连续纤维增强复合材料结构基频最大化设计

与传统的金属材料相比, 纤维增强复合材料在强度、刚度、抗断裂等诸多方面具备更优良的性能, 目前纤维增强复合材料已在汽车、航空航天等工业领域得到了广泛应用. 本文提出一种求解连续纤维增强复合材料结构无阻尼自由振动下的基频最大化问题的拓扑优化方法. 为了实现结构拓扑构型与纤维角度的同步优化, 建立了以准许的材料用量体积分数为约束、以结构的一阶特征值为目标函数的动力学拓扑优化模型, 该模型包括表征结构拓扑构型的密度设计变量和表征纤维方向的角度设计变量. 详细推导了特征值目标函数关于密度设计变量和角度设计变量的解析灵敏度列式, 并采用移动渐进线方法 (method of moving asymptotes, MMA) 进行了优化求解; 最后通过3个数值算例验证本文方法的有效性, 其中包括一个以刚度最大化为目标的静力学优化算例, 和两个以一阶特征值为目标的动力学优化算例. 结果表明, 所提方法优化迭代过程稳健, 收敛快, 能够在实现结构拓扑构型与纤维角度的一体化优化的同时, 有效提高结构的频率. 

FUNDAMENTAL FREQUENCY MAXIMIZATION DESIGN FOR CONTINUOUS FIBER-REINFORCED COMPOSITE STRUCTURES

Compared with traditional metal-materials, fiber-reinforced composite materials have better performance in many aspects such as strength, stiffness, and fracture resistance. At present, fiber-reinforced composite materials have been widely used in automotive, aerospace, and other industrial fields. This paper proposes a topology optimization method for solving the fundamental frequency maximization of undamped free vibration of continuous fiber-reinforced composite structures. To achieve the simultaneous optimization of the structural topological configuration and the fiber angle. A dynamic topological optimization model is established with the permitted material usage as the constraint and the structure's first-order eigenvalue as the objective function. The model includes density design variables that characterizes the topological configuration of the structure and angular design variables that characterizes the fiber orientation. The analytical sensitivity formulas of the objective function of eigenvalue with respect to density design variables and angle design variables are derived in detail, and the method of moving asymptotes (MMA) is used to solve the optimization problem. Finally, three numerical examples are performed to verify the effectiveness of the proposed method, which includes a static optimization example with the stiffness maximization as the goal and two dynamic optimization examples with the first-order eigenvalue maximization as the goal. The results show that the proposed method can achieve a stable iterative history and fast convergence, and can effectively improve the structural frequency while achieving the integrated optimization of the structural topological configuration and the fiber angle.