A PMA-Based Collaborative Strategy for Reliability Design and Optimization of Multidisciplinary Systems

2011 ◽  
Vol 418-420 ◽  
pp. 411-414 ◽  
Author(s):  
Rong Gang Yu ◽  
Jun Zhang ◽  
Bing Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Main Idea ◽  
Performance Measure ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Sequential Optimization ◽  
Reliability Design ◽  
Design And Optimization ◽  
Index Approach

To tackle the computing efficiency and robustness problems caused by the reliability index approach (RIA) in reliability-based multidisciplinary design optimization (RBMDO), a new performance measure approach-based method for RBMDO is proposed. Meanwhile, the traditional triple-level nested flowchart of RBMDO is decoupled through the main idea of sequential optimization and reliability assessment (SORA). Both deterministic multidisciplinary design optimization and the multidisciplinary reliability analysis are executed by collaborative optimization (CO). Finally, the proposed method is verified through the design example of gear transmission.

A Collaborative Approach for Multidisciplinary Systems Reliability Design and Optimization

2013 ◽  
Vol 694-697 ◽  
pp. 911-914 ◽  
Author(s):  
Jun Zhang ◽  
Bing Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Procedure ◽  
Performance Measure ◽  
Multidisciplinary Design ◽  
Sequential Optimization ◽  
Optimization Strategy ◽  
Reliability Design ◽  
Design And Optimization ◽  
Subspace Optimization

In order to improve the efficiency and robustness of reliability-based multidisciplinary design optimization (RBMDO), a new collaborative strategy (named C-RBMDO) which integrates performance measure approach (PMA) and concurrent subspace optimization strategy (CSSO) is proposed. Both the mathematical model and optimization procedure are put forward. The traditional triple-level nested flowchart of RBMDO is decoupled with the sequential optimization and reliability assessment (SORA). The deterministic multidisciplinary design optimization and the multidisciplinary reliability analysis are executed by CSSO and PMA respectively. Finally, the proposed method is verified through the design example of gear transmission.

Study on Multidisciplinary Design Optimization of 3-RRS Parallel Robot

2012 ◽  
Vol 214 ◽  
pp. 919-923
Author(s):  
Jing Zhang ◽  
Bai Lin Li
Keyword(s):  
Genetic Algorithm ◽  
Quadratic Programming ◽  
Design Optimization ◽  
Sequential Quadratic Programming ◽  
Multidisciplinary Design Optimization ◽  
Main Idea ◽  
Parallel Robot ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Robot System

The paper aims to apply the idea of multidisciplinary design optimization to the design of robot system. The main idea of collaborative optimization is introduced. The collaborative optimization frame of 3-RRS parallel robot is analyzed. With the method of genetic algorithm and Sequential Quadratic Programming, the investigation is made on the executing collaborative optimization of working stroke, driving performance and hydraulic components. The numerical results indicate that the collaborative optimization can be successfully applied to dealing with the complex robot system, and lay a foundation to solve more complex mechanical system.

Performance Measure Approach Based Multidisciplinary Design Optimization of Gear Transmission

2013 ◽  
Vol 694-697 ◽  
pp. 868-871
Author(s):  
Jun Zhang ◽  
Bing Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Performance Measure ◽  
Collaborative Optimization ◽  
Gear Transmission ◽  
System Level ◽  
Multidisciplinary Design ◽  
Engineering Systems ◽  
Performance Measure Approach ◽  
Design Cost

In order to reduce the influence of uncertainties on complicated engineering systems performance, a new method is proposed based on the performance measure approach and collaborative optimization (PMA-CO) to implement the reliability-based multidisciplinary design optimization of gear transmission. Both the mathematical model and procedures of PMA-CO are presented. With the adoption of slack factors in the system-level of collaborative optimization, both CO and PMA-CO are applied to the optimization of gear transmission. The proposed PMA-CO improves the reliability of the gear transmission and gained a tradeoff solution between design cost and reliability. Therefore, the PMA-CO is effective and practical in engineering design.

