Thermo-Bioconvection in a Square Porous Cavity Filled by Oxytactic Microorganisms

Magneto-hydrothermal triple-convection in a W-shaped porous cavity containing oxytactic bacteria

Bioconvective heat and mass transport phenomena have recently been the subject of interest in diverse fields of applications pertaining to the motion of fluids and their thermophysical properties. The transport processes in a system involving triple convective phenomena, irregular geometry, and boundary conditions constitute a complex phenomenon. This work aims to explore the mixed thermo-bioconvection of magnetically susceptible fluid containing copper nanoparticles and oxytactic bacteria in a novel W-shaped porous cavity. The buoyant convention is generated due to the isothermal heating at the wavy bottom wall, whereas the mixed convection is induced due to the shearing motion of the top-cooled sliding wall. Furthermore, the bioconvection is induced due to the manifestation of oxytactic bacteria or organisms. The inclined sidewalls are insulated. The geometry is packed with water based Cu nanoparticle mixed porous structure, which is subjected to a magnetizing field acted horizontally. The complex transport equations are transformed into nondimensional forms, which are then computed using the finite volume-based developed code. The coupled triple-convective flow physics are explored for a wide range of involved controlling parameters, which could provide helpful insight to the system designer for its proper operation. The shape of geometry can be considered one of the important parameters to control the heat and mass transport phenomena. In general, the influence of amplitude (δ) is more compared to the waviness number (m) of the undulations. The magnitude of heat (Nu) and mass (Sh) transfer rate for the W-shaped cavity is high compared to conventional square and trapezoidal-shaped cavities. The output of the analysis could be very helpful for the designer for modeling devices operating on nanotechnology-based bioconvection, microbial fuel cells, and others.

Estimating Relaxation Time and Fractionality Order Parameters in Fractional Non-Fourier Heat Conduction Using Conjugate Gradient Inverse Approach in Single and Three-Layer Skin Tissues

In this work, the relaxation parameter (τ) and fractionality order (α) in the fractional single phase lag (FSPL) non-Fourier heat conduction model are estimated by employing the conjugate gradient inverse method (CGIM). Two different physics of skin tissue are chosen as the studied cases; single and three-layer skin tissues. Single-layer skin is exposed to laser radiation having the constant heat flux of Qin. However, a heat pulse with constant temperature is imposed on the three-layer skin. The required inputs for the inverse problem in the fractional diffusion equation are chosen from the outcomes of the dual phase lag (DPL) theory. The governing equations are solved numerically by utilizing implicit approaches. The results of this study showed the efficiency of the CGIM to estimate the unknown parameters in the FSPL model. In fact, obtained numerical results of the CGIM are in excellent compatibility with the FSPL model.

Prediction of Nanofluid Characteristics and Flow Pattern on Artificial Differential Evolution Learning Nodes and Fuzzy Framework

A combination of a fuzzy inference system (FIS) and a differential evolution (DE) algorithm, known as the differential evolution-based fuzzy inference system (DEFIS), is developed for the prediction of natural heat transfer in Cu-water nanofluid within a cavity. In the development of the hybrid model, the DE algorithm is used for the training process of FIS. For this purpose, first, the case study is simulated using the computational fluid dynamic (CFD) method. The CFD outputs, including velocity in the y-direction, the temperature of the nanofluid, and the nanoparticle content (Ø), are employed for the learning process of the DEFIS model. By choosing the optimum number of inputs and the number of population, the underlying DEFIS variable parameters are studied. After reaching the high value of DEFIS intelligence, in the learning step, a variety of Ø values (e.g., 0.5, 1, and 2) are reviewed. For the full intelligence of DEFIS, the velocity of the nanofluid is predicted in further nodes of the cavity domain. Finally, the velocity of the nanofluid is predicted by using the data at Ø = 0.15, which are absent in the DEFIS process.

Utilization of Second Order Slip, Activation Energy and Viscous Dissipation Consequences in Thermally Developed Flow of Third Grade Nanofluid with Gyrotactic Microorganisms

In recent decades, an interest has been developed towards the thermal consequences of nanofluid because of utilization of nano-materials to improve the thermal conductivity of traditional liquid and subsequently enhance the heat transportation phenomenon. Following this primarily concept, this current work investigates the thermal developed flow of third-grade nanofluid configured by a stretched surface with additional features of activation energy, viscous dissipation and second-order slip. Buongiorno’s nanofluid model is used to explore the thermophoresis and Brownian motion features based on symmetry fundamentals. It is further assumed that the nanoparticles contain gyrotactic microorganisms, which are associated with the most fascination bioconvection phenomenon. The flow problem owing to the partial differential equations is renovated into dimensional form, which is numerically simulated with the help of bvp4c, by using MATLAB software. The aspects of various physical parameters associated to the current analysis are graphically examined against nanoparticles’ velocity, temperature, concentration and gyrotactic microorganisms’ density distributions. Further, the objective of local Nusselt number, local Sherwood number and motile density number are achieved numerically with variation of various parameters. The results presented here may find valuable engineering applications, like cooling liquid metals, solar systems, power production, solar energy, thermal extrusion systems cooling of machine equipment, transformer oil and microelectronics. Further, flow of nanoparticles containing gyrotactic microorganisms has interesting applications in microbial fuel cells, microfluidic devices, bio-technology and enzyme biosensors.

Stagnation Point Flow with Time-Dependent Bionanofluid Past a Sheet: Richardson Extrapolation Technique

The study of laminar flow of heat and mass transfer over a moving surface in bionanofluid is of considerable interest because of its importance for industrial and technological processes such as fabrication of bio-nano materials and thermally enhanced media for bio-inspired fuel cells. Hence, the present work deals with the unsteady bionanofluid flow, heat and mass transfer past an impermeable stretching/shrinking sheet. The appropriate similarity solutions transform the boundary layer equations with three independent variables to a system of ordinary differential equations with one independent variable. The finite difference coupled with the Richardson extrapolation technique in the Maple software solves the reduced system, numerically. The rate of heat transfer is found to be higher when the flow is decelerated past a stretching sheet. It is understood that the state of shrinking sheet limits the rate of heat transfer and the density of the motile microorganisms in the stagnation region.