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Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The study's main objective is to evaluate the morphological developments in the characteristics of the spatial configurations of the residential layouts in Kerman, Iran, in examining the impact on the level of visual privacy through the spectrum of permeability and wayfinding in space syntax analysis.

In this paper, plan graph analysis is used to measure the syntactic properties of seven topological residential architecture plans in Kerman, Iran, built from the 1970s to 2010s. The methodology involves the development of mathematical measurements to signify permeability and simulation of visibility graph analysis (VGA) to indicate wayfinding.

The findings reveal the residential layouts of Iranian houses tend to be less integrated over decades of design development from the 1970s to 2010s. Reduction in spatial integration corresponds to increase segregation allowing for enhanced visual privacy. The study underpins that, even with the constraints in the scale of the house and reduction in the number of nodes, as evident in the design of the modern residential layout, the efficient level of visual privacy is still achievable with regards to the standards demanded by the local culture.

The study examines the development in residential spatial configuration and building scale on visual privacy through a proposed methodology based on the level of permeability and wayfinding measured as a combined effect using the space syntax analysis and visual accessibility.

The purpose of the paper is to conduct a numerical and experimental investigation into the properties of nanofluids containing spherical nanoparticles of random sizes flowing through a porous medium. The study aims to understand how the thermophysical properties of the nanofluid are affected by factors such as nanoparticle volume fraction, permeability of the porous medium, and pore size. The paper provides insights into the behavior of nanofluids in complex environments and explores the impact of varying conditions on key properties such as thermal conductivity, density, viscosity, and specific heat. Ultimately, the research contributes to the broader understanding of nanofluid dynamics and has potential implications for engineering and industrial applications in porous media.

This paper investigates nanofluids with spherical nanoparticles in a porous medium, exploring thermal conductivity, density, specific heat, and dynamic viscosity. Studying three compositions, the analysis employs the classical Maxwell model and Koo and Kleinstreuer’s approach for thermal conductivity, considering particle shape and temperature effects. Density and specific heat are defined based on mass and volume ratios. Dynamic viscosity models, including Brinkman’s and Gherasim et al.'s, are discussed. Numerical simulations, implemented in Python using the Langevin model, yield results processed in Origin Pro. This research enhances understanding of nanofluid behavior, contributing valuable insights to porous media applications.

This study involves a numerical examination of nanofluid properties, featuring spherical nanoparticles of varying sizes suspended in a base fluid with known density, flowing through a porous medium. Experimental findings reveal a notable increase in thermal conductivity, density, and viscosity as the volume fraction of particles rises. Conversely, specific heat experiences a decrease with higher particle volume concentration.xD; xA; The influence of permeability and pore size on particle volume fraction variation is a key focus. Interestingly, while the permeability of the medium has a significant effect, it is observed that it increases with permeability. This underscores the role of the medium’s nature in altering the thermophysical properties of nanofluids.

This paper presents a novel numerical study on nanofluids with randomly sized spherical nanoparticles flowing in a porous medium. It explores the impact of porous medium properties on nanofluid thermophysical characteristics, emphasizing the significance of permeability and pore size. The inclusion of random nanoparticle sizes adds practical relevance. Contrasting trends are observed, where thermal conductivity, density, and viscosity increase with particle volume fraction, while specific heat decreases. These findings offer valuable insights for engineering applications, providing a deeper understanding of nanofluid behavior in porous environments and guiding the design of efficient systems in various industrial contexts.

The purpose of this study is to analyse the characteristics of cellulose fibres derived from the pseudo-stems of Curcuma longa and to evaluate the properties of non-woven fabric produced using these fibres.

The fibres were extracted via a decortication method. The acquired intrinsic qualities of the fibres were used to assess the feasibility of using them in textile applications. The thermal bonding approach was used for the development of the non-woven fabric, using a hot press machine with low-melt polyester fibre as a binder.

The mean length of Curcuma longa fibres was determined to be 52.73 cm, with a fineness value of 4.00 tex. The fibres exhibited an uneven cross-sectional morphology, characterized by a diverse range of oval-shaped lumens. The fibre exhibited a tenacity of 1.45 g/denier and an elongation value of 4.30%. The fibres possessed a moisture regain value of 11.30%. The experimental non-woven fabrics had consistent weight and thickness, while exhibiting different properties in terms of tensile strength and air permeability, with Fabric C having the highest tensile strength and the lowest air permeability value.

The features of Curcuma longa fibre, obtained with the decortication process, exhibited suitability for textile applications. Three experimental non-woven fabrics comprising different compositions of Curcuma longa fibre and low-melt polyester fibre were produced. The tensile strength and air permeability properties of these fabrics were influenced by the composition of the fibres.

