- Tobias Holzmann
Computational Fluid Dynamics.
Numerical simulations are used to analyze fluid flows and stress behavior inside solid materials. In most engineering investigations, the fluid flow pattern, species mixture, temperature distribution, or other quantities and distributions are of interest. Also, turbulent mixing is one of the key points during the numerical investigation. In special topics such as material casting such as in steel industries, non-measurable physical quantities can be analyzed. E.g., the velocity within the solidifying material.
Nevertheless, also for current engineering processes, the numerical analysis can be used to get a better understanding of the physics while improving and optimizing the design. The numerical investigation can be coupled with an optimization algorithm to find optimums for your individual needs.
Nowadays, Computational Fluid Dynamic (CFD) investigations are used in a wide area of engineering topics such as process, chemical, bio-mechanical, combustion engineering, and much more.
Visualization of Quantities.
During the numerical calculation, the calculated data can be saved at arbitrary time steps. For each stored data set, all relevant quantities that are evaluated during the numerical analysis can be visualized at each position inside the 3D geometry. This technique allows the investigation into non-measurable physical quantities. Furthermore, the visualization of different fields such as the velocity, energy, or pressure, allows a fast and reliable conclusion.
The video on the left-hand-side illustrates a moving water column. The motion is initiated due to moving walls. The velocity of the air-water mixture is presented as well as the pure water column.
Validation of Results.
While numerical investigations encourage to believe the data due to the colorful analysis, well-based expertise of the underlying mathematics and numerics is essential. New fields of studies ordinarily need a comparison of the numerical data against measurement data. During a matching, insufficiency within the used model can be analyzed and corrected.
The validation and verification of numerical data lead to sustainable and reliable investigations for research institutes and companies and is an essential part of developing new models or implementing new theory into numerical software packages.
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