Terry V. Reid, Scott D. Wilson, Nicholas A. Schifer, and Maxwell H. Briggs

Glenn Research Center, Cleveland, Ohio

A Computational Methodology for

Simulating Thermal Loss Testing

of the Advanced Stirling Convertor

NASA/TM—2012-217287

April 2012

AIAA–2011–5579
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Terry V. Reid, Scott D. Wilson, Nicholas A. Schifer, and Maxwell H. Briggs

Glenn Research Center, Cleveland, Ohio

A Computational Methodology for

Simulating Thermal Loss Testing

of the Advanced Stirling Convertor

NASA/TM—2012-217287

April 2012

AIAA–2011–5579

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Prepared for the

9th International Energy Conversion Engineering Conference (IECEC)

sponsored by the American Institute of Aeronautics and Astronautics

San Diego, California, July 31 to August 3, 2011
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Level of Review: This material has been technically reviewed by technical management. 

This report contains preliminary fi ndings, 

subject to revision as analysis proceeds.
NASA/TM—2012-217287 1 

A Computational Methodology for Simulating Thermal Loss 

Testing of the Advanced Stirling Convertor 

Terry V. Reid, Scott D. Wilson, Nicholas A. Schifer, and Maxwell H. Briggs 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Abstract 

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) 

have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system 

for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors 

(ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert 

thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, 

different operating conditions are used to simulate expected mission conditions. These conditions require 

achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical 

power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks 

have been performed which provided a more accurate value for net heat input into the ASCs, including 

the use of multi-dimensional numerical models. Validation test hardware has also been used to provide a 

direct comparison of numerical results and validate the multi-dimensional numerical models used to 

predict convertor net heat input and efficiency. These validation tests were designed to simulate the 

temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 

244.4 W. The methodology was applied to the multi-dimensional numerical model which resulted in a net 

heat input of 240.3 W. The computational methodology resulted in a value of net heat input that was 

1.7 percent less than that measured during laboratory testing. The resulting computational methodology 

and results are discussed. 

Nomenclature 

ASC Advanced Stirling Convertor 

ASRG Advanced Stirling Radioisotope Generator 

BOM Beginning of Mission 

CSAF Cold Side Adapter Flange 

DOE Department of Energy 

EOM End of Mission 

GRC Glenn Research Center 

HH heater head (watts/m-K) 

Q heat transfer (W or watts) 

RTH thermal resistance (degrees C per watt) 

T local temperature (degrees C or K) 

TP thermocouple probe 

TS thermocouple surface mount 

SR Stirling rod

 
NASA/TM—2012-217287 2 

1.0 Introduction 

Power conversion using free-piston Stirling engines to deliver power at high efficiency and low mass 

continues to be an appealing option for long duration deep space missions (Ref. 1). An application that 

utilizes the free-piston Stirling engine is the Advanced Stirling Convertor (ASC), which is shown in 

Figure 1. Numerous efforts are currently underway the NASA GRC to verify performance and assess 

durability of the ASC (Refs. 2 to 5). These efforts include experimental and computational analysis of the 

ASC hardware. 

During the early stages of development, a third order analysis was used to design the ASC so that it 

would perform in accordance with pre-determined criteria. A third order analysis uses control volumes or 

nodes to directly solve the one-dimensional governing equations (Ref. 6). In this case, the ASC was built 

based on the results of the one-dimensional solver SAGE (Refs. 7 to 9). SAGE solves the governing 

equations implicitly in space and time. The SAGE grid includes all time since the periodic solution is 

assumed/forced. As a result, it is not possible for SAGE to model startup transient behavior. SAGE output 

provides performance details as well as geometric and material details, allowing a prototype to be built. 

Once it is built, the performance is verified through a series of experimental and computational analyses. 

Instrumentation exists inside the prototype ASC hardware that provides information regarding the 

motion of some of the internal components. However, quantities such as the Stirling cycle heat addition 

and general heat distributions are difficult to verify. These quantities are needed to define the net heat 

input, which is used to assess the performance of the convertor. A definition for net heat input is shown in 

Equation (1). 

 Qnet-heat-input = Qgross-heat-in – (Qcold-end loss + Qheat-rejected + Qenvironment-heat-loss) (1)

The net heat input represents the heat that is used by the Stirling cycle. A portion of this heat is converted 

into mechanical power (Ref. 10), which then is used to generate electrical power. Knowing these heat 

quantities allow the overall convertor performance to be calculated, while knowledge of the internal 

temperature distribution provides information to assess the durability of the convertor’s internal 

components. These are important parameters that help verify the convertor’s performance. Expected 

convertor thermal loadings are shown in Figure 2. 

