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.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Time-Dependent Reliability-Based Robust Optimization Design of Components Structure

2011 ◽  
Vol 199-200 ◽  
pp. 456-462 ◽  
Author(s):  
Bao Yan Wang ◽  
Xin Gang Wang ◽  
Li Sha Zhu ◽  
Hao Lu
Keyword(s):  
Robust Optimization ◽  
Design Theory ◽  
Optimization Design ◽  
Time Dependent ◽  
Model Combining ◽  
Reliability Sensitivity ◽  
Reliability Sensitivity Analysis ◽  
Sensitivity Analysis Method ◽  
Robust Optimization Design ◽  
Reliability Based Optimization

Time-dependent reliability sensitivity design is discussed based on time-dependent reliability model, combining reliability optimization design theory and time-dependent reliability sensitivity analysis method, a problem on time-dependent reliability-based robust optimization design of components structure is studied, and a numerical method for reliability-based robust optimization design is also presented. The time-dependent reliability sensitivity is added to the reliability-based optimization design model and the reliability-based robust optimization design is described as a multi-objection optimization.

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 vehicle chassis product family

2021 ◽  
pp. 095440542110366
Author(s):  
Xiaokai Chen ◽  
Chenyu Wang ◽  
Guobiao Shi ◽  
Mingkai Zeng
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Multidisciplinary Design Optimization ◽  
Optimization Design ◽  
Optimization Problem ◽  
Product Family ◽  
Multidisciplinary Design ◽  
Product Family Design ◽  
Product Platforms ◽  
Product Family Optimization

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.

Multidisciplinary Design Optimization for Small Vertical Wind Turbine Design

2014 ◽  
Vol 571-572 ◽  
pp. 1083-1086
Author(s):  
Qiu Yun Mo ◽  
Fei Deng ◽  
Shuai Shuai Li ◽  
Ke Yan Zhang
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Design Theory ◽  
Optimization Problems ◽  
Vertical Wind ◽  
Multidisciplinary Design ◽  
Existing Problems ◽  
Depth Study ◽  
Turbine Design

Multidisciplinary design optimization (MDO) represents the development direction of complex products design theory and method, it shows a huge advantage in solving complex optimization problems in engineering applications, for example product design. This paper briefly analyzes some existing problems of small vertical wind turbine, and puts forward using the theory of MDO in small vertical wind turbine structural optimization. Then,the paper analyzes and points out the key technology of using MDO theory to optimize small vertical wind turbine, and provides a new train of thought for further in-depth study of small vertical wind turbine to improve the overall performance of the small vertical wind turbine products.

Robust Optimization Design of Compensative Pulley Block of Luffing Mechanism Using the Compromise Decision Support Problem

2008 ◽  
Vol 44-46 ◽  
pp. 463-470 ◽  
Author(s):  
Xian Fu Cheng
Keyword(s):  
Decision Support ◽  
Mathematical Programming ◽  
Robust Optimization ◽  
Robust Design ◽  
Optimization Design ◽  
Mathematic Model ◽  
Programming Formulation ◽  
Robust Optimization Design ◽  
The Mean

Robust optimization design essentially has multiple objectives. The compromise Decision Support Problem (DSP) is a multi-objective mathematical programming formulation that is used to model engineering decisions involving multiple tradeoffs. In this paper, the compromise DSP is introduced to robust optimization design, and mathematic model of a compromise DSP for robust optimization design is presented. In this framework, the tradeoff between the mean and deviation of performance is made by solving the bi-objective robust design problem. To demonstrate the feasibility of this approach, a case study involving the design of the compensative pulley block of luffing mechanism is considered.

