Deep learning and the collocation method are merged used to solve partial differential equations describing structures' deformation. We have considered different types of materials: linear elasticity, hyperelasticity (neo-Hookean) with large deformation, von Mises plasticity isotropic kinematic hardening. The performance this deep (DCM) depends on architecture neural network corresponding hyper...

In this paper we present a more accurate method for solving a frequency-dependent inductance of 3-D structures that contains permeable materials. The extracted inductance using the new method is much more accurate than when using the traditional collocation method for no increased cost. Computational results are presented and compared with data to demonstrate the accuracy improvement of the app...

We introduce a radial basis collocation method to solve axially moving beam problems

In this paper we introduce a measure for calculating statistically significant collocation sets that is related to the Poisson distribution. We show that results calculated using this measure are comparable to well-known measures like the log-likelihood measure. Additionally, we discuss asymptotic behaviour and additivity as general properties of the measure which may be applied to the analysis...