Introduction to the Thermodynamically Constrained Averaging Theory for Porous Medium Systems

William G. Gray

ISBN 10: 3319355015 / ISBN 13: 9783319355016

Published by Springer, Springer Okt 2016, 2016

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Thermodynamically constrained averaging theory provides a consistent method for upscaling conservation and thermodynamic equations for application in the study of porous medium systems. The method provides dynamic equations for phases, interfaces, and common curves that are closely based on insights from the entropy inequality.All larger scale variables in the equations are explicitly defined in terms of their microscale precursors, facilitating the determination of important parameters and macroscale state equations based on microscale experimental and computational analysis.The method requires that all assumptions that lead to a particular equation form be explicitly indicated, a restriction which is useful in ascertaining the range of applicability of a model as well as potential sources of error and opportunities to improve the analysis.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 616 pp. Englisch.

Seller Inventory # 9783319355016

Bibliographic Details

• Title: Introduction to the Thermodynamically Constrained Averaging Theory for Porous Medium Systems
• Publisher: Springer, Springer Okt 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3319355015
• ISBN 13: 9783319355016
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 33D millimeters 235 millimeters width by 155 millimeters height by 33 millimeters depth
• Weight: 920 grams

About this title

Synopsis

Thermodynamically constrained averaging theory provides a consistent method for upscaling conservation and thermodynamic equations for application in the study of porous medium systems. The method provides dynamic equations for phases, interfaces, and common curves that are closely based on insights from the entropy inequality. All larger scale variables in the equations are explicitly defined in terms of their microscale precursors, facilitating the determination of important parameters and macroscale state equations based on microscale experimental and computational analysis. The method requires that all assumptions that lead to a particular equation form be explicitly indicated, a restriction which is useful in ascertaining the range of applicability of a model as well as potential sources of error and opportunities to improve the analysis.