The identification of various flow regime transitions in both gas-liquid and slurry bubble columns (BCs) is a very important issue because different mass and heat transfers as well as mixing characteristics are observed in each flow regime. The flow regime transitions will be identified by applying both the chaos theory and statistics to Computer Automated Radioactive Particle Tracking (CARPT), Computed Tomography (CT) and Gamma Densitometry data which will be taken at Washington University in St. Louis (USA) (the outgoing host). Since all these techniques are very sophisticated and expensive, they are not available at any European research center. Therefore, the accumulation of rich experimental data base in the USA and its subsequent treatment by chaotic algorithms and statistics at TU Braunschweig (Germany) (the reintegration host) will contribute to the enhancement of the EU scientific excellence in the field of gas-liquid and slurry BCs. In Germany both chaos and statistical analyses will be applied also to mass transfer data obtained by means of an optical probe and differential pressure fluctuation data taken in a high-pressure (up to 4.0 MPa) BC. The above-mentioned measurements will be performed in various organic liquids in the presence or absence of different solids. Numerous gas distributor layouts will be tested, as well. The application of chaos theory to (slurry) BCs is a new and emerging research area. BCs exhibit a chaotic behaviour and thus chaos analysis can be a powerful tool for flow regime identification. The Kolmogorov entropy (KE) exhibits a sudden peak at each transitional gas velocity. By means of this criterion will be prepared flow regime maps for prediction of the various transitional gas velocities under different operating conditions. A model for KE prediction in some flow regimes will be developed, as well. By means of chaos theory will be extracted strategies for selecting the most useful hydrodynamic flow regime.
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