National Renewable Energy Laboratory 

Innovation for Our Energy Future 

A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 

Modeling and Test-and-Rate 

Methods for Innovative 

Thermosiphon Solar Water 

Heaters 

Preprint 

J. Burch 

National Renewable Energy Laboratory 

G. Shoukas, M. Brandemuhl, and M. Krarti 

University of Colorado

To be presented at Solar 2006 

Denver, Colorado 

July 8–13, 2006 

Conference Paper 

NREL/CP-550-39734 

May 2006 
NOTICE

The submitted manuscript has been offered by an employee of the Midwest Research Institute (MRI), a 

contractor of the US Government under Contract No. DE-AC36-99GO10337. Accordingly, the US 

Government and MRI retain a nonexclusive royalty-free license to publish or reproduce the published form of 

this contribution, or allow others to do so, for US Government purposes. 

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any 

warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or 

usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not 

infringe privately owned rights. Reference herein to any specific commercial product, process, or service by 

trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, 

recommendation, or favoring by the United States government or any agency thereof. The views and 

opinions of authors expressed herein do not necessarily state or reflect those of the United States 

government or any agency thereof. 

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy 

and its contractors, in paper, from: 

U.S. Department of Energy 

Office of Scientific and Technical Information 

P.O. Box 62 

Oak Ridge, TN 37831-0062 

phone: 865.576.8401 

fax: 865.576.5728 

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from: 

U.S. Department of Commerce 

National Technical Information Service 

5285 Port Royal Road 

Springfield, VA 22161 

phone: 800.553.6847 

fax: 703.605.6900 

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/ordering.htm

Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste
MODELING AND TEST-AND-RATE METHODS FOR 

INNOVATIVE THERMOSIPHON SOLAR WATER HEATERS 

Jay Burch 

National Renewable Energy Laboratory 

1617 Cole Blvd.; Golden, CO 80401 

E-mail: jay_burch@nrel.gov 

Greg Shoukas, Mike Brandemuhl, and Moncef Krarti 

University of Colorado at Boulder 

Architectural, Civil, and Environmental Engineering 

Boulder, CO 80302 

ABSTRACT

Simulation models for innovative thermosiphon solar 

systems (TS) have been generally unavailable, hindering 

innovative system design/optimization and system rating. A 

TRNSYS module is introduced that calculates the mass flow 

rate in general natural convection loops, allows use of any 

existing tank and heat-exchanger modules, and handles 

reverse flow in TS when used with a new pipe module. To 

achieve desired rating accuracy, it is proposed that the flow 

rate sub-model in the underlying rating simulation be 

calibrated via nonintrusive flow data from an assembled 

system. Three innovative TS are being tested to validate the 

new modeling and the proposed test-and-rate method: two 

unglazed systems and a glazed polymeric system. An 

ultrasonic meter and a calorimetric flow-rate method both 

showed that model friction was high by ~3X. After 

calibration, the model showed good agreement on both 

long-term collected energy and tank temperatures. 

1. INTRODUCTION

Reducing costs and increasing reliability of solar water 

heaters (SWH) is believed necessary for a substantial SWH 

market to exist in the U.S. (1). A strategy for cold climates 

is expanded use of passive SWH, which include 

thermosiphon systems (TS), as shown in Fig. 1. TS 

eliminate the pumps, controller, sensors, and electrical 

power needed for active systems, and, having insulated 

storage, perform better than integral-collector-storage 

during winter in cold climates. However, the market for TS 

has been limited to warm climates because of the risk of 

freeze-induced bursting of the supply and return lines (2). 

Innovative designs for cold-climate TS can be expected if 

the pipe freeze protection suggested in (3) proves viable. 

Solving inter-related modeling and rating issues with 

innovative, low-cost cold-climate TS as in (4) is the goal of 

this work. 

Fig. 1. TS schematic drawings, direct and roof-integrated 

(5). The simple balance-of-system lowers hardware costs 

and improves reliability compared to the more common and 

more complex active systems. 

