Pore size distribution and porosity influence on Sorptivity of ceramic tiles: From experimental data to fractal modelling

2016 ◽  
Vol 42 (8) ◽  
pp. 9583-9590 ◽  
Author(s):  
Giorgio Pia ◽  
Cristina Siligardi ◽  
Ludovica Casnedi ◽  
Ulrico Sanna
Keyword(s):  
Experimental Data ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Ceramic Tiles

An empirical soil water retention model based on probability laws for pore-size distribution

2021 ◽  
Author(s):  
Wenjuan Zheng ◽  
Chongyang Shen ◽  
Lianping Wang ◽  
Yan Jin
Keyword(s):  
Experimental Data ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Soil Water ◽  
Water Retention ◽  
The Other ◽  
Residual Water ◽  
Soil Water Retention ◽  
Lognormal Distributions

<p>Knowledge of the soil water retention curve (SWRC) is critical to mathematical modeling of soil water dynamics in the vadose zone. Traditional SWRC models were developed based on bundles of cylindrical capillaries (BCCs) using a residual water content, which fail to accurately describe the dry end of the curve. This study improved and expanded on the traditional BCC models. Specifically, the total water retention was treated as a weighed superposition of capillary and adsorptive components.We proposed a mathematical continuous expression for<br />water retention from saturation to oven dryness, which also allowed for a partition of capillary and adsorptive retention. We further evaluated six capillary retention functions using different probability laws for pore-size distribution - namely, the log-logistic, Weibull, lognormal, two-parameter van Genuchten (VG), three-parameter VG (or Dagum), and Fredlund–Xing (FX) distributions. Model testing against 144 experimental data showed better agreement of the proposed model with experimental observations than the traditional approaches that use the residualwater content. The Dagum and FX distributions, which have one more degree of freedom, provided better agreement with experimental data than the other four distributions. The log-logistic and lognormal distributions fitted the experimental data better than the Weibull and VG distribution for loam soils. In addition, the fitted weighting factor w using the log-logistic and lognormal distributions better correlated to soil clay content than the other four distributions. Our study suggests that the log-logistic and lognormal distributions are more suitable to model soils’ pore-size distribution than other tested distributions.</p>

Evaluation of Pore Size Distribution for Controlled Permeability Formwork Liner

2014 ◽  
Vol 534 ◽  
pp. 53-62
Author(s):  
Zheng Hong Tian ◽  
Xiao Dong Wang
Keyword(s):  
Experimental Data ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Good Accuracy ◽  
Functional Material ◽  
Nonwoven Fabrics ◽  
The Matrix ◽  
Accuracy And Repeatability ◽  
Good Agreement

Controlled permeability formwork liner (CPFL) is the functional material similar to nonwoven fabrics and its filtration and drainage performance is dominated by the pore size distribution (PSD) of matrix. In this paper, suction table method, generally used to measure soil pore diameter, is improved for testing PSD of CPFL and experimental data was compared to the results from four other normal experimental methods, i.e., wet sieving method, bubble point method, mercury intrusion porosimetry (MIP) method and image analysis. The comparison indicates that PSD of CPFL obtained from suction table show good accuracy and repeatability. Furthermore, a modified mathematical model derived from Rawal model and Fature model is proved to be suitable for determinating PSD of the matrix of CPFLwith bilayer structure, and have a good agreement with the experimental data from suction table.

scholarly journals Mathematical modeling and simulation of gel drying with supercritical carbon dioxide

2005 ◽  
Vol 70 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Aleksandar Orlovic ◽  
Stojan Petrovic ◽  
Dejan Skala
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Silica Gel ◽  
Particle Diameter ◽  
Effective Diffusivity ◽  
Supercritical Drying ◽  
Drying Time

Mathematical models of alumina/silica gel supercritical drying with carbon dioxide were studied using supercritical drying experimental data. An alumina/silica gel with zinc chloride was synthesized and dried with superciritical carbon dioxide, and its weight change was monitored as a function of drying time. The pore size distribution of the obtained aerogel was determined using the BET method and nitrogen adsorption/ desorption. The mathematical model of the supercritical drying of the wet gel was represented as unsteady and one-dimensional diffusion of solvent through the aerogel pores filled with supercitical carbon dioxide. Parallel pore model and pores in series model were developed on the basis of the measured porous structure of the aerogel. It was found that these models which use different effective diffusivity value for each pore size were in much better agreement with the experimental data than models which use an overall effective diffusivity. The local effective diffusivity coefficients were calculated using different tortuosity values for each pore size, and they were distributed according to the pore size distribution data. Model simulations of the superciritical drying with carbon dioxide confirmed that the drying temperature and gel particle diameter have a significant influence on the drying time.

scholarly journals Influence of Pore Size Distribution on the Electrokinetic Coupling Coefficient in Two-Phase Flow Conditions

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2316
Author(s):  
Jan Vinogradov ◽  
Rhiannon Hill ◽  
Damien Jougnot
Keyword(s):  
Experimental Data ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Coupling Coefficient ◽  
Water Saturation ◽  
Berea Sandstone ◽  
Sandstone Sample ◽  
Irreducible Water Saturation ◽  
Simulation Results

Streaming potential is a promising method for a variety of hydrogeophysical applications, including the characterisation of the critical zone, contaminant transport or saline intrusion. A simple bundle of capillary tubes model that accounts for realistic pore and pore throat size distribution of porous rocks is presented in this paper to simulate the electrokinetic coupling coefficient and compared with previously published models. In contrast to previous studies, the non-monotonic pore size distribution function used in our model relies on experimental data for Berea sandstone samples. In our approach, we combined this explicit capillary size distribution with the alternating radius of each capillary tube to mimic pores and pore throats of real rocks. The simulation results obtained with our model predicts water saturation dependence of the relative electrokinetic coupling coefficient more accurately compared with previous studies. Compared with previous studies, our simulation results demonstrate that the relative coupling coefficient remains stable at higher water saturations but vanishes to zero more rapidly as water saturation approaches the irreducible value. This prediction is consistent with the published experimental data. Moreover, our model was more accurate compared with previously published studies in computing the true irreducible water saturation relative to the value reported in an experimental study on a Berea sandstone sample saturated with tap water and liquid CO2. Further modifications, including explicit modelling of the capillary trapping of the non-wetting phase, are required to improve the accuracy of the model.

pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Surface Area ◽  
Isosteric Heat ◽  
Material Characterisation ◽  
Mixture Adsorption ◽  
Surface Energetics ◽  
Adsorption Processing ◽  
User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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