Article
Engineering, Multidisciplinary
Ewerton Grotti, Pedro Buhrer Santana, Jose Gilberto Picoral Filho, Herbert M. Gomes
Summary: This paper presents a method for incorporating uncertainties into the multiobjective optimization process by using first and second moments approximation and Taylor expansions. The results show that the method is efficient in solving multiobjective robust optimization problems and the different levels of Taylor approximation are compared in various engineering problems.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Civil
Yan Shi, Hong-Zhong Huang, Yu Liu, Michael Beer
Summary: This study presents an adaptive decoupled robust design optimization method based on the Kriging surrogate model, which transforms the nested double-loop estimation process into a traditional deterministic optimization procedure, reducing computational costs. A novel estimation expression for the performance standard deviation is established to reflect uncertainties in both prediction and performance mean simultaneously.
Article
Engineering, Mechanical
Jennifer Bracken Brennan, William B. B. Miney, Timothy W. W. Simpson, Kathryn W. W. Jablokow, Christopher McComb
Summary: This research provides evidence that fixation on certain manufacturing types can impact designers' ability to utilize new technologies. A workshop-based study with industry practitioners confirms the existence of manufacturing fixation in design and introduces a method to assess its impact.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Engineering, Aerospace
Qasim Zeeshan, Amer Farhan Rafique, Ali Kamran, Muhammad Ishaq Khan, Abdul Waheed
Summary: This research aims to enhance efficiency and reduce costs in the conceptual design phase through multidisciplinary design and optimization, exploring various configurations for an expendable microsatellite launch vehicle and successfully achieving the desired objectives. By applying multiple heuristic optimization methods, design variables were optimized within constraints, and the fundamental stochastic error was reduced through multiple runs.
AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY
(2021)
Article
Engineering, Mechanical
Jolan Wauters
Summary: This paper discusses robust design optimization (RDO) to account for variability in the design phase. The method is formulated as a multi-objective problem with the objective of minimizing both the mean and variance of the objective. The use of Bayesian optimization and surrogate modeling techniques are proposed to address computational cost and uncertainty. An analytical treatment of the problem is presented to obtain quantities of interest without sampling. The proposed method, which combines Bayesian optimization with analytical uncertainty quantification, is validated and proves to be efficient.
JOURNAL OF MECHANICAL DESIGN
(2022)
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
Engineering, Mechanical
Shiguang Deng, Carlos Mora, Diran Apelian, Ramin Bostanabad
Summary: Fracture modeling of metallic alloys with microscopic pores often ignores the spatial variabilities in porosity induced by manufacturing due to computational expenses. To address this challenge, we propose a data-driven framework that integrates a reduced-order model with a calibration scheme based on random processes. Our framework accelerates numerical simulations and takes into account the effects of clustering on fracture response. Using latent map Gaussian processes, we calibrate the damage parameters of the reduced-order model to faithfully surrogate direct numerical simulations. The application of our framework demonstrates the significant impact of microstructural porosity on the behavior of macro-components.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Engineering, Mechanical
Quan Lin, Qi Zhou, Jiexiang Hu, Yuansheng Cheng, Zhen Hu
Summary: This paper proposes a sequential sampling method for robust design optimization based on multi-fidelity modeling, which considers both design variable uncertainty and interpolation uncertainty during the sequential sampling. The extended upper confidence boundary (EUCB) function is developed to determine both the sampling locations and the fidelity levels of the sequential samples.
JOURNAL OF MECHANICAL DESIGN
(2022)
Article
Engineering, Multidisciplinary
Haitao Yu, Baolin Tian, Zhen Yan, Haibo Gao, Hongjian Zhang, Huiqiang Wu, Yingchao Wang, Yuhong Shi, Zongquan Deng
Summary: This study proposes a novel legged deployable landing mechanism (LDLM) for the reusable launch vehicle (RLV) through multi-objective optimization. The experimental results demonstrate that the proposed LDLM can provide rapid and smooth deployment and satisfactory impact attenuation.