Potential cold-climate TS can be configured in a wide 

variety of ways. For cold-climate TS, the most obvious 

collector freeze protection is an indirect glycol loop 

(although other freeze solutions are possible), with potential 

variations in the collector-storage heat exchanger including 

a side-arm counterflow heat exchanger, an immersed coil, a 

wrap-around coil, and a mantle tank. Various tanks might be 

used, in vertical or horizontal positions, with a variety of 

stratification-promoting devices inside the tank. Unpressurized membrane or thin-walled storage tanks can be 

lightweight and significantly reduce both hardware and 

installation costs (4). Potential variations for the heat 

exchanger between unpressurized tank and pressurized 

water include immersed coil, tank-in-tank, and side-arm 

heat exchanger. Unglazed collectors can be used to further 

lower costs, although performance is reduced by ~30%-50% 

(4,6). However, there are two inter-related barriers to 

developing such innovative systems: TS modeling is 

currently very limited, and there are no established test-andrate procedures for most potential innovative TS. This work 

addresses these two issues. 

1
The most common simulation tool for solar thermal design 

and rating models is the modular and extensible code 

TRNSYS (7). It is based upon combining “modules” 

representing components into a system model. However, TS 

modules in TRNSYS exist for only two TS configurations, 

direct (Type45) and indirect with pressurized mantle-tanks 

(8). Neither of these modules calculates reverse flow 

correctly. For any other natural convection loop (NCL) 

problem (including TS), it has been necessary to develop 

new TRNSYS modules, a resource-intensive endeavor. In 

section 2, a general NCL module is presented that computes 

the flow rate for any NCL composed of any of the 

components available to TRNSYS, avoiding the 

development of new modules. 

TRNSYS models are also the basis of the Solar Rating and 

Certification Corporation (SRCC) procedures for rating 

systems (9). The SRCC system rating procedure is to test 

key components (collectors, tanks, and heat exchangers) and 

then to assemble all the components with the measured 

inputs into a system model that is then used to predict 

ratings (10). Rating is thus tied to modeling capability; to be 

practical, models must be easily assembled. Because system 

performance is not sensitive to flow rate for the high-flow 

active systems common in the United States, flow rate for 

these systems has been estimated by the intersection of 

system friction (with measured ∆Pcoll(m)) and pump headflow curves. However, a similar procedure for TS will 

introduce significantly more error because friction at low 

flow and in real-world piping systems is hard to estimate 

accurately. In addition, low flow systems like TS stratify 

storage, and tank stratification depends ~inversely on flow 

rate. TS savings are sensitive to tank stratification if there 

are daytime draws. Section 3 describes tested systems, and 

Section 4 lays out a process to calibrate the modeled flow 

rates in TS, with an instantiation of the suggested test-andrate process in Section 5. 

2. GENERAL NCL MODEL

A general NCL schematic is shown in Fig. 2. For TS, the 

heat source is the collector, the hot leg is collector + return 

pipe, and the cold leg is the stratified storage tank + supply 

pipe. The driving force for the flow is the loop buoyancy, 

which is the difference in weight of the two vertically 

oriented columns of fluid in the loop: 

Pbuoy = ∫ sdg ( cold −=⋅ ρρρ hot)gH ρρ (1) 

The buoyant pressure is generated by heat sources and sinks 

exchanging thermal energy with the loop components. Pbuoy

is exactly dissipated by the friction pressure drops around 

the closed NCL: 

Pbuoy = Kfric*(Pfric,shear + Pfric,hyd) (2) 

In Eqn. (2), we have separated wall shear and hydraulic 

fitting losses and we have introduced a friction scale factor 

(Kfric), which will be used to adjust modeled flow to data. 

Calculations of the pressure drops depend on the component 

type, as in Table 1. For heat exchangers and collectors, the 

complexity of flow passages leads one to use only measured 

pressure drop relationships. Otherwise, correlations of the 

form ∆P(Re;...) are used for shear friction. 

Fig. 2. A general NCL schematic. The fluid rises on the 

right and descends on the left, with buoyancy maintained by 

interactions with a heat source (e.g., sun) and/or a heat sink 

(e.g., heat losses). 

