... in the latent space instead, i.e., based on x nom = G ( c p , 0 , 0 ). We will use “robust (uniform)” to refer to this optimization scenario. Fig. 10 An example of metasurface design with fabrication uncertainty modeled as uniform boundary variation [ 6 , 16 , 17 ] An example of metasurface...

... ]. Natural Sciences and Engineering Research Council of Canada 10.13039/501100000038 RGPIN-2019-06601 metal additive manufacturing finite element analysis uncertainty quantification validation metric metamodel metamodeling risk-based design simulation-based design uncertainty modeling...

... risk-based design simulation-based design uncertainty analysis uncertainty modeling 19 03 2022 14 06 2022 24 06 2022 04 08 2022 This work is in part a work of the U.S. Government. ASME disclaims all interest in the U.S. Government’s contributions. Contributed...

... 22 07 2022 model validation uncertainty correlation angle metric limited data Mahalanobis distance design validation uncertainty analysis uncertainty modeling National Natural Science Foundation of China 10.13039/501100001809 52111540267 State Key Laboratory...

... in the J ournal of M echanical D esign . 01 12 2021 28 04 2022 04 05 2022 13 06 2022 Gaussian processes data fusion calibration emulation manifold learning machine learning metamodeling uncertainty modeling National Aeronautics and Space Administration...

... sensing model updating design for manufacturing simulation-based design uncertainty analysis uncertainty modeling In an additive manufacturing (AM) process, the material is stacked in a layer-wise fashion based on a CAD model of the part geometry and a predefined slicing pattern. AM...

... 2022 13 06 2022 sequential optimal experimental design deep reinforcement learning uncertainty quantification Gaussian processes data-driven design design of experiments design optimization machine learning metamodeling uncertainty modeling Design of experiments (DOE) [ 1...

... from the so-called stochastic kriging (SK) [ 31 ], which focuses on the mean of repeated measurements. The variance of the mean prediction vanishes as the number of replications becomes large. That is, the uncertainty modeled in SK is purely epistemic and is reducible. In our case, the simulation noise...

... uncertainty modeling Traditional deterministic topology optimization (DTO) aims to achieve the optimal distribution of the predefined usable material in a certain design domain. Schemes including density-based approach [ 1 ], level-set method [ 2 , 3 ], evolutionary structural optimization [ 4...

... optimization generative design machine learning uncertainty modeling 21 04 2021 13 10 2021 15 10 2021 06 12 2021 Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . Email: fuge@umd.edu Email: wchen459...

... 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 autonomous ground vehicles (AGVs...

... the efficiency and is applied to reliability analysis of positioning accuracy for an industrial robot. reliability analysis evidence theory joint focal element Kriging model industrial robot reliability in design uncertainty analysis uncertainty modeling Uncertainties in relevant quantities...

... and methodology energy systems design machine learning multidisciplinary design and optimization systems design uncertainty analysis uncertainty modeling Engineering and Physical Sciences Research Council 10.13039/501100000266 EP/R513052/1 World Bank Group 10.13039/100004421...

... [ 3 ], where the aforementioned “models” connect component models from multiple domains of processing, microstructure, and properties, also known as p-s-p, the modeling chain. approximation-based optimal design multidisciplinary design and optimization simulation-based design uncertainty...

... design decision support design guidance complexity management uncertainty management knowledge management computer-aided engineering design for manufacturing design representation uncertainty modeling A decade ago, the need for disruptive change in the manufacturing sector emerged...

... group moment generating function robotic systems uncertainty analysis uncertainty modeling Robotic manipulators have been widely applied in practical engineering, such as automobile and aerospace manufacturing, automatic assembling plants of precise products and medical surgery [ 1...

... by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 11 05 2020 18 08 2020 22 08 2020 17 12 2020 reliability in design simulation-based design uncertainty modeling Time-dependent reliability analysis of vibratory systems...

... or locally optimal solutions, and how this is affected by their tools. 03 03 2020 07 08 2020 22 08 2020 16 10 2020 design optimization multiobjective optimization robust design uncertainty modeling Engineering designers use complex computational models to represent...

... learning metamodeling reliability in design uncertainty analysis uncertainty modeling Off-road vehicle mobility analysis and its modeling and simulation (M&S) are important steps in developing and operating off-road vehicles [ 1 ]. In battlefield especially, using M&S tools to predict...

... assimilation dimension reduction spatio-temporal prediction metamodeling uncertainty analysis uncertainty modeling Email: xzhao28@umd.edu Email: azarm@umd.edu Email: balab@umd.edu Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical...