典型分解在多参数计算结果可视化中的应用

Q4 Computer Science
A.K. Alekseev, A.E. Bondarev, Yu.S. Pyatakova
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引用次数: 0

摘要

从计算空气动力学中参数计算结果的存储和处理的角度考虑了多维函数离散化时张量的逼近。提出了一种新的基于梯度下降和近似可分解目标泛函的正则分解计算算法。该算法在与正则分解(“伞”)的计算核心正交的超平面上应用随机点集,以确保其灵活地应用于具有先验未知秩的张量的近似,并且可以自然地转移到诸如张量序列这样的张量分解上。给出了模型六维函数和二维欧拉方程数值解的集合的数值试验结果。这些方程描述了具有两个交叉激波的可压缩气体的流动。以马赫数和气流偏转角作为流动参数。给出了维数3(简单数值解)和维数4(依赖马赫数的数值解的集合)的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Application of Canonical Decomposition for the Visualization of Results of Multiparameter Computations
The approximation of the tensor appearing at a discretization of the multidimensional function is considered from the viewpoint of storing and treating of the results of parametric computations obtained in computational aerogasdynamics. The new algorithm for the computation of the canonical decomposition using gradient descent and approximately decomposable goal functional is described. This algorithm applies the random set of points on the hyperplane orthogonal to the computed core of the canonical decomposition (“umbrella”) that ensures its flexible application for an approximation of the tensors with a priori unknown rank and may be naturally transferred on such tensor decomposition as the tensor train. The results of the numerical tests are presented for the model six-dimensional functions and for an ensemble of the numerical solutions for the two-dimensional Euler equations. These equations describe the flow of the compressible gas with two crossing shock waves. The Mach number and angles of the flow deflection serve as the flow parameters. The results are provided for the dimensionality 3 (simple numerical solution) and 4 (the ensemble of the numerical solutions in dependence on the Mach number).
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来源期刊
Scientific Visualization
Scientific Visualization Computer Science-Computer Vision and Pattern Recognition
CiteScore
1.30
自引率
0.00%
发文量
20
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