Dynamic self-adaptive ANP algorithm and its application to electric field simulation of aluminum reduction cell
来源期刊：中南大学学报(英文版)2015年第12期
论文作者：WANG Ya-lin CHEN Dong-dong CHEN Xiao-fang CAI Guo-min YANG Chun-hua
文章页码：4731 - 4739
Key words：finite element parallel computing (FEPC); region partition (RP); dynamic self-adaptive ANP (DSA-ANP) algorithm; electric field simulation; aluminum reduction cell (ARC)
Abstract: Region partition (RP) is the key technique to the finite element parallel computing (FEPC), and its performance has a decisive influence on the entire process of analysis and computation. The performance evaluation index of RP method for the three-dimensional finite element model (FEM) has been given. By taking the electric field of aluminum reduction cell (ARC) as the research object, the performance of two classical RP methods, which are Al-NASRA and NGUYEN partition (ANP) algorithm and the multi-level partition (MLP) method, has been analyzed and compared. The comparison results indicate a sound performance of ANP algorithm, but to large-scale models, the computing time of ANP algorithm increases notably. This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration. To obtain the satisfied speed and the precision, an improved dynamic self-adaptive ANP (DSA-ANP) algorithm has been proposed. With consideration of model scale, complexity and sub-RP stage, the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight, and then dynamically adds these connected elements. The proposed algorithm has been applied to the finite element analysis (FEA) of the electric field simulation of ARC. Compared with the traditional ANP algorithm, the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s. This proves the superiority of the improved algorithm on computing time performance.
WANG Ya-lin(王雅琳), CHEN Dong-dong(陈冬冬), CHEN Xiao-fang(陈晓方), CAI Guo-min(蔡国民), YANG Chun-hua(阳春华)
(School of Information Science and Engineering, Central South University, Changsha 410083, China)
Abstract:Region partition (RP) is the key technique to the finite element parallel computing (FEPC), and its performance has a decisive influence on the entire process of analysis and computation. The performance evaluation index of RP method for the three-dimensional finite element model (FEM) has been given. By taking the electric field of aluminum reduction cell (ARC) as the research object, the performance of two classical RP methods, which are Al-NASRA and NGUYEN partition (ANP) algorithm and the multi-level partition (MLP) method, has been analyzed and compared. The comparison results indicate a sound performance of ANP algorithm, but to large-scale models, the computing time of ANP algorithm increases notably. This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration. To obtain the satisfied speed and the precision, an improved dynamic self-adaptive ANP (DSA-ANP) algorithm has been proposed. With consideration of model scale, complexity and sub-RP stage, the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight, and then dynamically adds these connected elements. The proposed algorithm has been applied to the finite element analysis (FEA) of the electric field simulation of ARC. Compared with the traditional ANP algorithm, the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s. This proves the superiority of the improved algorithm on computing time performance.
Key words:finite element parallel computing (FEPC); region partition (RP); dynamic self-adaptive ANP (DSA-ANP) algorithm; electric field simulation; aluminum reduction cell (ARC)
