2015
DOI: 10.1007/s40194-015-0235-2
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Development of idealized explicit FEM using GPU parallelization and its application to large-scale analysis of residual stress of multi-pass welded pipe joint

Abstract: In this research, the authors developed the idealized explicit finite element method (IEFEM) to achieve shorter computing time and lower memory consumption in analyses of welding deformation and residual stress. IEFEM was parallelized by a graphics processing unit (GPU) to achieve even faster computation. To show its applicability to largescale problems, the proposed method was applied to the analysis of the multi-pass welding of V-groove pipe joint that has 1 million elements, 13 layers, and 33 passes. In the… Show more

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Cited by 12 publications
(7 citation statements)
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“…Although computational speed has been increased using graphical processing units, parallel computation with multiprocessors in desktop workstations, and supercomputers (Refs. [94][95][96], it still could take days and weeks to analyze a large welded structure to predict distortion using a transient moving-arc TMM analysis method for one welding sequence.…”
Section: Simplified and Fast Analysis Methodsmentioning
confidence: 99%
“…Although computational speed has been increased using graphical processing units, parallel computation with multiprocessors in desktop workstations, and supercomputers (Refs. [94][95][96], it still could take days and weeks to analyze a large welded structure to predict distortion using a transient moving-arc TMM analysis method for one welding sequence.…”
Section: Simplified and Fast Analysis Methodsmentioning
confidence: 99%
“…Determination of K coefficients for various concentrators represented by drilled cracks is performed either by well-known dependencies, or by the results of solving the corresponding problems with the methods of the two-dimensional elasticity theory, or experimentally [1,3,[23][24][25][26][27][28][29].…”
Section: Theoretical Modelsmentioning
confidence: 99%
“…When ISM is applied to welding deformation problems, the model is divided into a strong nonlinear region around the weld pool and a weak non-linear region [9,10]. Recently, parallel computation methods using graphical processing units (GPU) have been utilized to accelerate computation speed for welding deformation prediction [11][12][13][14].…”
Section: Introductionmentioning
confidence: 99%