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Journal Articles

Modified Structure of Deep Neural Network for Training Multi-Fidelity Data With Non-Common Input Variables

Hwisang Jo, Byeong-uk Song, Joon-Yong Huh, Seung-Kyu Lee, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101702.
Paper No: MD-23-1583
https://doi.org/10.1115/1.4064782
Published Online: March 5, 2024
View Article titled, Modified Structure of Deep Neural Network for Training Multi-Fidelity Data With Non-Common Input Variables
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Topics: Artificial neural networks, Hafnium
Proceedings Papers

Hierarchical Gaussian Process Surrogate Modeling Framework for Heterogeneous Multi-Fidelity Dataset

Juyoung Lee, Mingyu Lee, Bong Jae Lee, Ikjin Lee
Proc. ASME. IDETC-CIE2023, Volume 2: 43rd Computers and Information in Engineering Conference (CIE), V002T02A001, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-110455
https://doi.org/10.1115/DETC2023-110455
View Paper titled, Hierarchical Gaussian Process Surrogate Modeling Framework for Heterogeneous Multi-Fidelity Dataset
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Topics: Metamodeling, Approximation, Electrolytes, Errors
Journal Articles

Surrogate-Based Time-Dependent Reliability Analysis for a Digital Twin

Weifei Hu, Jiquan Yan, Feng Zhao, Chen Jiang, Hongwei Liu, Hyunkyoo Cho, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2023, 145(9): 091708.
Paper No: MD-23-1042
https://doi.org/10.1115/1.4062668
Published Online: July 18, 2023
View Article titled, Surrogate-Based Time-Dependent Reliability Analysis for a Digital Twin
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Topics: Digital twin, Event history analysis, Failure, Probability, Stochastic processes, Errors, Reliability
Proceedings Papers

A New Framework for Efficient Sequential Sampling-Based RBDO Using Space Mapping

Jeong Woo Park, Ikjin Lee
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A003, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89776
https://doi.org/10.1115/DETC2022-89776
View Paper titled, A New Framework for Efficient Sequential Sampling-Based RBDO Using Space Mapping
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Topics: Accuracy and precision, Event history analysis, Failure, Metamodeling, Probability, Reliability-based optimization, Sampling methods, Sensitivity analysis, Simulation
Journal Articles

A New Framework for Efficient Sequential Sampling-Based RBDO Using Space Mapping

Jeong Woo Park, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2023, 145(3): 031702.
Paper No: MD-22-1354
https://doi.org/10.1115/1.4055547
Published Online: October 31, 2022
View Article titled, A New Framework for Efficient Sequential Sampling-Based RBDO Using Space Mapping
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Topics: Design, Optimization, Reliability, Reliability-based optimization, Probability, Failure
Journal Articles

Deep Generative Tread Pattern Design Framework for Efficient Conceptual Design

Mingyu Lee, Youngseo Park, Hwisang Jo, Kibum Kim, Seungkyu Lee, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. July 2022, 144(7): 071703.
Paper No: MD-21-1462
https://doi.org/10.1115/1.4053469
Published Online: February 15, 2022
View Article titled, Deep Generative Tread Pattern Design Framework for Efficient Conceptual Design
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Topics: Design, Performance evaluation, Tires, Conceptual design, Optimization, Generators
Proceedings Papers

Shared Autonomous Vehicle System Design for Battery Electric Vehicle (BEV) and Fuel Cell Electric Vehicle (FCEV)

Ungki Lee, Sunghyun Jeon, Ikjin Lee
Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A029, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-67734
https://doi.org/10.1115/DETC2021-67734
View Paper titled, Shared Autonomous Vehicle System Design for Battery Electric Vehicle (BEV) and Fuel Cell Electric Vehicle (FCEV)
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Topics: Autonomous vehicles, Batteries, Design, Electric vehicles, Fuel cell vehicles, Optimization, Proton exchange membrane fuel cells
Journal Articles

