) 0.14 0.13 -0.47 -0.31 -0.26 -0.19 -0.94 -0.55
7

pipe” condition when it was tested. The sensitivity in UA to emissivity is evident. To achieve a 

match to within 10% of the lab test value of 0.334, a highly polished emissivity of 0.02 was 

assumed. It is not clear why the rolled copper tubing comparison of lab versus simulated differs 

to a greater extent that the rigid 1⁄2 in. and 3⁄4 in. copper results.

Figure 1 plots the lab and simulated UA values for each of the cases reported in Tables 3 and 4.

Figure 1. Comparison of lab and simulated uninsulated pipe UAs

The second step in the validation process was to model insulated piping and compare to the 

laboratory test data. Prior AET lab findings suggested that pipe insulation performance was not 

meeting the manufacturer’s performance specifications with typical reported conductivity values 

of 0.02-0.021 Btu/hr-ft-°F (or 0.25 Btu-inch/hr-ft2

-°F). HWSIM runs performed prior to the 

incorporation of the current heat transfer methodology suggested that an insulation conductivity 

of ~ 0.042 Btu/hr-ft-°F provided the best match with the lab data. With the enhanced 

radiant/convective heat loss model in place, a series of runs were completed to assess the best 

fit”k” value for each pipe configuration. Figure 2 summarizes the findings for the case of a 100-

ft pipe at a 1 gpm flow rate. The values of 0.02 and 0.042 Btu/hr-ft-°F insulation conductivity are 

presented to bound the range, with the corresponding calculated UAs shown. The blue-shaded 

values represent the best modeling match with the lab data. Other than the 3⁄4 in. PEX with 3⁄4 in.

insulation, all plastic pipe and copper pipe cases center in fairly tight conductivity ranges, 

however, the difference between copper and plastic is fairly significant. The reason for this and 

0.368

0.330

0.438

0.406

0.545

0.503

0.460 0.458

0.345 0.335

0.417

0.447

0.334 0.351

0.396

0.00

0.10

0.20

0.30

0.40

0.50

0.60

3/8" PEX3/8" PEX1/2" PEX1/2" PEX3/4" PEX3/4" PEX

3/4" CPVC3/4" CPVC

1/2" CU1/2" CU3/4" CU

3/4" CU

Rolled 3/4" CU

Rolled 3/4" CU 0.02Rolled 3/4" CU 0.20

Pipe UA per Foot (Btu/hr-ft-deg F)

3/8" 

PEX

Lab

Simulated
8

the deviation of the 3⁄4 in. PEX case are not entirely clear, and may be an artifact related to the 

laboratory testing. Averaging the eight cases results in a mean conductivity value of 0.030 

Btu/hr-ft-°F.

Figure 3 shows the comparison of insulated pipe data from the lab relative to the simulated cases. 

With the exception of the 3⁄4 in. PEX with 3⁄4 in. insulation, all of the UA comparisons fall within 

10% of the lab values. Since the thermal characteristics of the pipe insulation dominate the heat 

transfer, one would expect the performance of the 3⁄4 in. PEX case to fall more in line with the 

other values. Our hypothesis is that the lab result for this particular case may be inaccurate. 

Figure 2. Insulated pipe UAs as a function of insulation conductivity

3/4" PEX 1/2" PEX 3/8" PEX 3/4" CPVC 1/2" CU 1/2 Cu 3/4" CU 3/4" CU

3/4" Insl 3/4" Insl 3/4" Insl 3/4" Insl 1/2" Insl 3/4" Insl 1/2" Insl 3/4" Insl

0.02 0.108 0.093 0.081 0.107 0.105 0.091 0.133 0.112

0.021

0.022

0.023

0.024

0.025 0.132

0.026 0.117 0.165

0.027

0.028 0.148

0.029

0.03

0.031

0.032 0.121

0.033 0.130 0.160

0.034

0.035

0.036

0.037

0.038

0.039

0.04 0.188

0.041

0.042 0.191 0.165 0.149 0.189 0.185 0.165 0.231 0.202

Insl Conductivity 

(Btu/hr-ft-°F)
9

Figure 3. Comparison of lab and simulated insulated pipe UAs

4 Conclusions and Recommendations 

The implementation of standard horizontal pipe heat transfer calculation utilizing fluid velocity 

for determining interior pipe heat transfer coefficient, and a combined radiant and convective 

outside coefficient was found to provide a good match with AET laboratory data. On average,

simulation results are within 8% of the laboratory findings. Some level of uncertainty lies in the 

identification of the mean radiant temperature, both in the lab environment, and more 

significantly, in many real-world piping applications such as attics and garages. In addition, 

copper surface emissivities, which will vary over time due to oxidation, are difficult to 

determine. Overall, based on the validation results, we feel confident that the enhanced HWSIM 

model, and the recently developed TRNSYS model (Maguire et al 2011), are ready for the next 

validation step of using detailed site monitoring data (NREL’s Solar Row dataset) to drive the 

model. Model outputs in the form of end use point hot water outlet temperatures can then be 

compared to model-predicted outlet temperatures. This work has been proposed by ARBI for 

2012, with the primary validation effort focused on the TRNSYS model.

The development and validation of these enhanced tools is a critical step in the process towards 

accurately evaluating the performance of residential distribution systems and the resulting impact 

on the water heater. Much fundamental work needs to be completed to address the broader water 

heating research questions presented earlier in this technical report. For residential, nonrecirculating distribution systems, the authors estimate that distribution losses may range from 

0.121

0.110

0.1300.126

0.180

0.147

0.160

0.144

0.132

0.146

0.117

0.126

0.165

0.184

0.148

0.155

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

3/8" PEX 3/4"3/8" PEX 3/4"1/2" PEX 3/4"1/2" PEX 3/4"3/4" PEX 3/4"3/4" PEX 3/4"

3/4" CPVC 3/4"3/4" CPVC 3/4"

1/2" Cu 1/2"1/2" Cu 1/2"1/2" Cu 3/4"1/2" Cu 3/4"3/4" Cu 1/2"3/4" Cu 1/2"3/4" Cu 3/4"3/4" Cu 3/4"

Pipe UA per Foot (Btu/hr-ft-deg F)

3/8" PEX 

3/4"

Lab

Simulated
10

10%-40% of annual hot water energy consumption, depending upon factors such as plumbing 

layout, pipe sizing and location, and hot water use quantity and patterns. Critical factors that 

affect the magnitude of the distribution loss include the layout of the distribution system and the 

magnitude and pattern of hot water loads within the household, which are highly variable from 

one house to the next. Both of these factors are currently not well understood, especially in terms 

of how they vary in different vintages of homes and what effect climate has in affecting heat loss 

due to varying environment temperatures and pipe locations (attic piping is common in milder 

regions). Improved knowledge in all these fronts will lead to validated simulation tools that can 

reliably provide results for a range of applications and climates.
11

References

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System: Temperature and Flow Analyses.” NREL/PR-550-48385. Presented at the 2010 ACEEE 

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Hiller, C. (2006a). Hot Water Distribution System Piping Time, Water, and Energy Waste -

Phase I Test Results. ASHRAE Transactions, vol. 114, pt. 1, 415-425.

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