 

Figure 1.—Advanced Stirling convertor. Figure 2.—Typical ASC thermal loads. 

 
NASA/TM—2012-217287 3 

Figure 3.—ASC experimental test assembly. 

In this document, Computational Fluid Dynamics (CFD—a fourth order multi-dimensional analysis 

technique) is used to calculate the thermal distributions. The CFD solver FLUENT (by ANSYS Inc.) was 

chosen because of its ability to include conjugate heat transfer and sliding mesh interfaces (when needed) 

during the inevitable transient calculations. There are different computational approaches that can be 

applied using FLUENT to calculate the behavior of the ASC convertor. They include solutions of: 

1. The steady-state Navier-Stokes equations—This can provide a conservative estimate of the heat 

distribution thru out the convertor. Heat distribution along with the temperature distribution allows 

the temperature limits of the internal components to be evaluated and coarse heat quantities to be 

calculated. Although convection would not be present in this calculation, the sum of conduction and 

convection could be accounted for by tuning the computational model so that the internal 

temperatures match the measured data. 

2. The unsteady Navier Stokes equations—This can provide a time-dependent history of the net 

mechanical power produced by the motion cycle which, when combined with experimental 

measurements of electrical power, can provide an estimate of efficiency. This time-dependent 

solution would also show the gas flow physics that are occurring inside of the convertor during 

operation. 

In the Stirling Research Laboratory at the NASA GRC, the typical experimental assembly for testing 

consists of an ASC and a heating package (to provide gross heat input to the Stirling cycle by means of an 

electric heater), both of which are encapsulated inside of an insulation package. Although the insulation 

package helps to minimize the amount of heat lost to the environment, it does not totally eliminate it. The 

ASC experimental test assembly is shown in Figure 3. 

Experimental tests using the ASC were conducted to gather temperature data along the perimeter of 

the insulation package, as well as at a variety of location along the insulation-convertor contact interface. 

The measured external temperatures were used as boundary conditions for a three-dimensional 

computational model of the ASC test assembly. As calculations were performed, the internal temperatures 

were monitored and the model tuned until the calculated internal temperatures matched measured 

experimental data. 

When performing computational simulations of the Advanced Stirling Convertor hardware version E2 

(ASC E2), there tend to be two unknowns: 

1. The thermal conductivity of the external insulation, which is Microsil Type 2. This is a micro porous 

insulation that undergoes shrinkage as it is aged, increasing the thermal conductivity over time. 

2. The net heat input consumed by the Stirling cycle. 
NASA/TM—2012-217287 4 

Figure 4.—Thermal standard hardware. 

The measured gross heat is applied to the internal volumes representing the heater in the 

computational model. When measured external temperatures are applied to the external surface of the 

insulation package in the computational mode, this provides a value for the amount of heat exiting the 

insulation and going into the laboratory environment. With a combination of the applied gross heat, the 

insulation heat loss to the environment, and the matching of internal temperatures with measurements, the 

net heat input can be calculated. For the convertor calculations, the net heat input consists of the Stirling 

cycle heat and the heat exiting the convertor at the cold end. 

For the ASC, there is presently no solid way to confirm the net heat input value that results from the 

solution of the computational model. As a result, another model called the Thermal Standard (shown in 

Fig. 4), was designed to verify the methodology used for the convertor calculations. The Thermal 

Standard has no moving parts and is made to simulate the thermal distribution that was observed during 

ASC-E2 experiments. Instead of a heat rejection via the Stirling cycle (conversion of thermal energy to 

mechanical energy), a highly conductive stationary rod is instead used to remove heat from the assembly 

during testing. The material of the highly conductive rod (GRCop-84) (Ref. 11), and its dimension were 

chosen so that the rod would remove by conduction) the same quantity of heat expected to be consumed 

by the Stirling cycle during its nominal operation. With the Thermal Standard, this verifiable heat 

quantity is a valuable quantity for the verification and validation of the methodology. 

The computational approach used was a two-step calculation methodology that includes solving two 

separate simulations. Analogous to the “two equations, two unknown” scenario that occurs frequently in 

mathematics, this computational strategy is utilizing two simulations to solve for the two unknowns. 

