General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation-Reference-Cited by-同舟云学术

General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation

Published:2023-12 Issue:12 Volume:149 Page:
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Chakroborty Promit¹^ORCID,Dhulipala Somayajulu L. N.²,Che Yifeng³^ORCID,Jiang Wen⁴^ORCID,Spencer Benjamin W.⁴^ORCID,Hales Jason D.⁵^ORCID,Shields Michael D.⁶^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Systems Engineering, Johns Hopkins Univ., Baltimore, MD 21218. ORCID:

2. Computational Scientist, Computational Mechanics and Materials, Idaho National Laboratory, 955 Mk Simpson Blvd., Idaho Falls, ID 83415.

3. Postdoctoral Researcher, Computational Mechanics and Materials, Idaho National Laboratory, 955 Mk Simpson Blvd., Idaho Falls, ID 83415. ORCID:

4. Computational Scientist, Computational Mechanics and Materials, Idaho National Laboratory, 955 Mk Simpson Blvd., Idaho Falls, ID 83415. ORCID:

5. Manager, Computational Mechanics and Materials, Idaho National Laboratory, 955 Mk Simpson Blvd., Idaho Falls, ID 83415. ORCID:

6. Associate Professor, Dept. of Civil and Systems Engineering, Johns Hopkins Univ., Baltimore, MD 21218 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

https://ascelibrary.org/doi/pdf/10.1061/JENMDT.EMENG-7111

Reference57 articles.

1. Optimal Importance‐Sampling Density Estimator

2. Reliability of uncertain dynamical systems with multiple design points

3. Estimation of small failure probabilities in high dimensions by subset simulation

4. Important sampling in high dimensions

5. Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions

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