Ohmic heating generates temperature with the help of electrical current and resists the flow of electricity. Also, it generates heat rapidly and uniformly in the liquid matrix. Electrically conducting biofluid flows with Ohmic heating have many biomedical and industrial applications. The purpose of this study is to provide the significance of the effects of Ohmic heating and viscous dissipation on electrically conducting Casson nanofluid flow driven by peristaltic pumping through a vertical porous channel.

In this analysis, the non-Newtonian properties of fluid will be characterized by the Casson fluid model. The long wavelength approach reduces the complexity of the governing system of coupled partial differential equations with non-linear components. Using a regular perturbation approach, the solutions for the flow quantities are established. The fascinating and essential characteristics of flow parameters such as the thermal Grashof number, nanoparticle Grashof number, magnetic parameter, Brinkmann number, permeability parameter, Reynolds number, Casson fluid parameter, thermophoresis parameter and Brownian movement parameter on the convective peristaltic pumping are presented and thoroughly addressed. Furthermore, the phenomenon of trapping is illustrated visually.

The findings indicate that intensifying the permeability and Casson fluid parameters boosts the temperature distribution. It is observed that the velocity profile is elevated by enhancing the thermal Grashof number and perturbation parameter, whereas it reduces as a function of the magnetic parameter and Reynolds number. Moreover, trapped bolus size upsurges for greater values of nanoparticle Grashof number and magnetic parameter.

There are some interesting studies in the literature to explain the nature of the peristaltic flow of non-Newtonian nanofluids under various assumptions. It is observed that there is no study in the literature as investigated in this paper.

Titanium(IV) oxide nanoparticles (TiO₂ NP) were deposited to cotton denim fabrics using a self-crosslinking acrylate – a polymer dispersion to extend the lifetime of the products. This study aims to determine the optimum conditions to increase abrasion resistance, to provide self-cleaning properties of denim fabrics and to examine the effects of these applications on other physical properties.

The denim samples were first treated with nonionic surfactant to increase their wettability. Three different amounts of the polymer dispersion and two different pH levels were selected for the experimental design. The finishing process was applied to the fabrics with pad-dry-cure method.

The presence of the coatings and the adhesion of TiO₂ NPs to the surfaces were confirmed by scanning electron microscope and Fourier transform infrared spectroscopy analysis. It was ascertained that the most appropriate self-crosslinking acrylate amount and ambient pH level is 10 mL and “2”, respectively, for providing increased abrasion resistance (2,78%) and enhanced self-cleaning properties (363,4%) in the denim samples. The coating reduced the air permeability and softness of the denim samples. Differential scanning calorimetry and thermogravimetry analysis results showed that the treatments increased the crystallization temperatures and melting enthalpy values of the denim samples. Based on the thermal test results, it is clear that mass loss of the denim samples at 370°C decreased as the amount of self-crosslinking acrylate increased (at pH 3).

This study helped us to find out optimum amount of self-crosslinking acrylate and proper pH level for enhanced self-cleaning and abrasion strength on denim fabrics. With this finishing process, an environmentally friendly and long-life denim fabric was designed.

Face masks are the most recommended precautionary measure since the emergence of SARS-CoV-2 since 2020 and the most useful PPE against this virus and its variants so far. This study aims to develop reusable and biodegradable mask from 100% regenerated bamboo or/and its blend. Selection of natural and regenerated textile materials is to minimize generation of solid waste. This attempt will eventually protect our earth by minimizing or better discontinuing the production of the disposable nonbiodegradable face masks available worldwide.

Hundred percent regenerated bamboo and 50:50 bamboo:cotton were selected to knit plain and interlock fabrics for manufacturing of reusable sustainable face masks. A 2³ 3²-mixed-level factorial design was applied to study the effect of liquor ratio and temperatures, fabric structure, blend ratios and finishes at three different levels. Model 2³ 3² has two factors (liquor ratio and temperatures) at three levels and three factors (fabric structure, blend ratios and type of finish) at two levels. Knitted fabrics were then applied with antibacterial finishes; sanitized T99-19 and sanitized T27-22, separately at three different liquor ratios (1:10, 1:12 and 1:15) and temperatures (45, 55 and 65 °C) via exhaust method. After completing processing, fabric thickness, pilling resistance, dimensional stability, bursting strength, Berger whiteness index, air permeability and antibacterial properties of each trial were evaluated using standard test procedures.