Confidence-Based Design Optimization for a More Conservative Optimum Under Surrogate Model Uncertainty Caused by Gaussian Process

Yongsu Jung, Kyeonghwan Kang, Hyunkyoo Cho, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2021, 143(9): 091701.
Paper No: MD-20-1678
https://doi.org/10.1115/1.4049883
Published Online: February 11, 2021
View Article titled, Confidence-Based Design Optimization for a More Conservative Optimum Under Surrogate Model Uncertainty Caused by Gaussian Process
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Topics: Design, Optimization, Reliability, Uncertainty, Modeling
Proceedings Papers

Sampling-Based Reliability Analysis Using Deep Feedforward Neural Network (DFNN)

Ungki Lee, Ikjin Lee
Proc. ASME. IDETC-CIE2020, Volume 5: 24th Reliability, Stress Analysis, and Failure Prevention Conference (RSAFP), V005T05A006, August 17–19, 2020
Publisher: American Society of Mechanical Engineers
Paper No: DETC2020-22275
https://doi.org/10.1115/DETC2020-22275
View Paper titled, Sampling-Based Reliability Analysis Using Deep Feedforward Neural Network (DFNN)
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Topics: Artificial neural networks, Event history analysis, Feedforward control, Design, Trains, Dimensions, Shapes, Analytical methods, Density, Polynomials
Proceedings Papers

Confidence-Based Design Optimization Under Data Uncertainty Using Most Probable Point-Based Approach

Yongsu Jung, Hyunkyoo Cho, Ikjin Lee
Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A042, August 18–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: DETC2019-97718
https://doi.org/10.1115/DETC2019-97718
View Paper titled, Confidence-Based Design Optimization Under Data Uncertainty Using Most Probable Point-Based Approach
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Topics: Design, Optimization, Reliability-based optimization, Uncertainty
Proceedings Papers

Determination of the Number of Input Data Through Bi-Objective Confidence-Based Design Optimization

Yongsu Jung, Hyunkyoo Cho, Zunyi Duan, Ikjin Lee
Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A043, August 18–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: DETC2019-97721
https://doi.org/10.1115/DETC2019-97721
View Paper titled, Determination of the Number of Input Data Through Bi-Objective Confidence-Based Design Optimization
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Topics: Design, Optimization, Reliability-based optimization, Uncertainty
Journal Articles

Deep Generative Design: Integration of Topology Optimization and Generative Models

Sangeun Oh, Yongsu Jung, Seongsin Kim, Ikjin Lee, Namwoo Kang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. November 2019, 141(11): 111405.
Paper No: MD-19-1151
https://doi.org/10.1115/1.4044229
Published Online: September 16, 2019
View Article titled, Deep Generative Design: Integration of Topology Optimization and Generative Models
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Topics: Design, Optimization, Topology
Proceedings Papers

Most Probable Point-Based Approximated Dimension Reduction Method in Reliability-Based Design Optimization

Yongsu Jung, Hyunkyoo Cho, Ikjin Lee
Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A062, August 26–29, 2018
Publisher: American Society of Mechanical Engineers
Paper No: DETC2018-86382
https://doi.org/10.1115/DETC2018-86382
View Paper titled, Most Probable Point-Based Approximated Dimension Reduction Method in Reliability-Based Design Optimization
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Topics: Dimensions, Reliability-based optimization, Approximation, Event history analysis, Finite element analysis, Reliability, Design, Failure, Probability
Proceedings Papers

Design Automation by Integrating Generative Adversarial Networks and Topology Optimization

Sangeun Oh, Yongsu Jung, Ikjin Lee, Namwoo Kang
Proc. ASME. IDETC-CIE2018, Volume 2A: 44th Design Automation Conference, V02AT03A008, August 26–29, 2018
Publisher: American Society of Mechanical Engineers
Paper No: DETC2018-85506
https://doi.org/10.1115/DETC2018-85506
View Paper titled, Design Automation by Integrating Generative Adversarial Networks and Topology Optimization
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Topics: Design automation, Optimization, Topology, Design, Automobiles, Machinery, Product design, Wheels
Journal Articles