Reliability allocation method based on multidisciplinary design optimization for electromechanical equipment

2014 ◽  
Vol 229 (14) ◽  
pp. 2573-2585 ◽  
Author(s):  
Yongjun Liu ◽  
Jinwei Fan ◽  
Donghui Mu
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Collaborative Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Main Task ◽  
Reliability Allocation ◽  
Reliability Design ◽  
Allocation Method ◽  
Electromechanical Equipment

Reliability design is one important link to assure the product’s quality. Reliability allocation is the main task of reliability design, which is influenced by cost, manufacturing consistency, and other factors. Reliability, cost, and manufacturing consistency are coupled and influenced by each other. To find the global optimal reliability indices, one modeling and solving method of reliability allocation based on multidisciplinary design optimization was proposed in the paper. The influence factors of reliability allocation were analyzed and calculated or fuzzy processed. The reliability allocation optimization models were created, and the models were decomposed by the calculation frame of collaborative optimization. The genetic algorithm of the system-level optimization and the sequential quadratic programming algorithm of the disciplinary-level optimization were adopted. As one typical electromechanical equipment, CNC cylindrical grinder was allocated of reliability by the method proposed in the paper. The results showed that the cost can be dropped 3.45%, 4.76%, 4.72%, and 8.45% compared by equal allocation method, fuzzy allocation method, AGREE allocation method, and actual cost, respectively. The reliability allocation method proposed in the article can be used in design of electromechanical equipment to reduce costs.

Support Vector Regression-Based Multidisciplinary Design Optimization for Ship Design

2012 ◽  
Author(s):  
Dongqin Li ◽  
Yifeng Guan ◽  
Qingfeng Wang ◽  
Zhitong Chen
Keyword(s):  
Design Optimization ◽  
Support Vector Regression ◽  
Design Process ◽  
Multidisciplinary Design Optimization ◽  
Initial Point ◽  
Ship Design ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Support Vector ◽  
Independent Design

The design of ship is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional design process of ship only involves independent design optimization within each discipline. With such an approach, there is no guarantee to achieve the optimum design. And at the same time improving the efficiency of ship optimization is also crucial for modem ship design. In this paper, an introduction of both the traditional ship design process and the fundamentals of Multidisciplinary Design Optimization (MDO) theory are presented and a comparison between the two methods is carried out. As one of the most frequently applied MDO methods, Collaborative Optimization (CO) promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, Design Of Experiment (DOE) and a new support vector regression algorithm are applied to CO to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. Then this new Collaborative Optimization (CO) method using approximate technology is discussed in detail and applied in ship design which considers hydrostatic, propulsion, weight and volume, performance and cost. It indicates that CO method combined with approximate technology can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.

scholarly journals Multidisciplinary design optimization of hard rock tunnel boring machine using collaborative optimization

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401875472 ◽  
Author(s):  
Wei Sun ◽  
Xiaobang Wang ◽  
Maolin Shi ◽  
Zhuqing Wang ◽  
Xueguan Song
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Hard Rock ◽  
Tunnel Boring Machine ◽  
Collaborative Optimization ◽  
Optimization Process ◽  
Multidisciplinary Design ◽  
Tunnel Boring ◽  
Geological Conditions ◽  
Rock Tunnel

A multidisciplinary design optimization model is developed in this article to optimize the performance of the hard rock tunnel boring machine using the collaborative optimization architecture. Tunnel boring machine is a complex engineering equipment with many subsystems coupled. In the established multidisciplinary design optimization process of this article, four subsystems are taken into account, which belong to different sub-disciplines/subsytems: the cutterhead system, the thrust system, the cutterhead driving system, and the economic model. The technology models of tunnel boring machine’s subsystems are build and the optimization objective of the multidisciplinary design optimization is to minimize the construction period from the system level of the hard rock tunnel boring machine. To further analyze the established multidisciplinary design optimization, the correlation between the design variables and the tunnel boring machine’s performance is also explored. Results indicate that the multidisciplinary design optimization process has significantly improved the performance of the tunnel boring machine. Based on the optimization results, another two excavating processes under different geological conditions are also optimized complementally using the collaborative optimization architecture, and the corresponding optimum performance of the hard rock tunnel boring machine, such as the cost and energy consumption, is compared and analysed. Results demonstrate that the proposed multidisciplinary design optimization method for tunnel boring machine is reliable and flexible while dealing with different geological conditions in practical engineering.