Selected fabrics treated either by sanitized T27 or sanitized T99 in a liquor ratio of 1:15 against 65 °C, showed excellent bacteriostatic/bactericidal activity. However, 100% regenerated bamboo interlock knitted fabric treated with sanitized T99 in a liquor ratio of 1:15 at 65 °C has the most desired values of dimensional stability, pilling resistance, Berger whiteness, fabric thickness, air permeability and bursting strength which made it the best for the manufacturing of the masks. Reusable mask is comprised of three layers in which the first and the third layers were of selected 100% regenerated bamboo fabric while a PM2.5 filter was inserted in between. Bacterial filtration efficiency, particle filtration efficiency, biocompatibility and microbial cleanliness will be evaluated in future, to compare the performance of proposed reusable and biodegradable face mask with N95 masks and other fabric masks available commercially.

This study resulted in a development of reusable eco-friendly facemask which was not attempted by the preceding investigations. Outcomes of this work pave the way for a greener and safer earth by using easily obtainable regenerated bamboo fabrics, antibacterial finishes and knitted structures.

This paper aims to improve the permeability and antifouling of polysulfone (PSF) ultrafiltration membranes, the PSF matrix was modified by incorporating sulfonated polysulfone (SPSF).

Systematic investigations were conducted on the synergistic effects of a pore-forming agent, coagulation bath temperature and SPSF doping in the casting solution on blended ultrafiltration membranes. The chemical composition of the membranes was analyzed using Fourier transform infrared spectroscopy. The morphology and surface roughness of the membranes were characterized using scanning electron microscopy and atomic force microscopy. The hydrophilicity of the membrane surface was analyzed using a contact angle meter. The permeability and antifouling properties of the blended membranes were also investigated through filtration experiments.

The results indicated that the blended ultrafiltration membranes demonstrated an optimal overall performance when PVP-K30 content was 5.0 Wt.%, coagulation bath temperature was 30°C and SPSF content was 2.4 Wt.%. In comparison to a pure PSF ultrafiltration membrane, there was a significant increase in pure water flux (390.7 L·m⁻²·h⁻¹) by 2.2 times, while bovine serum albumin retention slightly decreased to 93.8%. In addition, the flux recovery rate improved by 2.1 times (71.4%) compared to that of the original PSF ultrafiltration membrane.

The method provided a simple and practical solution for improving the antifouling and permeability of PSF ultrafiltration membranes.

SPSF was anticipated to serve as an excellent modification additive for the preparation of ultrafiltration membranes with superior properties.

This paper aims to establish a lattice Boltzmann (LB) method for solid-liquid phase transition (SLPT) from the pore scale to the representative elementary volume (REV) scale. By applying this method, detailed information about heat transfer and phase change processes within the pores can be obtained, while also enabling the calculation of larger-scale SLPT problems, such as shell-and-tube phase change heat storage systems.

Three-dimensional (3D) pore-scale enthalpy-based LB model is developed. The computational input parameters at the REV scale are derived from calculations at the pore scale, ensuring consistency between the two scales. The approaches to reconstruct the 3D porous structure and determine the REV of metal foam were discussed. The implementation of conjugate heat transfer between the solid matrix and the solid−liquid phase change material (SLPCM) for the proposed model is developed. A simple REV-scale LB model under the local thermal nonequilibrium condition is presented. The method of bridging the gap between the pore-scale and REV-scale enthalpy-based LB models by the REV is given.

This coupled method facilitates detailed simulations of flow, heat transfer and phase change within pores. The approach holds promise for multiscale calculations in latent heat storage devices with porous structures. The SLPT of the heat sinks for electronic device thermal control was simulated as a case, demonstrating the efficiency of the present models in designing and optimizing SLPT devices.

A coupled pore-scale and REV-scale LB method as a numerical tool for investigating phase change in porous materials was developed. This innovative approach allows for the capture of details within pores while addressing computations over a large domain. The LB method for simulating SLPT from the pore scale to the REV scale was given. The proposed method addresses the conjugate heat transfer between the SLPCM and the solid matrix in the enthalpy-based LB model.

This paper aims to investigate the hydrodynamic instability properties of a mixed convection flow of nanofluid in a porous channel.

The treated single-phase nanofluid is a suspension consisting of water as the working fluid and alumina as a nanoparticle. The anisotropy of the porous medium and the effects of the inclination of the magnetic field are highlighted. The effects of viscous dissipation and thermal radiation are incorporated into the energy equation. The eigenvalue equation system resulting from the stability analysis is processed numerically by the spectral collocation method.

Analysis of the results in terms of growth rate reveals that increasing the volume fraction of nanoparticles increases the critical Reynolds number. Parameters such as the mechanical anisotropy parameter and Richardson number have a destabilizing effect. The Hartmann number, permeability parameter, magnetic field inclination, Prandtl number, wave number and thermal radiation parameter showed a stabilizing effect. The Eckert number has a negligible effect on the growth rate of the disturbances.

Linear stability analysis of Magnetohydrodynamics (MHD) mixed convection flow of a radiating nanofluid in porous channel in presence of viscous dissipation.