For calculation of buoyancy, each component’s average 

temperature is an input to the NCL module. Collector 

models are based upon collector test data, as in type1 

(massless) and type539 (includes mass). Unglazed collectors 

are modeled as in (6), although necessary modifications 

have not yet been completed for type539. Heat exchangers 

could be noded, use the LMTD to generate the average 

temperature, or use the inlet/outlet average when flows are 

high and the temperature distribution across the heat 

exchanger is nearly linear. The TRNSYS pipe module was 

re-written with a finite difference approach that accounts for 

pipe mass and allows flow from either direction, enabling 

consistent calculation of reverse thermosiphoning. 

The solution of the coupled equations describing the NCL is 

based upon the Van Wijngaarden-Dekker-Brent method 

(11), which shifts optimally between three root-finding 

methods. Root bounds are estimated as a function of the 

previous flow. The module computes all pressure drops, 

including entrance/exit affects between components and 

pipe friction. The correlations used are shown in Table 1. 

The solution restarts when flow reversal is indicated. Even 

with storage above the collector, the model shows consistent 

reverse thermosiphoning that depends on pipe insulation 

and is similar to patterns seen in testing. Soluble problems 

with specified ∆P(m) relations were used to test the new 

coding. Module source code and documentation are 

available on the net (12). 

2
TABLE 1: CALCULATING PRESSURE DROPS

Element in loop ∆P approach/formula 

Components

Collector or 

heat exchanger 

Measured ∆P(m) input as 2nd order 

polynomial (from SRCC data) 

Pipe Churchill correlation, with added 

developing length correlation (12) 

Storage tank Set to zero 

Fittings (12) 

Tank expansion 1 

Tank contraction 160/Re = 0.5 

Pipe expansion [1-(d1/d2)

2

]

2

Pipe contraction 0.42[1-(d1/d2)

2

]

2

90° elbow 800/Re + 0.25(1 + 1/d) 

45° elbow 500/Re + 0.20(1 + 1/d) 

Run-thru T 150/Re + 0.50(1 + 1/d) 

3. SYSTEM TESTS

To compare unglazed and glazed thermosiphons, and to 

validate the new modeling and test-and-rate procedure, three 

TS were put on test (Fig. 3). The area (32 ft2

) and height 

from collector bottom to tank are the same. The collector 

loops are direct. The 42-gallon tanks are unpressurized, 

made of 1/4”-wall polypropylene tanks insulated with 4” of 

foamboard. Pipe insulation was 1” thick. The two left-most 

systems (#1, #2) use a polymer pool collector, with the first 

one glazed with an acrylic sheet. The far right system (#3) 

uses an unglazed, selectively coated absorber, with 

emissivity ~0.18 (weathered value, as measured with a GierDunkel DB-100 IR Reflectometer). There was no insulation 

under or on the sides of the collectors, except for the 

corrugated back-plane that is part of the recommended 

installation of system #3. Tank heat can be purged at night 

through a computer-controlled loop with pump and heat 

exchanger, which allows control of the tank/system starting 

temperature the following sunrise. 

Tank temperatures are monitored by: a) a thermocouple rake 

with sensors at the middle of 9 equal-volume tank nodes; 

and b) a line-averaging RTD extending both top-to-bottom 

and diagonally across the tank in a sawtooth pattern. 

Collector inlet-outlet and tank inlet-outlet temperatures are 

measured. Weather data include ambient temperature, wind 

speed and direction*

, humidity*, solar radiation (global 

horizontal*

, normal beam*, and incidence in the plane) and 

sky infrared exchange in the plane and on horizontal*

. 

(Note: *’d variables are actually measured at a nearby site 

(13)). Data are sampled every 5 seconds, and average/totals 

are stored every 5 minutes. 

Figure 3. Three thermosiphon systems on test, with a glazed 

collector on left and two unglazed collectors to the right. 

