The Asymptotic Expansion Load Decomposition elastoplastic beam model

Behavior of poroelastic isotropic beam derivation by asymptotic expansion method

Asymptotic Expansion of the Multi-Orientable Random Tensor Model

Three-dimensional random tensor models are a natural generalization of the celebrated matrix models. The associated tensor graphs, or 3D maps, can be classi ed with respect to a particular integer or half-integer, the degree of the respective graph. In this paper we analyze the general term of the asymptotic expansion in N , the size of the tensor, of a particular random tensor model, the multi...

Multilaminate Elastoplastic Model for Granular Media

A multilaminate based model capable of predicting the behavior of granular material on the basis of sliding mechanisms and elastic behavior of particles is presented. The capability of the model to predict the behavior of sand under arbitrary stress paths is examined. The influences of rotation of the direction of principal stress axes and induced anisotropy are included in a rational way witho...

A TFETI domain decomposition solver for elastoplastic problems

We propose an algorithm for the efficient parallel implementation of elastoplastic problems with hardening based on the so-called TFETI (Total Finite Element Tearing and Interconnecting) domain decomposition method. We consider an associated elastoplastic model with the von Mises plastic criterion and the linear isotropic hardening law. Such a model is discretized by the implicit Euler method i...

Distributed Generation Expansion Planning Considering Load Growth Uncertainty: A Novel Multi-Period Stochastic Model

Abstract – Distributed generation (DG) technology is known as an efficient solution for applying in distribution system planning (DSP) problems. Load growth uncertainty associated with distribution network is a significant source of uncertainty which highly affects optimal management of DGs. In order to handle this problem, a novel model is proposed in this paper based on DG solution, consideri...