PhD, Computational Mechanics
Trier, Germany
https://github.com/NicolasVerdon
Skills
Computational Fluid Dynamics
Extrusion modeling
DevOps
Data Science
Web Development
Project Management
Languages
French
English
German
Spanish
Hobbies
Canyoning
Hiking
Bike
Numerical Simulation
Strong expertise in FEA & numerical simulations using commercial packages (Ansys Polyow) as well as developing in-house solutions. Long experience in Extrusion Simulation and Simulation of the Shaping in the press, with the development of fully automated tools and new approaches for mixing simulations. Expertise in Data Mining and Visualization using Python (Dash & Streamlit) and Tableau together with establishing pipelines using Gitlab and Github.
Project ManagementPrincipal Investigator in a large scale project: communication with various stakeholders in many different departments of Goodyear, conception and follow-up of a project plan, review of the progress and assignement of tasks, presentation of the deliverables to the customers with associated training sessions.
Development of Reduced Order Models for real-time mechanical computations applied to archeology, work in cooperation with Human Computer Interaction team.
Development and implementation of a contact model into a massively parallel CFD code: application to the behaviour of solid particles in a shear flow (dilute and moderate dense suspensions).
Development of a Saint-Venant-code for the application to submarine gravity flows.
Improvement of the Finite Element model of the A380 aircraft with NASTRAN.
Teaching activities from BSc to MSc, option Civil Engineering.
The main aim of my work is to study the Reduced Order Models (ROM) for solving transfer equations. To perform accurate computations, we need very ne discretizations of the physical problems which leads to large systems of equations to solve. Using ROM allows to reduce the computational times required for solving these systems. The method I am currently developping is based on the Proper Orthogonal Decomposition which is the most used ROM in the field of Computational Fluid Dynamics, and the Krylov subspaces which are spaces used to build numerical methods for large sparse linear systems. The method has been tested for the convection-diffusion equation and is now applied to the Navier-Stokes equations, especially for the academic test case of a driven cavity.
Specialization in material science, continuum mechanics, Finite Element Method and Computational Fluid Dynamics, with distinction.
Windows, Linux
MS Office, LibreOffice, LATEX, Beamer
Polyflow, openFOAM, FlowVision, Abaqus
HTML, CSS, JavaScript, d3.js, Meteor, React, FastAPI, MongoDB, MS SQL
Gitlab, Github, Docker, Jira
Tableau, Dash, Streamlit
Python, Fortran, Shell, Julia, C/C++ (notions)
Paraview, CFX-Post, Tecplot, Gimp, Gnuplot, Matplotlib, Plotly