Dominik Brands

Modelling and convergence in arterial wall simulations using a parallel FETI solution strategy

Arterial walls are characterised by nearly incompressible, anisotropic, hyperelastic material behaviour. Several polyconvex material functions representing such materials are considered and adjusted to experimental data. For all of these functions and for different parameter sets numerical simulations using a three-dimensional model of a diseased artery are performed. A finite element tearing and interconnecting-dual primal domain decomposition algorithm is used to solve the linearised systems of equations. The numerical performance of the different models is discussed with respect to convergence of the linear and nonlinear solvers.

Parallel simulation of patient‐specific atherosclerotic arteries for the enhancement of intravascular ultrasound diagnostics

Purpose – The purpose of this paper is to present a computational framework for the simulation of patient‐specific atherosclerotic arterial walls. Such simulations provide information regarding the mechanical stress distribution inside the arterial wall and may therefore enable improved medical indications for or against medical treatment. In detail, the paper aims to provide a framework which takes into account patient‐specific geometric models obtained by in vivo measurements, as well as a fast solution strategy, giving realistic numerical results obtained in reasonable time.Design/methodology/approach – A method is proposed for the construction of three‐dimensional geometrical models of atherosclerotic arteries based on intravascular ultrasound virtual histology data combined with angiographic X‐ray images, which are obtained on a routine basis in the diagnostics and medical treatment of cardiovascular diseases. These models serve as a basis for finite element simulations where a large number of unknow...

FE 2 -Simulation of Microheterogeneous Steels Based on Statistically Similar RVEs

A main problem of direct homogenization methods is the high computational cost, when we have to deal with large random microstructures. This leads to a large number of history variables which needs a large amount of memory, and moreover a high computation time. We focus on random microstructures consisting of a continuous matrix phase with a high number of embedded inclusions. In this contribution a method is presented for the construction of statistically similar representative volume elements (SSRVEs) which are characterized by a much less complexity than usual random RVEs in order to obtain an efficient simulation tool. The basic idea of the underlying procedure is to find a simplified SSRVE, whose selected statistical measures under consideration are as close as possible to the ones of the original microstructure.

Construction of Statistically Similar Representative Volume Elements

In computational homogenization approaches the definition of a representative volume element (RVE) strongly influences the performance of the resulting numerical scheme, not only with respect to its physical accuracy but also with respect to the computational effort required. Here, we propose a method for the construction of statistically similar RVEs (SSRVEs), which are characterized by a reduced complexity compared to real microstructures and which therefore lead to computationally less expensive methods. These SSRVEs are obtained by minimizing a least-square functional taking into account differences of statistical measures that characterize the morphology of a real (target) microstructure and the SSRVE. By comparing the mechanical response in a series of numerical investigations it is shown that also the material behavior obtained by considering the real microstructure is well represented by the SSRVEs.

Construction of Statistically Similar RVEs

In modern engineering, micro-heterogeneous materials are designed to satisfy the needs and challenges in a wide field of technical applications. The effective mechanical behavior of these materials is influenced by the inherent microstructure and therein the interaction and individual behavior of the underlying phases. Computational homogenization approaches, such as the FE2 method have been found to be a suitable tool for the consideration of the influences of the microstructure. However, when real microstructures are considered, high computational costs arise from the complex morphology of the microstructure. Statistically similar RVEs (SSRVEs) can be used as an alternative, which are constructed to possess similar statistical properties as the realmicrostructure but are defined by a lower level of complexity. These SSRVEs are obtained from a minimization of differences of statistical measures and mechanical behavior compared with a real microstructure in a staggered optimization scheme, where the inner optimization ensures statistical similarity and the outer optimization problem controls themechanical comparativity of the SSRVE and the real microstructure. The performance of SSRVEs may vary with the utilized statistical measures and the parameterization of the microstructure of the SSRVE.With regard to an efficient construction of SSRVEs, it is necessary to consider statistical measures which can be computed in reasonable time and which provide sufficient information of the real microstructure.Minkowski functionals are analyzed as possible basis for statistical descriptors of microstructures and compared with other well-known statistical measures to investigate the performance. In order to emphasize the general importance of considering microstructural features by more sophisticated measures than basic ones, i.e. volume fraction, an analysis of upper bounds on the error of statistical measures and mechanical response is presented.