Predicting the thermal distribution in a convective wavy fin using a novel training physics-informed neural network method.

Fins are widely used in many industrial applications, including heat exchangers. They benefit from a relatively economical design cost, are lightweight, and are quite miniature. Thus, this study investigates the influence of a wavy fin structure subjected to convective effects with internal heat generation. The thermal distribution, considered a steady condition in one dimension, is described by a unique implementation of a physics-informed neural network (PINN) as part of machine-learning intelligent strategies for analyzing heat transfer in a convective wavy fin. This novel research explores the use of PINNs to examine the effect of the nonlinearity of temperature equation and boundary conditions by altering the hyperparameters of the architecture. The non-linear ordinary differential equation (ODE) involved with heat transfer is reduced into a dimensionless form utilizing the non-dimensional variables to simplify the problem. Furthermore, Runge-Kutta Fehlberg's fourth-fifth order (RKF-45) approach is implemented to evaluate the simplified equations numerically. To predict the wavy fin's heat transfer properties, an advanced neural network model is created without using a traditional data-driven approach, the ability to solve ODEs explicitly by incorporating a mean squared error-based loss function. The obtained results divulge that an increase in the thermal conductivity variable upsurges the thermal distribution. In contrast, a decrease in temperature profile is caused due to the augmentation in the convective-conductive variable values.

Impact of solid-fluid interfacial layer and nanoparticle diameter on Maxwell nanofluid flow subjected to variable thermal conductivity and uniform magnetic field.

The utilization of Maxwell fluid with nanoparticle suspension exhibits promising prospects in enhancing the efficacy of energy conversion and storage mechanisms. They have the potential to be utilized in sophisticated cooling systems for power generation facilities, thereby augmenting the overall energy efficacy. Keeping this in mind, the current research examines the Maxwell nanofluid flow over a rotating disk with the impact of a heat source/sink. The present study centers on the examination of flow characteristics in the existence of a uniform magnetic field. The conversion of governing equations into ordinary differential equations is achieved using appropriate similarity variables. To derive the Nusselt number (Nu) and skin friction (SF) model related to the flow and temperature parameters, the suggested back-propagation artificial neural networking (ANN) technique is used. The Runge-Kutta-Fehlberg fourth-fifth order (RKF-45) method is used to solve the reduced equations and produce the necessary data to create the Nu and SF model. Both the Nu and SF models require 1000 data for training the network, respectively. Graphs are utilized to communicate numerical outcomes. The results concluded that the upsurge in magnetic parameter drops the velocity profile but advances the heat transport. Rise in the thermal conductivity parameter, increases the heat transport.

Heat transfer analysis in magnetohydrodynamic nanofluid flow induced by a rotating rough disk with non-Fourier heat flux: aspects of modified Maxwell-Bruggeman and Krieger-Dougherty models.

Non-Newtonian fluids have unique heat transfer properties compared to Newtonian fluids. The present study examines the flow of a Maxwell nanofluid across a rotating rough disk under the effect of a magnetic field. Furthermore, the Cattaneo-Christov heat flux model is adopted to explore heat transport features. In addition, a comparison of fluid flow without and with aggregation is performed. Using similarity variables, the governing partial differential equations are transformed into a system of ordinary differential equations, and this system is then solved by employing the Runge-Kutta Fehlberg fourth-fifth order method to obtain the numerical solution. Graphical depictions are used to examine the notable effects of various parameters on velocity and thermal profiles. The results reveal that an increase in the value of Deborah number decreases the velocity profile. An increase in the thermal relaxation time parameter decreases the thermal profile. An artificial neural network is employed to calculate the rate of heat transfer and surface drag force. The R values for skin friction and Nusselt number were computed. The results demonstrate that artificial neural networks accurately predicted skin friction and Nusselt number values.

Exploration of the effects of Coriolis force and thermal radiation on water-based hybrid nanofluid flow over an exponentially stretching plate.

