Gaussian Surrogate Dimension Reduction for Efficient Reliability-Based Design Optimization
Author:
Affiliation:
1. Air Force Research Laboratory
2. Wright State University
Publisher
American Institute of Aeronautics and Astronautics
Reference20 articles.
1. Efficient Global Surrogate Modeling for Reliability-Based Design Optimization
2. Chaudhuri, A., Marques, A. N., Lam, R., and Willcox, K. E. “Reusing Information for Multifidelity Active Learning in Reliability-Based Design Optimization,” AIAA Scitech 2019 Forum.
3. Sampling-based RBDO using the stochastic sensitivity analysis and Dynamic Kriging method
4. Exact and Invariant Second-Moment Code Format
5. The Monte Carlo Method
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Efficient Multi-Fidelity Modeling of Constraints for Design Optimization Based on Expected Usefulness;AIAA Scitech 2021 Forum;2021-01-04
2. Gaussian Surrogate Dimension Reduction for Efficient Reliability-Based Design Optimization;AIAA Journal;2020-11
3. Analytic Sensitivities of Stochastic and Statistical Moments for Uncertainty Quantification;AIAA AVIATION 2020 FORUM;2020-06-08
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