New software partnership with M-STAR

By General

New partnership for the distribution of M-STAR CFD software in Europe

We are excited to announce a new reseller partnership between INVENT Umwelt- und Verfahrenstechnik AG and M-STAR Simulations LLC, which will enable the distribution and commercialization of the advanced Lattice-Boltzmann-based CFD Software M-STAR in Europe.

As part of this partnership, our CFD Business division, THINK Fluid Dynamix®, will not only be responsible for the commercialization of M-STAR but also for providing comprehensive support services such as trainings, seminars, and technical assistance to ensure successful and productive advanced CFD simulations.

M-STAR is the most advanced CFD software, specifically designed to address to the unique requirements of the chemical, process, and water industry. With M-STAR’s ability to solve advanced Lattice Boltzmann algorithms on GPUs, it is possible to produce detailed and accurate process simulations in a matter of minutes.

We believe that this reseller agreement will strengthen our product portfolio and allow us to provide better services to our customers across Europe.

Learn more about our partnership with M-STAR

Visualization of volumetric time-varying data

By General

Scientific visualization and stirred tank reactors visualization of volumetric time-varying data

Visualization is indispensable for understanding and communicating scientific results. Scientific visualization is an interdisciplinary branch of science that deals with the visual representation of scientific data-sets. These data-sets are usually a numerical representation of complex physical phenomena, and are acquired by means of experiments, data collections or computer simulations. Typical elements used to visualize data are color-coded images, volume renderings, iso-surfaces, particle traces, vector plots, etc.

The effective visualization of turbulent fluid dynamical phenomena is complex. Turbulent flows are inherently 3-dimensional and time-varying. Although in many cases only a steady-state approximation is sufficient, for most cases dynamic phenomena can only be understood through exploration of the transient (time-dependent) data as animation.

A clear example of the need for time-dependent analysis and visualization can be found in the study of mixing or resuspension behavior in complete stirred tank reactors. The sequence of figures below shows the concentration of solid particles at different time steps. These images are calculated from the results of a transient CFD simulation. The simulation starts at a state of complete quiescence with solids laying at the bottom. Over time, the solids are resuspended reaching a state of full homogenization over the entire fluid volume after 6 minutes.
The time dependent analysis provides precise answers for a number of questions:

Is the installed power sufficient to maintain particles of specific size and weight into suspension?
Does the reactor reach a state of full homogenization?
How long does it take from a state of full quiescence?
Furthermore, a CFD animation of the whole process over time helps to gain insights about the overall flow development and convective patterns.

The visualization of volumetric data is also essential to understand the behavior of non-ideal mixed tanks. Conventionally in the chemical and in the water treatment industry, experiments are carried out to describe the Residence Time Distribution (RTD) of a specific tank or reactor. As the RTD analysis is one-dimensional, it is a simple and useful method to identify mixing problems, but it cannot determine the specific cause of the issue.
The image sequence above shows the volumetric dispersion of a tracer in a flocculation basin equipped with two paddle wheel mixers. It shows the tendency of the tracer to spread on the water surface and the lack of mixing in the bottom part of the tank.

Scientific visualization is a fast growing and exciting field. New emerging techniques together with the increasing speed and capacity of hardware devices make possible to create a much more natural and understandable representation of complex phenomena.