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Journal Articles

An LSTM-Based Ensemble Learning Approach for Time-Dependent Reliability Analysis

Mingyang Li, Zequn Wang

J. Mech. Des. March 2021, 143(3): 031702.

Paper No: MD-20-1043

DOI: https://doi.org/10.1115/1.4048625

Published Online: November 10, 2020

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Topics: Event history analysis, Modeling, Reliability, Stochastic processes

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

Designing Deep Transfer Networks for Bearing Fault Diagnosis With Heterogeneous Data Fusion

Yunsheng Su, Zequn Wang

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A041, August 17–19, 2020

Paper No: DETC2020-22203

DOI: https://doi.org/10.1115/DETC2020-22203

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Topics: Artificial neural networks, Bearings, Data fusion, Design, Fault diagnosis, Optimization

Proceedings Papers

Reliability-Based Reinforcement Learning Under Uncertainty

Zequn Wang, Narendra Patwardhan

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A038, August 17–19, 2020

Paper No: DETC2020-22019

DOI: https://doi.org/10.1115/DETC2020-22019

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Topics: Optimization, Reliability, Uncertainty, Control equipment, Design, Dynamics (Mechanics), Modeling, Pendulums, Poles (Building), Reliability-based optimization

Proceedings Papers

Design of Control Systems Using Active Uncertainty Reduction-Based Reinforcement Learning

Zequn Wang, Narendra Patwardhan

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A036, August 17–19, 2020

Paper No: DETC2020-22014

DOI: https://doi.org/10.1115/DETC2020-22014

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Topics: Control systems, Design, Robotics, Uncertainty, Complex systems, Control equipment, Dynamics (Mechanics), Modeling, Optimization, Robustness

Proceedings Papers

LSTM-Based Ensemble Learning for Time-Dependent Reliability Analysis

Mingyang Li, Zequn Wang

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A035, August 17–19, 2020

Paper No: DETC2020-22006

DOI: https://doi.org/10.1115/DETC2020-22006

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Topics: Event history analysis, Stochastic processes

Journal Articles

Reliability-Based Multifidelity Optimization Using Adaptive Hybrid Learning

Mingyang Li, Zequn Wang

ASME J. Risk Uncertainty Part B. June 2020, 6(2): 021005.

Paper No: RISK-19-1034

DOI: https://doi.org/10.1115/1.4044773

Published Online: March 30, 2020

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Topics: Design, Optimization, Reliability, Algorithms

Journal Articles

Active Resource Allocation for Reliability Analysis With Model Bias Correction

Mingyang Li, Zequn Wang

J. Mech. Des. May 2019, 141(5): 051403.

Paper No: MD-18-1565

DOI: https://doi.org/10.1115/1.4042344

Published Online: January 11, 2019

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Topics: Event history analysis, Reliability, Resource allocation, Simulation, Simulation models, Modeling, Probability, Failure

Journal Articles

Confidence-Driven Design Optimization Using Gaussian Process Metamodeling With Insufficient Data

Mingyang Li, Zequn Wang

J. Mech. Des. December 2018, 140(12): 121405.

Paper No: MD-18-1171

DOI: https://doi.org/10.1115/1.4040985

Published Online: September 18, 2018

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Topics: Design, Optimization, Reliability, Modeling

Proceedings Papers

Sequential Kriging Optimization for Time-Variant Reliability-Based Design Involving Stochastic Processes

Mingyang Li, Zequn Wang

Proc. ASME. IDETC-CIE2017, Volume 2A: 43rd Design Automation Conference, V02AT03A042, August 6–9, 2017

Paper No: DETC2017-67426

DOI: https://doi.org/10.1115/DETC2017-67426

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Topics: Design, Optimization, Reliability, Stochastic processes, Uncertainty, Failure, Modeling, Probability, Reliability-based optimization, Simulation

Proceedings Papers

Model Validation of Dynamic Engineering Models Under Uncertainty

Zequn Wang, Yan Fu, Ren-Jye Yang, Saeed Barbat, Wei Chen

Proc. ASME. IDETC-CIE2016, Volume 2B: 42nd Design Automation Conference, V02BT03A048, August 21–24, 2016

Paper No: DETC2016-59437

DOI: https://doi.org/10.1115/DETC2016-59437

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Topics: Engineering models, Model validation, Uncertainty, Dynamic systems, Dynamic models, Engineering simulation, Manufacturing, Simulation, Computers, Data fusion

Journal Articles

Validating Dynamic Engineering Models Under Uncertainty

Zequn Wang, Yan Fu, Ren-Jye Yang, Saeed Barbat, Wei Chen

J. Mech. Des. November 2016, 138(11): 111402.

Paper No: MD-16-1128

DOI: https://doi.org/10.1115/1.4034089

Published Online: September 12, 2016

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Topics: Dynamic systems, Model validation, Signals, Simulation, Time series, Uncertainty, Dynamic models, Density, Data fusion, Engineering models

Journal Articles

Corrosion Reliability Analysis Considering the Coupled Effect of Mechanical Stresses

Chaoyang Xie, Pingfeng Wang, Zequn Wang, Hongzhong Huang

ASME J. Risk Uncertainty Part B. September 2016, 2(3): 031001.

