Visual Computing for Heterogeneous Simulation and Measurements Data
To take full advantage of data from automotive simulations and measurements, we combine interactive and automatic Visual Computing methods to find intuitive, efficient and effective solutions that are applicable in the daily routine of engineers.
Temperature in a cooling jacket of a four cylinder engine.
Only values on one sectional plane are displayed.
Temperature values for virtual probes - the views are linked, a single click in the graph highlights the probe position and vice versa.
Visualization of angular velocity flow lines in a color gradient, which are sown at the coolant inlet of an engine.
We aim to combine automatic and interactive methods to take full advantage of the rich data derived from automotive simulations and measurements. Our main goal is to explore intuitive, efficient and effective solutions that are applicable in the daily routine of engineers. In doing so, we build on our experience with visualization, parameter space research, network processing and ensemble simulation techniques. We base our work to a large extent on the results of our strategic research projects, in particular research on Machine Learning and Quantitative Visual Analysis.
Our main focus is on the creation of a novel visual analysis methodology that supports simulation control, control of simulation ensembles, integration of simulation and measurement results from heterogeneous sources (different simulations - e.g. computational fluid dynamics, rigid body or hydraulic simulation and different measurements).
Within this project, we are working in close cooperation with our industrial and scientific partners. We believe that this is the only way to ensure success in applied research projects. Together with our partners, we constantly evaluate and refine new methods that are developed within the project. This ensures the industrial relevance of the research and provides us with new questions and problems from the industry.