For large-scale numerical simulations on supercomputers, data transfer and storage present significant efficiency and productivity issues. Therefore, the jointed hierarchical precision compression number-data format (JHPCN-DF) technique was proposed for efficient visualization and analysis of plasma particle-in-cell simulation data. It is also available for lossless and lossy compression with user-defined errors. We implement a lossy compression method of JHPCN-DF in finite element code and evaluate the compression effectiveness and compression data accuracy in linear static and dynamic structural analyses. Our technique achieves the required accuracy, even for dynamic problems, and provides a significant increase in compression performance for variable datasets.
In order to educate teenager internet literacy on social network service, we have developed a Problem Solving Environment to evaluate the literacy-level of their messages on twitter for their teachers and them. We propose a method the system provides effective recognition for their risks. And we adapt the Naive Bayes classifier to evaluation for tweets on Twitter based on pattern-based classifier. In this result, the classification accuracy for word patterns increases from 39.6-57.6% to 68.0-79.9% using Naive Bayes classifier on a set of 3000 training data sets, and users obtain internet literacy skills base on this system.
The purpose of this study is to develop a snow model emphasizing the splashing phenomenon and the impact force acting on the train surface to ensure safe driving. Snow is assumed to be a Bingham fluid due to its peculiar shear thinning. A Bingham numerical model is proposed by using the Moving Particle Semi-Implicit (MPS) method and tested for collision between a train and snow. As well, verification of this special non-Newtonian fluid is carried out and good agreement is obtained by comparing the MPS numerical result with a reference solution. Furthermore, a collision simulation between train and snow is implemented in which a natural splashing phenomenon occurs by introducing the present Bingham snow model. Finally, the time history of pressure in the foremost area of the train head is analyzed, which can provide a reference for safe train driving.