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Proceedings Papers

Uncertainty Quantification for Dissimilar Material Joints Under Corrosion Environment

Parth Bansal, Zhuoyuan Zheng, Yumeng Li

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A039, August 14–17, 2022

Paper No: DETC2022-89654

DOI: https://doi.org/10.1115/DETC2022-89654

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Topics: Corrosion, Machine learning, Physics, Resilience, Uncertainty quantification

Proceedings Papers

Uncertainty Quantification of Physics-Based Label-Free Deep Learning and Probabilistic Prediction of Extreme Events

Huiru Li, Jianhua Yin, Xiaoping Du

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A001, August 14–17, 2022

Paper No: DETC2022-88277

DOI: https://doi.org/10.1115/DETC2022-88277

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Topics: Physics, Reliability, Uncertainty, Uncertainty quantification, Artificial neural networks, Errors, Machine learning, Design, Linkages, Regression models

Proceedings Papers

Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty

Wei (Wayne) Chen, Doksoo Lee, Oluwaseyi Balogun, Wei Chen

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A042, August 14–17, 2022

Paper No: DETC2022-89707

DOI: https://doi.org/10.1115/DETC2022-89707

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Topics: Design, Uncertainty, Manufacturing, Design under uncertainty, Optimization, Engineering design, Modeling, Reliability-based optimization, Shapes, Topology

Proceedings Papers

Uncertainty Quantification and Reduction Using Sensitivity Analysis and Hessian Derivatives

Josefina Sánchez, Kevin Otto

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A013, August 17–19, 2021

Paper No: DETC2021-71037

DOI: https://doi.org/10.1115/DETC2021-71037

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Topics: Design, Sensitivity analysis, Uncertainty, Uncertainty quantification, Noise (Sound), Experimental design, Jacobian matrices, Modeling, Optimization, Simulation

Proceedings Papers

Multifidelity Uncertainty Quantification for Online Simulations of Automotive Propulsion Systems

Hang Yang, Alex Gorodetsky, Yuji Fujii, Kon-Well Wang

Proc. ASME. IDETC-CIE2021, Volume 9: 17th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC), V009T09A043, August 17–19, 2021

Paper No: DETC2021-67585

DOI: https://doi.org/10.1115/DETC2021-67585

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Topics: Engineering simulation, Propulsion systems, Simulation, Uncertainty quantification, Chaos, Polynomials, Uncertainty, Errors, Modeling, Nonlinear systems

Proceedings Papers

Uncertainty Quantification With Maximum Entropy Method for Fatigue Life Estimation

S. M. Nielsen, H. A. Hougaard, O. Balling

Proc. ASME. IDETC-CIE2020, Volume 5: 24th Reliability, Stress Analysis, and Failure Prevention Conference (RSAFP), V005T05A008, August 17–19, 2020

Paper No: DETC2020-22728

DOI: https://doi.org/10.1115/DETC2020-22728

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Topics: Entropy, Fatigue life, Uncertainty quantification, Uncertainty, Ball bearings, Density, Fatigue, Finite element analysis, Maintenance, Probability

Proceedings Papers

Semi-Supervised Deep Learning for High-Dimensional Uncertainty Quantification

Zequn Wang, Mingyang Li

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A001, August 17–19, 2020

Paper No: DETC2020-22204

DOI: https://doi.org/10.1115/DETC2020-22204

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Topics: Dimensions, Evolutionary algorithms, Uncertainty quantification

Proceedings Papers

Quantification of Uncertainties Distributed in Network-Like Systems

Zihan Wang, Hongyi Xu

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A048, August 17–19, 2020

Paper No: DETC2020-22082

DOI: https://doi.org/10.1115/DETC2020-22082

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Topics: Simulation, Uncertainty, Uncertainty quantification, Additive manufacturing, Engineering systems and industry applications, Gaussian distribution, Heat conduction, Metamaterials, Stochastic processes

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

Proceedings Papers

Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation

Rohit Tripathy, Ilias Bilionis

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A074, August 18–21, 2019

Paper No: DETC2019-98099

DOI: https://doi.org/10.1115/DETC2019-98099

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Topics: Artificial neural networks, Chaos, Construction, Dimensions, Modeling, Polynomials, Response surface methodology, Space, Stochastic systems, Uncertainty

Proceedings Papers

Model Based Root Cause Analysis of Manufacturing Quality Problems Using Uncertainty Quantification and Sensitivity Analysis

Kevin Otto, Josefina Sanchez Mosqueda

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A071, August 18–21, 2019

Paper No: DETC2019-97766

DOI: https://doi.org/10.1115/DETC2019-97766

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Topics: Manufacturing, Root cause analysis, Sensitivity analysis, Simulation, Uncertainty quantification

Proceedings Papers

A Strategy for Adaptive Sampling of Multi-Fidelity Gaussian Processes to Reduce Predictive Uncertainty

Sayan Ghosh, Jesper Kristensen, Yiming Zhang, Waad Subber, Liping Wang

Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A024, August 18–21, 2019

Paper No: DETC2019-98418

DOI: https://doi.org/10.1115/DETC2019-98418

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Topics: Uncertainty, Design, Algorithms, Calibration, Computer software, Experimental design, Fluidized beds, Modeling, Optimization, Steady state

Proceedings Papers

Uncertainty Quantification of Reliability Analysis Under Surrogate Model Uncertainty Using Gaussian Process

Sangjune Bae, Chanyoung Park, Nam H. Kim

Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A055, August 26–29, 2018

Paper No: DETC2018-85541

DOI: https://doi.org/10.1115/DETC2018-85541

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Topics: Event history analysis, Uncertainty, Uncertainty quantification, Reliability, Chaos, Gaussian distribution, Simulation

