基于CAE的袋式除尘器多学科设计优化
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摘要
多学科设计优化技术(MDO)是针对复杂工程问题的优化提出的一种方法,主要应用在航空航天业的复杂产品的设计优化问题上,并得到飞速的发展。目前,多学科计优化已成为复杂产品设计的一个崭新的发展方向,是许多国际学术会议讨论的主题。
本文对多学科设计优化技术体系和方法应用进行了研究,并在此基础上将多学科设计优化技术和方法引入工业除尘设备设计领域,实现了袋式除尘器的多学科设计优化,有效的提高了袋式除尘器的综合性能。具体完成了如下工作：
一、在对国内外关于多学科设计优化技术方法的理论及工程应用的现状、多学科设计优化技术体系进行调研的基础上,论述了多学科设计优化技术体系的定义、组成及实质,对目前存在的多学科优化算法及其流程、特点进行了分析对比。
二、分析了协同优化的数学本质,建立协调优化数学模型；对基于CEA技术的协同优化框架的实现过程,引进响应面近似方法,建立了基于响应面协同优化算法数学模型,通过算例作了深入研究。
三、针对袋式除尘器这一产品复杂结构,结合工程实际设计要求,确定计算区域,给出计算工况及相关假设,建立了袋式除尘器基于响应面协同优化数学模型。对袋式除尘器多目标进行线性加权处理,构建了袋式除尘器综合性能评价函数。
四、在CAE集成环境下实现了袋式除尘器的多学科设计优化方法的计算框架,并成功将Gambit、Fluent及ANSYS等CEA软件进行集成,建立了针对协同优化特殊计算框架所需要并行计算的运行环境；利用该设计优化框架对袋式除尘器进行了设计优化,取得了良好的效果,为复杂工业产品设计提供了一种新的设计方法。
Multidisciplinary Design Optimization (MDO) is a method for optimization of complex engineering problems. Now,it is mainly used in complex product design optimization of aerospace industry,and rapid developing. Currently, Multidisciplinary Design Optimization (MDO) has become a new direction for complex product design.
In this paper, I research MDO's system and methods, on this basis,introduct it to industrial dust-removal equipment design,achieve MDO of bag filter, effectively improve the comprehensive performance of bag filter.
Specifically completed the following work:
First, on the basis of the domestic and international scholars researching on MDO's theory of technical methods,engineering application status and system, I discuss the MDO's definition,composition and substance, Meanwhile, analyze and contrast MDO's algorithm, process, characteristic.
Second, I analyze the mathematical nature of collaborative optimization and create mathematical model of collaborative optimization. On the process of achieving CEA-based collaborative optimization framework, I introduce response surface approximation, establish collaborative optimization algorithm based on response surface and depth study by an example.
Third, for bag filter such a complex structure, in combination with engineering design requirements, I determine the computational domain, propose calculation condition and underlying assumptions, establish collaborative optimization algorithm based on response surface for bag filter. I execute linear weighting for bag filter multi-objective and establish comprehensive performance evaluation function.
Fourth, I achieve the multi-disciplinary design optimization computational framework under the CAE environment, successfully integrate Gambit, Fluent and ANSYS such as CEA software and establish parallel operating environment for collaborative optimization special computing framework. Making use of design optimization framework, I design and optimize the bag filter, achieve good results, provide a new design for design of complex industrial products.
本文对多学科设计优化技术体系和方法应用进行了研究,并在此基础上将多学科设计优化技术和方法引入工业除尘设备设计领域,实现了袋式除尘器的多学科设计优化,有效的提高了袋式除尘器的综合性能。具体完成了如下工作：
一、在对国内外关于多学科设计优化技术方法的理论及工程应用的现状、多学科设计优化技术体系进行调研的基础上,论述了多学科设计优化技术体系的定义、组成及实质,对目前存在的多学科优化算法及其流程、特点进行了分析对比。
二、分析了协同优化的数学本质,建立协调优化数学模型；对基于CEA技术的协同优化框架的实现过程,引进响应面近似方法,建立了基于响应面协同优化算法数学模型,通过算例作了深入研究。
三、针对袋式除尘器这一产品复杂结构,结合工程实际设计要求,确定计算区域,给出计算工况及相关假设,建立了袋式除尘器基于响应面协同优化数学模型。对袋式除尘器多目标进行线性加权处理,构建了袋式除尘器综合性能评价函数。
四、在CAE集成环境下实现了袋式除尘器的多学科设计优化方法的计算框架,并成功将Gambit、Fluent及ANSYS等CEA软件进行集成,建立了针对协同优化特殊计算框架所需要并行计算的运行环境；利用该设计优化框架对袋式除尘器进行了设计优化,取得了良好的效果,为复杂工业产品设计提供了一种新的设计方法。
Multidisciplinary Design Optimization (MDO) is a method for optimization of complex engineering problems. Now,it is mainly used in complex product design optimization of aerospace industry,and rapid developing. Currently, Multidisciplinary Design Optimization (MDO) has become a new direction for complex product design.
In this paper, I research MDO's system and methods, on this basis,introduct it to industrial dust-removal equipment design,achieve MDO of bag filter, effectively improve the comprehensive performance of bag filter.
Specifically completed the following work:
First, on the basis of the domestic and international scholars researching on MDO's theory of technical methods,engineering application status and system, I discuss the MDO's definition,composition and substance, Meanwhile, analyze and contrast MDO's algorithm, process, characteristic.
Second, I analyze the mathematical nature of collaborative optimization and create mathematical model of collaborative optimization. On the process of achieving CEA-based collaborative optimization framework, I introduce response surface approximation, establish collaborative optimization algorithm based on response surface and depth study by an example.
Third, for bag filter such a complex structure, in combination with engineering design requirements, I determine the computational domain, propose calculation condition and underlying assumptions, establish collaborative optimization algorithm based on response surface for bag filter. I execute linear weighting for bag filter multi-objective and establish comprehensive performance evaluation function.
Fourth, I achieve the multi-disciplinary design optimization computational framework under the CAE environment, successfully integrate Gambit, Fluent and ANSYS such as CEA software and establish parallel operating environment for collaborative optimization special computing framework. Making use of design optimization framework, I design and optimize the bag filter, achieve good results, provide a new design for design of complex industrial products.
引文
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[2]卢键.脉冲布袋除尘器薄壳压型板结构优化设计[D].西安建筑科技大学,2004.
[3]赵友军.袋式除尘器内部流场分布试验测试及数值模拟研究[D].东华大学,2008.
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[21]王婧超.航空发动机三维单晶涡轮叶片的多学科设计优化[D].西北工业大学,2007.
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