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Keywords: uncertainty quantification
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Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. August 2024, 146(8): 081704.
Paper No: MD-23-1618
Published Online: March 5, 2024
... of reliability analysis and design optimization. The proposed multi-fidelity multi-task machine learning model utilizes a Bayesian framework, which significantly improves the performance of the predictive model and provides uncertainty quantification of the prediction. Additionally, the model provides a highly...
Journal Articles
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. January 2023, 145(1): 012001.
Paper No: MD-22-1210
Published Online: October 7, 2022
... for Manufacturing Committee of ASME for publication in the J ournal of M echanical D esign . 08 04 2022 21 07 2022 29 07 2022 07 10 2022 metal additive manufacturing finite element analysis uncertainty quantification validation metric metamodel metamodeling risk-based design...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2022, 144(9): 091704.
Paper No: MD-21-1740
Published Online: June 13, 2022
...@vanderbilt.edu Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 03 12 2021 02 05 2022 04 05 2022 13 06 2022 digital twin additive manufacturing uncertainty quantification process design process control...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2022, 144(9): 091705.
Paper No: MD-21-1780
Published Online: June 13, 2022
... Experimental Design ,” Int. J. Uncertainty Quantif. , 4 ( 6 ), pp. 479 – 510 . 10.1615/Int.J.UncertaintyQuantification.2014006730 [29] Shen , W. , and Huan , X. , 2021 , “ Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2021, 143(9): 091701.
Paper No: MD-20-1678
Published Online: February 11, 2021
... be prevented even at 95% confidence when 30 samples are used in Case 1 since the proposed surrogate model uncertainty quantification is basically obtained from the surrogate model. It could be related to the uncertainty of the hyperparameter issue (i.e., modeling issue) caused by too sparse simulation samples...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2021, 143(3): 031709.
Paper No: MD-20-1421
Published Online: December 15, 2020
... Division of ASME for publication in the J ournal of M echanical D esign . Manuscript received June 1, 2020; final manuscript received October 12, 2020; published online December 15, 2020. Special Editor Mian Li. 01 06 2020 12 10 2020 14 10 2020 15 12 2020 uncertainty...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2021, 143(5): 051702.
Paper No: MD-19-1898
Published Online: October 28, 2020
.... , and Wang , W. , 2020 , Uncertainty quantification for Bayesian Optimization . preprint arXiv:2002.01569 . [19] Pandita , P. , Bilionis , I. , Panchal , J. , Gautham , B. P. , Joshi , A. , and Zagade , P. , 2018 , “ Stochastic Multiobjective Optimization on a Budget...
Journal Articles
Journal Articles
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. October 2019, 141(10): 101404.
Paper No: MD-18-1592
Published Online: July 10, 2019
.... 26 07 2018 28 05 2019 29 05 2019 optimal experimental design Kullback–Leibler divergence uncertainty quantification information gain mutual information Gaussian processes Bayesian inference Engineering problems require either computationally intensive computer codes...
Journal Articles
Publisher: ASME
Article Type: Special Section: Methods For Uncertainty Characterizations In Existing Models Through Uncertainly Quantification Or Calibration
J. Mech. Des. October 2012, 134(10): 100909.
Published Online: September 28, 2012
... identifiability uncertainty quantification Multiple response emulator Quantification of model uncertainty is important to better understand how well a computer model represents physical reality. Two primary sources of uncertainty that account for differences between a computer model and physical reality...
Journal Articles
Publisher: ASME
Article Type: Special Section: Methods For Uncertainty Characterizations In Existing Models Through Uncertainly Quantification Or Calibration
J. Mech. Des. October 2012, 134(10): 100908.
Published Online: September 28, 2012
.... 27 08 2011 03 07 2012 21 09 2012 28 09 2012 calibration identifiability model updating uncertainty quantification Kriging Gaussian processes Uncertainty is ubiquitous in engineering design. Although recent years have seen a proliferation of research in design...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. August 2012, 134(8): 081003.
Published Online: July 23, 2012
... programming multi-objective optimization multibody dynamics uncertainty quantification generalized polynomial chaos Design engineers cannot quantify exactly every aspect of a given system. These uncertainties frequently create difficulties in accomplishing design goals and can lead to poor...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2008, 130(2): 021101.
Published Online: December 27, 2007
... experiments and the computer model, a Bayesian approach is employed to develop a prediction model as the replacement of the original computer model for the purpose of design. Based on the uncertainty quantification with the Bayesian prediction and, subsequently, that of a design objective, some decision...