Hybrid nanofluids' enhanced thermophysical properties make them applicable in a plethora of mechanical and engineering applications requiring augmented heat transfer. The present study focuses on a three-dimensional Copper-Aluminium Oxide [Formula: see text]-water based hybrid nanofluid flow within the boundary layer with heat transfer over a rotating exponentially stretching plate, subjected to an inclined magnetic field. The sheet rotates at an angular velocity [Formula: see text] and the angle of inclination of the magnetic field is [Formula: see text]. Employing a set of appropriate similarity transformation reduces the governing PDEs to ODEs. The resulting ODEs are solved with the finite difference code with Shooting Technique. Primary velocity increases at large rotation but the secondary velocity reduces as the rotation increases. In addition, the magnetic field is found to oppose the flow and thereby causing a reduction in both the primary and secondary velocities. Increasing the volume fraction reduces the skin friction coefficient and enhances the heat transfer rate.

The minimality of mean square error in chirp approximation using fractional fourier series and fractional fourier transform.

Chirps are familiar in nature, have a built-in resistance to noise and interference, and are connected to a wide range of highly oscillatory processes. Detecting chirp oscillating patterns by traditional Fourier series is challenging because the chirp frequencies constantly change over time. Estimating such types of functions considering the partial sums of a Fourier series in Fourier analysis does not permit an approximate solution, which entails more Fourier coefficients required for signal reconstruction. The standard Fourier series, therefore, has a poor convergence rate and is an inadequate approximation. In this study, we use a parameterized orthonormal basis with an adjustable parameter to match the oscillating behavior of the chirp to approximate linear chirps using the partial sums of a generalized Fourier series known as fractional Fourier series, which gives the best approximation with only a small number of fractional Fourier coefficients. We used the fractional Fourier transform to compute the fractional Fourier coefficients at sample points. Additionally, we discover that the fractional parameter has the best value at which fractional Fourier coefficients of zero degrees have the most considerable magnitude, leading to the rapid decline of fractional Fourier coefficients of high degrees. Furthermore, fractional Fourier series approximation with optimal fractional parameters provides the minimum mean square error over the fractional Fourier parameter domain.

Oral Toxicity Study for Salmonella Killing Lytic Bacteriophage NINP13076 in BALB/c Mice and Its Effect on Probiotic Microbiota.

Viruses that infect bacteria are emerging as attractive biocontrol agents and biopreservatives for foods. Since these bacteriophages kill the target pathogens by lysis and are also consumed along with food, it is essential to evaluate their collateral toxicity on the probiotic gut microbiota. In this study, we examined the acute oral toxicity of a Salmonella phage isolated from sewage in mice. Acute oral administration of the Salmonella phage for five consecutive days did not show any significant pathological changes in the vital organs like lung, kidneys, heart, liver, and intestine. In addition, growth of typical probiotic microbiota remained unaffected even after incubation up to 24 h with the Salmonella phage. The results of this study clearly showed that oral administration of the lytic Salmonella phage did not have any significant adverse effects on the animals, may not harm the probiotic gut microbiota, and are likely to be safe for use in food preservation.

Numerical study of bio-convection flow of magneto-cross nanofluid containing gyrotactic microorganisms with activation energy.

In this study, a mathematical model is developed to scrutinize the transient magnetic flow of Cross nanoliquid past a stretching sheet with thermal radiation effects. Binary chemical reactions and heat source/sink effects along with convective boundary condition are also taken into the consideration. Appropriate similarity transformations are utilized to transform partial differential equations (PDE's) into ordinary ones and then numerically tackled by shooting method. The impacts of different emerging parameters on the thermal, concentration, velocity, and micro-rotation profiles are incorporated and discussed in detail by means of graphs. Results reveal that, the escalation in magnetic parameter and Rayleigh number slowdowns the velocity and momentum of the fluid. The increase in Biot number, radiation and heat sink/source parameters upsurges the thermal boundary but, converse trend is seen for escalating Prandtl number. The density number of motile microorganisms acts as a growing function of bioconvection Lewis number and declining function of bioconvection Peclet number.