A Reliability-Based Multidisciplinary Design Optimization Method with Evidence Theory and Probability Theory

Uncertainties, including aleatory and epistemic uncertainties, always exist in multidisciplinary system. Due to the discontinuous nature of epistemic uncertainty and the complex coupled relation among subsystems, the computational efficiency of reliability-based multidisciplinary design optimization (RBMDO) with mixed aleatory and epistemic uncertainties is extremely low. A novel RBMDO procedure is presented in this paper based on combined probability theory and evidence theory (ET) to deal with hybrid-uncertainties and improve the computational efficiency. Firstly, based on Bayes method, a novel method to define the probability density function of the aleatory variables is proposed. Secondly, the conventional equivalent normal method (J-C method) is modified to reliability analysis with hybrid-uncertainties. Finally, a novel RBMDO procedure is suggested by integrating the modified J-C method into the frame of sequence optimization and reliability analysis (SORA). Numerical examples and engineering example are applied to demonstrate the performance of the proposed method. The examples show the excellence of the RBMDO method both in computational efficiency and accuracy. The proposed method provides a practical and effective reliability design method for multidisciplinary system.

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Reliability-Based Multidisciplinary Design Optimization Using Subset Simulation Analysis and its Application in the Hydraulic Transmission Mechanism Design

Volume 4: 19th Design for Manufacturing and the Life Cycle Conference; 8th International Conference on Micro- and Nanosystems ◽

10.1115/detc2014-34732 ◽

2014 ◽

Author(s):

Debiao Meng ◽

Hong-Zhong Huang ◽

Zhonglai Wang ◽

Xiaoling Zhang ◽

Yu Liu

Keyword(s):

Design Optimization ◽

Reliability Analysis ◽

Computational Efficiency ◽

Multidisciplinary Design Optimization ◽

Simulation Analysis ◽

High Reliability ◽

Transmission Mechanism ◽

Multidisciplinary Design ◽

Sequential Optimization ◽

Subset Simulation

The traditional Monte Carlo Simulation (MCS) approach can provide high reliability analysis accuracy, however, with low computational efficiency. Especially, it is computationally expensive to evaluate a very small failure probability. In this paper, a Subset Simulation-based Reliability Analysis (SSRA) approach is combined with the Multidisciplinary Design Optimization (MDO) to improve the computational efficiency in the Reliability based Multidisciplinary Design Optimization (RBMDO) problems. Furthermore, the Sequential Optimization and Reliability Assessment (SORA) approach is utilized to decouple the RBMDO into MDO and reliability analysis. The formula of MDO with SSRA within the framework of SORA (MDO-SSRA-SORA) is proposed to solve the design optimization problem of hydraulic transmission mechanism.

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A reliability-based multidisciplinary design optimization procedure based on combined probability and evidence theory

Structural and Multidisciplinary Optimization ◽

10.1007/s00158-013-0901-1 ◽

2013 ◽

Vol 48 (2) ◽

pp. 339-354 ◽

Cited By ~ 48

Author(s):

Wen Yao ◽

Xiaoqian Chen ◽

Qi Ouyang ◽

Michel van Tooren

Keyword(s):

Design Optimization ◽

Multidisciplinary Design Optimization ◽

Evidence Theory ◽

Optimization Procedure ◽

Multidisciplinary Design

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Multidisciplinary Design Optimization: A New Way to Bring Softer Bows

Volume 2: Structures, Safety and Reliability ◽

10.1115/omae2008-57145 ◽

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.

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An improved particle swarm optimization algorithm for dynamic analysis of chain drive based on multidisciplinary design optimization

Advances in Mechanical Engineering ◽

10.1177/1687814019829611 ◽

2019 ◽

Vol 11 (3) ◽

pp. 168781401982961

Author(s):

Mengjiang Chai ◽

Yongliang Yuan ◽

Wenjuan Zhao

Keyword(s):

Particle Swarm Optimization ◽

Design Optimization ◽

Optimization Algorithm ◽

Multidisciplinary Design Optimization ◽

Particle Swarm Optimization Algorithm ◽

Optimization Method ◽

Drive System ◽

Multidisciplinary Design ◽

Chain Drive ◽

Swarm Optimization

Chain drive is one of the most commonly used mechanical devices in the main equipment transmission system. In the past decade, scholars focused on basic performance research, but ignore its best performance. In this study, due to the large vibration of the chain drive in the transmission system, the vibration performance and optimization parameters are also considered as a new method to design the chain drive system to obtain the best performance of the chain drive system. This article proposes a new method and takes a chain drive design as a case based on the multidisciplinary design optimization. The system optimization objective and sub-systems are established by the multidisciplinary design optimization method. To obtain the best performance for the chain, the chain drive is executed by an improved particle swarm optimization algorithm. Dynamic characteristics of the chain drive system are simulated based on the multidisciplinary design optimization results. The impact force of the chain links, vibration displacement, and the vibration frequency are analyzed. The results show that the kinematics principle of the chain drive and the optimal parameter value are obtained based on the multidisciplinary design optimization method.

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