Measurement of flow rate is challenging because meter flow 

obstructions change the overall flow. Two non-intrusive 

techniques were used here, ultrasonic and calorimetric. The 

ultrasonic meter was available only for two weeks of the 

testing. The calorimetric method is based on writing the 

energy balance on the storage tank and solving for the mass 

flow rate m: 

m=[CtankdTtank/dt+UAtank(Ttank–Tamb’)]/[cp(Ttank,in–Ttank,out)](3) 

The tank temperature derivative dTtank/dt is calculated by 

fitting a quadratic curve through 9 points centered on the 

interval in question, and then taking the derivative of the 

resulting function evaluated at the midpoint. Tank 

capacitance Ctank includes the tank water, polymeric walls, 

and immersed instrumentation. Tamb’ is the area- and 

conductance-weighted average of Tamb and TIR(θ). UAtank is 

measured by a night-time temperature decay as in (9), 

inferring UAtank by the same energy balance approach as in 

Eq. 3 (but without the mass flow term). Because the tanks 

are well insulated (~R26), UAtank is sensitive to single-pipe 

convection and to air-sealing of the pipe penetrations. Table 

2 gives results for several combinations of sealing and pipe 

plugs (which prevent convective flows between tank and 

pipes). The UAtank value “with seals and plugs” was used in 

subsequent simulations, considering any additional losses to 

be accounted for with the piping model. 

TABLE 2. UATANK FOR SEVERAL TANK STATES

Tank State UAtank [W/°

C] 

No sealing, and no plugs 1.81 

No sealing, with plugs 1.36 

With sealing and with plugs 1.04 

3-D calculation with manufacturer’s kfoam 0.56 

3
Thermosyphon System # 3

0

30

60

90

9/17 9/18 9/19 9/20 9/21 9/22

Time

Temp [C], Vwind [m/s]

0

200

400

600

800

1000

1200

Insolation [W/m 2

]

Ttank,avg Tambient Vwind Insolation

Fig. 4. Weather variables and average tank temperature vs. 

time for TS #3, with the selective, unglazed collector. 

Systems were operated for 45 days in a warm-up mode, with 

no draws during the day. Data for System #3 is shown in 

Fig. 4 over a 5-day interval. A heat dump is started at 10 

p.m., indicated by the sharp discontinuity in the Ttank decay 

at night. The system starts hot, ~50 °

C, during this period. 

Fig. 5 shows the daily collection efficiency [Qcol,day/(Hday* 

Acoll)] versus a daily operating parameter ∆Tavg/Isun,avg. As 

expected, the glazed system operates best, and the selective 

unglazed system performs better than the non-selective 

unglazed system. After system models are calibrated for all 

three systems, annual performance of the systems will be 

compared for different climates and draw patterns. 

Daily Performance

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.00 0.02 0.04 0.06 0.08

DTavg,day/(Qinc,day/Dtday) [C-m2/W]

Daily Efficiency

Polymer Glazed

Polymer Unglazed

Selective Unglazed

Fig 5. System daily efficiency [Qcol,day/(Hday*Acoll)] vs. daily 

operating parameter [∆Tavg/Isun,avg]. Each point corresponds 

to a warm-up test. 

Fig. 6 shows the flow rate as measured by the ultrasonic 

meter and by tank calorimetry. The flow starts up typically 

~1–2 hours after sunrise. The two measurement techniques 

give roughly the same results on clear days, but the 

calorimetric technique is comparatively noisy, despite the 

averaging implicit in obtaining the temperature derivative 

and rejecting data with low values of (Ttank-in-Ttank-out). The 

ultrasonic data shows a characteristic, fairly repeatable 

pattern after sunset, as seen in Fig. 6. A low flow spike 

occurs (<~20 l/hr) starting just after sunset, then reverse 

flow following for several hours, and then a low forward 

flow (< ~10 l/hr) until sunrise. However, the ultrasonic 

meter used showed erratic fluctuations of this magnitude 

when tested in a closed pipe with no flow. Comparison with 

reverse thermosiphoning predicted by the new TS model has 

not been completed. 

Flow Rates vs. Time

-10

10

30

50

70

90

6264 6288 6312

Time [hr]

Flow rate (liters/hr)

0

2000

4000

6000

8000

10000

12000

14000

Irradiance KJ/hr-m2

Calorimetry

Ultrasonic

Model, Kfric=1.0 

Model, Kfric=.34

Radiation 

Fig. 6. Flow rate vs. time for system #3, as measured by the 

ultrasonic meter and the calorimetric method, and as 

predicted by TRNSYS with Kfric=1 and 0.34. 

