Parameters Of Medium Research Articles

Modeling industrial scale washing machine process using artificial neural networks

AbstractThe paper presents a dynamic model of a typical industrial washing machine fed with hot water, cold water and steam. Since industrial scale washing machines are not expressly designed to be energy efficient, there is scope to reduce energy consumption and wastewater discharge through dynamic model analysis of washing programs and washing machine units as regards heating medium parameters and prices. The paper presents a construction of the dynamic model using Aspen Hysys software that provides data to determine optimized parameters of water and steam delivered to the washing unit. The model has been validated with real data delivered by the dedicated measuring software from the washing machine manufacturer. Finally, the paper presents an economic analysis and sensitivity analysis regarding energy prices with various media parameters. Results show that the price of the washing process can be reduced by 64% depending on the parameters of the heating medium.

Dual Solutions of Two-Dimensional Hybrid Nanofluid Flow and Heat Transfer Past a Porous Medium Permeable Shrinking Sheet with Influence of Heat GenerationAbsorption and Convective Boundary Condition

In this study, the dual solutions of two-dimensional hybrid nanofluid flow and heat transfer past a porous medium permeable shrinking sheet with influence of heat generation/absorption and convective boundary condition were examined using the bvp4c solver with the MATLAB computational framework. The utilization of two-dimensional hybrid nanofluid flow and heat transfer in the presence of a porous medium permeable shrinking sheet, considering the effects of heat generation/absorption and convective boundary conditions, has wide-ranging applications in industries such as cooling systems, aerospace, chemical engineering, biomedical applications, energy systems, microfluidics, automotive thermal management, industrial drying, and nuclear reactor cooling, etc. These applications employ the improved thermal characteristics of hybrid nanofluids and the efficient heat control offered by porous media and convective boundary conditions. The governing partial differential equations (PDEs) are transformed into a collection of higher-order ordinary differential equations (ODEs) together with their corresponding boundary conditions. These equations are subsequently shown both numerically and graphically. The main objective of this inquiry is to examine the relationship between the solid volume fraction of copper and the permeability parameter of the porous medium, specifically focusing on the values of f''(0) and - (0) according to the suction effect. The current research has also integrated the temperature and velocity profile of a hybrid nanofluid flow, which corresponds to the influence of porous medium permeability, heat generation/absorption, and convective boundary condition. Dual solutions are acquired by certain combinations of parameters. Non unique solutions are obtained when the critical point reaches , for suction effects. Increasing the intensity of heat generation absorption and convective boundary condition leads to a more pronounced temperature profile and thicker boundary layer.

Application of statistical designs strategy to improve cellulase production using agro-waste residue by a novel isolate Bacillus licheniformis strain-MA1 and assessing the enzyme effect on apple juice quality

BackgroundCellulose is the major part of lignocellulosic biomass. It can be hydrolyzed into glucose units via specific enzymes called cellulases that have been applied in many commercial fields. There are several studies illustrate the influence of enzymes on apple juice clarification. However, to the best of our knowledge, the effect of microbial cellulase on volatile compounds of apple juice is not well known. The present study aimed to assess the effect of cellulase from a new bacterial isolate on the physicochemical properties of apple juice as well as volatile compounds. The hydrolysis of some polysaccharides (cellulose, hemicellulose, pectin) and polyphenols during apple juice production is necessary to reduce cloud sedimentation or color deterioration and increase the yield of juice. So, enzymes from new microbial isolates serve as processing aids to obtain clear juice with a high yield.ResultsCellulase-producing bacterium was isolated, characterized and molecularly identified as Bacillus licheniformis strain-MA1 with an accession number of ON840115. Optimization of medium parameters was implemented using Plackett–Burman design (PBd) followed by Box-Behnken design (BBd) of response surface methodology (RSM). The PBd revealed the three most important (significant) variables including carboxymethyl cellulose (CMC), corn cob, and peptone that had positive impact on cellulase production. Additionally, using the agricultural residue (corn cob) by the bacterial strain as a carbon source helps in reducing the costs of enzyme production, recycling the by-products, and preserving the environment. The optimized medium using PBd and BBd enhanced cellulase production from B. licheniformis strain-MA1 by 6.8-fold. A remarkable increase was observed in juice yield in enzyme treated-juice sample (88.2 ± 0.15%) in comparison with control juice (75.4 ± 0.09%). The total phenolic contents in cloudy and clarified apple juices were 0.957 ± 0.09 and 0.412 ± 0.03 mg/mL, respectively. Also, DPPH and FRAP assays showed a remarkable increase in antioxidant activity (Low IC50) in the control sample compared to enzyme treatment. Twenty-seven volatile compounds were extracted using headspace solid-phase microextraction-gas and analysis was performed by GC–MS. The identified volatile constituents belonged to several chemical classes: 15 esters; 6 alcohols; 4 aldehydes and 2 acids. The predominant class in apple juice volatile fraction was esters with a sweet and fruity odor.ConclusionThe crude cellulase obtained from the novel bacterial isolate B. licheniformis strain-MA1 was successfully applied as a clarifying agent in apple juice.

