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Semi-definite programming for topology optimization of trusses under multiple eigenvalue constraints

机译:多特征值约束下桁架拓扑优化的半定规划

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Topology optimization problem of trusses for specified eigenvalue of vibration is formulated as Semi-Definite Programming (SDP), and an algorithm is presented based on the Semi-Definite Programming Algorithm (SDPA) which utilizes extensively the sparseness of the matrices. Since the sensitivity coefficients of the eigenvalues with respect to the design variables are not needed, the SDPA is es- pecially useful for the case where the optimal design has multiple fundamental eigenvalues. Global and local modes are defined and a procedure is presented for generating optimal topology from the practical point of view. It is shown in the examples, that SDPA has advantage over existing methods in view of computational efficiency and accuracy of the solutions, and an optimal topology with five- fold fundamental eigenvalue is found without any difficulty.
机译:针对特定振动特征值的桁架拓扑优化问题被公式化为半定规划(SDP),并提出了一种基于半定规划算法(SDPA)的算法,该算法充分利用了矩阵的稀疏性。由于不需要特征值相对于设计变量的敏感度系数,因此SDPA对于最佳设计具有多个基本特征值的情况特别有用。定义了全局和局部模式,并提出了从实际角度生成最佳拓扑的过程。从示例中可以看出,考虑到计算效率和解决方案的准确性,SDPA具有优于现有方法的优势,并且可以轻松找到具有五倍基本特征值的最优拓扑。

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