Search Results for author: Barbara Wohlmuth

Found 6 papers, 1 papers with code

A 1D-0D-3D coupled model for simulating blood flow and transport processes in breast tissue

no code implementations14 Jan 2022 Marvin Fritz, Tobias Köppl, J. Tinsley Oden, Andreas Wagner, Barbara Wohlmuth, Chengyue Wu

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it.

A discontinuous Galerkin coupling for nonlinear elasto-acoustics

no code implementations8 Feb 2021 Markus Muhr, Vanja Nikolić, Barbara Wohlmuth

Inspired by medical applications of high-intensity ultrasound, we study a coupled elasto-acoustic problem with general acoustic nonlinearities of quadratic type as they arise, for example, in the Westervelt and Kuznetsov equations of nonlinear acoustics.

Numerical Analysis Numerical Analysis 65M12, 35L70

Modeling and simulation of vascular tumors embedded in evolving capillary networks

1 code implementation22 Jan 2021 Marvin Fritz, Prashant K. Jha, Tobias Köppl, J. Tinsley Oden, Andreas Wagner, Barbara Wohlmuth

The flow in the blood vessels is controlled by Poiseuille flow, and Starling's law is applied to model the mass transfer in and out of blood vessels.

Multidimensional coupling: A variationally consistent approach to fiber-reinforced materials

no code implementations7 Jan 2021 Ustim Khristenko, Stefan Schuß, Melanie Krüger, Felix Schmidt, Barbara Wohlmuth, Christian Hesch

The choice of our discrete basis functions of higher regularity is motivated by the fact, that as a result of the static condensation, we obtain second gradient terms in fiber direction.

Computational Engineering, Finance, and Science

Adaptive sampling strategies for risk-averse stochastic optimization with constraints

no code implementations7 Dec 2020 Florian Beiser, Brendan Keith, Simon Urbainczyk, Barbara Wohlmuth

This method is applicable to a broad class of expectation-based risk measures and leads to a significant reduction in the individual gradient evaluations used to estimate the objective function gradient.

Stochastic Optimization Optimization and Control

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