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Proceedings Papers

Descriptor Aided Bayesian Optimization for Mixed Variable Materials Design With High Dimensional Qualitative Variables

Akshay Iyer, Suraj Yerramilli, James M. Rondinelli, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A049, August 14–17, 2022

Paper No: DETC2022-90177

DOI: https://doi.org/10.1115/DETC2022-90177

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Topics: Design, Optimization

Journal Articles

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Akshay Iyer, Suraj Yerramilli, James M. Rondinelli, Daniel W. Apley, Wei Chen

J. Mech. Des. March 2023, 145(3): 031701.

Paper No: MD-22-1317

DOI: https://doi.org/10.1115/1.4055848

Published Online: October 31, 2022

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Topics: Design, Modeling, Optimization

Journal Articles

Multi-Model Bayesian Optimization for Simulation-Based Design

Siyu Tao, Anton van Beek, Daniel W. Apley, Wei Chen

J. Mech. Des. November 2021, 143(11): 111701.

Paper No: MD-20-1500

DOI: https://doi.org/10.1115/1.4050738

Published Online: May 4, 2021

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Topics: Design, Feedback, Optimization, Couplings, Simulation

Proceedings Papers

Bayesian Optimization for Simulation-Based Design of Multi-Model Systems

Siyu Tao, Anton van Beek, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A022, August 17–19, 2020

Paper No: DETC2020-22651

DOI: https://doi.org/10.1115/DETC2020-22651

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Topics: Design, Optimization, Simulation, Algorithms, Couplings, Electronic packaging, Engineering design, Feedback, Modeling, Simulation models

Journal Articles

Integration of Normative Decision-Making and Batch Sampling for Global Metamodeling

Anton van Beek, Siyu Tao, Matthew Plumlee, Daniel W. Apley, Wei Chen

J. Mech. Des. March 2020, 142(3): 031114.

Paper No: MD-19-1444

DOI: https://doi.org/10.1115/1.4045601

Published Online: January 25, 2020

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Topics: Approximation, Decision making, Design, Dynamic programming, Probability, Risk, Simulation, Uncertainty, Optimization, Preferences

Journal Articles

Reduction of Epistemic Model Uncertainty in Simulation-Based Multidisciplinary Design

Zhen Jiang, Shishi Chen, Daniel W. Apley, Wei Chen

J. Mech. Des. August 2016, 138(8): 081403.

Paper No: MD-15-1693

DOI: https://doi.org/10.1115/1.4033918

Published Online: June 30, 2016

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Topics: Resource allocation, Simulation, Uncertainty, Design

Journal Articles

Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem

Wei Li, Shishi Chen, Zhen Jiang, Daniel W. Apley, Zhenzhou Lu, Wei Chen

J. Verif. Valid. Uncert. March 2016, 1(1): 011004.

Paper No: VVUQ-15-1007

DOI: https://doi.org/10.1115/1.4031983

Published Online: February 19, 2016

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Topics: Calibration, Machine learning, Uncertainty, Displacement

Proceedings Papers

A Structural Equation Modeling Based Approach for Identifying Key Descriptors in Microstructural Materials Design

Yichi Zhang, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2015, Volume 2B: 41st Design Automation Conference, V02BT03A011, August 2–5, 2015

Paper No: DETC2015-47473

DOI: https://doi.org/10.1115/DETC2015-47473

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Topics: Design, Modeling, Algorithms, Materials properties, Epoxy adhesives, Epoxy resins, Redundancy (Engineering)

Proceedings Papers

Resource Allocation for Reduction of Epistemic Uncertainty in Simulation-Based Multidisciplinary Design

Zhen Jiang, Shishi Chen, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2015, Volume 2B: 41st Design Automation Conference, V02BT03A036, August 2–5, 2015

Paper No: DETC2015-47302

DOI: https://doi.org/10.1115/DETC2015-47302

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Topics: Design, Resource allocation, Simulation, Uncertainty, Electronic packaging, Optimization, Sensitivity analysis, Simulation models, Uncertainty analysis

Journal Articles

New Metrics for Validation of Data-Driven Random Process Models in Uncertainty Quantification

Hongyi Xu, Zhen Jiang, Daniel W. Apley, Wei Chen

J. Verif. Valid. Uncert. June 2016, 1(2): 021002.

Paper No: VVUQ-14-1007

DOI: https://doi.org/10.1115/1.4031813

Published Online: December 10, 2015

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Topics: Stochastic processes, Uncertainty quantification

Journal Articles

A Spatial-Random-Process Based Multidisciplinary System Uncertainty Propagation Approach With Model Uncertainty

Zhen Jiang, Wei Li, Daniel W. Apley, Wei Chen

J. Mech. Des. October 2015, 137(10): 101402.

Paper No: MD-14-1779

DOI: https://doi.org/10.1115/1.4031096

Published Online: August 10, 2015

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Topics: Design, Uncertainty, Modeling, Uncertainty quantification, Simulation, Optimization

Proceedings Papers

A System Uncertainty Propagation Approach With Model Uncertainty Quantification in Multidisciplinary Design

Zhen Jiang, Wei Li, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2014, Volume 2B: 40th Design Automation Conference, V02BT03A029, August 17–20, 2014

