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Combinatorial optimization of weld sequence by using a surrogate model to mitigate a weld distortion
Choosing an optimal sequence from the set of all possible combinations of a weld’s sub-passes is always a challenge for designers. The solution of such combinatorial optimization problems is limited by the available resources. For example, having n sub-passes leads to choosing from 2 n × n ! possi...
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Published in: | International journal of mechanics and materials in design 2011-06, Vol.7 (2), p.123-139 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Choosing an optimal sequence from the set of all possible combinations of a weld’s sub-passes is always a challenge for designers. The solution of such combinatorial optimization problems is limited by the available resources. For example, having n sub-passes leads to choosing from 2
n
×
n
! possible combinations of the sub-passes, e.g., 46,080 for
n
= 6. It is not feasible to choose the optimal sequence by evaluating all possible combinations either experimentally or by simulation models. The purpose of using a surrogate model based on a simulation model is to find the solution in the space of all possible combinations with a significant decrease in computational expenses. In effect, the surrogate model constructs an approximation model from some combinations of solutions of a more expensive model to mimic the behavior of the simulation model as closely as possible but at a much lower computational cost. This surrogate model, then, could be used to approximate the behavior of the other combinations. In this paper, a surrogate model is demonstrated that minimizes the distortion in a pipe girth weld with six sub-passes by analyzing only 14 combinations of sub-passes from total of 48 possible combinations. A comparison between the results of the surrogate model and the full transient FEM analysis all possible combinations shows the accuracy of the algorithm/model. |
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ISSN: | 1569-1713 1573-8841 |
DOI: | 10.1007/s10999-011-9154-6 |