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

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.

Multidisciplinary Design Optimization of Small Canister-Launched Space Launch Vehicle Using Genetic Algorithm

2013 ◽  
Vol 302 ◽  
pp. 583-588 ◽  
Author(s):  
Fredy M. Villanueva ◽  
Lin Shu He ◽  
Da Jun Xu
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimal Solution ◽  
Optimization Method ◽  
Launch Vehicle ◽  
Low Earth Orbit ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Design Variables

A multidisciplinary design optimization approach of a three stage solid propellant canister-launched launch vehicle is considered. A genetic algorithm (GA) optimization method has been used. The optimized launch vehicle (LV) is capable of delivering a microsatellite of 60 kg. to a low earth orbit (LEO) of 600 km. altitude. The LV design variables and the trajectory profile variables were optimized simultaneously, while a depleted shutdown condition was considered for every stage, avoiding the necessity of a thrust termination device, resulting in reduced gross launch mass of the LV. The results show that the proposed optimization approach was able to find the convergence of the optimal solution with highly acceptable value for conceptual design phase.

Multidisciplinary design optimization under correlated uncertainties

2017 ◽  
Vol 25 (3) ◽  
pp. 262-275 ◽  
Author(s):  
Huanwei Xu ◽  
Wei Li ◽  
Liudong Xing ◽  
Shun-Peng Zhu
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Quantitative Model ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Engineering System ◽  
Optimization Approach ◽  
Complex Mechanical Systems

Uncertainty analysis is a hot research topic in multidisciplinary design optimization for complex mechanical systems. Existing multidisciplinary design optimization works typically assume that uncertainties are uncorrelated of each other. In real-world engineering systems, however, correlations do exist between different uncertainties. The multidisciplinary design optimization methods without considering correlations between uncertainties may cause inaccuracy and thus misleading optimization results. In this article, we make contributions by proposing a new multidisciplinary design optimization approach based on the ellipsoidal set theory to investigate the characteristics of correlated uncertainties and incorporate their effects in the multidisciplinary design optimization through an advanced collaborative optimization method, where the quantitative model of correlated uncertainties is transformed into constrains of subsystems. Both a mathematical example and a case study of an engineering system are provided to illustrate feasibility and validity of the proposed method.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

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.

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

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.

Possibility-Based Multidisciplinary Design Optimization in the Framework of Sequential Optimization and Reliability Assessment

2009 ◽  
Author(s):  
Xudong Zhang ◽  
Hong-Zhong Huang ◽  
Shengkui Zeng ◽  
Zhili Wang
Keyword(s):  
Design Optimization ◽  
Engineering Design ◽  
Multidisciplinary Design Optimization ◽  
High Reliability ◽  
Reliability Assessment ◽  
Coupled Systems ◽  
Multidisciplinary Design ◽  
Sequential Optimization ◽  
Sufficient Information ◽  
Early Design

Reliability Based Multidisciplinary Design Optimization (RBMDO) has received increasing attention to reach high reliability and safety in complex and coupled systems. In early design of such systems, however, information is often not sufficient to construct the precise probabilistic distributions required by the RBMDO and consequently RBMDO can not be carried out effectively. The present work proposes a method of Possibility Based Multidisciplinary Design Optimization (PBMDO) within the framework of the Sequential Optimization and Reliability Assessment (PBMDO-SORA). The proposed method enables designers to solve MDO problems without sufficient information on the uncertainties associated with variables, and also to efficiently decrease the computational demand. The efficiency of the proposed method is illustrated with an engineering design.

Multidisciplinary Robust Optimization Design of Multi-Functional Open-Air Hydraulic Drill

2010 ◽  
Vol 44-47 ◽  
pp. 1135-1140 ◽  
Author(s):  
You Xin Luo ◽  
Hui Jun Wen ◽  
Heng Shu Li
Keyword(s):  
Robust Optimization ◽  
Uncertainty Analysis ◽  
Design Optimization ◽  
Robust Design ◽  
Multidisciplinary Design Optimization ◽  
Design Theory ◽  
Optimization Design ◽  
Optimal Solution ◽  
Multidisciplinary Design ◽  
Robust Optimization Design

In this paper, the basic concepts and methods of multidisciplinary design optimization, uncertainty analysis and robust design have been introduced. According to the features of a multi-functional open-air hydraulic drill, a new design theory called multidisciplinary robust optimization design was discussed. This theory can undertake uncertainty analysis and robust design in multidisciplinary design optimization. It fully considers both the synergy among each disciplinary or subsystem in the multi-functional open-air hydraulic drill to get the optimal solution to the whole system and the effect of the uncertainty factors upon the drill quality, and adopts the parallel design to improve the quality, robustness and reliability of the drill, to shorten the market cycles of products, to reduce product cost. Finally, the design points were discussed in detail in the paper.

scholarly journals Reliability-Based Multidisciplinary Design Optimization under Correlated Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Huanwei Xu ◽  
Xin Wang ◽  
Wei Li ◽  
Mufeng Li ◽  
Suichuan Zhang ◽  
...  
Keyword(s):  
Design Optimization ◽  
Set Theory ◽  
Multidisciplinary Design Optimization ◽  
Reliability Assessment ◽  
Multidisciplinary Design ◽  
Sequential Optimization ◽  
Engineering System ◽  
First Order ◽  
Reliability Method

Complex mechanical system is usually composed of several subsystems, which are often coupled with each other. Reliability-based multidisciplinary design optimization (RBMDO) is an efficient method to design such complex system under uncertainties. However, the present RBMDO methods ignored the correlations between uncertainties. In this paper, through combining the ellipsoidal set theory and first-order reliability method (FORM) for multidisciplinary design optimization (MDO), characteristics of correlated uncertainties are investigated. Furthermore, to improve computational efficiency, the sequential optimization and reliability assessment (SORA) strategy is utilized to obtain the optimization result. Both a mathematical example and a case study of an engineering system are provided to illustrate the feasibility and validity of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document