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Journal ArticleDOI

Probability, Reliability and Statistical Methods in Engineering Design

P.E. James T. P. Yao
- 01 Jan 2001 - 
- Vol. 127, Iss: 1, pp 101-101
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This article is published in Journal of Structural Engineering-asce.The article was published on 2001-01-01. It has received 451 citations till now. The article focuses on the topics: Probabilistic design & Reliability (statistics).

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Citations
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Journal ArticleDOI

A Novel Risk Assessment for Complex Structural Systems

TL;DR: A hybrid risk assessment approach is proposed by intelligently integrating the stochastic finite element method, and the response surface method, capable of estimating the probability just before failure considering all major sources of nonlinearity and uncertainty, eliminating the deficiencies of the currently available reliability methods.
Proceedings ArticleDOI

Creep Life Uncertainty Assessment of a Gas Turbine Airfoil

TL;DR: In this article, a complex multi-physics environment has been created to automate the bulk creep life assessment of a gas turbine airfoil for a land-based, heavy duty power generation unit.
Journal ArticleDOI

A novel reliability evaluation method for large engineering systems

TL;DR: In this article, a hybrid approach consisting of the stochastic finite element method (SFEM) developed by the author and his research team using FORM, response surface method (RSM), an interpolation scheme, and advanced factorial schemes is proposed.
Journal ArticleDOI

Bayesian Sensitivity Analysis and Uncertainty Integration for Robust Optimization

TL;DR: This paper presents a comprehensive methodology that combines uncertainty quantification, uncertainty propagation, and design optimization using a Bayesian framework to replace the expensive physics models and improve the computational efficiency.
References
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Journal ArticleDOI

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

TL;DR: Practical guidelines for verification and validation of NMS models and simulations are established that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies.
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Adaptive Designs of Experiments for Accurate Approximation of a Target Region

TL;DR: An iterative strategy to build designs of experiments is proposed, which is based on an explicit trade-off between reduction of global uncertainty and exploration of the regions of interest, which shows that a substantial reduction of error can be achieved in the crucial regions.
Journal ArticleDOI

Adaptive explicit decision functions for probabilistic design and optimization using support vector machines

TL;DR: This article presents a methodology to generate explicit decision functions using support vector machines (SVM) and proposes an adaptive sampling scheme that updates the decision function.
Journal ArticleDOI

Validation of reliability computational models using Bayes networks

TL;DR: The methodology includes uncertainty in the experimental measurement, and the posterior and prior distributions of the model output are used to compute a validation metric based on Bayesian hypothesis testing.
Journal ArticleDOI

Adaptive probability analysis using an enhanced hybrid mean value method

TL;DR: In this article, an adaptive probability analysis method is proposed to generate the probability distribution of the output performance function by identifying the propagation of input uncertainty to output uncertainty, which is based on an enhanced hybrid mean value (HMV+) analysis in the performance measure approach.