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

• Superior document: Springer Series in Materials Science Series ; v.333
• Author: Holzer, Lorenz.
• TeilnehmendeR: Marmet, Philip.; Fingerle, Mathias.; Wiegmann, Andreas.; Neumann, Matthias.; Schmidt, Volker.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2023.; ©2023.
• Year of Publication: 2023
• Edition: 1st ed.
• Language: English
• Series: Springer Series in Materials Science Series
• Physical Description: 1 online resource (198 pages)

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.