Nonparametric importance sampling for wind turbine reliability analysis with stochastic computer models

The Annals of Applied Statistics ◽

10.1214/21-aoas1490 ◽

2021 ◽

Vol 15 (4) ◽

Author(s):

Shuoran Li ◽

Young Myoung Ko ◽

Eunshin Byon

Keyword(s):

Wind Turbine ◽

Reliability Analysis ◽

Importance Sampling ◽

Computer Models

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Uncertainty modeling in reliability analysis of floating wind turbine support structures

Renewable Energy ◽

10.1016/j.renene.2020.10.068 ◽

2021 ◽

Vol 165 ◽

pp. 88-108

Author(s):

Salem Okpokparoro ◽

Srinivas Sriramula

Keyword(s):

Wind Turbine ◽

Reliability Analysis ◽

Uncertainty Modeling ◽

Support Structures ◽

Floating Wind Turbine

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Importance Sampling for Time-Variant Reliability Analysis

IEEE Access ◽

10.1109/access.2021.3054470 ◽

2021 ◽

Vol 9 ◽

pp. 20933-20941

Author(s):

Jian Wang ◽

Runan Cao ◽

Zhili Sun

Keyword(s):

Reliability Analysis ◽

Importance Sampling

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Reliability analysis of wind turbine combined TBM and CBM

2021 6th Asia Conference on Power and Electrical Engineering (ACPEE) ◽

10.1109/acpee51499.2021.9437137 ◽

2021 ◽

Author(s):

Jiaqi Zhang ◽

Hongsheng Su ◽

Li Chen ◽

Rui Yang

Keyword(s):

Wind Turbine ◽

Reliability Analysis

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Approximate Importance Sampling Approach Based on DSmT in Structural Reliability Analysis

Design, Construction, Rehabilitation, and Maintenance of Bridges ◽

10.1061/47630(409)6 ◽

2011 ◽

Author(s):

Donghua Chen ◽

Bohai Ji

Keyword(s):

Reliability Analysis ◽

Importance Sampling ◽

Structural Reliability ◽

Structural Reliability Analysis ◽

Sampling Approach

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Spatial reliability analysis of a wind turbine blade cross section subjected to multi-axial extreme loading

Structural Safety ◽

10.1016/j.strusafe.2017.01.007 ◽

2017 ◽

Vol 66 ◽

pp. 27-37 ◽

Author(s):

N. Dimitrov ◽

R.D. Bitsche ◽

J.P. Blasques

Keyword(s):

Wind Turbine ◽

Reliability Analysis ◽

Turbine Blade ◽

Cross Section ◽

Wind Turbine Blade

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Cross-entropy-based directional importance sampling with von Mises-Fisher mixture model for reliability analysis

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.108306 ◽

2021 ◽

pp. 108306

Author(s):

Xiaobo Zhang ◽

Zhenzhou Lu ◽

Kai Cheng

Keyword(s):

Reliability Analysis ◽

Mixture Model ◽

Importance Sampling ◽

Cross Entropy ◽

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An efficient hybrid reliability analysis method based on active learning Kriging model and multimodal‐optimization‐based importance sampling

International Journal for Numerical Methods in Engineering ◽

10.1002/nme.6847 ◽

2021 ◽

Author(s):

Tai Wang ◽

Xufeng Yang ◽

Mi Caiying

Keyword(s):

Active Learning ◽

Reliability Analysis ◽

Importance Sampling ◽

Kriging Model ◽

Multimodal Optimization ◽

Analysis Method ◽

Hybrid Reliability

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Application of measured loads to wind turbine fatigue and reliability analysis

10.2514/6.1997-949 ◽

1997 ◽

Author(s):

Paul Veers ◽

Steven Winterstein ◽

Paul Veers ◽

Steven Winterstein

Keyword(s):

Wind Turbine ◽

Reliability Analysis

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Efficient reliability analysis coupling importance sampling using adaptive subset simulation and PGD model reduction

PAMM ◽

10.1002/pamm.201900169 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Annika Robens-Radermacher ◽

Jörg F. Unger

Keyword(s):

Model Reduction ◽

Reliability Analysis ◽

Importance Sampling ◽

Subset Simulation

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Reliability analysis of wind turbine system using importance measures

2015 Annual IEEE India Conference (INDICON) ◽

10.1109/indicon.2015.7443292 ◽

2015 ◽

Author(s):

Urvashi Chauhan ◽

G. L. Pahuja ◽

Vijander Singh ◽

Asha Rani

Keyword(s):

Wind Turbine ◽

Reliability Analysis ◽

Wind Turbine System

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