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.

Multi-objective collaborative multidisciplinary design optimization using particle swarm techniques and fuzzy decision making

2012 ◽  
Vol 226 (9) ◽  
pp. 2281-2295 ◽  
Author(s):  
Mohammad Reza Farmani ◽  
Jafar Roshanian ◽  
Meisam Babaie ◽  
Parviz M Zadeh
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Fuzzy Decision ◽  
Swarm Optimization ◽  
Multi Objective

This article focuses on the efficient multi-objective particle swarm optimization algorithm to solve multidisciplinary design optimization problems. The objective is to extend the formulation of collaborative optimization which has been widely used to solve single-objective optimization problems. To examine the proposed structure, racecar design problem is taken as an example of application for three objective functions. In addition, a fuzzy decision maker is applied to select the best solution along the pareto front based on the defined criteria. The results are compared to the traditional optimization, and collaborative optimization formulations that do not use multi-objective particle swarm optimization. It is shown that the integration of multi-objective particle swarm optimization into collaborative optimization provides an efficient framework for design and analysis of hierarchical multidisciplinary design optimization problems.

Multidisciplinary Design Optimization: A New Way to Bring Softer Bows

2008 ◽  
Author(s):  
Zhiqiang Hu ◽  
Weicheng Cui ◽  
Jianmin Yang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Method ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Force Density ◽  
Optimization Analysis ◽  
Resistance Reduction ◽  
Collision Force ◽  
Bulbous Bow

It is well known that sharp bulbous bow has a good performance on ship resistance reduction, but it is also threatens the struck ships and the environment greatly. For their own economy profit, ship owners would like the bulbous bow to be designed sharp and rigid. However, from the viewpoint of environmental protection, the bulbous bow should be designed blunt and soft. Multidisciplinary Design Optimization (MDO) is a prosperous design concept and technique, to reconcile this problem effectively. The basic concept and theories of MDO are introduced in this paper. An optimization analysis is accomplished on the bulbous bow design for a container ship, using Collaborative Optimization Method. The characters of the bulbous bow on resistance reduction, collision force density and structural strength requirement are all considered at the same time. A compatible bulbous bow can be obtained by this way.

Application of Multidisciplinary Design Optimization in the Truss Spar Concept Design

2010 ◽  
Author(s):  
Zhe Jiang ◽  
Weicheng Cui ◽  
Xiaoping Huang
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Multidisciplinary Design Optimization ◽  
Coupling Effect ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Design Solution ◽  
Traditional Design ◽  
System Solution ◽  
Truss Spar

In the traditional design of a Truss Spar, designers usually choose different discipline as major concentration in different design phases. The coupling effect among disciplines can hardly be accounted for. Multidisciplinary design optimization has been proved to be an effective tool for the design of complex engineering systems, which takes all disciplines into account at the same time and exploit coupling effect among disciplines, thereby achieving the optimal system solution. In this paper, a multidisciplinary optimization scheme for a Truss Spar is firstly developed and the Truss Spar is decomposed into four modules: weight module, hydrodynamic module, structure module and stability module. Response surface method is used to replace the high-fidelity analysis to perform the approximate mathematical models of the objective function/constraints as a function of design variables. In order to enhance the accuracy of the predicted optimum, the response surface models are continuously updated using the information obtained from the numerical simulation of latest iterative results. Finally, an optimal design solution, which satisfies all the constraints, is obtained using collaborative optimization. The characteristics of the optimized design solution including hull weight, heave response, stability performance and strength of the bottom deck, are much improved comparing with traditional design.

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