Process Modelling and Simulation

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 application...

Full description

Saved in:
Bibliographic Details
:
Year of Publication:2019
Language:English
Physical Description:1 electronic resource (298 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 04556nam-a2201129z--4500
001 993548671404498
005 20231214133203.0
006 m o d
007 cr|mn|---annan
008 202102s2019 xx |||||o ||| 0|eng d
020 |a 3-03921-456-X 
035 |a (CKB)4100000010106138 
035 |a (oapen)https://directory.doabooks.org/handle/20.500.12854/57069 
035 |a (EXLCZ)994100000010106138 
041 0 |a eng 
100 1 |a De Prada, Cesar  |4 auth 
245 1 0 |a Process Modelling and Simulation 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2019 
300 |a 1 electronic resource (298 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
520 |a 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. 
546 |a English 
653 |a polyacrylonitrile-based carbon fiber 
653 |a coagulation bath 
653 |a binder dissolution 
653 |a sensitivity analysis 
653 |a simulation 
653 |a neural networks 
653 |a kernel development 
653 |a thermodynamics 
653 |a phytochemicals 
653 |a wave resonance 
653 |a natural extracts 
653 |a population balance model 
653 |a optimization 
653 |a vane 
653 |a parameter estimation 
653 |a grey-box model 
653 |a observability 
653 |a optimal clustering 
653 |a energy 
653 |a idling test 
653 |a data-mining 
653 |a extents 
653 |a computational fluid dynamics 
653 |a scrap dissolution 
653 |a Combined Heat and Power 
653 |a dynamic optimization 
653 |a scrap melting 
653 |a swelling 
653 |a engineering 
653 |a dry-jet wet spinning process 
653 |a fluid bed granulation 
653 |a point estimation method 
653 |a algebraic modeling language 
653 |a Design of Experiments 
653 |a costing stopping 
653 |a materials 
653 |a hydration 
653 |a SOS programming 
653 |a kinetics 
653 |a moisture content 
653 |a CHP legislation 
653 |a model predictive control 
653 |a graph theory 
653 |a robust optimization 
653 |a dynamic converter modelling 
653 |a partial least square regression 
653 |a uncertainty 
653 |a state decoupling 
653 |a utility management 
653 |a fluidized bed drying 
653 |a reactor coolant pump 
653 |a condensation 
653 |a wheat germ 
653 |a cooking 
653 |a maximum wave amplitude 
653 |a moving horizon estimation 
653 |a gray-box model 
653 |a chemistry 
653 |a barley 
653 |a machine learning 
653 |a heat and mass balance 
653 |a equality constraints 
653 |a porridge 
653 |a process model validation 
653 |a Pharmaceutical Processes 
653 |a mathematical model 
653 |a model identification 
653 |a Mammalian Cell Culture 
653 |a process modeling 
653 |a parameter correlation 
776 |z 3-03921-455-1 
700 1 |a Pantelides, Costas  |4 auth 
700 1 |a Pitarch, Jose Luis  |4 auth 
906 |a BOOK 
ADM |b 2023-12-15 05:46:06 Europe/Vienna  |f system  |c marc21  |a 2020-02-01 22:26:53 Europe/Vienna  |g false 
AVE |i DOAB Directory of Open Access Books  |P DOAB Directory of Open Access Books  |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338883940004498&Force_direct=true  |Z 5338883940004498  |b Available  |8 5338883940004498