Measured lab data from insulation loss testing (simulated non-operating) of the Thermal Standard is used 

as boundary conditions in the first step of the solution strategy, to define the instantaneous thermal 

conductivity profile of Microsil Type 2. Then, this newly acquired Microsil Type 2 thermal conductivity 

profile is held fixed in the second simulation (simulated operation), where a finite amount of heat is 

rejected by the highly conductive copper rod. The solution of this second simulation produces the ultimate 

result, which is the net heat input. 

This document describes the details of the methodology that was applied to both the ASC and the 

Thermal Standard computational models, but focuses on the Thermal Standard. It also discusses how the 

Thermal Standard was used to estimate the error associated with using a two-step methodology to 

calculate net heat input. These efforts are on-going. 
NASA/TM—2012-217287 5 

2.0 Assembly 

Figure 5 shows the CAD model of the Thermal Standard. Although there are slight material changes 

that differentiate it from the ASC (Ref. 12), the materials were chosen so that the temperatures 

distributions throughout both are very similar. For the computational model, this geometry was cut and 

some of the volumes beyond the Cold Side Adaptor Flange (CSAF) were eliminated. This includes the 

fluid heat exchanger. Detailed hardware measurements were available in this area, and eliminating the 

unwanted volumes helped the calculations run faster. 

The materials that make up the Thermal Standard were divided in three groups. These groups include 

the Thermal Standard, the Heating Package, and the Insulation Package. 

2.1 Thermal Standard 

Figure 6 shows the contents of the Thermal Standard materials. Throughout the calculation sequences, 

the temperature-dependent thermal conductivity profiles are unchanged. 

Figure 5.—Thermal Standard geometry. 

Figure 6.—Thermal Standard components. 
NASA/TM—2012-217287 6 

2.2 Heating Package Materials 

Figure 7 shows the contents of the heating package. Throughout the calculation sequences, these 

temperature-dependent thermal conductivity profiles are also unchanged. 

2.3 Insulation Package Materials 

Figure 8 shows the contents of the insulation package materials. During the calculations, the Microsil 

thermal conductivity is modified in an effort to adjust the absolute values of the internal temperatures. At 

the beginning of the calculations, the internal temperatures are always high. Because of the behavior 

(shrinkage) of the Microsil, increasing the thermal conductivity is considered a realistic adjustment. 

Figure 7.—Heating package materials. 

Figure 8.—Insulation package materials. 

 
NASA/TM—2012-217287 7 

Figure 9.—Location of Kaowool insulation. 

Microsil is a micro-porous insulation that experiences volumetric shrinkage (and an increase in 

thermal conductivity) when heated. When it arrives at the GRC Stirling Lab, it is typically baked at 

850 C for 24 hr, which causes it to undergo 80 percent of its maximum anticipated shrinkage. 

With continued baking, the rate of shrinkage decays asymptotically. However, the bake time required 

to eliminate all of the shrinkage becomes time prohibitive. The first step in the calculations is aimed at 

defining the instantaneous thermal conductivity at the time the experimental test temperatures were 

collected. 

Numerous experimental tests have been performed with Microsil Type 2 to define its thermal 

conductivity. One of the available measured thermal conductivity profiles was provided by 

Thermophysical Properties Research Lab (TPRL) for aged Microsil Type 2. At the end of the Insulation 

Loss calculations, the thermal conductivity of Microsil had to be increased by 5 percent above the 

measured value provide by TPRL, to match the experimental measurements. 

There are three grades of Kaowool that are available for the laboratory tests. These three grades differ 

in thermal conductivity by ~10 percent. The Kaowool is packed around the perimeter of the heater block 

and the actual Thermal Standard (or ASC). Its location is shown in Figure 9. 

There are contact resistances between the Thermal Standard and the Kaowool, as well as between the 

Kaowool and the Microsil. This exists in the form of a slight air gaps or imperfect contact between nonsmooth surfaces. This is not directly accounted for in the model setup since the surface roughness and 

pressure of application would be needed. Instead, the thermal conductivity of Kaowool is modified by 

small amounts to reflect the existence of the contact resistance. 

Figure 10 shows a thermal resistance schematic of the Kaowool and the other materials that it is in 

contact with adjacent to the Thermal Standard heater head cylinder wall. Looking at Equation (2), if 

contact resistance is assumed to be zero (perfect contact with no air gaps), then the effective thermal 

conductivity of Kaowool is the same as the actual thermal conductivity. However, if the is a non-zero 

contact resistance at the contact surfaces, then the effective thermal conductivity of the Kaowool would 

be lower than its actual thermal conductivity. This was the rationale used to lower the thermal 

conductivity of Kaowool 1 percent at a time until the calculated temperatures matched measured 

temperatures. 

