编织复合材料结构与材料一体化优化设计
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摘要
传统复合材料构件的设计过程,一般是先设计出具有一定性能的复合材料,再由这种具有特定性能的复合材料加工成构件,而编织复合材料构件和材料是同时形成,不再由复合材料加工成复合材料构件,因此采用传统的方法很难设计出具有最佳性能的复合材料构件。材料细观结构和宏观结构都对构件的性能有显著的影响,要充分发挥编织复合材料的潜能,需要同时从材料和结构两个尺度出发,发展新的优化设计方法。本文针对编织复合材料结构,围绕宏观力学性能预测、细观结构优化设计方法和结构与材料一体化优化设计方法开展研究工作。
在编织复合材料细观结构特征分析的基础上,采用正弦曲线和三次B样条曲线模拟纤维束的走向和截面形式,建立了二维编织复合材料的细观结构分析模型;假设经纱截面为矩形,采用三次B样条曲线和双切线模拟经向纤维束走向,直线和三次B样条曲线模拟纬纱的走向和截面形式,建立2.5维浅交直联编织复合材料的细观结构分析模型。以此为基础,论文对比分析了刚度平均法、细观力学有限元法、高精度通用单胞模型和节点插值子胞模型四种方法在编织复合材料的宏观力学性能预测中的可行性和有效性。
将水平集法和高精度通用单胞模型结合,将离散变量优化问题转化为连续变量优化问题,将多相材料细观结构拓扑优化设计转化为形状优化设计,提出了一种新的多相材料细观结构优化设计方法。为了实现细观拓扑结构的任意变化,采用数字阵列来描述细观结构形式,并对遗传算法的交叉方式进行了改进,提出了新的复合材料细观结构拓扑优化设计方法。利用编织复合材料细观结构分析模型和细观力学有限元法,建立宏观力学性能与细观结构参数之间的关系,提出了编织复合材料细观结构优化设计方法。
利用高精度通用单胞模型和多相材料构件结构分析,将细观结构形式和多相材料构件性能联系起来,建立了多相材料结构与材料一体化优化设计方法。将编织复合材料力学性能预测和复合材料构件结构分析结合起来,将材料优化和结构优化结合起来,同时以细观结构参数和宏观结构参数为设计变量,建立了编织复合材料结构与材料一体化优化设计方法。
分别以2维平纹和2.5维浅交直联编织复合材料为研究对象,进行编织复合材料涡轮导向叶片的结构与材料的一体化优化设计。将复合形法的局部搜索能力和遗传算法的全局寻优能力相结合,发展了混合遗传算法,分别采用复合形法、遗传算法和混合遗传算法进行结构与材料一体化优化设计,并研究了应力和位移约束对优化结果的影响情况。
分析了2维平纹编织复合材料涡轮导向叶片分析的多项式响应面和RBF神经网络模型的计算精度。以RBF神经网络为基础,提出了基于近似模型的编织复合材料涡轮导向叶片的结构与材料一体化优化设计方法。
During the traditional design of composite structures, the mechanical properties of the composites were designed at first, and then the composites were made into complex components. However, for the braided composites, the mechanical properties and the shape of the components were manufactured at the same time. It is difficult to get perfect properties of the braided composite components using the traditional design approach. The microstructure and macrostructure both have large influence on the performance of the composite components. In order to realize the large potential of the braided composites completely, a new optimization design method considering scales in both structure and material should be developed. In this thesis, the mechanical properties prediction approach, microstructure optimization design approach and integrated optimization design approach based on structure and material were investigated.
The microstructure model of the two-dimensional plain weave and braided composites were derived based on the microstructure analysis. The sinusoid curve was used to model the undulation of the yarns. The cross section shape was assumed to be cubic B-spline. For the 2.5-dimensional braided composites, the cross section of the warp yarn was assumed to be rectangle, and the undulation perform was modeled by the cubic B-spline and bitangent. The direction and cross section of weft yarn were modeled by beeline and B-spline respectively. The Stiffness Average Method (SAM), Micromechanical Finite Element Method (MFEM), High-fidelity Generalized Method of Cells (HFGMC) and Node Interpolation Cell Method (NICM) were used to predict the composites’mechanical property. The feasibility and validity of these four methods were also investigated.
By combining the Level Set Method with HFGMC, transferring the discrete variables optimization into continuous variables optimization, and changing the microstructure topological optimization design into shape optimization design, a new micro-structural optimization design method of multiple phases composite was proposed. To perform the random transformation of topological microstructure, another new composite topological optimization design method was developed. In this method, the microstructure was described by Digital Array, and the cross operation of genetic algorithm was improved. A microstructure optimization method of braided composite was proposed by establishing the relationship between the macro mechanical properties and micro structure parameters using the microstructure models and micromechanical finite element method.
The relationship between the microstructure and macrostructure mechanical properties was derived using HFGMC and structural analysis of composite components. An integrated optimization design method of multi-phase composites based upon structure and material was established. By combining the mechanical properties prediction with the components structural analysis, uniting the structure optimization with the material optimization, and taking the microstructure parameters and macrostructure parameters as the design variables, the integrated optimization design method of braided composites based upon structure and material was established.
The integrated optimization design of turbine guide vane made of two-dimensional plain weave and 2.5-dimensional angle-interlock braided composites based upon structure and material was investigated. By incorporating the advantages of Complex method’s local search capability with the Genetic Algorithm’s global search capability, the hybrid Genetic Algorithm method was developed. The Complex method, Genetic Algorithm method and hybrid Genetic Algorithm method were all used to perform the integrated optimization design of the composite turbine guide vane. The effects of stress and displacement constraints on optimization design were also analyzed.
