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Journal Articles

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

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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 Articletitled, 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

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

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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

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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

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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 Articletitled, Deep Generative Design: Integration of Topology Optimization and Generative Models
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Topics: Design, Optimization, Topology
Proceedings Papers

Design Automation by Integrating Generative Adversarial Networks and Topology Optimization

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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
Proceedings Papers

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

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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