Overview
For the handling of granular materials, DEM models have been of value in supporting the design of bulk handling equipment in many ways. The current models are very detailed and accurate, yet not suitable for design optimisation due to their high computational costs. For fast and efficient design optimisation approaches, low computational cost models are required.
As a PhD in this project, you will develop metamodels that are fast enough to be used for design optimisation. The metamodels will be trained based on readily available validated DEM simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data together in a Digital Twin. This Digital twin will enable integrated performance monitoring and metamodel-based design optimisation of bulk handling equipment and processing equipment involving granular materials, such as grabs.
This PhD position is available as of… 01-Jun-2024. You will be joining the group of Prof. Dingena Schott, working on Machine Cargo Interaction Engineering. The group has members with expertise in machine cargo interaction, modelling, experimentation and simulation-based design in various transport-related applications. There are vivid interactions within the group and between groups in the Maritime and Transport Technology department to foster collaborations and knowledge transfers. This project is in close collaboration with an industrial partner and may also have opportunities for collaboration with leading universities worldwide. There is also an opportunity to gain teaching experience in topic-related courses
Company:
Delft University of Technology (TU Delft)
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