Mathematical model and its solution for water-altering-gas (WAG) injection process incorporating the effect of miscibility, gravity, viscous fingering and permeability heterogeneity

AbstractThe oil recovery from the water-alternating-gas (WAG) injection process is significantly impacted by gravity, viscous fingering, and the permeability heterogeneity of the reservoir. Therefore, the combined effect of these parameters cannot be neglected in the WAG injection process. This article presents the development of a mathematical model of oil recovery and its solution for the WAG injection process that takes into account the combined effects of miscibility change, viscous fingering, gravity, and permeability heterogeneity in an inclined stratified reservoir. First, the governing equations and fractional flow functions were explained in relation to the effects of gravity, permeability heterogeneity, viscous fingering, and miscibility change in an inclined stratified porous medium. Then, a mathematical model was developed using fractional flow functions and conservation equations for both injected water and solvent. The model was generated in the form of a quasi-linear first-order partial differential equation, which was solved analytically in two dimensions (2-D) utilizing vector calculus. Next, this model was solved analytically by applying wave theory to practical constant pressure boundary conditions, which generate distinct waves at different times to provide pressure and saturation at the displacement front location. The total volumetric flux and breakthrough time are calculated from the analytical solution at various times. The presented analytical solutions can be used to predict different parameters for stratified porous media in a fast and efficient way. Finally, the results of analytical solution validated with high-resolution numerical simulation for a wide range of permeability heterogeneity, which shows excellent agreement for breakthrough time, saturation, and pressure versus displacement location of different waves at different times. This analytical solution will save time and money by offering guidance to engineers for analyzing the saturation and pressure distribution at different times and predicting oil recovery. It will also improve the understanding of the physics underlying the multiphase flow WAG injection process in heterogeneous reservoirs.

In-medium gluon radiation spectrum with all-order resummation of multiple scatterings in longitudinally evolving media

Over the past years, there has been a sustained effort to systematically enhance our understanding of medium-induced emissions occurring in the quark-gluon plasma, driven by the ultimate goal of advancing our comprehension of jet quenching phenomena. To ensure meaningful comparisons between these new calculations and experimental data, it becomes crucial to model the interplay between the radiation process and the evolution of the medium parameters, typically described by a hydrodynamical simulation. This step presents particular challenges when dealing with calculations involving the resummation of multiple scatterings, which have been shown to be necessary for achieving an accurate description of the in-medium emission process. In this paper, we extend our numerical calculations of the fully-resummed gluon spectrum to account for longitudinally expanding media. This new implementation allows us to quantitatively assess the accuracy of previously proposed scaling laws that establish a correspondence between an expanding medium and a “static equivalent”. Additionally, we show that such scaling laws yield significantly improved results when the static reference case is replaced by an expanding medium with the temperature following a simple power-law decay. Such correspondence will enable the application of numerical calculations of medium-induced energy loss in realistic evolving media for a broader range of phenomenological studies.

Comparison of methods for diagnosing marine IC engines based on working medium parameters including exhaust gas specific enthalpy

Article points out methods currently used to diagnose marine engines in operation. The development of tools and programs for implementing these methods was pointed out. The problem of unsatisfactory measurement susceptibility of marine engines was highlighted. Three methods of parametric diagnosis are presented: measurement of in-cylinder parameters and in exhaust gas duct, numerical simulation due to computer software and calculations based on Wibe function. Unfitness states that were analyzed during tests are presented: reduced injection pressure, obstructed intake air duct and reduced compression ratio. The specific enthalpy of the exhaust gas within one engine cycle was determined as a new diagnostic parameter. As a supplement, thermograms of the engine in various states of inoperability were presented. The obtained results were compared and a series of conclusions derived from them were presented. It was evaluated that numerical simulation is an excellent tool for planning experimental studies. Tests on the engine in operation were found to be the most diagnostically reliable.

