The primary objective of this work is to develop a computationally efficient and accurate approach to a reliability analysis of thermal protection systems using support vector machines. An adaptive sampling approach is introduced, which informs an iterative support vector machine approximation of the limit-state function, which is used for measuring reliability. The proposed sampling approach efficiently adds samples along the limit-state function until the reliability approximation is converged. This methodology is applied to two mathematical functions to test and demonstrate the applicability. Then, the adaptive sampling-based support vector machine approach is applied to the reliability analysis of a thermal protection system. The results of all three problems highlight the potential capability of the new approach in terms of accuracy and computational savings for determining thermal protection system reliability.
Reliability-Based Design of Thermal Protection Systems with Support Vector Machines
Journal of Spacecraft and Rockets ; 56 , 4 ; 1073-1083
2019-04-12
11 pages
Article (Journal)
Electronic Resource
English
Design Space Decomposition Using Support Vector Machines for Reliability-Based Design Optimization
British Library Conference Proceedings | 2006
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