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Tortuosity and Microstructure Effects in Porous Media : Classical Theories, Empirical Data and Modern Methods.

Bibliographic Details
Main Author: Holzer, Lorenz.
Other Authors: Marmet, Philip., Fingerle, Mathias., Wiegmann, Andreas., Neumann, Matthias., Schmidt, Volker.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2023.
Edition:1st ed.
Series:Springer Series in Materials Science Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Acknowledgements
  • Contents
  • 1 Introduction
  • References
  • 2 Review of Theories and a New Classification of Tortuosity Types
  • 2.1 Introduction
  • 2.1.1 Basic Concept of Tortuosity
  • 2.1.2 Basic Challenges
  • 2.1.3 Criteria for Classification
  • 2.1.4 Content and Structure of This Chapter
  • 2.2 Hydraulic Tortuosity
  • 2.2.1 Classical Carman-Kozeny Theory
  • 2.2.2 From Classical Carman-Kozeny Theory to Modern Characterization of Microstructure Effects
  • 2.3 Electrical Tortuosity
  • 2.3.1 Indirect Electrical Tortuosity
  • 2.3.2 Mixed Electrical Tortuosities
  • 2.4 Diffusional Tortuosity
  • 2.4.1 Knudsen Number
  • 2.4.2 Bulk Diffusion
  • 2.4.3 Knudsen Diffusion
  • 2.4.4 Limitations to the Concept of Diffusional Tortuosity
  • 2.5 Direct Geometric Tortuosity
  • 2.5.1 Skeleton and Medial Axis Tortuosity
  • 2.5.2 Path Tracking Method (PTM) Tortuosity
  • 2.5.3 Geodesic Tortuosity
  • 2.5.4 Fast Marching Method (FMM) Tortuosity
  • 2.5.5 Percolation Path Tortuosity
  • 2.5.6 Pore Centroid Tortuosity
  • 2.6 Tortuosity Types: Classification Scheme and Nomenclature
  • 2.6.1 Classification Scheme
  • 2.6.2 Nomenclature
  • 2.7 Summary
  • References
  • 3 Tortuosity-Porosity Relationships: Review of Empirical Data from Literature
  • 3.1 Introduction
  • 3.2 Empirical Data for Different Materials and Microstructure Types
  • 3.3 Empirical Data for Different Tortuosity Types
  • 3.4 Direct Comparison of Tortuosity Types Based on Selected Data Sets
  • 3.4.1 Example 1: Indirect Versus Direct Pore Centroid Tortuosity
  • 3.4.2 Example 2: Indirect Versus Direct Medial Axis Tortuosity
  • 3.4.3 Example 3: Indirect Versus Direct Geodesic Tortuosity
  • 3.4.4 Example 4: Indirect Versus Medial Axis Versus Geodesic Tortuosity
  • 3.4.5 Example 5: Direct Medial Axis Versus Direct Geodesic Tortuosity.
  • 3.4.6 Example 6: Mixed Streamline Versus Mixed Volume Averaged Tortuosity
  • 3.5 Relative Order of Tortuosity Types
  • 3.5.1 Summary of Empirical Data: Global Pattern of Tortuosity Types
  • 3.5.2 Interpretation of Different Tortuosity Categories
  • 3.6 Tortuosity-Porosity Relationships in Literature
  • 3.6.1 Mathematical Expressions for τ-ε Relationships and Their Limitations
  • 3.6.2 Mathematical Expressions for τ-ε Relationships and Their Justification
  • 3.7 Summary
  • References
  • 4 Image Based Methodologies, Workflows, and Calculation Approaches for Tortuosity
  • 4.1 Introduction
  • 4.2 Tomography and 3D Imaging
  • 4.2.1 Overview and Introduction to 3D Imaging Methods
  • 4.2.2 X-ray Computed Tomography
  • 4.2.3 FIB-SEM Tomography and Serial Sectioning
  • 4.2.4 Electron Tomography
  • 4.2.5 Atom Probe Tomography
  • 4.2.6 Correlative Tomography
  • 4.3 Available Software Packages for 3D Image Processing and Computation of Tortuosity
  • 4.3.1 Methodological Modules
  • 4.3.2 Different Types of SW Packages
  • 4.4 From Tomography Raw Data to Segmented 3D Microstructures: Step by Step Example of Qualitative Image Processing
  • 4.5 Calculation Approaches for Tortuosity
  • 4.5.1 Calculation Approaches and SW for Direct Geometric Tortuosities (τdir_geom)
  • 4.5.2 Calculation Approaches and SW for Indirect Physics-Based Tortuosities (τindir_phys)
  • 4.5.3 Calculation Approaches for Mixed Tortuosities
  • 4.6 Pore Scale Modeling for Tortuosity Characterization: Examples from Literature
  • 4.6.1 Examples of Pore Scale Modeling in Geoscience
  • 4.6.2 Examples of Pore Scale Modeling for Energy and Electrochemistry Applications
  • 4.7 Stochastic Microstructure Modeling
  • 4.7.1 Stochastic Modeling for Digital Materials Design (DMD) of Electrochemical Devices
  • 4.7.2 Stochastic Modeling for Digital Rock Physics and Virtual Materials Testing of Porous Media.
  • 4.8 Summary
  • References
  • 5 Towards a Quantitative Understanding of Microstructure-Property Relationships
  • 5.1 Introduction
  • 5.2 Quantitative Micro-Macro Relationships for the Prediction of Conductivity and Diffusivity
  • 5.3 Quantitative Micro-Macro Relationships for the Prediction of Permeability
  • 5.3.1 Bundle of Tubes Model
  • 5.3.2 Sphere Packing Model
  • 5.3.3 Determination of Characteristic Length and M-factor by Laboratory Experiments
  • 5.3.4 Determination of Characteristic Length and M-factor by 3D Image Analysis
  • 5.3.5 Determination of Characteristic Length and M-factor by Virtual Materials Testing
  • 5.4 Summary
  • References
  • 6 Summary and Conclusions.

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