4. MODEL CALIBRATION AND VALIDATION

The key inputs to rating models should be measured, 

including parameters for collectors, heat exchangers, and 

storage tanks (10). Certification test results were supplied 

for the selective collector by the manufacturer (14). For TS 

models, the collector-loop flow rate is difficult to predict, 

and this affects tank stratification significantly. The 

calibration procedure suggested here for TS models is to 

regress Kfric shown in Eqn. 2 through a fit on flow data. The 

χ2 metric used for the regression of Kfric is: 

χ2

(Kfric) = Σi[(mmodel,i(Kfric) – mdata,i )/σm]

2

/(Ndata-1), (4) 

where the dependence of χ2

 and mmodel,i on Kfric is explicitly 

shown. The regression data were restricted to noon ± 1 hour 

on days 1, 3 and 4 in Fig. 4 (clear days), avoiding times 

when noise is relatively high. χ2

(Kfric) is displayed in Fig. 7, 

showing that the model as configured is over-predicting the 

friction and under-predicting the flow. Kfric at χ2

min is 

somewhat different with the two different mass-flow data 

sets, 0.44 for the calorimetric method, and ~0.34 for the 

ultrasonic meter. χ2

 for the ultrasonic data is significantly 

lower and sharper than for the calorimetric method, 

reflecting that the ultrasonic data is “less noisy” and on this 

basis would be preferred to the calorimetric technique. It is 

also possible to use data on ∆Tcoll to tune the model flow 

rate, if accurate testing has been done on the collector. 

4
Chi Squared vs. Kfrict

0

3 0

6 0

9 0

0 .2 0 .3 0 .4 0 .5 0 .6

K adj Parameter

Chi Square

C a lorim e tric F low

Ultra-S o nic F low

Fig. 7. χ2

 vs. Kfric. Two cases were done, with flow rate data 

from the ultrasonic meter and the calorimetric method. 

The calibrated model predictions were compared to 45 days 

of data on two variables, collected energy [which is 

proportional to (Ttank,sunset-Ttank,sunrise)] and collector 

temperature rise ∆Tcoll. This data set has no “real” draws, 

only a nighttime purge. When validating a ratings model, 

the data set should include typical draw schedules and a 

variety of weather. Nonetheless, the data here serves as a 

reasonable indicator of model accuracy. A comparison on 

daily temperature rise is shown in Fig. 8. The starting 

temperature at sunrise heavily influences daily efficiency 

and temperature rise. Over the entire data set, the average 

deviation between data and model with Kfric=0.34 was 0.4 °

C, with a standard deviation of 2.2 °C. The model tends to 

be low at low wind, and high at high winds, as the wind 

dependence is not yet present in the unglazed collector 

model. Fig. 9 shows the relationship between the deviation 

and wind speed, which indicates some degree of correlation 

of the error with wind speed (R2

 = .45). 

Daily Temp Rise: Model vs Data

0

20

40

60

231 233 235 237 239 241 243

Julian Day

T or Delta-T [C]

0

1

2

3

Vwind [m/s], 

Hsun [GJ/m2/10]

Data

Modl Kf=.34

Modl Kf=1

Wind

sun

T_start

Fig. 8. Comparison between measured and modeled daily 

temperature rise over a two-week period. Key driving forces 

are also plotted: wind, sun and warmup starting temperature. 

The flow rate calibration significantly impacts predicted 

∆Tcoll and Ttank,top. ∆Tcoll(t) is shown in Fig. 10 for data and 

for TRNSYS models with Kfric=.34, .44, and 1.0. With 

Kfric=1.0, ∆Tcoll is too high, by about 8 °

C midday. ∆Tcoll is 

matched the best by Kfric = 0.34, and is ~1°

C high with 

Kfric=.44. Similarly, Ttank,top was too large, and Ttank,bottom too 

cold later in the day, with Kfric = 1, consistent with Fig. 10. 

If there were daytime draws, the temperature rise data 

would not agree well with the uncalibrated model, because 

that model would predict incorrect draw temperatures. 