A Study on Computational Efficiency Improvement of Novel SORM Using the Convolution Integration

Jeong Woo Park, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Technical Briefs
J. Mech. Des. February 2018, 140(2): 024501.
Paper No: MD-17-1293
https://doi.org/10.1115/1.4038563
Published Online: December 11, 2017
View Article titled, A Study on Computational Efficiency Improvement of Novel SORM Using the Convolution Integration
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Topics: Failure, Probability, Reliability, Errors, Dimensions
Proceedings Papers

Reliability-Based Design Optimization (RBDO) for Electric Vehicle Market Systems

Ungki Lee, Namwoo Kang, Ikjin Lee
Proc. ASME. IDETC-CIE2017, Volume 2A: 43rd Design Automation Conference, V02AT03A038, August 6–9, 2017
Publisher: American Society of Mechanical Engineers
Paper No: DETC2017-68045
https://doi.org/10.1115/DETC2017-68045
View Paper titled, Reliability-Based Design Optimization (RBDO) for Electric Vehicle Market Systems
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Topics: Electric vehicles, Reliability-based optimization, Design, Uncertainty, Batteries, Battery life, Engineering systems and industry applications, Failure, Preferences, Product design
Proceedings Papers

Design Sensitivity Method for Sampling-Based RBDO With Fixed COV

Hyunkyoo Cho, K. K. Choi, Ikjin Lee, David Lamb
Proc. ASME. IDETC-CIE2015, Volume 2B: 41st Design Automation Conference, V02BT03A059, August 2–5, 2015
Publisher: American Society of Mechanical Engineers
Paper No: DETC2015-47359
https://doi.org/10.1115/DETC2015-47359
View Paper titled, Design Sensitivity Method for Sampling-Based RBDO With Fixed COV
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Topics: Design, Failure, Probability, Event history analysis, Optimization, Reliability-based optimization, Simulation
Journal Articles

Design Sensitivity Method for Sampling-Based RBDO With Varying Standard Deviation

Hyunkyoo Cho, K. K. Choi, Ikjin Lee, David Lamb
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. January 2016, 138(1): 011405.
Paper No: MD-15-1333
https://doi.org/10.1115/1.4031829
Published Online: November 16, 2015
View Article titled, Design Sensitivity Method for Sampling-Based RBDO With Varying Standard Deviation
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Topics: Design, Failure, Probability, Optimization
Proceedings Papers

Inverse Reliability Analysis for Approximated Second-Order Reliability Method Using Hessian Update

Jongmin Lim, Byungchai Lee, Ikjin Lee
Proc. ASME. IDETC-CIE2014, Volume 2B: 40th Design Automation Conference, V02BT03A050, August 17–20, 2014
Publisher: American Society of Mechanical Engineers
Paper No: DETC2014-34581
https://doi.org/10.1115/DETC2014-34581
View Paper titled, Inverse Reliability Analysis for Approximated Second-Order Reliability Method Using Hessian Update
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Topics: Event history analysis, Reliability, Failure, Probability, Approximation, Computation
Journal Articles

Reliability-Based Vehicle Safety Assessment and Design Optimization of Roadway Radius and Speed Limit in Windy Environments

Jaekwan Shin, Ikjin Lee
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. August 2014, 136(8): 081006.
Paper No: MD-13-1361
https://doi.org/10.1115/1.4027512
Published Online: June 2, 2014
View Article titled, Reliability-Based Vehicle Safety Assessment and Design Optimization of Roadway Radius and Speed Limit in Windy Environments
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Topics: Design, Optimization, Roads, Vehicles, Wind velocity, Reliability, Safety, Wind