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Journal Articles

Uncertainty Separation Method for Simulation With Image and Numerical Data

Xiaoping Du
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. March 2024, 9(1): 011004.
Paper No: VVUQ-24-1003
https://doi.org/10.1115/1.4065637
Published Online: June 7, 2024
View Article titled, Uncertainty Separation Method for Simulation With Image and Numerical Data
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Topics: Separation (Technology), Simulation, Uncertainty, Uncertainty quantification
Journal Articles

Uncertainty Quantification With Mixed Data by Hybrid Convolutional Neural Network for Additive Manufacturing

Jianhua Yin, Zhen Hu, Xiaoping Du
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. September 2024, 10(3): 031103.
Paper No: RISK-23-1081
https://doi.org/10.1115/1.4065444
Published Online: May 28, 2024
View Article titled, Uncertainty Quantification With Mixed Data by Hybrid Convolutional Neural Network for Additive Manufacturing
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Journal Articles

Accounting for Machine Learning Prediction Errors in Design

Xiaoping Du
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051709.
Paper No: MD-23-1484
https://doi.org/10.1115/1.4064278
Published Online: January 29, 2024
View Article titled, Accounting for Machine Learning Prediction Errors in Design
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Topics: Design, Uncertainty
Proceedings Papers

Quantification Model Uncertainty of Label-Free Machine Learning for Multidisciplinary Systems Analysis

Huiru Li, Jitesh H. Panchal, Xiaoping Du
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A045, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-112948
https://doi.org/10.1115/DETC2023-112948
View Paper titled, Quantification Model Uncertainty of Label-Free Machine Learning for Multidisciplinary Systems Analysis
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Topics: Artificial neural networks, Machine learning, Systems analysis, Uncertainty, Errors, Engineering disciplines, Combustion, Design, Engineering systems and industry applications, Uncertainty quantification
Proceedings Papers

Accounting for Model Uncertainty in Machine Learning Assisted Mechanical Design

Xiaoping Du
Proc. ASME. IDETC-CIE2023, Volume 3B: 49th Design Automation Conference (DAC), V03BT03A068, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116622
https://doi.org/10.1115/DETC2023-116622
View Paper titled, Accounting for Model Uncertainty in Machine Learning Assisted Mechanical Design
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Topics: Accounting, Design, Design engineering, Machine learning, Uncertainty
Journal Articles

Time- and Space-Dependent Reliability-Based Design With Envelope Method

Hao Wu, Xiaoping Du
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2023, 145(3): 031708.
Paper No: MD-22-1351
https://doi.org/10.1115/1.4056599
Published Online: January 24, 2023
View Article titled, Time- and Space-Dependent Reliability-Based Design With Envelope Method
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Topics: Design, Event history analysis, Optimization, Reliability, Risk-based design, Failure, Probability
Proceedings Papers

Envelope Method for Time- and Space-Dependent Reliability-Based Design

Hao Wu, Xiaoping Du
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A002, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89492
https://doi.org/10.1115/DETC2022-89492
View Paper titled, Envelope Method for Time- and Space-Dependent Reliability-Based Design
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Topics: Design, Reliability, Uncertainty
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
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-88277
https://doi.org/10.1115/DETC2022-88277
View Paper titled, Uncertainty Quantification of Physics-Based Label-Free Deep Learning and Probabilistic Prediction of Extreme Events
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Topics: Physics, Reliability, Uncertainty, Uncertainty quantification, Artificial neural networks, Errors, Machine learning, Design, Linkages, Regression models
Proceedings Papers

Teaching Machine Learning for Analysis and Design to Mechanical Engineering Students

Xiaoping Du, Jianhua Yin
Proc. ASME. IDETC-CIE2022, Volume 4: 19th International Conference on Design Education (DEC), V004T04A007, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-87482
https://doi.org/10.1115/DETC2022-87482
View Paper titled, Teaching Machine Learning for Analysis and Design to Mechanical Engineering Students
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Topics: Design, Machine learning, Mechanical engineering, Students, Teaching, Education, Machining
Journal Articles

Envelope Method for Time- and Space-Dependent Reliability Prediction

Hao Wu, Xiaoping Du
Journal: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg
Publisher: ASME
Article Type: Research-Article
ASME J. Risk Uncertainty Part B. December 2022, 8(4): 041201.
Paper No: RISK-21-1071
https://doi.org/10.1115/1.4054171
Published Online: April 28, 2022
View Article titled, Envelope Method for Time- and Space-Dependent Reliability Prediction
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Topics: Failure, Probability, Reliability, Approximation
Proceedings Papers

High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables

Jianhua Yin, Xiaoping Du
Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A012, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-70067
https://doi.org/10.1115/DETC2021-70067
View Paper titled, High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables
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Topics: Accounting, Dimensions, Event history analysis, Reliability
Proceedings Papers