Article
Engineering, Multidisciplinary
Min Liu, WeiDong Wang, YingMin Zhu, YangBo Yuan, YanXu Niu, LinXi Dong, ChenYing Wang, Kyle Jiang, GuiMin Chen
Summary: This paper proposes an optimization method for finding the optimal design of a bistable mechanism with robust performance. The uncertainties in structural parameters and materials are characterized using interval numbers. A nonprobabilistic multiobjective optimization model is presented and transformed into a single objective optimization model. The sensitivity of the mechanical performance of bistable structures to uncertain parameters is analyzed. A neural network-based proxy model is established for the nonlinear characteristics of the bistable mechanism. A two-layer nested genetic algorithm is employed to solve the multiobjective robust optimization problem. The effectiveness of the method is verified through comparisons with finite element and experimental results. The method is applied in the design of silicon-based inertial switches.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Gustavo A. Prudencio de Morais, Lucas Barbosa Marcos, Filipe Marques Barbosa, Bruno H. G. Barbosa, Marco Henrique Terra, Valdir Grassi
Summary: This study proposes a robust recursive controller designed via multiobjective optimization to overcome the challenges of system uncertainties, along with a local search method for multiobjective optimization problems. This method is applicable to any established multiobjective evolutionary algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Jiahui Duan, Zhenan He, Gary G. Yen
Summary: This article focuses on the robust multiobjective optimization approach for the vehicle routing problem with time windows under uncertainty. By designing a new form of disturbance on travel time and incorporating an advanced encoding and decoding scheme, the proposed algorithm is able to generate enough robust solutions and ensure the optimality of these solutions, as validated by experimental results.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Liangqi Wan, Linhan Ouyang, Tianyu Zhou, Yuejian Chen
Summary: This paper proposes an improved loss function-based reliability-based robust design optimization method, which considers the variance-covariance structure of responses by introducing Bayesian inference and SUR models, as well as the multivariate loss function approach. The proposed method simultaneously considers design targets and the covariance structure of responses, and provides better optimization design solutions.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Information Systems
Jose Pablo Belletti Araque, Alessandro Zavoli, Domenico Trotta, Guido De Matteis
Summary: This paper proposes a hybrid approach to the design of the attitude control system for a launch vehicle, utilizing a genetic algorithm to tune a structured H-infinity controller. Control design is carried out by parameterizing H-infinity weighting functions once stability and robustness requirements are specified. The automated design procedure proves to be effective in reducing the burden of recurrent activities for controller tuning and validation.
Article
Engineering, Aerospace
Mathieu Balesdent, Loic Brevault, Jorge-Luis Valderrama-Zapata, Annafederica Urbano
Summary: Launch vehicle design involves multiple disciplines, and trajectory is a key discipline in the design process. This paper proposes a multidisciplinary approach using the Gauss-Lobatto collocation technique to solve the optimal control problem, and performs uncertainty quantification through post-optimality analysis. The efficiency of this approach is demonstrated on a representative Two-Stage-To-Orbit launch vehicle design problem.
Article
Engineering, Mechanical
Jafar Roshanian, Ali A. Bataleblu, Masoud Ebrahimi
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2018)
Article
Computer Science, Interdisciplinary Applications
J. Roshanian, A. A. Bataleblu, M. Ebrahimi
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2018)
Article
Engineering, Aerospace
Jafar Roshanian, Masoud Ebrahimi, Ehsan Taheri, Ali Asghar Bataleblu
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
(2014)
Article
Computer Science, Artificial Intelligence
Arian Abedini, Ali Asghar Bataleblu, Jafar Roshanian
Summary: This paper introduces a novel concept of a hybrid drone called MICOPTER to address the challenges faced by delivery drones in reliably delivering packages. By comparing it to other UAVs and utilizing multi-objective optimization and control methods, the MICOPTER is optimized for flight performance and controllability. Results indicate the MICOPTER's capabilities as a novel configuration in terms of design performance and controllability.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Arian Abedini, Ali Asghar Bataleblu, Jafar Roshanian
Summary: This study combines incremental control action with the backstepping design methodology to propose a robust nonlinear flight control strategy for a bi-copter drone. By gradually stabilizing or tracking the control variables of the nonlinear system, the proposed method reduces the dependency on the dynamic model and exhibits strong robustness in compensating for external disturbances.
2022 10TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM)
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Arian Abedini, Ali Asghar Bataleblu, Jafar Roshanian
Summary: This paper explores the position and attitude control of a Bi-copter drone, presents a robust controller design, and validates its performance on a circular flight path through simulation.
2021 9TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Ali A. Bataleblu, J. Roshanian
2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
(2015)
Proceedings Paper
Engineering, Aerospace
Ali Asghar Bataleblu, Jafar Roshanian, Masoud Ebrahimi
2015 7TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES (RAST)
(2015)