Multidisciplinary Design Optimization Approach to Conceptual Design of a LEO Earth Observation Microsatellite

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

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Multidisciplinary Design Optimization of a Lunar Lander’s Soft-Landing Gear

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.42.118 ◽

2010 ◽

Vol 42 ◽

pp. 118-121

Author(s):

Yun Tong Lu ◽

Chun Jie Wang ◽

Ang Li ◽

Han Wang

Keyword(s):

Design Optimization ◽

Multidisciplinary Design Optimization ◽

Rapid Development ◽

Fem Analysis ◽

Landing Gear ◽

Collaborative Optimization ◽

Multidisciplinary Design ◽

Optimization Approach ◽

Soft Landing ◽

Multi Body

The rapid development of Multidisciplinary Design Optimization (MDO) approach can simultaneously guarantee the cut of cost on design and optimal performance of spacecraft. Based on the theory of Collaborative Optimization approach (CO) of MDO, present paper proposes the method of CO by integrating Pro/E(3D modeling), Patran/Nastran(FEM analysis) and ADAMS(multi-body dynamic analysis) with the Isight software. In the analysis of the soft-landing gear of Lunar Lander, this method can optimize the mass of the landing gear and meanwhile ensures the reliability of structure statics, structure dynamics and multi-body dynamics. Thus the feasibility, applied value and guideline significance of this method in spacecraft structural design are proven.

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Reliability and Possibility Based Multidisciplinary Design Optimization for Aircraft Conceptual Design

11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference ◽

10.2514/6.2011-6960 ◽

2011 ◽

Cited By ~ 3

Author(s):

Hyeong-Uk Park ◽

Joon Chung ◽

Jaewoo Lee ◽

Kamran Behdinan ◽

Daniel Neufeld

Keyword(s):

Design Optimization ◽

Conceptual Design ◽

Multidisciplinary Design Optimization ◽

Multidisciplinary Design ◽

Aircraft Conceptual Design

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Multidisciplinary Design Optimization on Conceptual Design of Aero-engine

International Journal of Turbo and Jet Engines ◽

10.1515/tjj-2015-0024 ◽

2016 ◽

Vol 33 (2) ◽

Cited By ~ 2

Author(s):

Xiao-bo Zhang ◽

Zhan-xue Wang ◽

Li Zhou ◽

Zeng-wen Liu

Keyword(s):

Design Optimization ◽

Conceptual Design ◽

Multidisciplinary Design Optimization ◽

System Level ◽

Multidisciplinary Design ◽

Design Stage ◽

Surface Model ◽

Coupled Problem ◽

Aero Engine ◽

Integrated Performance

AbstractIn order to obtain better integrated performance of aero-engine during the conceptual design stage, multiple disciplines such as aerodynamics, structure, weight, and aircraft mission are required. Unfortunately, the couplings between these disciplines make it difficult to model or solve by conventional method. MDO (Multidisciplinary Design Optimization) methodology which can well deal with couplings of disciplines is considered to solve this coupled problem. Approximation method, optimization method, coordination method, and modeling method for MDO framework are deeply analyzed. For obtaining the more efficient MDO framework, an improved CSSO (Concurrent Subspace Optimization) strategy which is based on DOE (Design Of Experiment) and RSM (Response Surface Model) methods is proposed in this paper; and an improved DE (Differential Evolution) algorithm is recommended to solve the system-level and discipline-level optimization problems in MDO framework. The improved CSSO strategy and DE algorithm are evaluated by utilizing the numerical test problem. The result shows that the efficiency of improved methods proposed by this paper is significantly increased. The coupled problem of VCE (Variable Cycle Engine) conceptual design is solved by utilizing improved CSSO strategy, and the design parameter given by improved CSSO strategy is better than the original one. The integrated performance of VCE is significantly improved.

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Uncertainty-Based Multidisciplinary Design Optimization for Feedback-Coupled Systems Under Both Parametric and Metamodeling Uncertainties

Volume 11B: 46th Design Automation Conference (DAC) ◽

10.1115/detc2020-22161 ◽

2020 ◽

Author(s):

Zhao Liu ◽

Zhouzhou Song ◽

Ping Zhu ◽

Can Xu

Keyword(s):

Design Optimization ◽

Multidisciplinary Design Optimization ◽

Optimal Solution ◽

Simulation Models ◽

Coupled Systems ◽

Multidisciplinary Design ◽

Engineering System ◽

Optimization Approach ◽

Satellite Design ◽

Consistency Constraints

Abstract Uncertainty-based multidisciplinary design optimization (UMDO) is an effective methodology to deal with uncertainties in the engineering system design. In order to shorten the design cycle and improve the design efficiency, the time-consuming computer simulation models are often replaced by metamodels, which consequently introduces metamodeling uncertainty into the UMDO procedure. The optimal solutions may deviate from the true results or even become infeasible if the metamodeling uncertainty is neglected. However, it is difficult to quantify and propagate the metamodeling uncertainty, especially in the UMDO process with feedback-coupled systems since the interdisciplinary consistency needs to be satisfied. In this paper, a new approach is proposed to solve the UMDO problem for the feedback-coupled systems under both parametric and metamodeling uncertainties. This approach adopts the decoupled formulation and it applies the Kriging technique to quantify the metamodeling uncertainty. The polynomial chaos expansion (PCE) technique is applied to propagate the two types of uncertainties and represent the interdisciplinary consistency constraints. In the optimization approach, the proposed method uses the iterative construction of PCE models for response means and variances to satisfy the multidisciplinary consistency at the optimal solution. The proposed approach is verified by a mathematical example and applied to the fire satellite design. The results demonstrate the proposed approach can solve the UMDO problem for coupled systems accurately and efficiently.

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