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Stochastic Modeling in Process Technology
ID: 175070
Herold Dehling, Timo Gottschalk, Alex Hoffmann
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There is an ever increasing need for the reliably complex of processes. Computational modeling techniques, such as CFD and MD may be used as a tool for analysis, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behavior and becoming omnipresent in the processing industry.
This book discusses the stochastic process modeling.
The technique is based on the problem of the distribution of the concept of a different phenomenon in the process of the vessel, and it is traditionally done conservation equations.
Using the technique can be greatly simplified. The traditional method is impracticable.
Stochastic modeling has sporadically been used in various ways and guises. This book gives an overview of basic mathematical tools and techniques.
The book also demonstrates how stochastic modeling can be formulated by solving differential balance equations.
This book discusses the stochastic process modeling.
The technique is based on the problem of the distribution of the concept of a different phenomenon in the process of the vessel, and it is traditionally done conservation equations.
Using the technique can be greatly simplified. The traditional method is impracticable.
Stochastic modeling has sporadically been used in various ways and guises. This book gives an overview of basic mathematical tools and techniques.
The book also demonstrates how stochastic modeling can be formulated by solving differential balance equations.
Key Features:
- Introduction to stochastic process modeling as an alternative modeling technique
- Shows how stochastic modeling may be succesful where the traditional technique fails
- Overview of stochastic modeling in the process of studying literature
- Illustration of the principle of 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 modeling as an alternative modeling technique
- Shows how stochastic modeling may be succesful where the traditional technique fails
- Overview of stochastic modeling in the process of studying literature
- Illustration of the principle of 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
175070
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Herold Dehling, Timo Gottschalk, Alex Hoffmann