On the reliability of constraining surface conductivity using induced polarization measurements in sedimentary rocks

SUMMARY Recent advances in understanding the induced polarization (IP) method have led to improvements in interpreting hydraulic properties from electrical measurements. Distinguishing the effect of surface conduction from conduction through the electrolyte filling the interconnected pore spaces has been an ongoing challenge in interpreting field-scale electrical resistivity data sets. Previously proposed mechanistic models have suggested that this limitation can be overcome by utilizing the coefficient that describes the ratio between IP measurements and surface conductivity. In this study, we examine this proportionality coefficient (ℓ) through the relationship between IP parameters (imaginary conductivity and normalized chargeability) and surface conductivity for a sample group of 98 sedimentary rocks, composed of sandstones, carbonates and mudstones. A strong linear relationship is observed between the IP parameters and surface conductivity. However, values of ℓ vary significantly across each sample group such that low-salinity estimates of formation factor (F) using the single universal estimate of ℓ are poor. Estimates of F for a single rock type (sandstone, carbonate or mudstone) are improved using ℓ values unique to that rock type, although F estimates for mudstones show high sensitivity to changes in ℓ. Using ℓ coefficients calibrated on a sample group with similar lithological properties to the investigated group moderately improves the estimation of F. Consistent with theory, no relationship is observed between the proportionality coefficient and the measured petrophysical parameters of the porous medium. Our results suggest that, although IP measurements provide a valuable field-scale proxy for surface conductivity, improving petrophysical predictions (i.e. in this case, estimating F) remains a challenge.

Presentation of representative shape parameters of porous media based on mathematical computation on images

The shape parameters of porous media are really important to describe the petrophysical and geomechanical parameters of reservoirs. In addition, shape analysis can provide essential information about the origin, transport, deposition history of particles, etc. Because macroscopic properties (such as permeability, diffusion, etc.) are influenced by microscopic properties (such as pore size, grain shape, etc.). So far, various studies have been conducted to calculate some shape parameters, however, there is no comprehensive study that first includes most of the geometric parameters of the shape and then presents the representative shape parameters. Therefore, the aim of this study is to present representative shape parameters of porous media based on mathematical computation on images. The shape parameters studied included roundness, circularity, angularity, convexity, compactness, sphericity, aspect ratio, elongation, eccentricity, shape factor, and regularity. Calculation of shape parameters is done digitally using the developed program. The necessary data for the desired analysis are obtained from real sandstone samples. To develop this research, first, the mentioned shape parameters are calculated using the developed program for all rock samples. Then, by establishing a relationship between the mentioned parameters, the representative parameters that can show the shape of the porous medium are expressed. The results of this study show that the representative shape parameters of the porous medium are compactness, shape factor-round, and aspect ratio, which are good indicators for the shape of the porous medium.

A GPR layered media parameters inversion method under rough surface

Abstract Ground Penetrating Radar (GPR) plays an important role in pavement detection and road exploration due to its efficiency. Traditional media parameter inversion algorithms only consider ideal smooth surfaces and neglect the roughness of interfaces, leading to significant errors in practical applications. Therefore, a GPR rough surface-layered medium parameter inversion method based on genetic algorithm is proposed in this paper. The method uses the generalized reflection coefficient and considers the influence of the surface roughness of the medium. Then, a radar echo signal time-domain model is established. Finally, the cost function is optimized by genetic algorithm. The effectiveness and accuracy are validated and analysed by utilizing simulated data through random rough surfaces models.

Amplitude variation with azimuth direct inversion for effective pressure-sensitivity parameters in horizontal transversely isotropic media

Effective pressure prediction is of great significance for fracturability evaluation in unconventional reservoirs. Quantitative characterization of effective pressure remains a great challenge in the inversion prediction of subsurface media. Our goal is to develop a novel Bayesian amplitude varying with azimuth (AVAZ) inversion method to estimate fracture weaknesses and effective pressure for a horizontal transversely isotropic (HTI) medium. Using Schoenberg’s linear slip model and pore space compressibility theory, an anisotropic saturated stiffness matrix directly characterized by effective pressure is derived based on a weak-contrast interface separating two weakly anisotropic half-spaces of HTI medium. Based on the perturbation stiffness matrix and scattering theory, we derive a PP-wave reflection coefficient approximation directly characterized by fracture weaknesses and effective pressure-sensitive parameters, which establishes a quantitative relationship between seismic reflection coefficient and effective pressure. The analysis of accuracy and sensitivity is performed to verify the reliability and applicability of the constructed reflection coefficient. And then, the azimuth-amplitude-difference forward solver is constructed based on seismic reflection coefficients to eliminate the influence of isotropic background perturbations on seismic reflection coefficients and reduce the condition number of the forward solver. Finally, we present a novel Bayesian azimuth-amplitude-difference AVAZ inversion method for transversely isotropic media constrained by Cauchy and Gaussian regularization to directly estimate the fracture weaknesses and effective pressure-sensitive parameters. The application of synthetic data and field data verifies that the inversion results are in good agreement with the actual data, indicating that the method can effectively realize the stable prediction of anisotropic parameters and effective pressure-sensitive parameters of complex media.

