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multidisciplinary design optimization of the first-stage waverider based on boost-glide flight trajectory

AEROSPACE SCIENCE AND TECHNOLOGY 2025年 160卷

作者： Leng, Jun-xue Xie, Zan Huang, Wei Shen, Yang Wang, Zhen-guo Natl Univ Def Technol Hyperson Technol Lab Changsha 410073 Hunan Peoples R China

Multistage waverider vehicles based on the combined trajectory flight possess aerodynamic performance advantages, offer more flexible trajectories, and can achieve extended ranges. However, current multistage waverider design technology remains underdeveloped and is still in the preliminary theoretical research stage. This paper extends the design methodology for two-stage waverider vehicles, enabling the design of a first-stage widespeed-range waverider that conforms to the leading edge of a given irregular second-stage airbreathing liftingbody configuration, thus forming a two-stage waverider structure. According to the specific optimization requirements, we refined the multi-fidelity data-mining-based MDO (multidisciplinary design optimization) framework, yielding an optimized first-stage wide-speed-range lifting body configuration with superior performance under viscous conditions. Compared with the initial configuration, the optimized first-stage vehicle, with a constant takeoff mass, achieved a 5.84 % increase in range for the boost-glide combined trajectory, further verifying the effectiveness and flexibility of the multi-fidelity data-mining-based MDO framework.

关键词： Two-stage waverider Wide-speed-range waverider Aerodynamic analysis Data mining multidisciplinary design optimization

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multidisciplinary design optimization of electric car body and battery tray based on improved collaborative optimization framework

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2025年第6期239卷 2051-2071页

作者： Duan, Libin Yao, Zhenchang Du, Zhanpeng Xu, Fengxiang Xu, Wei Liu, Xing Jiangsu Univ Inst Lightweight & Safety New Energy Vehicle Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan Peoples R China Wuhan Univ Technol Hubei Collaborat Innovat Ctr Automot Components Te Wuhan Peoples R China

The lightweight design of electric car body and battery tray is an important way to improve the endurance mileage of electric vehicles, which is a multidisciplinary optimization (MDO) problem with multiple design variables and multiple constraints such as stiffness, modal, and crashworthiness performances, thereby leading it to be inefficient. To improve the MDO efficiency while ensuring the search accuracy, an improved collaborative optimization (CO) framework is proposed in this paper including a system-level optimization, multiple disciplinary subproblem optimizations, and a loop control. The disciplinary subproblem optimizations use the evolutionary optimization algorithm for global search, whose current optimal solutions are combined as the starting point of system-level optimization. The system-level optimization uses the gradient based optimization algorithm for local search, whose current optimal solution is divided into the starting points of the disciplinary subproblem optimizations. The above process is repeated until the convergence condition of the loop control is satisfied. The loop control is mainly used for the data transfer and convergence judgment between the disciplinary subproblem optimizations and the system-level optimization. The convergence and the efficiency of improved CO framework are verified by solving a simple MDO problem. In solving the MDO of electric car body and battery tray with all constraints satisfied, the iteration number and the computational time of improved CO framework are respectively reduced by 69.3% and 60% than those of original CO framework.

关键词： Electric car body battery tray multidisciplinary design optimization collaborative optimization lightweight design

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multidisciplinary design optimization Processes for Efficiency Improvement of Aircraft: State-of-the-Art Review

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2024年 1-23页

作者： Leng, Jun-xue Wang, Zhen-guo Huang, Wei Shen, Yang An, Kai Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Hunan Peoples R China

During actual flight processes, aircraft face various complex operating conditions and must consider the requirements of different disciplines to achieve good overall performance. multidisciplinary design optimization (MDO) for aircraft is a complex and time-consuming task, making efficiency crucial in aircraft design. This paper starts from the conventional MDO process, covering five aspects including design variables, performance evaluation methods, MDO strategies, optimization algorithms, and knowledge extraction for enhancing MDO efficiency. It introduces multiple techniques and current research status aimed at improving MDO efficiency, and, combined with artificial intelligence, outlines future directions for MDO development. This paper aims to help MDO researchers clarify their thoughts and provide references for advancing current MDO methods.

关键词： multidisciplinary design optimization Data dimensionality reduction Machine learning MDO strategy optimization algorithms Data mining

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multidisciplinary design optimization of an autonomous underwater vehicles based on random uncertainty

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OCEAN ENGINEERING 2024年第Part3期312卷

作者： Liu, Feng Yang, Songyuan Wang, He Zhang, Wei Harbin Engn Univ Coll Shipbldg Engn Harbin 150001 Peoples R China China Classificat Soc Harbin Branch Harbin 150070 Peoples R China China Yantai Salvage Technol Dept Yantai 264012 Peoples R China

Herein, discipline decomposition was performed for an autonomous underwater vehicle (AUV) based on multidisciplinary design optimization (MDO), and its design parameters were determined. Parameterized analysis of the hull-form and structure disciplines was performed, and an approximate model of these disciplines was established with a high fitting accuracy. An analysis model of propulsion, energy, and system disciplines was developed based on the formula method. Based on collaborative optimization as well as discipline and system level models, a deterministic MDO framework for AUVs was established. Subsequently, an optimized solution was obtained. By considering the random uncertainty of design variables, an MDO framework for the uncertainty of AUVs was established and optimized solutions were obtained. The distribution of solutions obtained from uncertainty optimization was more concentrated and the distribution range was smaller than that obtained using deterministic optimization. Robustness analysis was performed on the initial scheme, typical deterministic optimization schemes, and typical uncertainty optimization schemes. Results showed that fluctuations in design variables may lead to constraints that exceed boundary conditions in the deterministic optimization design scheme. Using uncertainty and objective function optimization, the robustness of the overall scheme of AUVs was improved.

