Daniel Nsikane

After a practical internship as a industrial mechanic, Daniel started BEng course in Vehicle Engineering at the University of Aalen in Germany. While writing his bachelor dissertation at BMW in Munich, he decided to focus further on combustion engine technology and went on to complete a MSc in Advanced Mechanical Engineering at the University of Sussex. This course laid the groundwork for him to join the Advanced Engineering Centre at the University of Brighton. He is now in his third year of an EngD course in close cooperation with Ricardo Innovations.

Email address: d.nsikane@brighon.ac.uk

Qualification: PhD

Timeframe: 2015 - 2019

Daniel-Nsikane

Thesis title

Multivariable interactions at direct injected, reactive diesel spray conditions in a RANS framework.

My research

Current simulation setup processes have no standardised approach to ensure a company wide simulation standard. Default settings are used and models selected based on individual preference and experience. The consequences are inconsistent quality of simulations, followed by uncertainty in the results and increased test bed validation efforts. This EngD project in cooperation with Ricardo Innovations will carry out extensive parametric studies and compare them to available experimental data from various institutions and cases. The focus hereby will lie in diesel DI combustion technology. The goal is to develop a tool in form of an algorithm, framework or guideline for simulation setup assistance. In other words: Intelligent model tuning technique to account for changing boundary conditions. The guidance tool will help the software user to choose appropriate simulation settings and models tailored to the investigated cases based on standardised decision making and adjust model tuning constants for varying engine conditions based on their physical expression. Positive side effects will be enhanced confidence in simulation tools & techniques for predictive purposes and a deeper understanding of simulation models, sub-models and tuning constants.

Supervisors

Academic

Dr Rob Morgan

Dt Konstantina Vogiatzaki

Dr David Mason

Professor Morgan Heikal

Industrial:

Andy Ward

Nick Winder

Kenan Mustafa