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Department of Particulate Flow Modelling

Improving Technology by Smart Particulate Flow Models

Particulate flows can be defined as multiphase flow in which a dispersed phase (e.g. in form of solid particles, droplets or gas bubbles) interacts with a continuous phase (e.g. liquid or gas).

Particulate flows can be investigated either by (a) analytical considerations, (b) experimental measurements or (c) numerical simulations.

Particulate Flow Modelling aims at picturing particulate flow phenomena by some mathematical approach. Thereby, those mathematical representations (i.e. those numerical simulations) should not be developed independently. Rather they should be supported by corresponding experiments and associated measurement techniques.

Particulate Flow Modelling of Industrial Processes require the identification of the process’ physical core phenomenon prior to the start of any experimental or numerical simulation activities. Once this physical core phenomenon is identified (e.g. by analytical considerations) a simplified experiment can be proposed. This experiment should focus on the physics of the specific particulate flow phenomenon – it is not required to reproduce the geometry of the original industrial aggregate. In parallel to the experimental investigations different numerical simulation models can be applied and tested against the numerical results. Along with the experimental results new simulation models can be developed. Finally, after validation these numerical simulation models can be applied to the original industrial particulate process. In this knowledge transfer phase we test our new simulation skills by real world processes and hand over specific simulation tools to our industrial partners.

Particulate Flow Modelling in an Academic Environment is based on two main challenges: Inward and outward communication.

Before a PhD Student embarks on experimental or numerical research activities of applied particulate flows he should be introduced to the topic by specific analytical considerations. Once a junior researcher has understood the underlying physics of a particulate flow process he will be ready for dedicated experiments and numerical simulations. There should be a careful guidance by senior researchers in the field of experimental and numerical techniques. The success of our research group depends on the quality of supervision of PhD students as well as on the interplay between senior researchers. A vibrant communication between team members creates synergies and enables efficient research.

Two former PhD students (Dr. Christoph Kloss and Dr. Christoph Goniva) had the brilliant idea to contribute their numerical models as open source software. They founded a web-portal dedicated to open source scientific computing of particulate flows (www.cfdem.com). On this website it is possible to download up to date simulation software, to post feed-back and questions and to discuss specific challenges with colleagues from all over the world. Two years after its start this international open source computing portal has attracted more than 2000 scientists. Lectures in our team are attended by colleagues from five continents and visiting scientists contribute to our particulate flow models.


Johannes Kepler Universität Linz
Department of Particulate Flow Modelling
Altenbergerstrasse 69
4040, Linz, Austria

Tel.: +43 732 2468 6477
Fax: +43 732 2468 6462

E-Mail: stefan.pirker(/\t)jku.at
Web: http://www.particulate-flow.at

Bereich Name
Head Stefan Pirker
Deputy Head Simon Schneiderbauer
Administration Andrea Scharinger
Senior Scientists Christoph Goniva
Senior Scientists Damir Kahrimanovic
Senior Scientists Christoph Kloss
Senior Scientists Stefan Puttinger
Senior Scientists Gijsbert Wierink
Scientists Andreas Aigner
Scientists Stefan Amberger
Scientists Luca Benvenuti
Scientists Richard Berger
Scientists Gerhard Holzinger
Scientists Bernhard König
Scientists Daniel Queteschiner
Scientists Mahdi Saeedipour
Scientists Daniel Schiochet Nasato
Scientists Philippe Seil
Scientists Afsaneh Soleimani
Scientists Roland Winkler
Laboratory Lukas Fiel
Laboratory Philip Hörmandinger
Laboratory Niklas Hofer
Laboratory Oliver Ploder
 

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