 (2)   th th CONTACT A th KAOWOOL th CONTACT B

eff

th

A R R R

x

A R

x k

kA

x

Q

T R

   

   

   




NASA/TM—2012-217287 8 

Figure 10.—Contact thermal resistance network. 

During the calculations, Grade 4 is used initially and slight modifications are made to it in an effort to 

fine tune the internal temperatures so they match the experimental data. There is also a 0.016 in. alumina 

disk between the nickel heater block and the heat collector plate. Once the Microsil thermal conductivity 

is modified to get the absolute value of the internal temperatures in the vicinity of the measured data, 

modifications to Kaowool and the Alumina disk are made to fine tune the temperatures. 

3.0 Computational Methodology 

The computational methodology consists of two separate calculations. The strategy involves 

simulating two different experimental tests. Test one is simulated non-operating (insulation loss), and test 

two is simulated operation via GRCop-84 rod heat rejection. There are no moving parts. For both 

simulations, slight adjustments are made to the properties of selected materials with the intention of 

matching internal temperatures observed during experiments. There are various property modifications 

and temperature mappings that need to be done to complete these calculations, and are discussed in the 

following sections. 

3.1 Adjustable Parameters 

There are four different parameters that are modified during the course of the calculations. Their 

modifications are based on the internal temperatures relative to the measured data. The parameters being 

adjusted are shown in Figure 11, and include Microsil, the alumina disk, and two independent sections of 

Kaowool. The effects of modifying the properties differ depending on the material being modified. As the 

thermal conductivity modifications were made during the calculations, the following observations were 

made with each material: 

 Microsil Thermal Conductivity: An increase causes a decrease in heat source and hot-end 

temperatures. 

 Kaowool Thermal Conductivity: An increase causes a decrease in the T between the heat source and 

the hot-end. 

 Ceramic Paper Thermal Conductivity: An increase causes a decrease in the heat source temperature. 

 Thermal Barrier Thermal Conductivity: An increase causes a decrease in the T between the heat 

source and the hot-end. 
NASA/TM—2012-217287 9 

Figure 11.—Materials that are modified during thermal loss simulations. 

Figure 12.—Portion of heater head used for generation of radiation look-up table. 

3.2 Radiation Lookup Table 

The initial steps in performing calculations with this model were done without accounting for 

radiation. Activating a radiation model on the full model requires an enormous amount of computational 

time before the solution converges. Instead, a solution is first obtained without accounting for radiation. 

Then, a radiation look-up table is applied to account for the radiation across the expansion space (air gap), 

and the calculation sequences are performed once again, until all of the relevant calculated temperatures 

match the data obtained from through measurements. 

Generation of the radiation lookup table involved making calculations on a reduced version of the 

Thermal Standard computational model. This model is shown in Figure 12. The insulation and heating 

packages are not included in this reduced calculation. 
NASA/TM—2012-217287 10 

Cold end boundary conditions (obtained from lab measurements) were applied, and a fixed 

temperature was applied to the heat collector plate. Calculations were then performed with the Discrete 

Ordinances radiation model activated. Once the solution converged, three items were collected: 

1. Area-averaged temperature of the heater head inner wall (where it interfaces with the air) 

2. Total heat entering the inner acceptor (where it interfaces with the air) 

3. Total heat entering the rod (where it interfaces with the air) 

Two radiation look tables were generated because for the insulation loss case, there was Kaowool 

insulation instead of a copper rod. 

3.3 Procedure 

A flowchart for step 1 of this solution strategy is shown in Figure 13. Step 1 is the simulation of the 

insulation loss experiment, and the heater head cylinder is filled with Kaowool insulation. Calculations 

are performed and the temperatures at the heat source and hot end are checked relative to measured data. 

If the temperatures are high, the thermal conductivity of Microsil is increased. If these temperatures are 

too low, then it is decreased. 

The temperature difference between the heat source and hot end are controlled in a similar manner. If 

the temperature difference is too big, the thermal conductivity of the alumina disk (thermal barrier) is 

increased. If it is too low, then the thermal conductivity is lowered. The previously mentioned 

modifications are typically enough to produce temperatures at the heat source and hot end that match 

measured data. 