A Bayesian Approach to Recovering Missing Component Dependence for System Reliability Prediction via Synergy Between Physics and Data

Huiru Li, Xiaoping Du
Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A009, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-67958
https://doi.org/10.1115/DETC2021-67958
View Paper titled, A Bayesian Approach to Recovering Missing Component Dependence for System Reliability Prediction via Synergy Between Physics and Data
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Topics: Physics, Reliability
Journal Articles

High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables

Jianhua Yin, Xiaoping Du
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2022, 144(4): 041702.
Paper No: MD-21-1105
https://doi.org/10.1115/1.4051982
Published Online: November 11, 2021
View Article titled, High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables
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Topics: Dimensions, Event history analysis, Reliability, Failure, Probability
Includes: Supplementary data
Journal Articles

Recovering Missing Component Dependence for System Reliability Prediction via Synergy Between Physics and Data

Huiru Li, Xiaoping Du
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2022, 144(4): 041701.
Paper No: MD-21-1346
https://doi.org/10.1115/1.4052624
Published Online: November 9, 2021
View Article titled, Recovering Missing Component Dependence for System Reliability Prediction via Synergy Between Physics and Data
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Topics: Reliability, Stress, Failure, Physics
Journal Articles

Probabilistic Feasibility Design of a Laser Powder Bed Fusion Process Using Integrated First-Order Reliability and Monte Carlo Methods

Lingbin Meng, Xiaoping Du, Brandon McWilliams, Jing Zhang
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. September 2021, 143(9): 091004.
Paper No: MANU-20-1170
https://doi.org/10.1115/1.4050544
Published Online: March 29, 2021
View Article titled, Probabilistic Feasibility Design of a Laser Powder Bed Fusion Process Using Integrated First-Order Reliability and Monte Carlo Methods
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Topics: Design, Reliability, Lasers, Simulation
Journal Articles

A Safety Factor Method for Reliability-Based Component Design

Jianhua Yin, Xiaoping Du
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2021, 143(9): 091705.
Paper No: MD-20-1572
https://doi.org/10.1115/1.4049881
Published Online: March 19, 2021
View Article titled, A Safety Factor Method for Reliability-Based Component Design
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Topics: Design, Reliability, Safety
Journal Articles

Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface

Xinpeng Wei, Jianxun Zhao, Xiaoming He, Zhen Hu, Xiaoping Du, Daoru Han
Journal: Journal of Verification, Validation and Uncertainty Quantification
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. March 2021, 6(1): 011006.
Paper No: VVUQ-20-1029
https://doi.org/10.1115/1.4050073
Published Online: March 9, 2021
View Article titled, Adaptive Kriging Method for Uncertainty Quantification of the Photoelectron Sheath and Dust Levitation on the Lunar Surface
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Topics: Dust, Levitation, Photoelectrons, Uncertainty quantification, Errors, Electric potential
Journal Articles

Physics-Based Gaussian Process Method for Predicting Average Product Lifetime in Design Stage

Xinpeng Wei, Daoru Han, Xiaoping Du
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. August 2021, 21(4): 041006.
Paper No: JCISE-20-1217
https://doi.org/10.1115/1.4049509
Published Online: February 11, 2021
View Article titled, Physics-Based Gaussian Process Method for Predicting Average Product Lifetime in Design Stage
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Topics: Design, Failure, Physics, Reliability, Stochastic processes, Event history analysis, Statistics, Testing, Errors, Experimental design
Proceedings Papers

Towards a Better Understanding of Modeling Feasibility Robustness in Engineering Design

Xiaoping Du, Wei Chen
Proc. ASME. DETC99, Volume 1: 25th Design Automation Conference, 1289-1300, September 12–16, 1999
Publisher: American Society of Mechanical Engineers
Paper No: DETC99/DAC-8565
https://doi.org/10.1115/DETC99/DAC-8565
View Paper titled, Towards a Better Understanding of Modeling Feasibility Robustness in Engineering Design
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Topics: Engineering design, Modeling, Robustness, Design, Optimization, Probability, Statistical analysis, Corners (Structural elements), Evaluation methods, Event history analysis
Proceedings Papers

A Most Probable Point Based Method for Uncertainty Analysis

Xiaoping Du, Wei Chen
Proc. ASME. IDETC-CIE2000, Volume 2: 26th Design Automation Conference, 429-438, September 10–13, 2000
Publisher: American Society of Mechanical Engineers
Paper No: DETC2000/DAC-14263
https://doi.org/10.1115/DETC2000/DAC-14263
View Paper titled, A Most Probable Point Based Method for Uncertainty Analysis
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Topics: Uncertainty analysis, Uncertainty, Algorithms, Complex systems, Cycles, Design, Engine design, Probability, Risk