Profiling The Growth Conditions and Persistent Organic Pollutants (POPS) Tolerance of Phenoliferia glacialis USM-PSY62

Antarctica is characterized by extreme cold, isolated, and unique ecosystems. Nevertheless, Antarctica harbors diverse species of microorganisms, particularly in its ice-covered lakes and subglacial environments. These microorganisms have special adaptations to extreme cold and low-nutrient conditions. Some extremophiles, like psychrophiles can thrive in these harsh environments. Phenoliferia glacialis USM-PSY62, previously identified as Rhodotorula sp. USM-PSY62 is a psychrophilic yeast isolated from the ice brine of Antarctica. However, there is very little information on this psychrophilic yeast. This study aims to characterize the P. glacialis USM-PSY62 through the identification of the optimum growth parameters in different media (Yeast Peptone Dextrose, YPD & Yeast Malt, YM), temperature (4°C, 15°C, 20°C) and pH (6, 7, 8, 9) as well as their ability in carbon assimilation and extracellular enzyme production. It has an optimal growth in YPD compared to YM broth media. P. glacialis USM-PSY62 grows optimally at 15°C and pH 7.0. This Antarctic yeast enters the stationary phase on day six of incubation under optimum conditions. It appeared mainly as elongated-shape and oval-shaped with budding formation and was found to produce extracellular enzymes such as protease and amylase in the presence of 2% glucose concentration in YM media. P. glacialis USM-PSY62 also can assimilate various types of carbon sources including raffinose, arabinose, and maltose. Interestingly, the psychrophilic yeast presented growth in media supplemented with Persistent Organic Pollutants (POPs) such as dichlorophenyldichloroethylene (DDE) and polychlorinated biphenyl (PCB). These preliminary findings suggest that P. glacialis USM-PSY62 has tremendous potential for bioremediation application in polluted cold regions, as well as deepening our knowledge of its optimal growth conditions.

Influence of Granular Medium Parameters on Poncelet Drag Coefficient

The Poncelet equation can effectively characterize the resistance of a granular medium to a projectile. However, the determination of the drag coefficient remains challenging. This study aims to explore the potential effects of granular medium parameters on the drag coefficient and to identify key granular medium parameters. Horizontal ballistic tests and quasi-static penetrometer tests were conducted on dry silica sand of four different grain sizes (0.3–0.6 mm, 0.6–2.0 mm, 2.0–4.0 mm and 4.0–8.0 mm). During the ballistic tests, the bulk density of the sand targets was kept consistent, and the entering velocities and the penetration depth of the projectiles were recorded. The bearing strength of the sand targets with different relative densities (30%, 50% and 70%) was measured in the quasi-static tests. Furthermore, two methods were employed to determine the drag coefficients, namely, (1) single-parameter fitting (SF), where the static resistance term was defined as the average bearing strength and the drag coefficients were fitted using the ballistic test data, and (2) two-parameter fitting (TF), where the optimal drag coefficients and bearing strengths were derived from ballistic data. The results showed that the TF method was susceptible to the size effect, differing significantly from the SF method when the projectile diameter was less than 21 times the grain size. The relative density was identified by the SF method as a critical factor affecting the drag coefficient of the granular medium.

Analysis of erosion and sealing characteristics of V-regulating ball valves for coal chemical industry

