ISSN 2079-3537      

 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             

Scientific Visualization, 2019, volume 11, number 4, pages 102 - 114, DOI: 10.26583/sv.11.4.09

Generalized Computational Experiment and Visual Analysis of Multidimensional Data

Authors: A.E.  Bondarev1,A, V.A.  Galaktionov2,A

Keldysh Institute of Applied Mathematics Russian Academy of Sciences

1 ORCID: 0000-0003-3681-5212, bond@keldysh.ru

2 ORCID: 0000-0001-6460-7539, vlgal@gin.keldysh.ru

 

Abstract

The work considers the problems of constructing a generalized computational experiment in the problems of computational aerodynamics. The construction of a generalized computational experiment is based on the possibility of carrying out parallel calculations of the same problem with different input data in multitasking mode. This allows carrying out parametric studies and solving problems of optimization analysis. The results of such an experiment are multidimensional arrays, for the study of which visual analytics methods should be used. The construction of a generalized experiment allows one to obtain dependences for valuable functionals on the determining parameters of the problem under consideration. The implementation of a generalized experiment allows one to obtain a solution for a class of problems in the ranges under consideration, and not just for one problem. Examples of constructing a generalized computational experiment for various classes of problems of computational aerodynamics are presented. The article also provides an example of constructing such an experiment for a comparative assessment of the accuracy of numerical methods. This approach is a synthesis of parallel computing, multi-dimensional data processing methods and visual analysis. The application of this approach makes it possible to increase the efficiency of research for a number of applied problems of mathematical modeling.

 

Keywords: generalized computational experiment, visual analysis, multidimensional data, parallel computations.