Other modifications are required at this point to make sure temperatures at the Microsil-Kaowool 

interface match measured data. This typically involves a slight modification to the thermal conductivity of 

the Kaowool. For these calculations, Kaowool was defined as a constant in these two regions and was 

modified so that in was in the range of 0.20 W/m-K  k  0.30 W/m-K. 

At this point, the temperatures match the measured data, and the radiation look-up table is applied. 

The area-averaged temperature of the inner heater head dome is extracted from the model and the 

appropriate heat transfer rate is applied to the surface of the acceptor and the insulation (or rod if this is 

step 2). All of the previous steps are repeated while constantly updating these boundary conditions until 

all internal temperatures match measured data. This sometimes involves another adjustment to the 

Microsil, but it is minor at this point. The resulting Microsil thermal conductivity value is carried over to 

the second simulation. 

A flowchart for step 2 of this solution strategy is shown in Figure 14. In this simulation, the internal 

Kaowool is replaced with a GRCop-84 rod and Microsil is not allowed to change. The internal acceptor 

and the GRCop-84 rod are not in direct contact as they are separated by a thin layer of ceramic paper. 

When the thermal conductivity of the ceramic paper is increased ( 1 percent at a time), the temperatures 

of the heat source and hot end decrease, while increasing the amount of heat rejected by the rod. The 

opposite is also true. For step two, the ceramic paper thermal conductivity modification serves the same 

purpose as the Microsil adjustment in step one. All other adjustments are done in the same way for the 

same purpose as step 1. 
NASA/TM—2012-217287 11 

Figure 13.—Step 1: Determination of Microsil thermal conductivity. 

Figure 14.—Step 2: Determination of net heat input. 

 
NASA/TM—2012-217287 12 

4.0 Available Test Data 

A variety of experimental measurements were made to establish the thermal gradients throughout the 

test hardware. The locations of these temperature measurements are shown in Figure 15. The details of 

the experimental test and results are available (Ref. 12), but not described in this document. 

4.1 Experimental Temperature Mapping 

The external surface temperatures of the measured data are used to create the model boundary 

conditions. The measured temperatures and their intended position on the model are used to generate a 

curve fit equation, which is then directly mapped onto the model and held fixed during the duration of the 

calculations. Temperature mappings on faces were done in a similar manner and resulted in constant, 

linear, or nonlinear temperature profiles depending on the number of measurements on a particular 

surface.

4.2 Lead Wire Temperature Mapping 

An infrared (IR) camera was used to collect pictures of the lead wires and the exposed fire rods during 

testing. The post-processing of these IR images provided a temperature profile as a function of position, 

which was then mapped onto the external surface of the lead wire outer sheath. The temperature profile 

curve-fit was defined as a quadratic equation. 

4.3 Gross Heat Input 

Gross heat input produced by the fire rods was recorded during the laboratory experiments. This value 

was used to set the boundary condition of the computational fire rod. The target gross heat was divided by 

the total volume of the computational heating elements, producing a heat generation rate in W/m3

. This 

value was applied to all of the heating elements as a boundary condition. Figure 16 shows the cross 

section of an actual fire rod as it is compared to the solution volumes of the computational fire rod. 

Figure 15.—Measurement locations in thermal standard computational model. 
NASA/TM—2012-217287 13 

Figure 16.—Fire rod hardware and simulation geometry. 

5.0 Results 

The solution strategy was applied to the simulated non-operating (no rod) case. After application of 

the radiation look-up table was completed and matching of the internal temperatures was verified, the 

resulting Microsil thermal conductivity was 5 percent above the value measured by TPRL 

(Thermophysical Property Research Laboratory, Inc.). 

This value of Microsil (TPRL plus 5 percent) was then applied to the second simulation. The internal 

Kaowool was replaced with a GRCop-84 rod. The heat generation rate on the fire rods and the external 

temperature boundary conditions were updated with the appropriate boundary conditions for the 

simulated operation (14 mm rod) case. 

While holding the Microsil properties fixed, the solution strategy was applied until internal 

temperatures matched experimental data. 

Figure 17 shows the calculated and measured temperatures at the Kaowool-Microsil interface, and the 

external surface of the nickel heater block. The largest temperature difference is at TP41. Calculated 

values are ~17 C lower than the measured data. In this model, Kaowool was divided into three volumes. 

One volume is adjacent to the nickel block, the second to the heat collector and the third to the heater 

head cylinder. Adjustments to each block of Kaowool controlled each temperature at TP20, TP33, and 

TP41. 

