CONSISTENCY OF THE DRIFT PARAMETERS ESTIMATES IN THE FRACTIONAL BROWNIAN DIFFUSION MODEL AND ESTIMATION OF THE HURST PARAMETER BY MAXIMUM LIKELIHOOD METHOD

In this paper, we study the problem of estimating the unknow parameters in a long memory process based on the maximum likelihood method. We consider again a diffusion model involving fractional Brownian motion. Our goal is to study the consistency of the drift parameter estimates depending on the form of the model.

Electromagnetohydrodynamic peristaltic flow of a couple stress nanofluid through a vertical annulus in the presence of Hall currents and thermal radiation

This paper investigates the electric properties of gold nanoparticles mixed with a convection dielectric couple stress fluid inside a vertical cylindrical tube with moving endoscope in the presence of Hall currents and thermal radiation. Under the long wavelength approximation and the use of appropriate conversion relationships between fixed and moving frame coordinates, the exact solutions have been evaluated for temperature distribution, gold nanoparticles concentration, electrical potential function and nanofluid pressure, while analytical solution is found for the axial velocity using the homotopy analysis method. The results show that the presence of the electric field enhances the effects of Brownian motion parameter, thermophoresis parameter, radiation parameter, Hall currents and wave amplitude ratio on the axial nanofluid velocity, while it was found that its presence reduces the effects of couple stress parameter, thermophoresis diffusion constant and Brownian diffusion constant.

Modified Arrhenius and Thermal Radiation Effects on Three-Dimensional Magnetohydrodynamic Flow of Carbon Nanotubes Nanofluids Over Bi-Directional Stretchable Surface

In the current study, 3D hydro-magnetic flow of CNTs-EG/EO/H2O nanofluids over bi-directional stretchable surface along with linear thermal radiation, modified Arrhenius, thermophoresis and Brownian diffusion are studied. The three base fluids i.e., EG (Ethylene Glycol), EO (Engine Oil) and H2O are considered for the analysis. For computing the effective viscosity and thermal conductivity of nanofluid, Wang’s viscosity model and Hamilton-Crosser’s thermal conductivity model have been used. The system of transformed non-linear ODEs is solved by shooting scheme. The comparison of heat transfer rate in CNTs-EG, CNTs-EO and CNTs-H2O nanofluids is depicted by bar diagrams. The outcomes of the present work showed that MWCNTs based nanofluids have a higher temperature gradient compared to that of SWCNTs based nanofluids. Moreover, temperature distribution corresponding to the engine oil-based nanofluids declined at a very high rate followed by ethylene glycol and water-based nanofluids, respectively.

Thermal Analysis of 3D Electromagnetic Radiative Nanofluid Flow with Suction/Blowing: Darcy–Forchheimer Scheme

This paper discusses the Darcy–Forchheimer three dimensional (3D) flow of a permeable nanofluid through a convectively heated porous extending surface under the influences of the magnetic field and nonlinear radiation. The higher-order chemical reactions with activation energy and heat source (sink) impacts are considered. We integrate the nanofluid model by using Brownian diffusion and thermophoresis. To convert PDEs (partial differential equations) into non-linear ODEs (ordinary differential equations), an effective, self-similar transformation is used. With the fourth–fifth order Runge–Kutta–Fehlberg (RKF45) approach using the shooting technique, the consequent differential system set is numerically solved. The influence of dimensionless parameters on velocity, temperature, and nanoparticle volume fraction profiles is revealed via graphs. Results of nanofluid flow and heat as well as the convective heat transport coefficient, drag force coefficient, and Nusselt and Sherwood numbers under the impact of the studied parameters are discussed and presented through graphs and tables. Numerical simulations show that the increment in activation energy and the order of the chemical reaction boosts the concentration, and the reverse happens with thermal radiation. Applications of such attractive nanofluids include plastic and rubber sheet production, oil production, metalworking processes such as hot rolling, water in reservoirs, melt spinning as a metal forming technique, elastic polymer substances, heat exchangers, emollient production, paints, catalytic reactors, and glass fiber production.

