Thermal Test Correlation with Stochastic Technique

Mareschi, Vincenzo; Perotto, Valter; Gorlani, Matteo

doi:10.4271/2005-01-2855

Cited by 8 publications

(4 citation statements)

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“…6 the number of iterations needed for the presented algorithms (10 to 30) to the typical number of iterations needed for genetic (25600 (van Zijl, 2013), 843 to 33072 (Jouffroy, 2007)), adaptive particle swarm optimization (6000 (van Zijl, 2013)) or the stochastic design improvement (555, (Mareschi et al, 2005)), this approach is much faster. The number of parameters of the models used in these evaluations is comparable to the complex model used in this paper, but the the number of iterations needed for the tested algorithms is 20 to 1,000 times smaller than the number of iterations reported for genetic or adaptive particle swarm algorithms.…”

Section: Discussion Of the Resultsmentioning

confidence: 99%

“…In contrast to most correlation methods developed (Jouffroy, 2007;De Palo et al, 2011;Momayez et al, 2009;Harvatine and DeMauro, 1994;Roscher, 2006;van Zijl, 2013;WenLong et al, 2011;Mareschi et al, 2005), this method will not attempt to minimize the length of the vector ||F(p) -t mes ||, but searches a root of the equation system:…”

Section: The Methodsmentioning

confidence: 99%

“…Many methods have been developed and analyzed to perform model-to-measurement correlation (Jouffroy, 2007;De Palo et al, 2011;Momayez et al, 2009;Harvatine and De Mauro, 1994;Roscher, 2006;van Zijl, 2013;WenLong et al, 2011;Mareschi et al, 2005). Most methods are based on stochastic optimization algorithms and often require several hundred iterations to converge.…”

Section: Introductionmentioning

confidence: 99%

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On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

Klement

2014

J.Aerosp. Technol. Manag.

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ABSTRACT:The correlation of a model with test results is a common task in engineering. Often genetic algorithms or adaptive particle swarm algorithms are used for this task. In this paper another approach is presented using two quasiNewton algorithms of the class defined by Broyden. A study was conducted with thermal models showing the performance of this approach. Comparing the results to other studies reveals that the approach reduces the number of iterations by several orders of magnitude; typical calculation times for model correlation times are reduced from the order of weeks and months to the order of hours and days.

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Section: Discussion Of the Resultsmentioning

confidence: 99%

Section: The Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

Klement

2014

J.Aerosp. Technol. Manag.

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“…The method is more suitable to the correction of multi-parameter and large-scale thermal models than traditional methods 1) , so the application prospects of the method in the field of space thermal model correction has attracted considerable attention from scholars, both in China and abroad, in recent years 2) , [11,12]. Mareschi et al [13] used the method to improve the efficiency of the correction of the INTEGRAL satellite thermal model, but its accuracy needs to be improved. Cheng et al [14,15] corrected a virtual satellite thermal model and obtained good effect when the optical properties of spacecraft surface coatings, contact heat transfer coefficients and so on were regarded as uncertain parameters.…”

mentioning

confidence: 99%

Application study of a correction method for a spacecraft thermal model with a Monte-Carlo hybrid algorithm

Cheng

Liu

et al. 2011

Chin. Sci. Bull.

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The correction of a thermal model for a thermally controlled satellite in ground test conditions is studied using a Monte Carlo hybrid algorithm. First, the global and local parameters are summarized according to sensitivity analyses on uncertain parameters, and then the model correction is treated as a parameter optimization problem to be solved with a hybrid algorithm. Finally, the correction of the thermal model is completed using a layered correction method. The sensitivity analysis showed that the effective emissivities across the multi-layer insulation (MLI) and the emissivities of the thermal control coating are global parameters, while the contact heat transfer coefficients are local parameters. After correction, the deviations between the calculated and test values were all within ±3°C. The final results prove that the method in this study is superior to traditional methods and satisfies the requirements for thermal model correction.

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Efficient Correlation Method for Satellite Thermal Analysis Model Using Multiple Linear Regression and Optimization Algorithms

Kang

Kim

Shin

et al. 2023

Int. J. Aeronaut. Space Sci.

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Thermal Test Correlation with Stochastic Technique

Cited by 8 publications

References 1 publication

On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

Application study of a correction method for a spacecraft thermal model with a Monte-Carlo hybrid algorithm

Efficient Correlation Method for Satellite Thermal Analysis Model Using Multiple Linear Regression and Optimization Algorithms

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