Paul Kieckhefen

Paul Kieckhefen

Computational Engineer

BASF SE

Paul Kieckhefen is a Computational Research Engineer in the chemical industry and was formerly a researcher at Hamburg University of Technology (TUHH). His interests include developing novel data-driven modeling techniques for old-school process industry challenges.

Skills

Multi-Phase Flow Simulation
Solids and Chemical Process Engineering
Machine Learning
High-Performance Computing
C/C++/CUDA
Python

Experience

 
 
 
 
 
Fluid, Particle and Reaction Modelling, BASF SE
Senior Specialist Digitalization
October 2021 – Present Ludwigshafen am Rhein, Germany
 
 
 
 
 
Hamburg University of Technology
Research Assistant
February 2018 – September 2021 Hamburg, Germany

Dissertation: A Novel Method for Predicting Product Properties in Fluidized Bed Spray Granulation

  • Perform coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) simulations of various apparatuses using OpenFOAM and LIGGGHTS
  • Design and develop pipelines for analyzing data and simulation data
  • Define projects with commercial customers from pharmaceutical, food and chemical industries
  • Acquire funding (DFG454277381, DFG438775980, TUHH i3 project, joint DFG-Fraunhofer project TwinGuide)
 
 
 
 
 
Digitalization in Research & Development, BASF SE
Master Thesis
September 2017 – December 2017 Ludwigshafen am Rhein, Germany
Title: Evaluation of the Recurrence CFD method for the Simulation of Industrially Relevant Fluid and Particle Dynamics

Posts