Stochastic Modelling in Process Technology

There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. Introduction to stochastic process modelling as an alternative modelling technique Shows how stochastic modelling may be succesful where the traditional technique fails Overview of stochastic modelling in process technology in the research literature Illustration of the principle by a wide range of practical examples In-depth and self-contained discussions Points the way to both mathematical and technological research in a new, rewarding field

Produk Detail:

  • Author : Herold G. Dehling
  • Publisher : Elsevier
  • Pages : 290 pages
  • ISBN : 9780080548975
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKStochastic Modelling in Process Technology

Stochastic Modelling in Process Technology

Stochastic Modelling in Process Technology
  • Author : Herold G. Dehling,Timo Gottschalk,Alex C. Hoffmann
  • Publisher : Elsevier
  • Release : 03 July 2007
GET THIS BOOKStochastic Modelling in Process Technology

There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique

Stochastic Models in Reliability Engineering

Stochastic Models in Reliability Engineering
  • Author : Lirong Cui,Ilia Frenkel,Anatoly Lisnianski
  • Publisher : CRC Press
  • Release : 01 September 2020
GET THIS BOOKStochastic Models in Reliability Engineering

This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years. The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a

An Introduction to Stochastic Modeling

An Introduction to Stochastic Modeling
  • Author : Howard M. Taylor,Samuel Karlin
  • Publisher : Gulf Professional Publishing
  • Release : 20 February 1998
GET THIS BOOKAn Introduction to Stochastic Modeling

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Third Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of

Stochastic Models In Engineering, Technology And Management - Proceedings Of The Australia-japan Workshop

Stochastic Models In Engineering, Technology And Management - Proceedings Of The Australia-japan Workshop
  • Author : Osaki Shunji,Murthy D N Pra
  • Publisher : World Scientific
  • Release : 27 April 1993
GET THIS BOOKStochastic Models In Engineering, Technology And Management - Proceedings Of The Australia-japan Workshop

Chinese Remainder Theorem, CRT, is one of the jewels of mathematics. It is a perfect combination of beauty and utility or, in the words of Horace, omne tulit punctum qui miscuit utile dulci. Known already for ages, CRT continues to present itself in new contexts and open vistas for new types of applications. So far, its usefulness has been obvious within the realm of “three C's”. Computing was its original field of application, and continues to be important as regards

Stochastic Modelling for Systems Biology, Third Edition

Stochastic Modelling for Systems Biology, Third Edition
  • Author : Darren J. Wilkinson
  • Publisher : CRC Press
  • Release : 07 December 2018
GET THIS BOOKStochastic Modelling for Systems Biology, Third Edition

Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been

A First Course in Stochastic Models

A First Course in Stochastic Models
  • Author : Henk C. Tijms
  • Publisher : John Wiley & Sons
  • Release : 18 April 2003
GET THIS BOOKA First Course in Stochastic Models

The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides

Stochastic Modeling of Scientific Data

Stochastic Modeling of Scientific Data
  • Author : Peter Guttorp
  • Publisher : CRC Press
  • Release : 29 March 2018
GET THIS BOOKStochastic Modeling of Scientific Data

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods

Stochastic Models in Reliability and Maintenance

Stochastic Models in Reliability and Maintenance
  • Author : Shunji Osaki
  • Publisher : Springer Science & Business Media
  • Release : 02 November 2012
GET THIS BOOKStochastic Models in Reliability and Maintenance

Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to

Cyber-Physical Systems: Advances in Design & Modelling

Cyber-Physical Systems: Advances in Design & Modelling
  • Author : Alla G. Kravets,Alexander A. Bolshakov,Maxim V. Shcherbakov
  • Publisher : Springer Nature
  • Release : 25 November 2019
GET THIS BOOKCyber-Physical Systems: Advances in Design & Modelling

This book presents new findings on cyber-physical systems design and modelling approaches based on AI and data-driven techniques, identifying the key industrial challenges and the main features of design and modelling processes. To enhance the efficiency of the design process, it proposes new approaches based on the concept of digital twins. Further, it substantiates the scientific, practical, and methodological approaches to modelling and simulating of cyber-physical systems. Exploring digital twins of cyber-physical systems as well as of production systems, it

Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling
  • Author : Oliver Ibe
  • Publisher : Newnes
  • Release : 22 May 2013
GET THIS BOOKMarkov Processes for Stochastic Modeling

Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas

Advances in Stochastic Modelling and Data Analysis

Advances in Stochastic Modelling and Data Analysis
  • Author : Jacques Janssen,Christos H. Skiadas,Constantin Zopounidis
  • Publisher : Springer Science & Business Media
  • Release : 17 April 2013
GET THIS BOOKAdvances in Stochastic Modelling and Data Analysis

Advances in Stochastic Modelling and Data Analysis presents the most recent developments in the field, together with their applications, mainly in the areas of insurance, finance, forecasting and marketing. In addition, the possible interactions between data analysis, artificial intelligence, decision support systems and multicriteria analysis are examined by top researchers. Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and

Stochastic Modelling in Innovative Manufacturing

Stochastic Modelling in Innovative Manufacturing
  • Author : Anthony H. Christer,Shunji Osaki,Lyn C. Thomas
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKStochastic Modelling in Innovative Manufacturing

This monograph contains some ofthe papers presented at a UK-Japanese Workshop on Stochastic Modelling in Innovative Manufacturing held at Churchill College, Cambridge on July 20 and 21st 1995, sponsored jointly by the UK Engineering and Physical Science Research Council and the British Council. Attending were 19 UK and 24 Japanese delegates representing 28 institutions. The aim of the workshop was to discuss the modelling work being done by researchers in both countries on the new activities and challenges occurring in manufacturing. These challenges have arisen

Energy Efficiency in Process Technology

Energy Efficiency in Process Technology
  • Author : P.A. Pilavachi
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKEnergy Efficiency in Process Technology

Since 1975 the Commission has been stimulating R & D work aimed at energy saving. The conference objective was to provide an international forum for the presentation and discussion of recent R & D relevant to energy efficiency, taking into account environmental aspects, in the energy intensive process industries.