Inverse modeling of cancellous bone using artificial neural networks

Article Biophysics

Multiscale modeling of cancellous bone considering full coupling of mechanical, electric and magnetic effects

Mischa Blaszczyk et al.

Summary: This paper introduces a fully coupled multiscale approach for modeling cancellous bone, considering mechanical, electric and magnetic effects using the multiscale finite element method and a two-phase material model on the microscale. Numerical results show that the magnetic field strength resulting from a small mechanical impact differs significantly between bones affected by different stages of osteoporosis.

BIOMECHANICS AND MODELING IN MECHANOBIOLOGY (2022)

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Article Engineering, Multidisciplinary

Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy

Li Zheng et al.

Summary: This study introduces a two-scale topology optimization framework for the design of macroscopic bodies with optimized elastic response, utilizing a spatially-variant cellular structure on the microscale. The chosen cellular structure parameters at the microscale are parametrized by a Gaussian random field, while the macroscale boundary value problem is discretized using finite elements instead of traditional FE2-type methods. A data-driven surrogate model, based on deep neural networks, is used to map microscale design parameters to the effective elasticity tensor for multiscale topology optimization.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)

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Article Biochemistry & Molecular Biology