Describing convective nonwetting phase flow in unsaturated porous media requires knowledge of the nonwetting phase relative permeability. This study was conducted to formulate and derive a generalized expression for the nonwetting phase relative permeability via combining with the Kosugi water retention function. This generalized formulation is then used to flexibly investigate the Burdine, Mua...

With significant increase of tomographic equipment power, demand for Prediction relative permeability prediction Predicting in porous media from digital image data. In this work, it is predicted three -phase relative permeabilities with co-applying Darcy’s and Stokes equations in two case studies, namely Bentheimer sandstone and Estaillades limestone which their micro-CT data files were downloa...

The prediction of porosity is achieved by using available core and log data; however, the estimation of permeability is limited to the scare core data. Hence, porosity and saturation data through the framework of flow units can be used to make an estimation of reservoir permeability. The purpose of this study is to predict the permeability of a carbonate gas reservoir by using physical-based em...

Stenberg, P., 2001. Computational Models for the Prediction of Intestinal Membrane Permeability. Acta Universitatis Upsaliensis. Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy 247. 66 pp. Uppsala. ISBN 91-554-4934-4. Lead compounds generated in high-throughput drug discovery programs often have unfavorable biopharmaceutical properties, resulting in a low success r...

Determination of the permeability coefficient is crucial for the solution of several geotechnical engineering problems such as modeling of underground flow, determination of the hydraulic properties of leachate water in waste disposal areas, calculation of the compressibility, and so on. Constant head permeability test, which is usually performed for the determination of the permeability, is ea...

We present a research study aimed at testing of applicability of machine learning techniques for prediction of permeability of digitized rock samples. We prepare a training set containing 3D images of sandstone samples imaged with X-ray microtomography and corresponding permeability values simulated with Pore Network approach. We also use Minkowski functionals and Deep Learning-based descriptor...

Linagliptin is a highly selective inhibitor of dipeptidyl peptidase-4 and therefore clinically utilized to treat adults with type 2 diabetes mellitus. The objective this study was predict how the ions normally found in extracellular or intracellular fluids within body system will influence linagliptin’s rate passive diffusion across cell membrane. methodology involved measuring linagliptin part...

Amongst the scientific community, the interest on durability of concrete structures has been high for quite a long time of over 40 years. Of the various causes of degradation of concrete structures, corrosion is the most widespread durability problem and carbonation is one of the two causes of steel reinforcement corrosion. While much scientific understanding has been gained from the numerous c...