Reprint

Process Modelling and Simulation

Edited by
September 2019
298 pages
  • ISBN978-3-03921-455-6 (Paperback)
  • ISBN978-3-03921-456-3 (PDF)

This is a Reprint of the Special Issue Process Modelling and Simulation that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Summary

Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Format
  • Paperback
License and Copyright
© 2019 by the authors; CC BY-NC-ND license
Keywords
process model validation; partial least square regression; phytochemicals; natural extracts; wheat germ; fluidized bed drying; mathematical model; moisture content; condensation; simulation; Pharmaceutical Processes; Mammalian Cell Culture; sensitivity analysis; parameter estimation; Design of Experiments; algebraic modeling language; dynamic optimization; model predictive control; moving horizon estimation; fluid bed granulation; heat and mass balance; population balance model; binder dissolution; kernel development; robust optimization; uncertainty; point estimation method; equality constraints; parameter correlation; barley; simulation; hydration; swelling; cooking; porridge; extents; graph theory; model identification; observability; optimal clustering; parameter estimation; state decoupling; data-mining; machine learning; neural networks; chemistry; materials; engineering; energy; grey-box model; machine learning; SOS programming; process modeling; scrap dissolution; scrap melting; thermodynamics; kinetics; dynamic converter modelling; Combined Heat and Power; gray-box model; utility management; CHP legislation; optimization; polyacrylonitrile-based carbon fiber; coagulation bath; dry-jet wet spinning process; computational fluid dynamics; wave resonance; maximum wave amplitude; reactor coolant pump; vane; costing stopping; mathematical model; idling test; n/a

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