A model updating optimization algorithm under quadratic constraints is applied to structure dynamic model updating. The updating problems of structure models are turned into the optimization with a quadratic constrain...A model updating optimization algorithm under quadratic constraints is applied to structure dynamic model updating. The updating problems of structure models are turned into the optimization with a quadratic constraint. Numerical method is presented by using singular value decomposition and an example is given. Compared with the other method, the method is efficient and feasible.展开更多
在交错网格的情况下,构造了一类不需解R iemann问题的求解三维双曲守恒律的二阶显式差分格式,证明了该格式在CFL(Courant-Friedrichs-Lewy)条件限制下为MmB(Maximum and m ini-mum Bounds)格式,进行了并行计算数值试验,得到的试验结果...在交错网格的情况下,构造了一类不需解R iemann问题的求解三维双曲守恒律的二阶显式差分格式,证明了该格式在CFL(Courant-Friedrichs-Lewy)条件限制下为MmB(Maximum and m ini-mum Bounds)格式,进行了并行计算数值试验,得到的试验结果令人满意。在交错网格的情况下构造的这类差分格式,不需要求解R iemann问题,不需要进行特征分解,可用于求解弱双曲方程组,计算快、编程简便。展开更多
文摘本文设计了求解Lyapunov矩阵方程的一种新方法。所考虑的矩阵方程是 AX—XB=C(1)其中A,B,C分别是m×m,n×n和m×n的已知矩阵。 该方法首先是将系数矩阵A,B初等相似约化为三对角矩阵,即存在可逆矩阵U,V,使U^(-1)AU=A,V^(-1)BV=B,其中A,B为三对角矩阵。然后设计了矩阵方程AY—YB=C的公式解法,分三步: 1)求f(λ)=det(λI—A)的λ各次幂的系数a_0,…,a_m; 2)计算sum from i=1 to m (A_(m-i)-CB^(m-i)),f(B); 3)求解Y。解方程AY—YB=C的方法称为THR算法。 最后经逆变换获得原矩阵方程(1)的解X。 求解矩阵方程(1)的方法称为R—THR算法。该方法的计算量约为m^3+4/3n^3+7m^2n+5nm^2+m^2。 本文给出了R—THR的串行计算的数值例子,并给出了THR算法的并行计算格式。最后通过几种数值方法的比较,表明该方法是可行的,也是有效的。
文摘A model updating optimization algorithm under quadratic constraints is applied to structure dynamic model updating. The updating problems of structure models are turned into the optimization with a quadratic constraint. Numerical method is presented by using singular value decomposition and an example is given. Compared with the other method, the method is efficient and feasible.
文摘在交错网格的情况下,构造了一类不需解R iemann问题的求解三维双曲守恒律的二阶显式差分格式,证明了该格式在CFL(Courant-Friedrichs-Lewy)条件限制下为MmB(Maximum and m ini-mum Bounds)格式,进行了并行计算数值试验,得到的试验结果令人满意。在交错网格的情况下构造的这类差分格式,不需要求解R iemann问题,不需要进行特征分解,可用于求解弱双曲方程组,计算快、编程简便。
