scholarly journals From micro-scale to macro-scale modeling of solute transport in drying capillary porous media

2021 ◽  
Vol 165 ◽  
pp. 120722
Author(s):  
Faeez Ahmad ◽  
Arman Rahimi ◽  
Evangelos Tsotsas ◽  
Marc Prat ◽  
Abdolreza Kharaghani
Keyword(s):  
Porous Media ◽  
Solute Transport ◽  
Micro Scale ◽  
Scale Modeling ◽  
Macro Scale

scholarly journals Micro- and Macro-Scale Measurement of Flow Velocity in Porous Media: A Shadow Imaging Approach for 2D and 3D

Optics ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 71-87 ◽  
Author(s):  
Reza Sabbagh ◽  
Mohammad Amin Kazemi ◽  
Hirad Soltani ◽  
David S. Nobes
Keyword(s):  
Porous Medium ◽  
Porous Media ◽  
Flow Pattern ◽  
Flow Measurement ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Detailed Knowledge ◽  
Micro Scale ◽  
Macro Scale

Flow measurement in porous media is a challenging subject, especially when it comes to performing a three-dimensional (3D) velocimetry at the micro scale. Volumetric flow measurement techniques such as defocusing and tomographic imaging generally involve rigorous procedures, complex experimental setups, and multi-part data processing procedures. However, detailed knowledge of the flow pattern at the pore and subpore scales is important in interpreting the phenomena that occur inside the porous media and understanding the macro-scale behaviors. In this work, the flow of an oil inside a porous medium is measured at the pore and subpore scales using refractive index matching (RIM) and shadowgraph imaging techniques. At the macro scale, flow is measured using the particle image velocimetry (PIV) method in two dimensions (2D) to confirm the volumetric nature of the flow and obtain the overall flow pattern in the vicinity of the flow entrance and at the far field. At the micro scale, the three-dimensional (3D) flow within an arbitrary volume of the porous medium was quantified using 2D particle-tracking velocimetry (PTV) utilizing the law of conservation of mass. Using the shadowgraphy method and a single camera makes the flow measurement much less complex than the approaches using laser light sheets or multiple cameras with multiple viewing angles.

scholarly journals Simulation of dry powder inhalers: Combining micro-scale, meso-scale and macro-scale modeling

AIChE Journal ◽  
2016 ◽  
Vol 63 (2) ◽  
pp. 501-516 ◽  
Author(s):  
Berend van Wachem ◽  
Kyrre Thalberg ◽  
Johan Remmelgas ◽  
Ingela Niklasson-Björn
Keyword(s):  
Dry Powder Inhalers ◽  
Dry Powder ◽  
Micro Scale ◽  
Scale Modeling ◽  
Macro Scale ◽  
Meso Scale

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 106 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. Numerical models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS APDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

2018 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. FE models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS PDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

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