| Contributions are sought in the general area of population balance modeling and control of particle formation processes. Topics of interest include, but are not limited to: (1) the identification of nucleation kinetics and kernels for coalescence, aggregration, agglomeration, and breakage; (2) numerical algorithms for efficiently solving the associated population balance equations with complex particle dynamics; (3) model reduction methods and their application to optimization and feedback control; (4) experimental design methods, to focus experimental efforts on identifying kernels and nucleation kinetics; (5) nonlinear control methods designed to optimize distributions; and (6) mathematical methods for analyzing the sensitivities of the distributions to model uncertainties and disturbances. All application areas involving population balance modeling are of interest including nanoparticle formation, solids flows, granulation processes, solution crystallization, spray drying, precipitation, and emulsion and suspension polymerization |
| Welcoming Remarks |
Numerical Bifurcation Analysis of Periodic Solution of Population Balance Models
Mykhaylo Krasnyk, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, Magdeburg, Germany, Michael Mangold, Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, 39106, Germany and Achim Kienle, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany |
Modeling Soot Formation in Turbulent Flames by Direct Quadrature Method of Moments
Federica Furcas, Alessandro Zucca, Daniele Marchisio and Antonello Barresi, Scienza dei Materiali e Ingegneria Chimica, Politecnico di Torino, C.so Duca degli Abruzzi 24, Torino, 10129, Italy |
A Mechanistic Model for Nucleation and Aggregation in Population Balances of Granulation: Batch Characterisation Studies and Experimental Validation
Rohit Ramachandran1, Jonathan M. -H. Poon1, Constantijn F. W. Sanders2, Thomas Glaser2, Francis J. Doyle III2, James D. Litster3, Frantisek Stepanek1, Fu-Yang Wang3, I. T. Cameron3 and Charles D. Immanuel1, (1)Department of Chemical Engineering and Chemical Technology, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom, (2)UCSB, Department of Chemical Engineering, Santa Barbara, CA 93106, (3)Particle and Systems Design Centre, School of Engineering, The University of Queensland, St. Lucia, Brisbane, QLD, 4072, Australia |
Numerical Solution Of Multi-Variable Cell Population Balance Models With A Free Boundary Algorithm
Mihail E. Kavousanakis, School of Chemical Engineering, National Technical University of Athens, Athens, Greece, Andreas G. Boudouvis, School of Chemical Engineering, National Technical University of Athens (NTUA), GR-15780, Athens, Greece and Nikos V. Mantzaris, Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005 |
Fast Monte Carlo Algorithms for Modeling and Optimization of Complex Particulate Processes
Roberto Irizarry, Electronic Technologies, DuPont, 14 TW Alexander Drive, Research Triangle Park, Raleigh, NC 27709 |
A New Simulation Method For Population Balances Using Constant-Number Monte Carlo With Adjustable Time Step
Samira Khalili, Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, Antonios Armaou, Chemical Engineering, The Pennsylvania State University, 170 Fenske Laboratory, University Park, PA 16802 and Themis Matsoukas, Chemical Engineering, Penn State, 150 Fenske Laboratory, University Park, PA 16802 |
Validation of Fcmom for Bi-Variate Population Balance Equations
Matteo Strumendo, Department of Chemical and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616 and Hamid Arastoopour, department of chemical and environmental engineering, Illinois Institute of Technology, Chicago, IL 60616 |
| Concluding Remarks |
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