Error in DTrise vs. Vwind

R2 = 0.45

-4

-2

0

2

4

012

Wind Speed [m/s]

DT Model - Data [C]

3

Fig. 9. Relation between error in temperature rise and 

daytime-average wind speed. 

DeltaT_Collector

0

5

10

15

20

6216 6222 6228 6234 6240

Time [hr]

DeltaT_across 

collector [C]

0

100

200

300

400

Mass Flow [kg/hr] 

Solar [kJ/h-m2/50]

DT_data

DT,K=1

DT, K=.44

DT, K=.34

Flow (Ultrasonic)

Solar/75

Fig. 10. ∆Tcoll from data and 3 TRNSYS models vs. time. 

6. CONCLUSIONS AND FUTURE WORK 

For innovative TS, design optimization and SRCC 

certification depend on being able to model these systems 

accurately and easily. To facilitate modeling involving 

NCL, a general module was developed for TRNSYS that 

can use any existing component modules and solves the 

head-friction balance for the loop flow rate. For ratings, the 

mass flow rate calculations in the model should be adjusted 

to fit observed data. Three TS systems have been tested, two 

unglazed (one selective, one non-selective) and one glazed. 

The model calibration procedure was exemplified on one 

system. Flows were measured non-intrusively with a 

calorimetric technique and an ultrasonic flow meter. The 

5
ultrasonic data were less noisy, and led to better agreement 

with measured ∆Tcoll(t) and Ttank,top. The calibrated model 

predicted the energy collected over all the warmups to 

~1.7%, and closely predicted ∆Tcoll, Ttank,bot, and Ttank,top. The 

unglazed TRNSYS collector model needs to have wind 

dependence added, and the test-and-rate method will be 

validated against normal operation data for all three 

systems. 

8. ACKNOWLEDGMENTS

The authors acknowledge funding from the U.S. Department 

of Energy’s Solar Energy Technology Program, Solar 

Heating and Lighting (SH&L) sub-program. We gratefully 

recognize encouragement from Tex Wilkins and Glen 

Strahs, SH&L program managers, to pursue low-cost 

concepts and PSWH market extension. 

7. NOMENCLATURE 9. REFERENCES

(1) Solar Energy Technology Program: Multi-year 

Technical Plan 2007-2011. The document is available at 

http://www1.eere.energy.gov/solar/about.html. 

Symbols

A Area 

cp Heat capacity at constant pressure 

 (2) Salasovich, J., Burch, J., and Barker, G., “Pipe Freeze 

Probability for Passive-solar Water Heating Systems in 

the United States”, Proc. ASES 2004. ASES, Boulder, 

CO. 

C Capacitance of tank (water + walls) 

D Diameter of air duct 

g Gravity 

H Vertical height of NCL, or Daily solar irradiance 

(3) Burch, J, and Heater, M., “Northward Market Extension 

for Passive Solar Water Heaters By Using Pipe Freeze 

Protection with Freeze-tolerant Piping”, Proc. ASES 

2006. ASES, Boulder, CO. 

K Calibration factor for pressure drop calculations 

m mass flow rate 

N Number of data points in the regression 

P Pressure 

(4) Burch, J., Salasovich, J., and Hillman, T., “Cold-Climate 

Solar Domestic Water Heating Systems: Life-cycle 

Analyses and Opportunities for Cost Reduction”, Proc. 

ASES 2005. ASES, Boulder, CO., ASES, Boulder, CO. 

s Distance along the path of integration 

t Time 

T Temperature 

U Unit area conductance 

(5) A thermosiphon schematic from Solargenix, Inc., at: 

http://www.solargenix.com/hot_water_products.cfm ρ Density (average density with top bar) 

χ2

 Metric of deviation between model and data 

(6) Burch, J., Salasovich, J., and Hillman, T., “An 

Assessment of Unglazed Solar Domestic Water 

Heaters”, Proc. ASES 2005. ASES, Boulder, CO. 

