Article
Green & Sustainable Science & Technology
Thomas Nystrom, Katherine A. Whalen, Derek Diener, Marcel den Hollander, Robert H. W. Boyer
Summary: This conceptual paper highlights the importance of product adaptivity in circular business models and proposes the Future Adaptive Design framework to help manage product-related business risks. It identifies a research gap in the field of circular economy and design, especially in the early stages of business development.
Article
Computer Science, Interdisciplinary Applications
Wei Li, Liang Gao, Akhil Garg, Mi Xiao
Summary: The paper introduces a new framework MRDO-UPM to address parameter and metamodeling uncertainties in multidisciplinary design optimization. The effectiveness of the new framework is validated through numerical examples and practical design.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Van-Nam Hoang, Trung Pham, Duc Ho, H. Nguyen-Xuan
Summary: This paper presents a novel multiscale topology optimization approach that can optimize incompressible multi-material designs at both macro and micro scales, and demonstrates the effectiveness of the technique through examples of solving incompressible porous multi-material designs under single and multiple random loads.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Aerospace
Yuhang Ma, Jiecheng Du, Tihao Yang, Yayun Shi, Libo Wang, Wei Wang
Summary: This study establishes a robust optimization design framework for three-dimensional aerodynamic shape optimization, combines uncertainty quantification with a powerful optimization algorithm, and investigates the impacts of deterministic optimization and robust optimization on aircraft performance through a flying-wing configuration case study.
Article
Engineering, Aerospace
Lorenzo Federici, Alessandro Zavoli
Summary: This paper explores the application of meta-reinforcement learning in the robust design of low-thrust interplanetary trajectories under multiple uncertainties. It uses a deep recurrent neural network to approximate the control policy and adapts it to different stochastic scenarios through training.
Article
Engineering, Aerospace
Yifu Chen, Hanyue Rao, Neng Xiong, Jun Fan, Yayun Shi, Tihao Yang
Summary: Due to the high sensitivity of laminar wings to uncertain factors, laminar flow technology has not been effectively applied to large passenger aircraft wings. To address this issue, a robust optimization design framework is developed, which includes various components such as a Reynolds-Averaged Navier-Stokes solver, coupled adjoint equations, and a statistical moment gradient solver. The results demonstrate that the robust design can improve the ability of the laminar airfoil to resist uncertain flight conditions and reduce drag coefficients.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Aerospace
Qijia Yao
Summary: This paper investigates the finite-time attitude stabilization of spacecraft under multiple uncertainties and proposes a novel robust finite-time attitude control approach based on a dual-disturbance-observer. The proposed controller is not only robust against uncertainties and actuator faults, but also insensitive to measurement uncertainties, benefiting from feedforward disturbance compensation.
ADVANCES IN SPACE RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Saman Dadjo Tavakoli, Eduardo Prieto-Araujo, Sajjad Fekriasl, Jef Beerten, Hasan Mehrjerdi, Oriol Gomis-Bellmunt
Summary: This paper proposes a robust multivariable controller for high-voltage direct current (HVDC) transmission systems, which is able to maintain system stability and performance under uncertain grid impedance conditions. The structured singular value of the system is minimized via an iterative procedure to ensure the controller operates robustly in a wide range of grid impedances, while tuning the weighting functions to meet the robustness criteria defined by the small-gain theorem.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Paul Christoph Gembarski, Stefan Plappert, Roland Lachmayer
Summary: Making design decisions involves high uncertainty, and complexity management aims to reduce uncertainty to minimize or avoid the need for design changes. Bayesian decision network helps engineers make decisions under uncertainty and contributes to knowledge formalization in development projects.
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
(2021)
Article
Optics
Guan-Jie Fan-Yuan, Feng-Yu Lu, Shuang Wang, Zhen-Qiang Yin, De-Yong He, Wei Chen, Zheng Zhou, Ze-Hao Wang, Jun Teng, Guang-Can Guo, Zheng-Fu Han
Summary: This study proposes an MDI-QKD networking scheme that is robust against environmental disturbance and adaptable to multi-user access. It allows multiple users to generate keys simultaneously in a multi-user scenario.