关键词： Autonomous underwater vehicle multidisciplinary design optimization Approximate model Collaborative optimization Uncertainty Robustness

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multidisciplinary design optimization WITH MULTIPLE DEGREES OF FREEDOM FOR AN AXIAL COMPRESSOR BASED ON DATA-DRIVEN 69

MULTIDISCIPLINARY DESIGN OPTIMIZATION WITH MULTIPLE DEGREES ...

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69th ASME Turbomachinery Technical Conference and Exposition (ASME Turbo Expo) (GT)

作者： Luo, Chuwei Chen, Jiang Liu, Yi Xiang, Hang Beihang Univ Beijing Peoples R China

ISBN: (纸本)9780791888087

Compressor design represents a multidisciplinary coupling problem encompassing aerodynamics, structure strength, vibration, fatigue, and acoustics. multidisciplinary design optimization enables a comprehensive consideration of the interconnectedness among these disciplines, reasonably balances the conflicting requirements, and ultimately enhances the performance of products significantly while reducing the development cycle. In this paper, a multidisciplinary optimization system is established based on a data-driven multi-objective evolution algorithm. This algorithm is combined with the directly manipulated free-form deformation method to achieve multi-degree-of-freedom parameterized control. The research focuses on optimizing the aerodynamic and aeroelastic design of a 1.5-stage axial flow compressor in a gas turbine. Maximum efficiency and surge margin are set as the optimization objectives, while the constraint conditions involve flow rate, total pressure ratio, as well as the strength and resonance margin of the rotor blade. To improve the prediction accuracy of surge margin during optimization, a successive approximation method combined with efficiency-based residual convergence determination is utilized. The results show a significant reduction in the stress distribution of blades, with the maximum stress value decreased by 30.6%. Simultaneously, the surge margin of the compressor is increased by 3.36%, and the efficiency at the design point is also slightly improved. The optimization system can not only ensure optimization effectiveness, but also greatly reduce the design variables and evaluation time, which is effectively applicable to the multidisciplinary design optimization of compressors.

关键词： multidisciplinary design optimization data-driven evolution algorithm free-form deformation compressor

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multidisciplinary design optimization in design for additive manufacturing

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JOURNAL OF COMPUTATIONAL design AND ENGINEERING 2022年第1期9卷 128-143页

作者： Liu, Guang Xiong, Yi Rosen, David W. Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen 518055 Peoples R China Singapore Univ Technol & Design Digital Mfg & Design DManD Ctr Singapore 487372 Singapore Georgia Inst Technol GW Woodruff Sch Mech Engn Atlanta GA 30332 USA

design for additive manufacturing (AM) involves decision making in various design domains, including product design, material selection, and process planning. In practice, engineers typically adopt a sequential design process to optimize these design domains in consecutive order. However, coupling factors, e.g. shared variables, related constraints, and conflicting objectives, are not sufficiently considered within the sequential design process, resulting in an inefficient workflow and suboptimal design solutions. To address the above issues, this paper proposes a multidisciplinary design optimization framework to simultaneously optimize different domains, which enables rapid exploration and complete exploitation of the AM design space under complex constraints. More specifically, the proposed framework is based on the concurrent optimization method, which coordinates the optimization of different design domains by allowing an automated exchange of design information. Also, the framework utilizes the surrogate modeling approach to approximate high-fidelity simulations for facilitating the iterative process. The effectiveness of the proposed framework is validated with two examples, a plate with a hole design and a hook design, which involve multiple design objectives from both process and structure domains, i.e. the print time, print area, strain energy, and maximum von Mises stress.

关键词： design for additive manufacturing multidisciplinary design optimization concurrent engineering design theory and methodology

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multidisciplinary design optimization of the Composite Cooling Structure for Nickel-based Alloy Turbine Blade

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2022年第1期39卷 103-115页

作者： Qian, Xiaoru Yan, Peigang Han, Wanjin Harbin Inst Technol Sch Energy Sci & Engn 92 Xidazhi St Harbin 150001 Heilongjiang Peoples R China

A designed method, multidisciplinary coupling computation and multiobjective optimization, has been established for the composite cooling structure of heavy gas turbine blade manufactured with a directionally solidified Ni-based superalloy. The method combines the one-dimensional fluid network gas-thermal coupling computation, three-dimensional flow field coupled with solid stress field, and anisotropic stress calculation based on finite deformation crystal slip. The temperature, flow field, Von-Mises stress and maximum resolved shear stress of the blade before and after optimization were analyzed. The results show that the optimized blade has lower maximum blade temperature, a more uniform temperature distribution, a lower flow resistance of the coolant channel at the leading edge than that of the original blade. The maximum Von-Mises stress of the optimized blade increases by 10.05 % more than the original blade. The maximum shear stress on the suction side and the pressure surface of the optimized blade are improved and slightly deteriorated compared with that of the original blade, respectively. The corresponding relationship of the maximum shear stress distribution with the local temperature gradient reveals further space for the improvement of the composite cooling structure. This paper has a particular guiding significance for the cooling structure design of the turbine blade.