Method of Genetic Algorithm Optimization Design of Permanent Magnet Retarder

2012 ◽  
Vol 215-216 ◽  
pp. 362-367
Author(s):  
Yi Qi Huang ◽  
Gan Wei Cai ◽  
Yu Jiang ◽  
Zhao Yu Luo
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Permanent Magnet ◽  
Multidisciplinary Design Optimization ◽  
Optimization Design ◽  
Basic Structure ◽  
Multidisciplinary Design ◽  
Design Parameters ◽  
Magnetic Flux Density ◽  
Algorithm Optimization

This paper introduced the method of multidisciplinary design optimization based on genetic algorithm. The basic structure and new auxiliary braking mechanism of permanent magnet retarder was analyzed. The influences of magnetic field parameters, structural design parameters, rotor parameters and permanent magnet temperature parameters on the behaviors performance of the permanent magnet retarder were discussed. The conceptual model of permanent magnet retarder was developed to maximize the brake torque of the permanent magnet retarder. The design variables included the radial width and the axis length of permanent magnet, the number of permanent magnet, the radius of rotor, the thickness of rotor, and the air gas. The constraint conditions included permitting temperature of rotor, saturation magnetic flux density of magnet material, and relation of structural geometry. The results of design optimization variables were obtained by applying genetic algorithm. The multidisciplinary design optimization in this paper is an effective method for the global design optimization of the permanent magnet retarder.

Reliability-Based Robust Optimization Design for Rubbing Rotor System

2011 ◽  
Vol 105-107 ◽  
pp. 1100-1104
Author(s):  
Chang Qing Su ◽  
Le Xin Li ◽  
Yi Min Zhang
Keyword(s):  
Robust Design ◽  
Design Theory ◽  
Optimization Design ◽  
Design Method ◽  
Rotor System ◽  
Fourth Moment ◽  
Reliability Sensitivity ◽  
Robust Optimization Design ◽  
Reliability Based Optimization ◽  
First Four Moments

Based on the reliability-based optimization design theory, the reliability sensitivity technique and the robust design method, the reliability-based robust design of rubbing rotor system is extensively discussed and a numerical method for reliability-based robust design is proposed. The reliability sensitivity is added to the reliability-based optimization design model and the reliability-based robust design is described as a multi-objection optimization. On the condition of known first four moments of basic random variables, the respective program can be used to obtain the reliability-based robust design information of rubbing rotor system accurately and quickly using the fourth moment technique. According to the numerical results, the approach proposed is a convenient and practical reliability-based roust design method.

Design and Optimization of Injector Structure in Diesel Engine Based on ISIGHT Platform DOE Methods

2011 ◽  
Vol 335-336 ◽  
pp. 1376-1380
Author(s):  
Xin Ying Wu ◽  
Guang Yao Ouyang ◽  
Yu Xue Li
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Design ◽  
Design Method ◽  
Optimization Methods ◽  
Multidisciplinary Design ◽  
Design And Optimization ◽  
Traditional Design ◽  
Improved Performance

The traditional design method of injector structure cannot meet the demand of farther improved performance,the change of modern environment demand not only the optimization of one performance but also the optimization of various comprehensive performance.iSIGHT is a multidisciplinary design optimization platform that offer a integrated designenvironment and advanced design optimization methods. The optimization design of injector structure based on design of experiment of iSIGHT platform to improve the spray quality of injector is implemented.

Practical Robust Design Optimization Using Evolutionary Algorithms

2011 ◽  
Vol 133 (10) ◽  
Author(s):  
Amit Saha ◽  
Tapabrata Ray
Keyword(s):  
Evolutionary Algorithms ◽  
Robust Optimization ◽  
Design Optimization ◽  
Robust Design ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Computational Design ◽  
Robust Design Optimization ◽  
Function Evaluation ◽  
Engineering Design Problems

Robust design optimization (RDO) seeks to find optimal designs which are less sensitive to the uncontrollable variations that are often inherent to the design process. Studies using Evolutionary Algorithms (EAs) for RDO are not too many. In this work, we propose enhancements to an EA based robust optimization procedure with explicit function evaluation saving strategies. The proposed algorithm, IDEAR, takes into account a specified expected uncertainty in the design variables and then imposes the desired robustness criteria during the optimization process to converge to robust optimal solution(s). We pick up a number of Bi-objective engineering design problems from the standard literature and study them in the proposed robust optimization framework to demonstrate the enhanced performance. A cross-validation study is performed to analyze whether the solutions obtained are truly robust and also make some observations on how robust optimal solutions differ from the performance maximizing solutions in the design space. We perform a rigorous analysis of the key features of IDEAR to illustrate its functioning. The proposed function evaluation saving strategies are generic and their applications are worth exploring in other areas of computational design optimization.

Sign in / Sign up

Export Citation Format

Share Document