Journal ArticleDOI
Improved Moving Least Square-Based Multiple Dimension Decomposition (MDD) Technique for Structural Reliability Analysis
Reads0
Chats0
TLDR
This paper presents the state-of-the-art on different moving least square (MLS) based dimension decomposition schemes for reliability analysis and demonstrates a modified version for high fidelity analysis.Abstract:
This paper presents the state-of-the-art on different moving least square (MLS)-based dimension decomposition schemes for reliability analysis and demonstrates a modified version for high fidelity read more
Citations
More filters
Journal Article
State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning
Sourav Das,Solomon Tesfamariam +1 more
TL;DR: This study demonstrates the necessity of the design of experiment schemes for the Physics-Informed Neural Network (PINN), which belongs to the supervised learning class, and sees that the Hammersley sampling-based PINN performs better than other DoE sample strategies.
Journal ArticleDOI
Stochastic configuration network for structural reliability analysis
TL;DR: Wang et al. as discussed by the authors proposed an efficient structural reliability analysis method based on stochastic configuration networks (SCNs), which is constructed by learning the real performance function of the structure.
Journal ArticleDOI
A novel imprecise stochastic process model for time-variant or dynamic uncertainty quantification
TL;DR: In this article , an imprecise probabilistic model is employed to characterize the uncertainty at each time point for a time-variant parameter, which provides an effective tool for problems with limited experimental samples.
References
More filters
Book
Stochastic Finite Elements: A Spectral Approach
Roger Ghanem,Pol D. Spanos +1 more
TL;DR: In this article, a representation of stochastic processes and response statistics are represented by finite element method and response representation, respectively, and numerical examples are provided for each of them.
Book
Mechanics of Laminated Composite Plates and Shells : Theory and Analysis, Second Edition
TL;DR: The use of composite materials in engineering structures continues to increase dramatically, and there have been significant advances in modeling for general and composite materials and structures in particular as discussed by the authors. But the use of composites is not limited to the aerospace domain.
Journal ArticleDOI
Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
TL;DR: In this article, global sensitivity indices for rather complex mathematical models can be efficiently computed by Monte Carlo (or quasi-Monte Carlo) methods, which are used for estimating the influence of individual variables or groups of variables on the model output.
Journal ArticleDOI
Surrogate-based Analysis and Optimization
Nestor V. Queipo,Raphael T. Haftka,Wei Shyy,Tushar Goel,Rajkumar Vaidyanathan,P. Kevin Tucker +5 more
TL;DR: The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.
Journal ArticleDOI
Global sensitivity analysis using polynomial chaos expansions
TL;DR: In this article, generalized polynomial chaos expansions (PCE) are used to build surrogate models that allow one to compute the Sobol' indices analytically as a post-processing of the PCE coefficients.