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Bifurcation & chaos in nonlinear structural dynamics: Novel & highly efficient optimal-feedback accelerated Picard iteration algorithms

机译:非线性结构动力学中的分叉与混沌:新颖且高效的最优反馈加速Picard迭代算法

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A new class of algorithms for solving nonlinear structural dynamical problems are derived in the present paper, as being based on optimal-feedback-accelerated Picard iteration, wherein the solution vectors for the displacements and velocities at any time t in a finitely large time interval t(i) = t = t(i+1) are corrected by a weighted (with a matrix.) integral of the error from t(i) to t. We present 3 approximations to solve the Euler-Lagrange equations for the optimal weighting functions.; thus we present 3 algorithms denoted as Optimal-Feedback-Accelerated Picard Iteration (OFAPI) algorithms-1, 2, 3. The interval (t(i+1) - t(i)) in the 3 OFAPI algorithms can be several hundred times larger than the increment (Delta t) required in the finite difference based implicit or explicit methods, for the same stability and accuracy. Moreover, the OFAPI algorithms-2, 3 do not require the inversion of the tangent stiffness matrix, as is required in finite difference based implicit methods. It is found that OFAPI algorithms-1, 2, 3 (especially OFAPI algorithm-2) require several orders of magnitude of less computational time than the currently popular implicit and explicit finite difference methods, and provide better accuracy and convergence. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文基于最优反馈加速的Picard迭代,推导了一类新的求解非线性结构动力学问题的算法,其中有限时间间隔t中任意时间t的位移和速度的求解矢量(i)<= t <= t(i + 1)通过从t(i)到t的误差的加权(带有矩阵)积分进行校正。我们提出了3个近似值来求解最优加权函数的Euler-Lagrange方程。因此,我们提出了3种算法,分别表示为最优反馈加速皮卡德迭代(OFAPI)算法1、2、3。3种OFAPI算法中的间隔(t(i + 1)-t(i))可能是数百倍对于相同的稳定性和准确性,该值要大于基于有限差分的隐式或显式方法所需的增量(Delta t)。此外,OFAPI算法2、3不需要像基于有限差分的隐式方法那样需要切线刚度矩阵的求逆。发现与目前流行的隐式和显式有限差分方法相比,OFAPI算法1、2、3(尤其是OFAPI算法2)需要几个数量级的计算时间,并且提供了更好的准确性和收敛性。 (C)2018 Elsevier B.V.保留所有权利。

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