Stochastic Modelling Process Technology by Dehling (11 results)

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  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

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  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

    • Hardcover

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  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

    • Hardcover

    Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections

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    Condition: New. In English.

  • Language: English

    Published by Elsevier Science and Technology, GB, 2007

    0444520260 / 9780444520265

    • Hardcover

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    Hardback. Condition: New. 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. …

  • Language: English

    Published by Amsterdam, Elsevier, 2007

    0444520260 / 9780444520265

    • Hardcover

    Seller: Antiquariat Bookfarm, Löbnitz, GermanyAntiquariat Bookfarm

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    Hardcover. Condition: Gut. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 60 DEH 9780444520265 Sprache: Englisch Gewicht in Gramm: 1150.…

  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

    • Hardcover

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  • Language: English

    Published by Elsevier Science, 2007

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    • Hardcover

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  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

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  • Language: English

    Published by Elsevier Science, 2013

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    • Softcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Paperback. Condition: Brand New. 290 pages. 9.10x6.10x0.66 inches. In Stock.

  • Language: English

    Published by Elsevier Science and Technology, GB, 2007

    0444520260 / 9780444520265

    • Hardcover

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    Hardback. Condition: New. 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. …

  • Language: English

    Published by Elsevier Science & Technology, 2007

    0444520260 / 9780444520265

    • Hardcover
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    Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.