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A. Bahreininejad, B.H.V. Topping and A.I. Khan

Heriot-Watt University, Edinburgh, United Kingdom

doi:10.4203/ccp.20.4.8

A. Bahreininejad, B.H.V. Topping, A.I. Khan, "Subdomain Generation using Multiple Neural Networks Models", in B.H.V. Topping, M. Papadrakakis, (Editors), "Advances in Parallel and Vector Processing for Structural Mechanics", Civil-Comp Press, Edinburgh, UK, pp 173-184, 1994. doi:10.4203/ccp.20.4.8

Abstract

This paper examines the application of neural networks to the partitioning of unstructured adaptive meshes for parallel explicit time-stepping finite element analysis. The use of Mean Field Annealing (MFA) technique, which is based on the Mean Field Theory (MFT), for finding approximate solutions to the partitioning of the finite element meshes is investigated. The partitioning is based on the recursive bisection approach. The method of mapping the mesh bisection problem onto the neural network, the solution quality and the convergence times are presented. All computational studies were carried out using a single T800 transputer.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 20 ADVANCES IN PARALLEL AND VECTOR PROCESSING FOR STRUCTURAL MECHANICS Edited by: B.H.V. Topping and M. Papadrakakis Paper IV.8 Subdomain Generation using Multiple Neural Networks Models A. Bahreininejad, B.H.V. Topping and A.I. Khan Heriot-Watt University, Edinburgh, United Kingdom doi:10.4203/ccp.20.4.8 purchase the full-text of this paper Full Bibliographic Reference for this paper A. Bahreininejad, B.H.V. Topping, A.I. Khan, "Subdomain Generation using Multiple Neural Networks Models", in B.H.V. Topping, M. Papadrakakis, (Editors), "Advances in Parallel and Vector Processing for Structural Mechanics", Civil-Comp Press, Edinburgh, UK, pp 173-184, 1994. doi:10.4203/ccp.20.4.8 Abstract This paper examines the application of neural networks to the partitioning of unstructured adaptive meshes for parallel explicit time-stepping finite element analysis. The use of Mean Field Annealing (MFA) technique, which is based on the Mean Field Theory (MFT), for finding approximate solutions to the partitioning of the finite element meshes is investigated. The partitioning is based on the recursive bisection approach. The method of mapping the mesh bisection problem onto the neural network, the solution quality and the convergence times are presented. All computational studies were carried out using a single T800 transputer. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £60 +P&P)
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