关键词： nickel-based turbine blade composite cooling structures multidisciplinary design optimization transversely isotropic resolved shear stress

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multidisciplinary design optimization of vehicle chassis product family

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2022年第5期236卷 498-508页

作者： Chen, Xiaokai Wang, Chenyu Shi, Guobiao Zeng, Mingkai Beijing Inst Technol Sch Mech Engn Beijing Peoples R China Natl Engn Lab Elect Vehicles Beijing Peoples R China

In order to improve the performance of automotive product platforms and product families while keeping high development efficiency, a product family optimization design method that combines shared variable decision-making and multidisciplinary design optimization (MDO) is proposed. First, the basic concepts related to product family design optimization were clarified. Then, the mathematical description and MDO model of the product family optimization problem were established, and the improved product family design process was given. Finally, for the chassis product family optimization problem of an automotive product platform, the effectiveness of the proposed optimization method, and design process were exemplified. The results show that the collaboratively optimized product family can effectively handle the coordination between multiple products and multiple targets, compared to Non-platform development, it can maximize the generalization rate of vehicle parts and components under the premise of ensuring key performance, and give full play to the advantages of product platforms.

关键词： Vehicle chassis product family platformization multidisciplinary design optimization optimization

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multidisciplinary design optimization of Reentry-Powered Hypersonic Vehicles Based on Surrogate Model

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INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING 2024年第1期2024卷

作者： Ma, Shoudong Yang, Yuxin Chen, Yesi Yang, Hua Chen, Weifang Zhejiang Univ Sch Aeronaut & Astronaut Hangzhou 310027 Peoples R China

Two problems exist in the study of the trajectory optimization problem of powered hypersonic gliding vehicles (HGVs) due to insufficient consideration of the overall design constraints as well as the strong couplings among relevant disciplines: (1) the engine and thrust models are not compatible with the existing HGV;(2) configuration parameters of the HGV are not included as design variables during trajectory optimization (i.e., propulsion discipline is decoupled in the process of the HGV configuration design), thus failing to fully explore the effect of power to improve the performance of the HGV. Therefore, the application of multidisciplinary design optimization (MDO) in the overall design of powered HGVs should be investigated. First, a MDO task analysis and a multidisciplinary model analysis are carried out for the powered HGV. Second, the multidisciplinary optimization problem is defined, and the couplings between disciplines of the powered HGV are analyzed so that a six-discipline model is established that is suitable for the overall design process, including the parameterized configuration geometry, aerodynamics, propulsion, mass properties, trajectory, and aerodynamic heat/thermal protection system (TPS). Finally, a surrogate model is used to replace the time-consuming accurate model, and numerical optimization examples verify the effectiveness of the method. The optimization results show that the method has a good convergence speed, which increases the gliding range of the optimized vehicle by 8.37%. In addition, by decoupling the propulsion discipline, the validation shows that the coupled propulsion discipline during the overall design can increase the range of the powered HGV by 3.87% compared to the powered HGV optimized with the decoupled propulsion discipline. The work done in this paper provides a new design idea for the overall design of a powered HGV.

关键词： multidisciplinary design optimization powered hypersonic glide vehicle surrogate model

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multidisciplinary design optimization of a generic b-pillar under package and design constraints

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ENGINEERING optimization 2021年第11期53卷 1884-1901页

作者： Werner, Yannis Vietor, Thomas Weinert, Matthias Erber, Thomas Tech Univ Carolo Wilhelmina Braunschweig Inst Engn Design Braunschweig ME Germany FordWerke GmbH Cologne Germany

This article introduces a novel constraining approach for structural optimization that aims to support the conceptual engineer during the early embodiment phase for structural lightweight design. It reduces the time spent on structural engineering studies by enabling optimization algorithms to detect geometric intersections by analysing the mesh information. This article reviews approaches from the literature focusing on computer aided design environments, sampling methods, data analytics and optimization techniques for design and sizing optimization with finite-element models. The evaluated approaches are integrated into a Python-based optimization environment. Accordingly, the introduced methodology enables the environment to handle geometrically infeasible designs. The presentation of the first results focuses on the feasibility of structural assemblies and the results demonstrate the viability of NSGA-II for optimization tasks. The example considers the design of a generic b-pillar structure under crash-safety requirements. Using this approach, the NSGA-II algorithm avoids geometrically infeasible areas and increases comparative structural performance.

关键词： multidisciplinary design optimization constraint strategies lightweight design geometric feasibility

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