Article
Computer Science, Artificial Intelligence
Neerav Karani, Ertunc Erdil, Krishna Chaitanya, Ender Konukoglu
Summary: In this study, a method to address the mismatch between training and test images in medical image segmentation is proposed. The segmentation network consists of a shallow image normalization CNN and a deep CNN, with a denoising autoencoder used to model an implicit prior. Experimental results demonstrate the performance improvement achieved by test-time adaptation.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Engineering, Electrical & Electronic
Jiqi Wu, Xiaoyong Zhu, Deyang Fan, Zixuan Xiang, Lei Xu, Li Quan
Summary: A robust optimization design method considering magnet material uncertainties is proposed in this article. By constructing a robust optimization model and using appropriate solution methods, the influence of magnet material uncertainties on PM machine performance can be effectively reduced.
IEEE TRANSACTIONS ON MAGNETICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Kai Wang, Jianhua Liu, Hao Gong, Xinjian Deng
Summary: This study proposes a novel method for the robust optimization design of key structural sizes in globe-cone joint considering manufacturing and assembly uncertainties. First, an accurate three-dimensional finite element model of globe-cone joint is built, including size error and surface micro-topography. Second, the second-order polynomial response surface model is built for establishing the relationship between uncertain parameters, optimized structural parameters, and sealing performance. Third, the combination of the interval possibility method, penalty function method and improved particle swarm optimization algorithm are proposed to optimize the structural parameters for improving the robustness of sealing performance.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Electrical & Electronic
Jaegyeong Mun, K. K. Choi, Dong-Hun Kim
Summary: In the presence of design parameter uncertainties, a system-level robust design optimization method is proposed for a permanent magnet motor to enhance the dynamic and steady performances of the motor drive system. The influence of individual motor parameters on transient system responses is investigated through Taguchi experimental planning. The temperature-dependent material property of each motor component is examined, and the motor drive system is then optimized using the univariate dimension reduction method to ensure robustness against manufacturing tolerance and operating temperature fluctuation.
IEEE TRANSACTIONS ON MAGNETICS
(2023)
Article
Engineering, Aerospace
Christian Sabater, Philipp Bekemeyer, Stefan Goertz
Summary: This paper introduces a robust direct design approach for transonic natural laminar flow wings, which considers uncertainties to generate more balanced configurations than deterministic methods and improves the stability of laminar wings.
Article
Engineering, Industrial
Biao Yu, Han Zhao, Deyi Xue
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
Review
Engineering, Industrial
Moustafa Gadalla, Deyi Xue
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
Article
Computer Science, Artificial Intelligence
Hongzhan Ma, Xuening Chu, Deyi Xue, Dongping Chen
JOURNAL OF INTELLIGENT MANUFACTURING
(2019)
Article
Engineering, Mechanical
Yupeng Li, Zhaotong Wang, Lei Zhang, Xuening Chu, Deyi Xue
JOURNAL OF MECHANICAL DESIGN
(2017)
Article
Automation & Control Systems
Baigong Zeng, Longzhe Quan, Jin Tong, Jin Ye, Deyi Xue
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2018)
Article
Engineering, Industrial
Moustafa Gadalla, Deyi Xue
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Engineering, Mechanical
Maribel Martinez, Deyi Xue
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2018)
Article
Engineering, Industrial
Lei Zhang, Xuening Chu, Deyi Xue
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2019)
Article
Transportation
Biao Yu, Lin Dong, Deyi Xue, Hui Zhu, Xinli Geng, Ruling Huang, Jie Wang
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2019)
Article
Engineering, Mechanical
Qiang Cheng, Baobao Qi, Zhifeng Liu, Caixia Zhang, Deyi Xue
MECHANISM AND MACHINE THEORY
(2019)
Article
Computer Science, Artificial Intelligence
Hongzhan Ma, Xuening Chu, Weizhong Wang, Xinwang Liu, Deyi Xue
ADVANCED ENGINEERING INFORMATICS
(2019)
Article
Computer Science, Interdisciplinary Applications
Hang Liu, Xuening Chu, Deyi Xue
COMPUTERS IN INDUSTRY
(2019)
Article
Green & Sustainable Science & Technology
Zhifeng Liu, Jun Yan, Qiang Cheng, Congbin Yang, Shuwen Sun, Deyi Xue
JOURNAL OF CLEANER PRODUCTION
(2020)
Article
Engineering, Manufacturing
Guanying Huo, Xin Jiang, Cheng Su, Zehong Lu, Yuwen Sun, Zhiming Zheng, Deyi Xue
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING
(2019)
Proceedings Paper
Engineering, Industrial
Deyi Xue, David Imaniyan
28TH CIRP DESIGN CONFERENCE 2018
(2018)