This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
MonteCarlo Techniques in Thermal Analysis – Design Margins Determination Using Reduced Models and Experimental Data
Technical Paper
2006-01-2113
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
In the paper several application techniques of MonteCarlo (MC) method applied to thermal analysis of space vehicles are presented. Although these methods are widely used in other engineering domains, their introduction to the thermal one is quite recent and not fully developed in the industrial practice.
This paper aims at showing that, even without demanding computation resources (all what presented has been obtained with a single processor PC) MonteCarlo analysis techniques, in a preliminary design phase, can support and integrate engineering judgment of the thermal designer. In particular, it is exploited the applicability of the method to reduced thermal models, with a clear advantage in terms of computation time. An original approach is proposed, and results are shown.
The papers shows the applicability of the MC method to the case when experimental data of the uncertain parameters are available, using the bootstrap re-sampling techniques. A third domain is the margin determination, using the queue definition. Finally, the MC tools are used as design instruments, and a design optimization is presented.
Citation
Molina, M. and Finzi, A., "MonteCarlo Techniques in Thermal Analysis – Design Margins Determination Using Reduced Models and Experimental Data," SAE Technical Paper 2006-01-2113, 2006, https://doi.org/10.4271/2006-01-2113.Also In
References
- Stochastic approach to Spacecraft Thermal control system Lamela F. Sepulveda, A. SAE ICES conference 2000
- “Stochastic analysis in space engineering: a survey of existing tools and methodologies for thermal analysis” Molina Marco Amalia Ercoli Finzi - CONGRESSO AIDAA 2003
- Cullimore, B “Optimization, Data Correlation, and Parametric Analysis Features in SINDA/FLUINT Version 4.0;” SAE- 981574 2001
- Cullimore, B “Automated determination of Worst-Case design scenarios” SAE 2003-01-2609 2003
- Space Engineering- Mechanics-Thermal Control
- Welch, M. A comparison of satellite flight temperatures with thermal balance test data SAE 2003-01-2460 2003
- Douglas C. Montgomery Design and Analysis of Experiments Wiley