Short Description of Institute/Facility - Please insert text
What you can expect
A safety-relevant topic in aviation is the detection and avoidance of turbulence in the atmosphere. We develop simulations that can generate realistic turbulence, e.g. caused by gravity waves or convection. These simulations are important for investigating the properties of turbulence and the dynamic effects on an aircraft in cruise flight. DLR is developing lidar measuring devices that can recognise turbulence in flight in advance. High-resolution simulations are required to test these measuring devices in a virtual environment and to analyse the effects of turbulence on aircraft. The aim is to understand the dynamic processes of turbulence in order to describe its occurrence in aviation applications.
The aim of this project is to use idealised simulations to describe the differences between turbulence from different excitation processes. The aim is to show whether the simulations can realistically predict and reproduce the turbulence that actually occurs. In addition, the simulations are to be prepared for use in a lidar simulator.
Your tasks
- Development of the LES model PMAP for the realisation of simulations of turbulence in the free atmosphere
- Optimisation of the numerical setup for high-performance GPU-based simulations
- Setting up idealised simulations of turbulence triggered by rock waves
- Post-simulation of a real turbulence case in civil aviation
- Comparison of the simulations with measurement data from the HALO research aircraft
- Implementation of a lidar simulator in the LES code for the design of lidar measurement strategies and analysis of the expected measurement accuracy
- Management of internal DLR (sub-)projects on the topic of turbulence in aviation
What you bring with you
- Completed scientific university degree (Master's or Diplom Uni) in natural sciences, e.g. in meteorology, physics or mathematics, or engineering sciences such as aerospace engineering or other degree programmes relevant to the job
- Good knowledge of the basics and interest in atmospheric dynamics, (turbulence) modelling and model/measurement data evaluation
- Good knowledge of programming, preferably Python
- Experience with Linux and mainframe computing
- Good written and spoken English skills
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 1912) please contact:
Norman Wildmann
Tel.: +49 8153 28 1578