Survey and Evaluation of Multilayer Insulation Heat Transfer Measurements

Doenecke, Jochen

doi:10.4271/932117

Cited by 16 publications

(7 citation statements)

References 16 publications

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“…Also, in the same study, the empirical constant 𝐶𝐶 𝑒𝑒 in the solid conduction equation was modified for a wider range of temperature in between 80 K to 300 K. Equation of 𝐶𝐶 𝑒𝑒 is shown in Eq. ( 7) ε = 0.011823 + 6.17562𝑥𝑥10 −5 𝑇𝑇 (6) HTFF 160-5 𝐶𝐶 𝑒𝑒 = 0.008(−0.2005673 + 3.2843027)0.011823 + 6.17562𝑥𝑥10 −5 𝑇𝑇 2 (7) Gas conduction equation shown in Eq. ( 4) requires the accommodation factor and the 𝐶𝐶 𝑔𝑔 values.…”

Section: Layer By Layer MLI Calculation Using a Separated Mode Equationmentioning

confidence: 99%

“…After the iteration process, the heat flux prediction of MLI blanket and the temperature distribution of shields can be obtained. Doenecke [7] investigated many experimental data in the literature and developed an equation for prediction of thermal performance of MLI blankets based on these experimental data. With this equation, heat flux prediction of MLI blankets for spacecraft applications can be calculated for different number of shields, shield perforation and blanket areas.…”

Section: Introductionmentioning

confidence: 99%

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Heat Flux Prediction Accuracy Assessment of Separated Mode and Doenecke Equations for MLI Blankets

Er¹,

Ekici²

2022

Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering

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Assessment of thermal performance of Multilayer Insulation (MLI) blankets is necessary to achieve thermal design criteria of the spacecraft applications where the MLI blankets are massively employed. This assessment can be done by either experimental observations or by the empirical and numerical equations which predicts the heat flux through MLI blankets with limited accuracies. In this paper, two different heat flux prediction equations, Layer by Layer MLI Calculation Using a Separated Mode Equation and Doenecke Equation, were discussed, and the required numerical programming codes for these equations were generated in MATLAB. In addition, an in-house experimental study for two different MLI blankets at 146 K and 198 K cold boundary temperatures was introduced and explained. The experimental setup and the experimental steps were explained. The steady state heat flux results of MLI blankets were used to evaluate the prediction accuracies of discussed equations based on the generated codes. The accuracy of equations was compared with each other and with the experimental data. Based on this study, the heat flux prediction accuracies of separated mode equation and Doenecke equation were calculated to be 13.2% and 7.3% with respect to experimental data for 8 layer MLI blanket sample for 198 K and 146 K cold boundary temperatures. As for 22 layer MLI blanket sample, heat flux prediction accuracies of separated mode equation and Doenecke equation were calculated to be 13.2% and 11.8% with respect to experimental data obtained at the same cold boundary temperatures.

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Section: Layer By Layer MLI Calculation Using a Separated Mode Equationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heat Flux Prediction Accuracy Assessment of Separated Mode and Doenecke Equations for MLI Blankets

Er¹,

Ekici²

2022

Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering

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“…The heat flux of radiation-dominated MLI was calculated through the iterative calculation of Equations (7) and (8) for a set of initial trial values of the radiation heat flux and boundary temperature. The effective emittance and heat transfer coefficient were estimated from the calculated results of heat flux of the radiation-dominated MLI, as shown in Figures 9 and 10.…”

Section: Confirmation Of Temperature Dependence Of MLI Thermal Permentioning

confidence: 99%

Temperature Dependence of Thermal Performance of Space Using Multilayer Insulation

Kawasaki

Okazaki

Murakami

2012

42nd International Conference on Environmental Systems

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“…The SINDA model of cryocooler operation used a bivariate array for the cryocooler performance, with load capability dependent on both ambient temperature and coldfinger temperature. The effective emissivity (ε*) of the MLI in the SINDA model was a temperature dependent array derived from tested values, with an average value of about 0.05 [5]. In general, the cryogenic portion of the experiment was modeled separately from the ambient temperature portions.…”

Section: Thermal Modelingmentioning

confidence: 99%

Thermal Design and Analysis for the Cryogenic MIDAS Experiment

Ruth

1997

SAE Technical Paper Series

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The Materials In Devices As Superconductors (MIDAS) spaceflight experiment is a NASA payload which launched in September 1996 on the Shuttle, and was transferred to the Mir Space Station for several months of operation. MIDAS was developed and built at NASA Langley Research Center (LaRC). The primary objective of the experiment was to determine the effects of microgravity and spaceflight on the electrical properties of high-temperature superconductive (HTS) materials. The thermal challenge on MIDAS was to maintain the superconductive specimens at or below 80 K for the entire operation of the experiment, including all ground testing and 90 days of spaceflight operation. Cooling was provided by a small tactical cryocooler. The superconductive specimens and the coldfinger of the cryocooler were mounted in a vacuum chamber, with vacuum levels maintained by an ion pump. The entire experiment was mounted for operation in a stowage locker inside Mir, with the only heat dissipation capability provided by a cooling fan exhausting to the habitable compartment. The thermal environment on Mir can potentially vary over the range 5 to 40°C; this was the range used in testing, and this wide range adds to the difficulty in managing the power dissipated from the experiment's active components.Many issues in the thermal design are discussed, including: thermal isolation methods for the cryogenic samples; design for cooling to cryogenic temperatures; cryogenic epoxy bonds; management of ambient temperature components' self-heating; and fan cooling of the enclosed locker. Results of the design are also considered, including the thermal gradients across the HTS samples and cryogenic thermal strap, electronics and thermal sensor cryogenic performance, and differences between ground and flight performance. Modeling was performed in both SINDA-85 and MSC/PATRAN (with direct geometry import from the CAD design tool Pro/Engineer). Advantages of both types of models are discussed. Correlation of several models to ground testing and flight data (where available) is presented. Both SINDA and PATRAN models predicted the actual thermal performance of the experiment well, even without post-flight correlation adjustments of the models.

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Survey and Evaluation of Multilayer Insulation Heat Transfer Measurements

Cited by 16 publications

References 16 publications

Heat Flux Prediction Accuracy Assessment of Separated Mode and Doenecke Equations for MLI Blankets

Heat Flux Prediction Accuracy Assessment of Separated Mode and Doenecke Equations for MLI Blankets

Temperature Dependence of Thermal Performance of Space Using Multilayer Insulation

Thermal Design and Analysis for the Cryogenic MIDAS Experiment

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