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Surrogate optimization of a lattice foot orthotic.
Moeini, Mohammadreza; Yue, Lingyu; Begon, Mickael; Lévesque, Martin.
Afiliação
  • Moeini M; Laboratory for Multiscale Mechanics, Polytechnique de Montréal, Montréal, Québec H3C3A7, Canada. Electronic address: mohammadreza.moeini@polymtl.ca.
  • Yue L; Laboratory for Multiscale Mechanics, Polytechnique de Montréal, Montréal, Québec H3C3A7, Canada. Electronic address: lingyu.yue@polymtl.ca.
  • Begon M; Laboratory of Simulation and Movement Modelling, School of Kinesiology and Physical Activity Sciences, Québec, Canada; CHU Sainte-Justine - Research Center, Québec, Canada. Electronic address: mickael.begon@umontreal.ca.
  • Lévesque M; Laboratory for Multiscale Mechanics, Polytechnique de Montréal, Montréal, Québec H3C3A7, Canada. Electronic address: martin.levesque@polymtl.ca.
Comput Biol Med ; 155: 106376, 2023 03.
Article em En | MEDLINE | ID: mdl-36796183
BACKGROUND: Additive manufacturing enables to print patient-specific Foot Orthotics (FOs). In FOs featuring lattice structures, the variation of the cell's dimensions provides a locally variable stiffness to meet the therapeutic needs of each patient. In an optimization problem, however, using explicit Finite Element (FE) simulation of lattice FOs with converged 3D elements is computationally prohibitive. This paper presents a framework to efficiently optimize the cell's dimensions of a honeycomb lattice FO for flat foot condition. METHODS: We built a surrogate based on shell elements whose mechanical properties were computed by the numerical homogenization technique. The model was submitted to a static pressure distribution of a flat foot and it predicted the displacement field for a given set of geometrical parameters of the honeycomb FO. This FE simulation was considered as a black-box and a derivative-free optimization solver was employed. The cost function was defined based on the difference between the predicted displacement by the model against a therapeutic target displacement. RESULTS: Using the homogenized model as a surrogate significantly accelerated the stiffness optimization of the lattice FO. The homogenized model could predict the displacement field 78 times faster than the explicit model. When 2000 evaluations were required in an optimization problem, the computational time was reduced from 34 days to 10 hours using the homogenized model rather than explicit model. Moreover, in the homogenized model, there was no need to re-create and re-mesh the insole's geometry in each iteration of the optimization. It was only required to update the effective properties. CONCLUSION: The presented homogenized model can be used as a surrogate within an optimization framework to customize cell's dimensions of honeycomb lattice FO in a computationally efficient manner.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pé Chato / Medicina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pé Chato / Medicina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article