Purpose This study aims to research the erosion wear characteristics and sealing performance of V-regulating ball valve in coal chemical process pipelines, which provides a theoretical reference for improving its antiwear and sealing performance. Design/methodology/approach Taking the V-regulating ball valve as the research object, based on the computational fluid dynamics and the theory of erosion wear, the authors studied its erosion characteristics under different medium parameters and analyzed the sealing performance under the heat-fluid–solid coupling working condition. Findings The erosion wear mechanism of the valve sealing surface is the simultaneous action of cutting and deformation. When the medium flow velocity, particle mass flow rate and particle size increase, the maximum erosion rate and average erosion rate in the V-regulating valve increase. The inner diameter Mises contact stress of the sealing surface is symmetrically distributed in a “wing shape,” and the contact stress of the outer diameter is distributed in a “butterfly shape.” Due to the superposition of thermal stress and pressure stress in the contact transition zone to produce a significant stress concentration. Practical implications The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry. Social implications V-type regulating ball valve is widely favored by coal chemical enterprises and petrochemical enterprises because of its wide adjustment ratio and good erosion resistance. Originality/value The V-regulating ball valve wear mechanism for cutting and deformation simultaneously, and its wear rate is positively correlated with the medium flow rate, particle mass flow rate and particle size. After the valve is opened, there is a significant stress concentration occurs in the contact transition zone due to the superposition of thermal stress and compressive stress. The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0205/

Physics-guided full waveform inversion using Encoder-Solver convolutional neural networks

Abstract Full Waveform Inversion (FWI) is an inverse problem for estimating the wave velocity distribution in a given domain, based on observed data on the boundaries. The inversion is computationally demanding because we are required to solve multiple forward problems, either in time or frequency domains, to simulate data that are then iteratively fitted to the observed data. We consider FWI in the frequency domain, where the Helmholtz equation is used as a forward model, and its repeated solution is the main computational bottleneck of the inversion process. To ease this cost, we integrate a learning process of an Encoder-Solver preconditioner that is based on convolutional neural networks (CNNs). The Encoder-Solver is trained to effectively precondition the discretized Helmholtz operator given velocity medium parameters. Then, by re-training the CNN between the iterations of the optimization process, the Encoder-Solver is adapted to the iteratively evolving velocity medium as part of the inversion. Without retraining, the performance of the solver deteriorates as the medium changes. Using our light retraining procedures, we obtain the forward simulations effectively throughout the process. We demonstrate our approach to solving FWI problems using 2D geophysical models with high-frequency data.

Enhanced biocatalytic laccase production using agricultural waste in solid-state fermentation by Aspergillus oryzae for p-chlorophenol degradation

Agricultural residues are one of the most cost-effective and readily accessible carbon resources for producing commercially significant enzymes. Several enzymes have been used in different industries like pharmaceuticals, foods, textiles, and dyes that can be generated by various species of microbes found in waste from agriculture. The current research investigated laccase production by Aspergillus oryzae utilizing agricultural wastes. Physical and chemical properties, including pH, temperature, sucrose, yeast extract, and copper sulfate levels, were optimized. The utilization of the response surface methodology along with the centralized composite design method, which assesses multiple media parameters and utilizes a two-level experimental approach, aids in determining the variable and its significance in increasing production quality. The centralized composite design enhancement showed that the optimal conditions for highest laccase activity (623.16 U/mL) were pH 7.0, temperature 25 °C, corn cobs as substrate, sucrose (2.0 %), yeast extract (1.0 %), and copper sulfate (0.1 mM) level. The laccase enzyme was optimized using various pH, temperature, metal ions, and inhibitors combinations. The extracted laccase enzyme maximum activity was attained at pH 6.0 and 40 °C. The inclusion of divalent ions can enhance laccase activity, while the use of various inhibitors decreases laccase activity. Under various pH circumstances, the Aspergillus oryzae laccase enzyme can successfully degrade p-chlorophenol. The present study describes statistically validated optimal methodologies for enhancing laccase synthesis, leading to a laccase production technique that is simultaneously highly efficient and economically profitable, with possible use of p-chlorophenol degradation.

Stirred media mills of fine and ultrafine grinding for subsequent beneficiation operations

This paper presents a brief review of the designs, characteristics, and operating parameters of Stirred media mills supplied by foreign manufacturers. An analysis of information on Stirred media mills , which are used to improve the efficiency of beneficiation and metallurgical operations, is carried out using available publications. The obtained results indicate the inexpediency of using conventional drum ball mills for flotation separation of ores and concentrates with a fine interpenetration of minerals. The application of conventional mills in extraction of ores and concentrates resistant to cyanidation, where gold is finely disseminated in sulfides, is limited by their high power consumption and the corresponding operating costs. In this work, different types of Stirred media mills are considered, including their vertical and horizontal types. The advantages of Stirred media mills over conventional ball mills, particularly in terms of energy efficiency, are noted. The designs and main characteristics of Stirred media mills , which have received wide application, are presented. According to the data presented in the reviewed publications, the main parameters determining the grinding process in such mills are outlined, including the ratio of bead size to mill feed size, density of grinding medium, density of pulp in the mill, volume loading of beads, stirring speed, etc. The conducted analysis of literature data indicated high efficiency of mills based on agitation of grinding media for fine and ultrafine grinding of ores and concentrates in comparison with conventional ball mills. Given that the volume of ores and concentrates resistant to processing by conventional methods is increasing, the application of Stirred media mills is expected become more widespread, thereby increasing the efficiency of subsequent beneficiation and metallurgical operations.

