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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.
Key Features:
- 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
- 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
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