A5102876570- Elasticity and Material Modeling
- 3D Shape Modeling and Analysis
- Advanced Numerical Analysis Techniques
- Fluid Dynamics Simulations and Interactions
- Model Reduction and Neural Networks
- Advanced Numerical Methods in Computational Mathematics
- Lattice Boltzmann Simulation Studies
- Optical measurement and interference techniques
- Medical Image Segmentation Techniques
- Tissue Engineering and Regenerative Medicine
- Composite Structure Analysis and Optimization
- Drilling and Well Engineering
- Advanced Mathematical Modeling in Engineering
- Ultrasound Imaging and Elastography
- Structural Analysis and Optimization
- Machine Learning in Materials Science
- Medical Imaging and Analysis
- Magnetic Properties and Applications
- Topology Optimization in Engineering
- NMR spectroscopy and applications
- Vibration and Dynamic Analysis
- Fluid Dynamics and Thin Films
- Fluid Dynamics and Heat Transfer
- Surgical Simulation and Training
- Ship Hydrodynamics and Maneuverability
University of Luxembourg
2012-2024
Université de franche-comté
2023
Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies
2023
Centre National de la Recherche Scientifique
2023
University of Utah
2023
China Medical University Hospital
2022-2023
China Medical University
2022-2023
Cardiff University
2022
Duy Tan University
2022
Abstract In this paper we develop a framework for solving inverse deformation problems using the FEniCS Project finite-element software. We validate our approach with experimental imaging data acquired from soft silicone beam under gravity. contrast iterative algorithms that require multiple solutions of standard elasticity problem, proposed method can compute undeformed configuration by only one modified problem. This problem has complexity comparable to one. The is implemented within an...
A new adaptive multiscale method for the non-linear fracture simulation of heterogeneous materials is proposed. The two major sources errors in finite element are discretization and modelling errors. In failure problems, error increases due to strain localization which also a source homogenization underlying microstructure. this paper, controlled by an mesh refinement procedure following Zienkiewicz–Zhu technique, error, resultant microstructure, replacing macroscopic model with scale...
This study presents a novel semi-analytical model for nonlinear liquid sloshing response of two-dimensional (2D) storage tanks in the context scaled boundary finite element method (SBFEM). The potential flow tank is governed by 2D Laplace equation, with free surface considered as condition. To trace motions liquid-free surface, semi-Lagrange (SL) employed, and two Cartesian coordinate systems are established, including fixed inertial system moving system. Meanwhile, fourth-order Runge–Kutta...
Being able to reposition tumors from prone imaging supine surgery stances is key for bypassing current invasive marking used conservative breast surgery. This study aims demonstrate the feasibility of using Digital Volume Correlation (DVC) measure deformation a female quarter thorax between two different body positioning when subjected gravity. A segmented multipart mesh (bones, cartilage and tissue) was constructed three-step FE-based DVC procedure with heterogeneous elastic regularization...
Abstract We describe the SOniCS (SOFA + FEniCS) plugin to help develop an intuitive understanding of complex biomechanics systems. This new approach allows user experiment with model choices easily and quickly without requiring in-depth expertise. Constitutive models can be modified by one line code only. ease in building makes ideal surrogate, reduced order train machine-learning algorithms for enabling real-time patient-specific simulations. is thus not only a tool that facilitates...
In this paper, we develop a framework for solving inverse deformation problems using the FEniCS Project finite element software. We validate our approach with experimental imaging data acquired from soft silicone beam under gravity. contrast iterative algorithms that require multiple solutions of standard elasticity problem, proposed method can compute undeformed configuration by only one modified problem. This problem has complexity comparable to one. The is implemented within an...
This new approach allows the user to experiment with model choices easily and quickly without requiring in-depth expertise, as constitutive models can be modified by one line of code only. ease in building makes SOniCS ideal develop surrogate, reduced order train machine learning algorithms for uncertainty quantification or enable patient-specific simulations. is thus not only a tool that facilitates development surgical training simulations but also, perhaps more importantly, paves way...