Process Modelling and Simulation

• Main Author: De Prada, Cesar (auth)
• Other Authors: Pantelides, Costas (auth), Pitarch, Jose Luis (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
• Subjects: History of engineering & technology; polyacrylonitrile-based carbon fiber; n/a; coagulation bath; binder dissolution; sensitivity analysis; simulation; neural networks; kernel development; thermodynamics; phytochemicals; wave resonance; natural extracts; population balance model; optimization; vane; parameter estimation; grey-box model; observability; optimal clustering; energy; idling test; data-mining; extents; computational fluid dynamics; scrap dissolution; Combined Heat and Power; dynamic optimization; scrap melting; swelling; engineering; dry-jet wet spinning process; fluid bed granulation; point estimation method; algebraic modeling language; Design of Experiments; costing stopping; materials; hydration; SOS programming; kinetics; moisture content; CHP legislation; model predictive control; graph theory; robust optimization; dynamic converter modelling; partial least square regression; uncertainty; state decoupling; utility management; fluidized bed drying; reactor coolant pump; condensation; wheat germ; cooking; maximum wave amplitude; moving horizon estimation; gray-box model; chemistry; barley; machine learning; heat and mass balance; equality constraints; porridge; process model validation; Pharmaceutical Processes; mathematical model; model identification; Mammalian Cell Culture; process modeling; parameter correlation
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.