Proceedings Papers

Assessing the Impact of Product Use Variation on Environmental Sustainability

Melissa Tensa, Vincenzo Ferrero, Donovan Ross, Bryony DuPont

Proc. ASME. IDETC-CIE2018, Volume 4: 23rd Design for Manufacturing and the Life Cycle Conference; 12th International Conference on Micro- and Nanosystems, V004T05A031, August 26–29, 2018

Paper No: DETC2018-85694

DOI: https://doi.org/10.1115/DETC2018-85694

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Topics: Sustainability, Uncertainty, Cycles, Decision making, Engineering design processes, Life cycle assessment, Uncertainty quantification

Proceedings Papers

Uncertainty Quantification and Validation of Lattice Structures Fabricated by Selective Laser Melting

Recep M. Gorguluarslan, Seung-Kyum Choi, Hae-jin Choi

Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A085, August 6–9, 2017

Paper No: DETC2017-67438

DOI: https://doi.org/10.1115/DETC2017-67438

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Topics: Lasers, Melting, Uncertainty quantification, Struts (Engineering), Uncertainty, Additive manufacturing, Simulation models, Accounting, Compression, Elasticity

Proceedings Papers

Towards Model Order Reduction for Uncertainty Propagation in Blast-Induced Traumatic Brain Injury

Athanasios P. Iliopoulos, John G. Michopoulos, Philip Avery, Charbel Farhat, Kirubel Teferra, Siddiq Qidwai

Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A086, August 6–9, 2017

Paper No: DETC2017-67556

DOI: https://doi.org/10.1115/DETC2017-67556

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Topics: Traumatic brain injury, Uncertainty, Dynamic response, Manufacturing, Physics, Shock (Mechanics), Uncertainty quantification

Proceedings Papers

Management of Sampling Uncertainty Using Conservative Estimate of Probability in Bayesian Network

Sangjune Bae, Nam H. Kim, Seung-gyo Jang

Proc. ASME. IDETC-CIE2017, Volume 2B: 43rd Design Automation Conference, V02BT03A053, August 6–9, 2017

Paper No: DETC2017-67620

DOI: https://doi.org/10.1115/DETC2017-67620

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Topics: Probability, Uncertainty, Design, Safety, Failure, Sensitivity analysis, Errors, Shapes, Uncertainty quantification

Proceedings Papers

Bayesian Network Learning for Uncertainty Quantification

Zhen Hu, Sankaran Mahadevan

Proc. ASME. IDETC-CIE2017, Volume 2A: 43rd Design Automation Conference, V02AT03A044, August 6–9, 2017

Paper No: DETC2017-68187

DOI: https://doi.org/10.1115/DETC2017-68187

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Topics: Uncertainty quantification, Algorithms, Design, Topology, Calibration, Engineering design, Event history analysis, Modeling, Probability

Proceedings Papers

Uncertainty Quantification in Metamodel-Based Reliability Prediction

Saideep Nannapaneni, Zhen Hu, Sankaran Mahadevan

Proc. ASME. IDETC-CIE2016, Volume 2B: 42nd Design Automation Conference, V02BT03A023, August 21–24, 2016

Paper No: DETC2016-59225

DOI: https://doi.org/10.1115/DETC2016-59225

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Topics: Reliability, Uncertainty quantification, Uncertainty, Event history analysis, Errors, Modeling, Optimization, Stress, Approximation, Cantilever beams

Proceedings Papers

Molecular Dynamics Simulation With Interval-Valued Interatomic Potentials

Anh Tran, Yan Wang

Proc. ASME. IDETC-CIE2016, Volume 1A: 36th Computers and Information in Engineering Conference, V01AT02A022, August 21–24, 2016

Paper No: DETC2016-59431

DOI: https://doi.org/10.1115/DETC2016-59431

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Topics: Molecular dynamics simulation, Uncertainty, Uncertainty quantification, Molecular dynamics, Simulation, Pressure, Reliability, Temperature

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NARROW

Uncertainty Quantification for Dissimilar Material Joints Under Corrosion Environment

Uncertainty Quantification of Physics-Based Label-Free Deep Learning and Probabilistic Prediction of Extreme Events

Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty

Uncertainty Quantification and Reduction Using Sensitivity Analysis and Hessian Derivatives

Multifidelity Uncertainty Quantification for Online Simulations of Automotive Propulsion Systems

Uncertainty Quantification With Maximum Entropy Method for Fatigue Life Estimation

Semi-Supervised Deep Learning for High-Dimensional Uncertainty Quantification

Quantification of Uncertainties Distributed in Network-Like Systems

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

Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation

Model Based Root Cause Analysis of Manufacturing Quality Problems Using Uncertainty Quantification and Sensitivity Analysis

A Strategy for Adaptive Sampling of Multi-Fidelity Gaussian Processes to Reduce Predictive Uncertainty

Uncertainty Quantification of Reliability Analysis Under Surrogate Model Uncertainty Using Gaussian Process

Assessing the Impact of Product Use Variation on Environmental Sustainability

Uncertainty Quantification and Validation of Lattice Structures Fabricated by Selective Laser Melting

Towards Model Order Reduction for Uncertainty Propagation in Blast-Induced Traumatic Brain Injury

Management of Sampling Uncertainty Using Conservative Estimate of Probability in Bayesian Network

Bayesian Network Learning for Uncertainty Quantification

Uncertainty Quantification in Metamodel-Based Reliability Prediction

Molecular Dynamics Simulation With Interval-Valued Interatomic Potentials

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