Thermal energy transport in thin film flow of nanofluid over a decelerating rotating disk

The thin film flow in nanotechnology is one of the most modern progresses in the study of thin films. This includes coating with nanocomposite materials, thus providing the materials improved mechanical properties due to a so-called size effect. The ultimate functional properties that can be gained are of high adherence, wear resistance, thermal conductivity, oxidation resistance, higher toughness and hardness. This article studies the transient motion of nanofluid thin film over a disk rotating with angular velocity inversely proportional to the time. The importance of Lorentz force arises due to the axial projection of magnetic flux is studied on thin film flow and heat transfer. Two active mechanisms of nanoparticles, namely thermophoresis and Brownian diffusion, are discussed using Buongiorno model. By adopting a similarity method, the velocity distribution thermal and concentration fields above the rotating disk are simulated numerically and assessed graphically. Numerical illustrations for nanofluid film thickness, skin friction and heat and mass transfer rates are depicted against the impacts of several influential parameters. Results highlight that film thickness reduces with unsteadiness and rotation parameters. The results also spectacle that the involvement of a magnetic beam reduces the velocity of nanofluid film. Further, it is observed that thermophoresis and Brownian motion effects make a better influence in enhancing the heat transfer rate.

Impact of Maxwell velocity slip and Smoluchowski temperature slip on CNTs with modified Fourier theory: Reiner-Philippoff model

The present article presents a novel idea regarding the implementation of Tiwari and Das model on Reiner-Philippoff fluid (RPF) model by considering blood as a base fluid. The Cattaneo-Christov model and thermal radiative flow have been employed to study heat transfer analysis. Tiwari and Das model consider nanoparticles volume fraction for heat transfer enhancement instead of the Buongiorno model which heavily relies on thermophoresis and Brownian diffusion effects for heat transfer analysis. Maxwell velocity and Temperature slip boundary conditions have been employed at the surface of the sheet. By utilizing the suitable transformations, the modeled PDEs (partial-differential equations) are renewed in ODEs (ordinary-differential equations) and treated these equations numerically with the aid of bvp4c technique in MATLAB software. To check the reliability of the proposed scheme a comparison with available literature has been made. Other than Buongiorno nanofluid model no attempt has been made in literature to study the impact of nanoparticles on Reiner-Philippoff fluid model past a stretchable surface. This article fills this gap available in the existing literature by considering novel ideas like the implementation of carbon nanotubes, CCHF, and thermal radiation effects on Reiner-Philippoff fluid past a slippery expandable sheet. Momentum, as well as temperature slip boundary conditions, are never studied and considered before for the case of Reiner-Philippoff fluid past a slippery expandable sheet. In the light of physical effects used in this model, it is observed that heat transfer rate escalates as a result of magnification in thermal radiation parameter which is 18.5% and skin friction coefficient diminishes by the virtue of amplification in the velocity slip parameter and maximum decrement is 67.9%.

Comparative Numerical Study of Thermal Features Analysis between Oldroyd-B Copper and Molybdenum Disulfide Nanoparticles in Engine-Oil-Based Nanofluids Flow

Apart from the Buongiorno model, no effort was ably accomplished in the literature to investigate the effect of nanomaterials on the Oldroyd-B fluid model caused by an extendable sheet. This article introduces an innovative idea regarding the enforcement of the Tiwari and Das fluid model on the Oldroyd-B fluid (OBF) model by considering engine oil as a conventional base fluid. Tiwari and Das’s model takes into account the volume fraction of nanoparticles for heat transport enhancement compared to the Buongiorno model that depends significantly on thermophoresis and Brownian diffusion impacts for heat transport analysis. In this paper, the thermal characteristics of an Oldroyd-B nanofluid are reported. Firstly, the transformation technique is applied on partial differential equations from boundary-layer formulas to produce nonlinear ordinary differential equations. Subsequently, the Keller-box numerical system is utilized to obtain final numerical solutions. Copper engine oil (Cu–EO) and molybdenum disulfide engine oil (MoS2–EO) nanofluids are considered. From the whole numerical findings and under the same condition, the thermodynamic performance of MoS2–EO nanofluid is higher than that of Cu–EO nanofluid. The thermal efficiency of Cu–EO over MoS2–EO is observed between 1.9% and 43%. In addition, the role of the porous media parameter is to reduce the heat transport rate and to enhance the velocity variation. Finally, the impact of the numbers of Reynolds and Brinkman is to increase the entropy.

