Journal ArticleDOI
Probability, Reliability and Statistical Methods in Engineering Design
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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).read more
Citations
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Proceedings ArticleDOI
Multimodal Reliability Assessment for Complex Engineering Applications using Efficient Global Optimization
TL;DR: The application of ecient global optimization to reliability assessment is described to provide a method that eciently characterizes the limit state throughout the uncertain space and is both accurate for any arbitrarily shaped limit state and computationally ecient even for expensive response functions.
Journal ArticleDOI
Complexity science of multiscale materials via stochastic computations
Wing Kam Liu,Larbi Siad,Rong Tian,Sang Hoon Lee,Dockjin Lee,Xiaolei Yin,Wei Chen,Stephanie Chan,Gregory B. Olson,Lars Erik Lindgen,Mark F. Horstemeyer,Yoon Suk Chang,Jae-Boong Choi,Young Jin Kim +13 more
TL;DR: In this article, a multiresolution data sets mechanics framework is proposed to predict the governing laws of the materials microstructure evolution and assess the impact of multiscale material design, geometry design of a structure, and manufacturing process conditions, by following the cause-effect relationships from structure to property and then to performance.
Journal ArticleDOI
Reliability–sensitivity analysis using dimension reduction methods and saddlepoint approximations
Xianzhen Huang,Yimin Zhang +1 more
Journal ArticleDOI
Reliability-based design optimization with confidence level under input model uncertainty due to limited test data
TL;DR: In this paper, reliability-based design optimization (RBDO) with the confidence level for input normal random variables is proposed to offset the inaccurate estimation of the input statistical model by using adjusted standard deviation and correlation coefficient that include the effect of inaccurate estimation.
Proceedings ArticleDOI
Epistemic Uncertainty in the Calculation of Margins
TL;DR: This paper examines three methods used in propagating epistemic uncertainties: interval analysis, Dempster-Shafer evidence theory, and second-order probability, and the use of surrogate methods in epistemic analysis, both surrogate-based optimization in interval analysis and use of polynomial chaos expansions to provide upper and lower bounding approximations.
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.
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
Anirban Basudhar,Samy Missoum +1 more
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
Sankaran Mahadevan,Ramesh Rebba +1 more
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.