LEADER 05105nam 22012853a 450 001 9910367757903321 005 20250203235432.0 010 $a9783039214563 010 $a303921456X 024 8 $a10.3390/books978-3-03921-456-3 035 $a(CKB)4100000010106138 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/57069 035 $a(ScCtBLL)690f0a26-ca48-42b6-8842-b0e944519c88 035 $a(OCoLC)1163829433 035 $a(oapen)doab57069 035 $a(EXLCZ)994100000010106138 100 $a20250203i20192019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aProcess Modelling and Simulation$fJose Luis Pitarch, Cesar De Prada, Costas Pantelides 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2019. 215 $a1 electronic resource (298 p.) 311 08$a9783039214556 311 08$a3039214551 330 $aSince 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. 606 $aHistory of engineering and technology$2bicssc 610 $apolyacrylonitrile-based carbon fiber 610 $acoagulation bath 610 $abinder dissolution 610 $asensitivity analysis 610 $asimulation 610 $aneural networks 610 $akernel development 610 $athermodynamics 610 $aphytochemicals 610 $awave resonance 610 $anatural extracts 610 $apopulation balance model 610 $aoptimization 610 $avane 610 $aparameter estimation 610 $agrey-box model 610 $aobservability 610 $aoptimal clustering 610 $aenergy 610 $aidling test 610 $adata-mining 610 $aextents 610 $acomputational fluid dynamics 610 $ascrap dissolution 610 $aCombined Heat and Power 610 $adynamic optimization 610 $ascrap melting 610 $aswelling 610 $aengineering 610 $adry-jet wet spinning process 610 $afluid bed granulation 610 $apoint estimation method 610 $aalgebraic modeling language 610 $aDesign of Experiments 610 $acosting stopping 610 $amaterials 610 $ahydration 610 $aSOS programming 610 $akinetics 610 $amoisture content 610 $aCHP legislation 610 $amodel predictive control 610 $agraph theory 610 $arobust optimization 610 $adynamic converter modelling 610 $apartial least square regression 610 $auncertainty 610 $astate decoupling 610 $autility management 610 $afluidized bed drying 610 $areactor coolant pump 610 $acondensation 610 $awheat germ 610 $acooking 610 $amaximum wave amplitude 610 $amoving horizon estimation 610 $agray-box model 610 $achemistry 610 $abarley 610 $amachine learning 610 $aheat and mass balance 610 $aequality constraints 610 $aporridge 610 $aprocess model validation 610 $aPharmaceutical Processes 610 $amathematical model 610 $amodel identification 610 $aMammalian Cell Culture 610 $aprocess modeling 610 $aparameter correlation 615 7$aHistory of engineering and technology 700 $aPitarch$b Jose Luis$01786855 702 $aDe Prada$b Cesar 702 $aPantelides$b Costas 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910367757903321 996 $aProcess Modelling and Simulation$94319193 997 $aUNINA