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.


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    Title :

    Reliability-Based Design of Thermal Protection Systems with Support Vector Machines


    Contributors:

    Published in:

    Publication date :

    2019-04-12


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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