Finite element analysis-enabled optimization of process parameters in additive manufacturing
A design optimization framework is proposed for process parameters in additive manufacturing. A finite element approximation of the coupled thermomechanical model is used to simulate the fused deposition of heated material and compute the objective function for each analysis. Both gradient-based and...
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| Published in | Finite elements in analysis and design Vol. 244; p. 104282 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.02.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0168-874X |
| DOI | 10.1016/j.finel.2024.104282 |
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| Abstract | A design optimization framework is proposed for process parameters in additive manufacturing. A finite element approximation of the coupled thermomechanical model is used to simulate the fused deposition of heated material and compute the objective function for each analysis. Both gradient-based and gradient-free optimization methods are developed. The gradient-based approach, which results in a balance law-constrained optimization problem, requires sensitivities computed from the fully discretized finite element model. These sensitivities are derived and subsequently applied to a projected gradient-descent algorithm. For the gradient-free approach, two distinct algorithms are proposed: a search algorithm based on local variations and a Bayesian optimization algorithm using a Gaussian process. Two design optimization examples are considered in order to illustrate the effectiveness of these approaches and explore the range of their usefulness.
•Fully-coupled thermomechanical modeling of additive manufacturing.•Optimization of process parameters enabled by finite element analysis.•Gradient-based and gradient-free approaches for optimization of process parameters.•Shape optimization for printed parts subject to cooling.•Simulation of two-dimensional printing involving curved domains. |
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| AbstractList | A design optimization framework is proposed for process parameters in additive manufacturing. A finite element approximation of the coupled thermomechanical model is used to simulate the fused deposition of heated material and compute the objective function for each analysis. Both gradient-based and gradient-free optimization methods are developed. The gradient-based approach, which results in a balance law-constrained optimization problem, requires sensitivities computed from the fully discretized finite element model. These sensitivities are derived and subsequently applied to a projected gradient-descent algorithm. For the gradient-free approach, two distinct algorithms are proposed: a search algorithm based on local variations and a Bayesian optimization algorithm using a Gaussian process. Two design optimization examples are considered in order to illustrate the effectiveness of these approaches and explore the range of their usefulness.
•Fully-coupled thermomechanical modeling of additive manufacturing.•Optimization of process parameters enabled by finite element analysis.•Gradient-based and gradient-free approaches for optimization of process parameters.•Shape optimization for printed parts subject to cooling.•Simulation of two-dimensional printing involving curved domains. |
| ArticleNumber | 104282 |
| Author | Wang, Jingyi Papadopoulos, Panayiotis |
| Author_xml | – sequence: 1 givenname: Jingyi surname: Wang fullname: Wang, Jingyi – sequence: 2 givenname: Panayiotis orcidid: 0000-0002-8631-1250 surname: Papadopoulos fullname: Papadopoulos, Panayiotis email: panos@berkeley.edu |
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| Keywords | Finite element method Gradient-descent optimization Sensitivity Additive manufacturing Bayesian optimization Method of local variations |
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