Probing a planet from the subsurface to the atmosphere with infrasound data

The analysis of infrasound waves has a significant potential for retrieving a range of geophysical parameters across various scales, such as atmospheric structures, characteristics of surface and buried sources, and seismic velocity structures. This potential was recently showcased in infrasound studies that illustrated the ability to retrieve Earth's shallow velocities and Mars' near-surface atmospheric winds from remote acoustic observations. Consequently, infrasound is becoming an essential component of planetary missions, providing insights into the interiors and atmospheres of other terrestrial planets in the solar system. However, utilizing infrasound data requires efficient forward wave simulation techniques and an accurate description of waveform sensitivity to source and medium parameters. Even under ideal conditions, many inverse problems associated with infrasound-based probing are inherently ill-posed, necessitating regularization or other approaches to ensure reliable results. In this contribution, we highlight recent seismo-acoustic research findings, addressing atmospheric probing at both smaller and global scales, as well as innovative methods to accelerate infrasonic wave propagation modeling.

Porous material characterization with Bayesian and machine learning method

Two main classes of characterization methods are usually employed for acoustic parameters of porous media, namely the analytical inversion method or the numerical fitting procedure. While analytical inverse methods suffer from a high sensivity to the operator, the numerical fitting methods can lead to non physical sets of parameters. The fitting procedure can be bounded by the analytical inversion. The Bayesian method, which is presented in this work, is the appropriate tool to couple these methods. It enables to carry out a numerical fitting procedure using the analytical inversion as prior estimation while increasing the confidence in the resulting uncertainties. In a second part, machine learning method and data mining are used as an alternative characterization method which could be a good prior estimation for the Bayesian method. Results and performances will be shown for various porous media.

Measuring audible acoustic frequencies parameters of rigid porous media via an innovative impedance tube method - Solving the inverse problem

This study introduces an experimental approach to measuring audible acoustic frequency parameters of a rigid porous medium using an impedance tube. Grounded in the equivalent fluid model, a derivative of Biot's theory, our investigation delves into the propagation of waves within porous media, emphasizing the importance of effective density and dynamic compressibility of the saturated fluid. Our primary focus is on resolving the inverse problem by minimizing both experimental and theoretical absorption coefficient expressions within the audible frequency range. Concurrently, we determine four pivotal parameters: viscous and thermal permeability, the inertia factor introduced by Norris, and the thermal tortuosity introduced by Lafarge. The outcomes include a comparative analysis between experimental and simulated absorption coefficients, leveraging optimized parameters, across two distinct polyurethane foam samples.

Modeling of Electric MHD Flow of Nanoparticles in a CMC-Water Based Casson Hybrid Nanofluid over a Porous Medium

The principal focus of this exploration is to study the computationally simulate the combined convection of CMC-water-based Casson hybrid nanofluid through a stretching sheet with electric magnetic force in a porous medium. Copper (Cu) and Silver (Ag) nanoparticles are included to enhance the heat transfer performance of CMC-water. The physical problem is formulated with mathematical PDEs, and to solve this, initially we used similarity transformation technique to reduce the PDEs into ODEs, then Runge-Kutta Fehlberg method (RKFM) of order four with shooting technique is adopted for further reduction from the non-linear ODEs to first order DEs. The influence of key parameters such as the magnetic field parameter (M), porous medium parameters (K), electric field factor (E), radiation parameter (Nr), permeability parameter (λ), Casson parameter (β), and Eckert number (Ec) on relevant physical quantities is illustrated through tables and graphical visualizations. The impact of these parameters on velocity and temperature profiles, as well as on the skin friction coefficient and Nusselt number of the nanofluid, is observed. Our results indicate that an increase in the Casson parameter values leads to a decrease in the velocity of the host fluid in the case of opposite flow, and a similar behavior is observed with the nanoparticle porous medium parameter (K) in the case of assisting flow. Furthermore, the use of the Runge-Kutta Fehlberg Method (RKFM) is found to be more accurate and reliable in dealing with the problem studied in this work.