基于信息熵与耦元杂交集成的高比刚度结构仿生拓扑优化方法研究

The research start point of this project is that the mechanical structure bionic topology optimization design is realized by imitating the efficient space topology structure of biology. The indeterminacy effect on structure bionic topology optimization is caused by inherent differences of same species. So the information entropy is introduced to eliminate the interference from this indeterminacy. A recognition and extraction method of feature information of coupling element topology structure based on the information entropy is proposed, so as to obtain the rule of topology structure–bearing mechanism of biology (i.e. the efficient space topology structure information) accurately. Also the structure bionic topology optimization design method based on information entropy is proposed, so as to establish the mapping relationship between biology space topology structure and structure bionic topology optimization high specific stiffness design, and to realize the mapping transfer from biology space topology information to structure bionic topology optimization high specific stiffness design accurately. Aiming at that the structure bionic topology optimization is always only oriented towards the topology structure of certain one biology, the method for complementing /enhancing high stiffness performance of mechanical topological structure based on hybrid integration of coupling element is proposed. With the efficient topology structures of different biologies, through hybrid integration of different structure coupling element, the complementary/enhanced stiffness performances of structure bionic topology optimization design are further realized. Finally the multi objective properties requirements of structure bionic topology optimization design such as high specific stiffness in different directions are satisfied. The bionic topology optimization layout redesigns of structure stiffener of typical plate-shell-shape bearing part and box-shape bearing part are taking as examples to verify this structure bionic topology optimization method.

以借助生物体高效承载拓扑构型实现机械结构仿生拓扑优化高比刚度设计为研究出发点。针对同种生物固有差异性对结构仿生拓扑优化带来的不确定性影响，引入信息熵消除该不确定性影响干扰，提出基于信息熵的耦元拓扑构型特征信息提取方法，准确获取生物空间拓扑构型－承载机制规律（即生物空间拓扑构型信息）；提出基于信息熵的结构仿生拓扑优化高比刚度设计方法，构建生物空间拓扑构型与拓扑优化高比刚度设计结构之间的映射关系，实现生物拓扑构型信息至仿生拓扑优化设计的准确映射传递。针对结构仿生拓扑优化多仅为面向某一生物拓扑构型的结构仿生设计，提出基于耦元杂交集成的高效能拓扑结构高比刚度优势互补/增强方法，通过多种生物高效拓扑构型耦元杂交，进一步实现拓扑结构高比刚度优势互补/增强，达到结构仿生设计中如不同方向高比刚度的多目标性能要求。以典型板壳式及箱体式承载件的结构加强筋仿生拓扑优化布局再设计为例，验证该结构仿生拓扑优化方法。

用仿生学方法，借助生物体高效承载空间拓扑构型，对机械装备承载件进行结构仿生拓扑优化高比刚度设计，达到结构轻量化高比刚度设计目的，是机械结构轻量化的重要手段之一。. 本研究包括：（1）基于子结构技术的思想，将子结构技术引入结构仿生拓扑设计，提出了基于生物胞元的结构仿生拓扑设计方法。提取表征生物高效承载性能的空间拓扑构型子结构即表征生物高效承载的生物胞元，基于子结构方法以生物胞元进行机械承载件中筋、肋、框等加强结构的仿生拓扑设计，借助生物高效承载拓扑构型实现机械承载件高比刚度拓扑优化。进一步地，提出了基于TRIZ创新原理的生物混合胞元建模，以实现面向不同生物高效承载空间拓扑结构集成的结构仿生拓扑优化设计。（2）提出了统计学原理的生物胞元建模方法，以消除同种生物差异性影响给生物胞元建模过程带来的不确定性影响。根据相似性原理确定仿生源的基础上，以统计学方法对生物胞元高效承载构型特征进行统计研究，获取生物高效承载胞元的确定性特征参数。进一步借助前述基于生物胞元的结构仿生拓扑设计方法，实现生物胞元到高比刚度结构的映射设计。（3）提出了基于RMI和耦元杂交的生物多优势性能集成的结构仿生过程建模及设计方法，通过不同生物高比刚度耦元杂交，以实现不同的生物体高比刚度优势性能集成。该研究主要用以解决以下问题：单一生物拓扑构型的高比刚度结构仿生设计的力学适应性单一化，最终实现的多为面向单一承载性能目标的结构仿生优化设计，其承载力学性能存在不足或较大优化空间。. 共发表论文6篇，其中以第一作者发表SCI论文2篇、EI论文2篇；以第一发明人获授权发明专利3项、获授权实用新型专利2项、实审阶段发明专利7项，培养硕士研究生2名。. 该课题为面向生物体高效能空间拓扑构型的结构仿生拓扑优化方法，对丰富工程机械轻量化设计研究路径、完善机械装备轻量化设计理论体系具有重要意义。

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