Paper No: DETC2014-34708

DOI: https://doi.org/10.1115/DETC2014-34708

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Topics: Design, Uncertainty, Uncertainty quantification, Engineering disciplines, Simulation, Design under uncertainty, Electronic packaging, Uncertainty analysis

Proceedings Papers

Preposterior Analysis to Select Experimental Responses for Improving Identifiability in Model Uncertainty Quantification

Zhen Jiang, Wei Chen, Daniel W. Apley

Proc. ASME. IDETC-CIE2013, Volume 3B: 39th Design Automation Conference, V03BT03A051, August 4–7, 2013

Paper No: DETC2013-12457

DOI: https://doi.org/10.1115/DETC2013-12457

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Topics: Uncertainty quantification, Calibration, Uncertainty, Computer simulation, Modeling, Physics, Simply supported beams

Proceedings Papers

Objective–Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Paul D. Arendt, Wei Chen, Daniel W. Apley

Proc. ASME. IDETC-CIE2012, Volume 3: 38th Design Automation Conference, Parts A and B, 717-726, August 12–15, 2012

Paper No: DETC2012-70639

DOI: https://doi.org/10.1115/DETC2012-70639

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Topics: Design, Simulation, Uncertainty, Noise (Sound), Interpolation, Algorithms, Computer simulation, Design under uncertainty, Engineering design, Optimization

Journal Articles

Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Paul D. Arendt, Daniel W. Apley, Wei Chen

J. Mech. Des. May 2013, 135(5): 051005.

Paper No: MD-12-1307

DOI: https://doi.org/10.1115/1.4023922

Published Online: April 23, 2013

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Topics: Design, Uncertainty, Interpolation, Algorithms, Noise (Sound), Simulation

Journal Articles

Improving Identifiability in Model Calibration Using Multiple Responses

Paul D. Arendt, Daniel W. Apley, Wei Chen, David Lamb, David Gorsich

J. Mech. Des. October 2012, 134(10): 100909.

DOI: https://doi.org/10.1115/1.4007573

Published Online: September 28, 2012

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Topics: Calibration, Computers, Uncertainty

Journal Articles

Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability

Paul D. Arendt, Daniel W. Apley, Wei Chen

J. Mech. Des. October 2012, 134(10): 100908.

DOI: https://doi.org/10.1115/1.4007390

Published Online: September 28, 2012

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Topics: Calibration, Computers, Uncertainty, Simulation

Proceedings Papers

Improving Identifiability in Model Calibration Using Multiple Responses

Paul D. Arendt, Wei Chen, Daniel W. Apley

Proc. ASME. IDETC-CIE2011, Volume 5: 37th Design Automation Conference, Parts A and B, 1213-1222, August 28–31, 2011

Paper No: DETC2011-48623

DOI: https://doi.org/10.1115/DETC2011-48623

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Topics: Calibration, Uncertainty, Computer simulation, Engineering simulation, Simulation, Approximation, Complex systems, Design, Physics, Simulation models

Proceedings Papers

Updating Predictive Models: Calibration, Bias Correction and Identifiability

Paul D. Arendt, Wei Chen, Daniel W. Apley

Proc. ASME. IDETC-CIE2010, Volume 1: 36th Design Automation Conference, Parts A and B, 1089-1098, August 15–18, 2010

Paper No: DETC2010-28828

DOI: https://doi.org/10.1115/DETC2010-28828

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Topics: Calibration, Uncertainty, Computers, Computer simulation, Design, Engineering simulation, Model validation, Physics, Simulation

Proceedings Papers

Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments

Jun Liu, Daniel W. Apley, Wei Chen

Proc. ASME. IDETC-CIE2006, Volume 1: 32nd Design Automation Conference, Parts A and B, 1183-1192, September 10–13, 2006

Paper No: DETC2006-99500

DOI: https://doi.org/10.1115/DETC2006-99500

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Topics: Computers, Design, Uncertainty, Interpolation, Optimization, Automotive engines, Chaos, Containers, Design under uncertainty, Noise (Sound)

Journal citation

NARROW

Descriptor Aided Bayesian Optimization for Mixed Variable Materials Design With High Dimensional Qualitative Variables

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Multi-Model Bayesian Optimization for Simulation-Based Design

Bayesian Optimization for Simulation-Based Design of Multi-Model Systems

Integration of Normative Decision-Making and Batch Sampling for Global Metamodeling

Reduction of Epistemic Model Uncertainty in Simulation-Based Multidisciplinary Design

Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem

A Structural Equation Modeling Based Approach for Identifying Key Descriptors in Microstructural Materials Design

Resource Allocation for Reduction of Epistemic Uncertainty in Simulation-Based Multidisciplinary Design

New Metrics for Validation of Data-Driven Random Process Models in Uncertainty Quantification

A Spatial-Random-Process Based Multidisciplinary System Uncertainty Propagation Approach With Model Uncertainty

A System Uncertainty Propagation Approach With Model Uncertainty Quantification in Multidisciplinary Design

Preposterior Analysis to Select Experimental Responses for Improving Identifiability in Model Uncertainty Quantification

Objective–Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Improving Identifiability in Model Calibration Using Multiple Responses

Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability

Improving Identifiability in Model Calibration Using Multiple Responses

Updating Predictive Models: Calibration, Bias Correction and Identifiability

Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments

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