Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification

Richa Verma; Dinesh Kumar; Kazuma Kobayashi; Syed Alam

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arXiv · 2210.07521

Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification

Richa Verma·Dinesh Kumar·Kazuma Kobayashi·Syed Alam

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Abstract

Robust optimization is a method for optimization under uncertainties in engineering systems and designs for applications ranging from aeronautics to nuclear. In a robust design process, parameter variability (or uncertainty) is incorporated into the engineering systems' optimization process to assure the systems' quality and reliability. This chapter focuses on a robust optimization approach for developing robust and reliable advanced systems and explains the framework for using uncertainty quantification and optimization techniques. For the uncertainty analysis, a polynomial chaos-based approach is combined with the optimization algorithms MOSA (Multi-Objective Simulated Annealing), and the process is discussed with a simplified test function. For the optimization process, gradient-free genetic algorithms are considered as the optimizer scans the whole design space, and the optimal values are not always dependent on the initial values.

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Richa Verma, Dinesh Kumar, Kazuma Kobayashi, Syed Alam. 2022-10-14. Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification. https://arxiv.org/abs/2210.07521

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