The computation accuracy of the analysis results for the two-dimensional plain weave composite turbine vanes using polynomial response surface model and radical basis function (RBF) neural network model was analyzed. An integrated optimization design method of braided composites turbine guide vane based upon structure and material using RBF neural network model was proposed.
在编织复合材料细观结构特征分析的基础上,采用正弦曲线和三次B样条曲线模拟纤维束的走向和截面形式,建立了二维编织复合材料的细观结构分析模型;假设经纱截面为矩形,采用三次B样条曲线和双切线模拟经向纤维束走向,直线和三次B样条曲线模拟纬纱的走向和截面形式,建立2.5维浅交直联编织复合材料的细观结构分析模型。以此为基础,论文对比分析了刚度平均法、细观力学有限元法、高精度通用单胞模型和节点插值子胞模型四种方法在编织复合材料的宏观力学性能预测中的可行性和有效性。
将水平集法和高精度通用单胞模型结合,将离散变量优化问题转化为连续变量优化问题,将多相材料细观结构拓扑优化设计转化为形状优化设计,提出了一种新的多相材料细观结构优化设计方法。为了实现细观拓扑结构的任意变化,采用数字阵列来描述细观结构形式,并对遗传算法的交叉方式进行了改进,提出了新的复合材料细观结构拓扑优化设计方法。利用编织复合材料细观结构分析模型和细观力学有限元法,建立宏观力学性能与细观结构参数之间的关系,提出了编织复合材料细观结构优化设计方法。
利用高精度通用单胞模型和多相材料构件结构分析,将细观结构形式和多相材料构件性能联系起来,建立了多相材料结构与材料一体化优化设计方法。将编织复合材料力学性能预测和复合材料构件结构分析结合起来,将材料优化和结构优化结合起来,同时以细观结构参数和宏观结构参数为设计变量,建立了编织复合材料结构与材料一体化优化设计方法。
分别以2维平纹和2.5维浅交直联编织复合材料为研究对象,进行编织复合材料涡轮导向叶片的结构与材料的一体化优化设计。将复合形法的局部搜索能力和遗传算法的全局寻优能力相结合,发展了混合遗传算法,分别采用复合形法、遗传算法和混合遗传算法进行结构与材料一体化优化设计,并研究了应力和位移约束对优化结果的影响情况。
分析了2维平纹编织复合材料涡轮导向叶片分析的多项式响应面和RBF神经网络模型的计算精度。以RBF神经网络为基础,提出了基于近似模型的编织复合材料涡轮导向叶片的结构与材料一体化优化设计方法。
During the traditional design of composite structures, the mechanical properties of the composites were designed at first, and then the composites were made into complex components. However, for the braided composites, the mechanical properties and the shape of the components were manufactured at the same time. It is difficult to get perfect properties of the braided composite components using the traditional design approach. The microstructure and macrostructure both have large influence on the performance of the composite components. In order to realize the large potential of the braided composites completely, a new optimization design method considering scales in both structure and material should be developed. In this thesis, the mechanical properties prediction approach, microstructure optimization design approach and integrated optimization design approach based on structure and material were investigated.
The microstructure model of the two-dimensional plain weave and braided composites were derived based on the microstructure analysis. The sinusoid curve was used to model the undulation of the yarns. The cross section shape was assumed to be cubic B-spline. For the 2.5-dimensional braided composites, the cross section of the warp yarn was assumed to be rectangle, and the undulation perform was modeled by the cubic B-spline and bitangent. The direction and cross section of weft yarn were modeled by beeline and B-spline respectively. The Stiffness Average Method (SAM), Micromechanical Finite Element Method (MFEM), High-fidelity Generalized Method of Cells (HFGMC) and Node Interpolation Cell Method (NICM) were used to predict the composites’mechanical property. The feasibility and validity of these four methods were also investigated.
By combining the Level Set Method with HFGMC, transferring the discrete variables optimization into continuous variables optimization, and changing the microstructure topological optimization design into shape optimization design, a new micro-structural optimization design method of multiple phases composite was proposed. To perform the random transformation of topological microstructure, another new composite topological optimization design method was developed. In this method, the microstructure was described by Digital Array, and the cross operation of genetic algorithm was improved. A microstructure optimization method of braided composite was proposed by establishing the relationship between the macro mechanical properties and micro structure parameters using the microstructure models and micromechanical finite element method.
The relationship between the microstructure and macrostructure mechanical properties was derived using HFGMC and structural analysis of composite components. An integrated optimization design method of multi-phase composites based upon structure and material was established. By combining the mechanical properties prediction with the components structural analysis, uniting the structure optimization with the material optimization, and taking the microstructure parameters and macrostructure parameters as the design variables, the integrated optimization design method of braided composites based upon structure and material was established.
The integrated optimization design of turbine guide vane made of two-dimensional plain weave and 2.5-dimensional angle-interlock braided composites based upon structure and material was investigated. By incorporating the advantages of Complex method’s local search capability with the Genetic Algorithm’s global search capability, the hybrid Genetic Algorithm method was developed. The Complex method, Genetic Algorithm method and hybrid Genetic Algorithm method were all used to perform the integrated optimization design of the composite turbine guide vane. The effects of stress and displacement constraints on optimization design were also analyzed.
The computation accuracy of the analysis results for the two-dimensional plain weave composite turbine vanes using polynomial response surface model and radical basis function (RBF) neural network model was analyzed. An integrated optimization design method of braided composites turbine guide vane based upon structure and material using RBF neural network model was proposed.
引文
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