1 to 10 of 14 Results
May 11, 2026 - Optimization & Uncertainty Quantification
Grünfelder, Nicolas; Pi Savall, Berta; Seyedpour, Seyed Morteza; Waschinsky, Navina; Ricken, Tim, 2026, "Exploring the Dependencies of Poisson’s Ratio in Auxetic Structures", https://doi.org/10.18419/DARUS-4322, DaRUS, V1
In this repository, an Abaqus Python scripting approach for a natural frequency analysis of an auxetic lattice structure is presented. The script "Modal_4x4x4_Lattice.py" produces an input file for Abaqus that controls all necessary preprocessing and simulation steps. Additionally, for the first step of postprocessing, all needed results are extrac... |
May 11, 2026 - Optimization & Uncertainty Quantification
Grünfelder, Nicolas; Kälber, Lars; Waschinsky, Navina; Ricken, Tim, 2026, "Replication Data for: Shape Optimization of auxetic unit cells under dynamic loading in macroscopic components", https://doi.org/10.18419/DARUS-4777, DaRUS, V1
In this repository, an Python scripting approach for a Bayesian shape optimization, with an Abaqus implimentation for solving for natural frequencies and harmonic response simulation, is presented. The script "Shape_Opt_Master.py" controls all the necessary functions and contains the optimization as a wrapping function around the Abaqus simulations... |
Jul 24, 2025 - Computational Biomechanics
Egli, Franziska S.; Seyedpour, Seyed Morteza; Ricken, Tim; Pierce, David; Pachenari, Mohammad, 2025, "Sensitivity analyses and parameter fitting of biphasic articular cartilage model", https://doi.org/10.18419/DARUS-4729, DaRUS, V1
This dataset contains a zip of the used program FEBio as well as all files and produced results for the investigations presented in Egli et al.. Therein, we combine experiments with sensitivity analyses (SAs) and simulations of a biphasic model of three boundary value problems (BVPs): uniaxial tension (UT), confined compression (CC) and biaxial ten... |
Dec 18, 2024 - Computational Biomechanics
Suditsch, Marlon; Wagner, Arndt; Ricken, Tim, 2024, "Onco* version 0.1.0", https://doi.org/10.18419/DARUS-4651, DaRUS, V1
Onco* version 0.1.0 Onco* is a module based umbrella software project for numerical simulations of patient-specific cancer diseases, see following figure. From given input states of medical images the disease is modelled and its evolution is simulated giving possible predictions. In this way, a digital cancer patient is created, which could be used... |
Dec 18, 2024 - Computational Biomechanics
Suditsch, Marlon; Wagner, Arndt; Ricken, Tim, 2024, "Onco* tutorial", https://doi.org/10.18419/DARUS-4639, DaRUS, V2
Onco* tutorial This repository contains a tutorial for the following software packages: OncoFEM OncoSTR OncoTUM OncoGEN The goal is to demonstrate all functions and provide users with easier access to the tools. After successfully installing one or all of the packages, the respective tutorial can be started with Python, for example: python oncofem_... |
Dec 16, 2024 - Computational Biomechanics
Suditsch, Marlon; Wagner, Arndt; Ricken, Tim, 2024, "OncoTUM models", https://doi.org/10.18419/DARUS-4647, DaRUS, V1
OncoTUM models This repository hosts pretrained neural network models for OncoTUM, a key software package within the umbrella project Onco* for modelling and numerical simulations of tumours. OncoTUM is designed to facilitate tumour segmentations from medical images, leveraging state-of-the-art deep learning techniques. Purpose The pretrained model... |
Oct 18, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Bertrand, Fleurianne; Ricken, Tim, 2024, "dolfinx_eqlb v1.2.0", https://doi.org/10.18419/DARUS-4498, DaRUS, V1
This library contains an add-on to FEniCSx enabling local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [5][8], elasticity [1][9] or poro-elasticity [2][10]. The equilibration process relies on so called patches, groups of all cells,... |
Oct 18, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Bertrand, Fleurianne; Ricken, Tim, 2024, "AFEM-by-Equilibration", https://doi.org/10.18419/DARUS-4500, DaRUS, V1
This repository showcases how adaptive finite element solvers using equilibration based a posteriori error estimates can be build. Therefore, FEniCSx [1] alongside with dolfinx_eqlb [2], an extension for efficient flux equilibration are used. Classical benchmarks for the Poisson problem and linear elasticity are shown. The here presented code can b... |
Sep 25, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Bertrand, Fleurianne; Ricken, Tim, 2024, "dolfinx_eqlb v1.1.0", https://doi.org/10.18419/DARUS-4479, DaRUS, V1
dolfinx_eqlb is an open source library, extending FEniCSx by local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [1], elasticity [2][3][4] or poro-elasticity [5][6]. The flux equilibration relies on so called patches, groups of all ce... |
Sep 16, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Suditsch, Marlon; Seyedpour, Seyed Morteza; Ricken, Tim, 2024, "Data for: Phase transition in porous materials - Effects of material parameters and deformation regime on mass conservativity", https://doi.org/10.18419/DARUS-4460, DaRUS, V1, UNF:6:liYTqWrj3J/cX+8NzdBIAA== [fileUNF]
This dataset contains the original results published in "Phase transition in porous materials: effects of material parameters and deformation regime on mass conservativity" (doi: 10.1007/s00466-024-02557-2). Abstract: Phase transition in porous materials is relevant within different engineering applications, such as freezing in saturated soil or pa... |
