000			03621cam a2200289 i 4500
005			20241005102300.0
008			151104s2015 xxu grb 001 0 eng d
020			_a9781482205923 _a9781138075085
040			_aUISEK-EC _bspa _erda
041			_heng
082	0	4	_a660.2815 _bV522p 2014 _2
100	1		_a Verma, Ashok Kumar _96591 _eaut
245	1	0	_aProcess modelling and simulation in chemical, biochemical and environmental engineering/ _cAshok Kumar Verma
264		1	_aNew York : _bCRC Press Taylor & Franis Group, _c2015
300			_axxxvi, 388 páginas ; _c24 cm. _bilustraciones;
336			_atxt
337			_2rdamedia _an
338			_2rdacarrier _anc
504			_aIncluye referencias bibliográficas e índice
505	1	0	_aIntroduction to modelling and simulation .-- An overview of modelling and simulation .-- Models based on simple laws. -- Models based on laws of conservation. -- Multiphase systems without reaction .--. Multiphase systems with reaction. -- Population balance models and discrete-event models. -- Artificial neural network-based models. -- Model validation and sensitivity analysis. -- Case studies .-- Simulation of large plants.
520	3		_aThe use of simulation plays a vital part in developing an integrated approach to process design. By helping save time and money before the actual trial of a concept, this practice can assist with troubleshooting, design, control, revamping, and more. Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering explores effective modeling and simulation approaches for solving equations. Using a systematic treatment of model development and simulation studies for chemical, biochemical, and environmental processes, this book explains the simplification of a complicated process at various levels with the help of a "model sketch." It introduces several types of models, examines how they are developed, and provides examples from a wide range of applications. This includes the simple models based on simple laws such as Fick’s law, models that consist of generalized equations such as equations of motion, discrete-event models and stochastic models (which consider at least one variable as a discrete variable), and models based on population balance. Divided into 11 chapters, this book: Presents a systematic approach of model development in view of the simulation need Includes modeling techniques to model hydrodynamics, mass and heat transfer, and reactors for single as well as multi-phase systems Provides stochastic and population balance models Covers the application and development of artificial neural network models and hybrid ANN models Highlights gradients based techniques as well as statistical techniques for model validation and sensitivity analysis Contains examples on development of analytical, stochastic, numerical, and ANN-based models and simulation studies using them Illustrates modeling concepts with a wide spectrum of classical as well as recent research papers Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering includes recent trends in modeling and simulation, e.g. artificial neural network (ANN)-based models, and hybrid models. It contains a chapter on flowsheeting and batch processes using commercial/open source software for simulation.
526			_aAmbiental
650	1	7	_aProcesos químicos _xMétodos de simulación _2lemb _96590
650	2	7	_aProcesos químicos _xProgramas para computador _2lemb _96590
653	2	6	_aSimulación de proceso
942			_cBK
999			_c10105 _d10105