Computational weld mechanics (CWM) framework for exploring parametric design space to manage weld optimization

Asadi, Mahyar

doi:10.22215/etd/2011-09659

Cited by 2 publications

(9 citation statements)

References 27 publications

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“…A surrogate model is constructed in this analysis to explore the design space. The details of constructing such model and methodology used to find the best and worse sequences, are discussed in reference [10]. The highlight the focus of this paper is the user's setup time and CPU time to solve the generated DOE matrices for this problem.…”

Section: A Discontinuous Combinatorial Cwm Opti-mization Problemmentioning

confidence: 99%

“…In order to find the optimum values of the design parameters, two algorithms are used: a) regular direct-search algorithm b) least-square direct search algorithm. The details of this CWM optimization problem including a comparison between the methods are presented in [10]. This paper focuses on the use of a DOE matrix in the algorithms described below.…”

Section: Side Heater Mitigationmentioning

confidence: 99%

“…The algorithm starts with the L 9 Taguchi matrix [13] and continues with a full-factorial DOE matrix of (X, Y) over a set of 4 nodes in the feasible region for η and R. Thereafter, the algorithm starts an iterative process to generate and solve a new DOE matrix in each iteration to search for the design parameters that minimize distortion. Details of the algorithm are given in [10]. In terms of CPU time, each single analysis takes 48 minutes.…”

Section: Regular Direct Searchmentioning

confidence: 99%

“…Least-Square Direct Search Similar to the regular direct-search, the start point is the L 9 Taguchi matrix and a fullfactorial DOE matrix of (X, Y) over a set of 4 nodes in the feasible region for η and R. The difference is in the iterative process to generate and use DOE matrices needed to reach the minimum distortion (Details are given in [10]). Table 2 summarizes the number of cores, number of analyses and computation time, used in each iteration for the Least-square direct-search DOE matrix.…”

Section: Regular Direct Searchmentioning

confidence: 99%

“…Therefore this technique can reduce the distortion. In [10], this technique is employed by applying the pre-bending value a) in the middle of the bar as a nodal displacement, b) as a parabolic displacement along the bottom edge of the bar. The pre-bending value is highly correlated with the delay time that the pre-bending release after the weld is finished.…”

Section: Pre-bending Mitigationmentioning

confidence: 99%

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A Framework for Designer-Driven Exploration of Computational Weld Mechanics Design Space

Asadi

Goldak

2011

Volume 6: Materials and Fabrication, Parts a and B

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This paper demonstrates a framework for analyzing multiple analyses of welds and welded structures as a single run. For each point in the design space a 3D transient thermal-stress analyses is solved for the weld and/or a welded structure. This enables the designer to explore the design state space for the design points specified in a Design of Experiments (DOE) matrix. This makes it simpler and quicker for a human to set up tens or hundreds of analyses. Also the CPU time to solve each analysis must be sufficiently short. Examples of DOE matrices created for Computational Weld Mechanics (CWM) optimization analyses are presented; i) a discontinuous combinatorial optimization of the weld sequence to minimize distortion in a girth weld, ii) a continuous optimization to mitigate distortion of an edge welded bar using side heaters, pre-bending with prescribed deflections at isolated points and pre-bending with a smooth prescribed displacement function.

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Section: A Discontinuous Combinatorial Cwm Opti-mization Problemmentioning

confidence: 99%

Section: Side Heater Mitigationmentioning

confidence: 99%

Section: Regular Direct Searchmentioning

confidence: 99%

Section: Regular Direct Searchmentioning

confidence: 99%

Section: Pre-bending Mitigationmentioning

confidence: 99%

See 3 more Smart Citations

A Framework for Designer-Driven Exploration of Computational Weld Mechanics Design Space

Asadi

Goldak

2011

Volume 6: Materials and Fabrication, Parts a and B

Self Cite

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The Evolution of Stress and Strain Tensors in Welds With Mitigation of Residual Stress and Distortion

Goldak

Asadi

2011

Volume 6: Materials and Fabrication, Parts a and B

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By getting the data from an ordered set of Gauss points on the flow line of a material point that passes near the weld pool, the evolution of the stress/strain tensor fields is visualized. The principal plastic strain tensor, principal deviatoric stress tensor, hydrostatic stress and temperature are visualized. This is done for three weld distortion mitigation strategies: i) pre-bending by applying a prescribed displacement, ii) applying a tensile load to the weld and iii) applying side heaters to the weld. Visualizing the evolution of the principal stress and strain vectors gives interesting insight into the mechanics of plastic deformation near a weld pool.

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Computational weld mechanics (CWM) framework for exploring parametric design space to manage weld optimization

Cited by 2 publications

References 27 publications

A Framework for Designer-Driven Exploration of Computational Weld Mechanics Design Space

A Framework for Designer-Driven Exploration of Computational Weld Mechanics Design Space

The Evolution of Stress and Strain Tensors in Welds With Mitigation of Residual Stress and Distortion

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