Paper No: RISK-15-1034

DOI: https://doi.org/10.1115/1.4032003

Published Online: July 1, 2016

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Topics: Corrosion, Event history analysis, Stress, Reliability, Failure

Proceedings Papers

Reliability Analysis and Design Considering Disjointed Active Failure Regions

Pingfeng Wang, Xiaolong Cui, Zequn Wang

Proc. ASME. IDETC-CIE2015, Volume 2B: 41st Design Automation Conference, V02BT03A058, August 2–5, 2015

Paper No: DETC2015-47003

DOI: https://doi.org/10.1115/DETC2015-47003

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Topics: Design, Event history analysis, Failure, Simulation, Engineering systems and industry applications, Failure mechanisms, Reliability

Journal Articles

An Integrated Performance Measure Approach for System Reliability Analysis

Zequn Wang, Pingfeng Wang

J. Mech. Des. February 2015, 137(2): 021406.

Paper No: MD-14-1187

DOI: https://doi.org/10.1115/1.4029222

Published Online: February 1, 2015

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Topics: Event history analysis, Failure, Probability, Reliability, Approximation

Proceedings Papers

Evolving Design Model Synchronization for System Health Management Using Laplace Approximation

Pingfeng Wang, Adebayo O. Adewunmi, Zequn Wang

Proc. ASME. IDETC-CIE2014, Volume 2A: 40th Design Automation Conference, V02AT03A039, August 17–20, 2014

Paper No: DETC2014-34552

DOI: https://doi.org/10.1115/DETC2014-34552

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Topics: Approximation, Design, Synchronization, Failure, Reliability, Resilience, System failures

Proceedings Papers

Design of Smart Sensing Functions Using Piezoelectric Materials for Failure Diagnostics

Pingfeng Wang, Zequn Wang, Byeng D. Youn, Soobum Lee

Proc. ASME. IDETC-CIE2014, Volume 2A: 40th Design Automation Conference, V02AT03A038, August 17–20, 2014

Paper No: DETC2014-34550

DOI: https://doi.org/10.1115/DETC2014-34550

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Topics: Design, Failure, Piezoelectric materials, Uncertainty, Multifunctional materials, Reliability, Robustness

Proceedings Papers

A Confidence-Based Adaptive Sampling Approach for Dynamic Reliability Analysis

Zequn Wang, Pingfeng Wang

Proc. ASME. IDETC-CIE2014, Volume 2B: 40th Design Automation Conference, V02BT03A048, August 17–20, 2014

Paper No: DETC2014-34546

DOI: https://doi.org/10.1115/DETC2014-34546

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Topics: Event history analysis, Reliability, Modeling, Probability, Sensitivity analysis, Simulation

Proceedings Papers

An Integrated Performance Measure Approach for System Reliability Assessment

Zequn Wang, Pingfeng Wang

Proc. ASME. IDETC-CIE2014, Volume 2B: 40th Design Automation Conference, V02BT03A049, August 17–20, 2014

Paper No: DETC2014-34549

DOI: https://doi.org/10.1115/DETC2014-34549

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Topics: Reliability, Approximation, Failure, Computation, Errors, Event history analysis, Failure mechanisms, Filtration, Integrated systems, Response surface methodology

Proceedings Papers

Probabilistic Design of Smart Sensing Functions for Structural Health Monitoring and Prognosis

Abdulaziz T. Almaktoom, Zequn Wang, Pingfeng Wang

Proc. ASME. IDETC-CIE2013, Volume 3A: 39th Design Automation Conference, V03AT03A047, August 4–7, 2013

Paper No: DETC2013-12598

DOI: https://doi.org/10.1115/DETC2013-12598

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Topics: Design, Structural health monitoring, Damage, Sensor networks, Accounting, Design methodology, Engineering simulation, Gases, Genetic algorithms, Materials properties

Journal citation

NARROW

An LSTM-Based Ensemble Learning Approach for Time-Dependent Reliability Analysis

Semi-Supervised Deep Learning for High-Dimensional Uncertainty Quantification

Designing Deep Transfer Networks for Bearing Fault Diagnosis With Heterogeneous Data Fusion

Reliability-Based Reinforcement Learning Under Uncertainty

Design of Control Systems Using Active Uncertainty Reduction-Based Reinforcement Learning

LSTM-Based Ensemble Learning for Time-Dependent Reliability Analysis

Reliability-Based Multifidelity Optimization Using Adaptive Hybrid Learning

Active Resource Allocation for Reliability Analysis With Model Bias Correction

Confidence-Driven Design Optimization Using Gaussian Process Metamodeling With Insufficient Data

Sequential Kriging Optimization for Time-Variant Reliability-Based Design Involving Stochastic Processes

Model Validation of Dynamic Engineering Models Under Uncertainty

Validating Dynamic Engineering Models Under Uncertainty

Corrosion Reliability Analysis Considering the Coupled Effect of Mechanical Stresses

Reliability Analysis and Design Considering Disjointed Active Failure Regions

An Integrated Performance Measure Approach for System Reliability Analysis

Evolving Design Model Synchronization for System Health Management Using Laplace Approximation

Design of Smart Sensing Functions Using Piezoelectric Materials for Failure Diagnostics

A Confidence-Based Adaptive Sampling Approach for Dynamic Reliability Analysis

An Integrated Performance Measure Approach for System Reliability Assessment

Probabilistic Design of Smart Sensing Functions for Structural Health Monitoring and Prognosis

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