∆ Difference 

σ Error 

Σ Summation (7) TRNSYS description can be found at: 

http://sel.me.wisc.edu/trnsys/default.htm Subscripts

amb Ambient (8) Morrison, G., private communication of the TRNAUS 

package of thermosiphon and related modules, 3/04. amb’ Effective temperature (ambient + sky) 

bot Bottom of tank (9) SRCC. SRCC Standards OG100, OG300; and Test 

Methods TM-1. Available at http://solar-rating.org/ buoy Buoyancy 

cold Cold side of the NCL (10) Burch, J.; Huggins, J.; Wood, B.; Thornton, J., 

“Simulation-Based Ratings for Solar Hot Water 

Systems.” Proc. ASES 1993. ASES, Boulder, CO. 

coll Collector 

data Data 

day Daytime total or average (11) Press, W., Flannery, B, Teukolsky, S., and Vetterling, 

W., Numerical Recipes. The Art of Scientific 

Computing. Cambridge University Press, Cambridge, 

UK. 1989. 

fric Friction 

hot Hot side of the NCL 

i Index for data points 

IR Sky infrared (12) NCL module code and documentation are available at: 

ftp://ftp.nrel.gov/pub/solar_waterheat-out/NCL. mod Model 

tank Thermosiphon system storage tank (13) Solar Radiation and Research Laboratory, Golden, CO. 

National Renewable Energy Laboratory. Data described 

at http://www.nrel.gov/srrl/ (last accessed 4/06). 

top top of tank 

(14) Bernard Thiessen, private communication, 4/05. 

bernard@energie-solaire.com. A test report using DIN 

EN 12975-2 was provided. 

6
F1147-E(12/2004) 

REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, 

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this 

collection of information, including suggestions for reducing the burden, to Department of Defense, Executive Services and Communications Directorate (0704-0188). Respondents 

should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a 

currently valid OMB control number. 

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION.

1. REPORT DATE (DD-MM-YYYY)

May 2006 

2. REPORT TYPE

Conference paper 

3. DATES COVERED (From - To)

 

5a. CONTRACT NUMBER

DE-AC36-99-GO10337 

5b. GRANT NUMBER

4. TITLE AND SUBTITLE

Modeling and Test-and-Rate Methods for Innovative Thermosiphon 

Solar Water Heaters: Preprint 

5c. PROGRAM ELEMENT NUMBER

5d. PROJECT NUMBER

NREL/CP-550-39734 

5e. TASK NUMBER

SH06.2003 

6. AUTHOR(S)

J. Burch: NREL 

G. Shoukas, M. Brandemuhl, and M. Krarti: University of Colorado 

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401-3393 

8. PERFORMING ORGANIZATION 

REPORT NUMBER

NREL/CP-550-39734 

10. SPONSOR/MONITOR'S ACRONYM(S)

NREL 

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

11. SPONSORING/MONITORING 

AGENCY REPORT NUMBER

12. DISTRIBUTION AVAILABILITY STATEMENT

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

13. SUPPLEMENTARY NOTES

14. ABSTRACT (Maximum 200 Words)

Simulation models for innovative thermosiphon solar systems (TS) have been generally unavailable, hindering 

innovative system design/optimization and system rating. A TRNSYS module is introduced that calculates the mass 

flow rate in general natural convection loops, allows use of any existing tank and heat-exchanger modules, and 

handles reverse flow in TS when used with a new pipe module. To achieve desired rating accuracy, it is proposed 

that the flow rate sub-model in the underlying rating simulation be calibrated via nonintrusive flow data from an 

assembled system. Three innovative TS are being tested to validate the new modeling and the proposed test-andrate method: two unglazed systems and a glazed polymeric system. An ultrasonic meter and a calorimetric flow-rate 

method both showed that model friction was high by ~3X. After calibration, the model showed good agreement on 

both long-term collected energy and tank temperatures. 

15. SUBJECT TERMS

solar domestic water heating; solar water heating; cold-climate solar domestic water heating; cold-climate solar water 

heating; thermosiphon solar water heating; freeze-protection for solar water heating 

16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON 

a. REPORT 

Unclassified 

b. ABSTRACT 

Unclassified

c. THIS PAGE 

Unclassified

17. LIMITATION 

OF ABSTRACT

UL 

18. NUMBER 

OF PAGES 

19b. TELEPHONE NUMBER (Include area code)

Standard Form 298 (Rev. 8/98) 

Prescribed by ANSI Std. Z39.18