... simulation-based design uncertainty analysis uncertainty modeling Journal of Mechanical Design. Received April 19, 2023; Accepted manuscript posted September 01, 2023. doi:10.1115/1.4063404 Copyright © 2023 by ASME A multi-fidelity integration method for reliability analysis of industrial robots Jinhui...

... reliability in design uncertainty analysis uncertainty modeling Rare events are events that have low probabilities of occurring (e.g., p ≤ 10 − 4 ), but are significant enough to justify an accurate study. For example, in the engineering design process of structures, assessing the probability...

... uncertainty analysis Hebei Province Science and Technology Support Program 10.13039/501100005064 B2021005004 National Natural Science Foundation of China 10.13039/501100001809 52275244 51905146 12102122 In practical engineering problems, uncertainties generally exist...

.../j.ress.2020.107256 [7] Zhang , Z. , Ruan , X. X. , Duan , M. F. , and Jiang , C. , 2018 , “ An Efficient Epistemic Uncertainty Analysis Method Using Evidence Theory ,” Comput. Methods Appl. Mech. Eng. , 339 , pp. 443 – 466 . 10.1016/j.cma.2018.04.033 [8] Jiang , C...

... for publication in the J ournal of M echanical D esign . 13 06 2022 21 12 2022 31 12 2022 24 01 2023 design optimization time- and space-dependent reliability analysis uncertainty analysis Engineers always encounter uncertainty in material properties, part dimensions...

... Calibration ,” Rob. Comput. Integr. Manuf. , 29 ( 2 ), pp. 370 – 384 . 10.1016/j.rcim.2012.09.007 [6] Hafezipour , M. , and Khodaygan , S. , 2017 , “ An Uncertainty Analysis Method for Error Reduction in End-Effector of Spatial Robots With Joint Clearances and Link Dimension Deviations...

... simulations reduced-order model microstructural uncertainties machine learning metamodeling multiobjective optimization uncertainty analysis Multiscale models are increasingly employed to quantify the effects of manufacturing-induced microscopic defects on the performance of macroscopic...

... FY2021 reliability-based design optimization (RBDO) reliability analysis sequential sampling surrogate modeling Gaussian process regression (GPR) space mapping design methodology metamodeling reliability in design uncertainty analysis 14 06 2022 01 09 2022 02 09 2022...

.... , 2020 , “ AKOIS: An Adaptive Kriging Oriented Importance Sampling Method for Structural System Reliability Analysis ,” Struct. Saf. , 82 , p. 101876 . 10.1016/j.strusafe.2019.101876 [10] Zhang , X. F. , Pandey , M. D. , and Luo , H. Y. , 2021 , “ Structural Uncertainty Analysis...

... machine learning risk-based design simulation-based design uncertainty analysis uncertainty modeling As an emerging technique, autonomous ground vehicles (AGVs) have gained much attention in different applications in recent years, since they can increase traffic efficiency, reduce...

... Committee of ASME for publication in the J ournal of M echanical D esign . 26 02 2022 02 06 2022 21 06 2022 22 07 2022 model validation uncertainty correlation angle metric limited data Mahalanobis distance design validation uncertainty analysis uncertainty modeling...

... learning metamodeling reliability in design uncertainty analysis National Natural Science Foundation of China 10.13039/501100001809 51875525 51905475 52111540267 Natural Science Foundation of Zhejiang Province 10.13039/501100004731 LY21E050008 Structural reliability...

... and implement uncertainty analysis under different uncertainty levels (UL) and distributions. Then, with the use of a set of orthogonal polynomials for uniform and Gaussian distribution, respectively, the high dimensional model representation of the mapping relationship is approximately expressed...

... variability. A virtual representation of the LPBF process is first constructed using a physics-based model. To enable faster computation required in uncertainty analysis and decision-making, the physics-based model is replaced by a cheaper surrogate model. A two-step surrogate model is proposed when...

... of M echanical D esign . 18 10 2021 16 02 2022 17 02 2022 08 04 2022 conceptual design data-driven design design theory and methodology machine learning uncertainty analysis The designs for new engineering products are developed within the design space...

... Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 28 05 2021 24 11 2021 01 12 2021 17 01 2022 design theory systems design systems engineering uncertainty analysis Flexible design is a well-established...

.... , 2005 , “ High-Order Collocation Methods for Differential Equations With Random Inputs ,” SIAM J. Sci. Comput. , 27 ( 3 ), pp. 1118 – 1139 . 10.1137/040615201 [39] Xiu , D. , 2007 , “ Efficient Collocational Approach for Parametric Uncertainty Analysis ,” Commun. Comput. Phys. , 2 ( 2...

... functionally graded materials (FGMs) graphene platelets (GPLs) critical load Gauss–Laguerre quadrature realization vector set design optimization design theory and methodology robust design uncertainty analysis uncertainty modeling Traditional deterministic topology optimization (DTO) aims...

... rapidly exploring random tree uncertain environment mobile robots reliability in design simulation-based design uncertainty analysis uncertainty modeling Automotive Research Center 10.13039/100008192 W56HZV-04-2-0001 Identifying a reliable mission path is important for off-road...

... in design uncertainty analysis Directorate for Engineering 10.13039/100000084 1923799 In engineering design, physics-based reliability is commonly used to predict the probability of failure using physical models derived from physical principles. Such a model is called a limit-state...