Abstract
The aim of this study is to amplify a capability of a mesh analysis. A data which belongs to some mesh might be keenly identified according to the original mesh. Therefore, a relationship between two parameters is estimated always in the same scale, in other wors in the same dimension. It is possible to imagine that the numerical value of a parameters in an area might have influence on the other parameters in the bigger areas. In this study, we show a corelationship of two parameters in 36 cases which are composed by 6 different levels about both parameters. There are 6 levels of data accumulation. The first level means a data in the original mesh. The second level means a data integrated from 9 meshes; eight out of nine surround the original mesh on center. Accumulated data belongs to the center. The third level from 25 meshes, and so fourth. The changing of the corelationship concerning to the change of levels, is in seven cases all together; A is no changing, B is increasing two-dimensionally, C is decreasing, D is increasing only on one dimension, E is constantly relative on a series of the equivalent levels, F is once increasing and then decreasing, and G is gradually increasing on equivalent levels. Conclusion; According to a parameter, a change of co-relationship has some tendency. It is very important to know the real relationship among several parameters in the exact scale.