Figure 18 shows the calculated and measured temperatures along the heater head cylinder’s exterior 

wall. Heater head (HH) locations 1 to 4 were measured during laboratory experimentation. The largest 

difference between calculations and measurements is at HH2. Predictions at this location were 12 C 

lower than what was measured in the lab. 

Figure 19 shows the calculated and measured temperatures along the GRCop-84 centerline. Stirling 

rod (SR) locations 1 to 6 were measured during laboratory experiments. The largest difference between 

calculations and measurements is at SR1. Predictions at this position were 9 C lower than what was 

measured. 

When this set of calculations was completed, the 14 mm rod was rejecting 205.5 W of heat and the 

cold end was rejecting 34.8 W of heat. When compared to the values obtained in the lab (208.7 and 

35.7 W, respectively), the calculations were 1.7 percent lower. Heat distribution results can be seen in 

Figure 20. 

At the end of these calculations, the final temperatures at the heat source and the hot end were: 

THEAT SOURCE = 994.5 C (target 995.5 C) 

THOT-END = 844.1 C (target 844.8 C) 

Because contact resistances were not included in this model, there effects were absorbed into kW1 and 

kAlO2, resulting in an adjustment that would make the effective thermal conductivities lower. 
NASA/TM—2012-217287 14 

 

 

Figure 19.—Temperatures along the centerline 

of the GRCop-84 rod. Figure 20.—Calculated heat distribution for simulated 

operation case.

Figure 17.—Temperatures on KaowoolMicrosil interface and nickel heater block 

surface. 

Figure 18.—Temperatures on the external surface of 

the heater head cylinder.
NASA/TM—2012-217287 15 

6.0 Conclusions 

Convertor and generator testing is carried out in tests designed to characterize convertor performance 

when subjected to environments intended to simulate launch and space conditions. The value of net heat 

input must be known in order to calculate convertor efficiency. In an effort to improve the accuracy of the 

efficiency calculation, numerous tasks have been performed which provided a more accurate value for net 

heat input into the ASCs, including the use of multi-dimensional numerical models to predict net heat 

input. This effort produced a methodology for making net heat input predictions, which was successfully 

validated using specially designed test hardware enabling measurement of heat transferred through a 

simulated Stirling cycle. This methodology will be applied to future ASC convertors to obtain values for 

net heat input. 

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Conversion Engineering Conference (IECEC 2011), American Institute for Aeronautics and 

Astronautics, 2011. 
REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188 

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1. REPORT DATE (DD-MM-YYYY)

01-04-2012 

2. REPORT TYPE

Technical Memorandum 

3. DATES COVERED (From - To)

4. TITLE AND SUBTITLE

A Computational Methodology for Simulating Thermal Loss Testing of the Advanced 

Stirling Convertor 

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Reid, Terry, V.; Wilson, Scott, D.; Schifer, Nicholas, A.; Briggs, Maxwell, H. 

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

WBS 138494.05.02.04.01 

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

National Aeronautics and Space Administration 

John H. Glenn Research Center at Lewis Field 

Cleveland, Ohio 44135-3191 

8. PERFORMING ORGANIZATION

 REPORT NUMBER

E-17822 

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

National Aeronautics and Space Administration 

Washington, DC 20546-0001 

10. SPONSORING/MONITOR'S

 ACRONYM(S)

NASA 

11. SPONSORING/MONITORING

 REPORT NUMBER

NASA/TM-2012-217287 

12. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified-Unlimited 

Subject Category: 20 

Available electronically at http://www.sti.nasa.gov 

This publication is available from the NASA Center for AeroSpace Information, 443-757-5802

13. SUPPLEMENTARY NOTES

14. ABSTRACT

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced 

Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs 

convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating 

conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end 

and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, 

numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including the use of multidimensional numerical models. Validation test hardware has also been used to provide a direct comparison of numerical results and validate 

the multi-dimensional numerical models used to predict convertor net heat input and efficiency. These validation tests were designed to 

simulate the temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 244.4 W. The methodology 

was applied to the multi-dimensional numerical model which resulted in a net heat input of 240.3 W. The computational methodology 

resulted in a value of net heat input that was 1.7 percent less than that measured during laboratory testing. The resulting computational 

methodology and results are discussed. 

15. SUBJECT TERMS

Computational Fluid Dynamics (CFD); Heat transfer; Stirling convertor 

16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

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21 

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STI Help Desk (email:help@sti.nasa.gov) 

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