Pore Forming Protein Induced Biomembrane Reorganization and Dynamics: A Focused Review

Pore forming proteins are a broad class of pathogenic proteins secreted by organisms as virulence factors due to their ability to form pores on the target cell membrane. Bacterial pore forming toxins (PFTs) belong to a subclass of pore forming proteins widely implicated in bacterial infections. Although the action of PFTs on target cells have been widely investigated, the underlying membrane response of lipids during membrane binding and pore formation has received less attention. With the advent of superresolution microscopy as well as the ability to carry out molecular dynamics (MD) simulations of the large protein membrane assemblies, novel microscopic insights on the pore forming mechanism have emerged over the last decade. In this review, we focus primarily on results collated in our laboratory which probe dynamic lipid reorganization induced in the plasma membrane during various stages of pore formation by two archetypal bacterial PFTs, cytolysin A (ClyA), an α-toxin and listeriolysin O (LLO), a β-toxin. The extent of lipid perturbation is dependent on both the secondary structure of the membrane inserted motifs of pore complex as well as the topological variations of the pore complex. Using confocal and superresolution stimulated emission depletion (STED) fluorescence correlation spectroscopy (FCS) and MD simulations, lipid diffusion, cholesterol reorganization and deviations from Brownian diffusion are correlated with the oligomeric state of the membrane bound protein as well as the underlying membrane composition. Deviations from free diffusion are typically observed at length scales below ∼130 nm to reveal the presence of local dynamical heterogeneities that emerge at the nanoscale—driven in part by preferential protein binding to cholesterol and domains present in the lipid membrane. Interrogating the lipid dynamics at the nanoscale allows us further differentiate between binding and pore formation of β- and α-PFTs to specific domains in the membrane. The molecular insights gained from the intricate coupling that occurs between proteins and membrane lipids and receptors during pore formation are expected to improve our understanding of the virulent action of PFTs.

Intelligent computing for the dynamics of entropy optimized nanofluidic system under impacts of MHD along thick surface

This article examines entropy production (EP) of magneto-hydrodynamics viscous fluid flow model (MHD-VFFM) subject to a variable thickness surface with heat sink/source effect by utilizing the intelligent computing paradigm via artificial Levenberg–Marquardt back propagated neural networks (ALM-BPNNs). The governing partial differential equations (PDEs) of MHD-VFFM are transformed into ODEs by applying suitable similarity transformations. The reference dataset is obtained from Adam numerical solver by the variation of Hartmann number (Ha), thickness parameter [Formula: see text], power index ([Formula: see text], thermophoresis parameter (Nt), Brinkman number (Br), Lewis number (Le) and Brownian diffusion parameter (Nb) for all scenarios of proposed ALM-BPNN. The reference data samples arbitrary selected for training/testing/validation are used to find and analyze the approximated solutions of proposed ALM-BPNNs as well as comparison with reference results. The excellent performance of ALM-BPNN is consistently endorsed by Mean Squared Error (MSE) convergence curves, regression index and error histogram analysis. Intelligent computing based investigation suggests that the rise in values of Ha declines the velocity of the fluid motion but converse trend is seen for growing values of [Formula: see text]. The rising values of Ha, Nt and Br improve the heat transfer but converse trend is seen for growing values of [Formula: see text]. The inclining values of Nt incline the mass transfer but it shows reverse behavior for escalating values of Le. The inclining values of Br incline the EP.