Extrema Prediction and Fatigue Assessment of Highly Non-Gaussian Random Processes Using a Homogenous Reproduction Method-Reference-Cited by-同舟云学术

Extrema Prediction and Fatigue Assessment of Highly Non-Gaussian Random Processes Using a Homogenous Reproduction Method

Published:2020-04 Issue:4 Volume:146 Page:04020018
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Zheng X. Y.¹,Gao S.²^ORCID,Huang Y.³

Affiliation:

1. Professor, Div. of Ocean Science and Technology, Shenzhen International Graduate School, Tsinghua Univ., Shenzhen 518055, China.

2. Ph.D. Candidate, School of Naval Architecture and Ocean Engineering, Dalian Univ. of Technology, Dalian 116024, China (corresponding author). ORCID: .

3. Professor, School of Naval Architecture and Ocean Engineering, Dalian Univ. of Technology, Dalian 116024, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0001746

Reference50 articles.

1. Comparison of spectral methods for fatigue analysis of broad-band Gaussian random processes

2. Efficient multidimensional regularization for Volterra series estimation

3. Critical review and latest developments of a class of simulation algorithms for strongly non-Gaussian random fields

4. OCEAN WAVE SIMULATION FOR ENGINEERING DESIGN

5. Evaluation of mechanical component fatigue behavior under random loads: Indirect frequency domain method

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