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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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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.
Journal ArticleDOI

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.
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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.
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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.
References
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Proceedings ArticleDOI

System Reliability-Based Design Optimization Using MPP-Based Dimension Reduction Method

TL;DR: The most probable point (MPP)-based dimension reduction method (DRM) is proposed to use for the analytic calculation of the component probability of failure and design sensitivity analysis for the system reliability-based design optimization (RBDO) is carried out.
Proceedings ArticleDOI

Monte carlo simulation in reliability based optimization applied to multidisciplinary system design

TL;DR: The work presented in the paper deals with the incorporation of Monte Carlo Simulation techniques in Reliability Based Optimization (RBO) and a strategy for performing RBO using the axis-orthogonal simulation is presented.

Real-Time Monitoring and Prediction of Airspace Safety

TL;DR: This work develops a novel model-based framework for real-time monitoring and prediction of the safety of the NAS using dynamic models of airspace operations, aircraft, and weather, along with a rigorous, mathematical treatment of uncertainty.
Journal ArticleDOI

Parametric Sensitivity Analysis for Importance Measure on Failure Probability and Its Efficient Kriging Solution

TL;DR: In this paper, the parametric sensitivity of the moment-independent importance measure (IM) on the failure probability is defined and their computational formulae derived for the purpose of identifying the influential distribution parameters.
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Monte Carlo Simulations of Wind Speed Data

TL;DR: In this article, a new Monte Carlo simulation procedure and nearby regional weather station data are used to predict wind speed and turbine energy using cumulative distribution function (CDF) graphs and Weibull shape and scale values developed from 1, 12, 20 and 24 years of record for each weather station.