A computational fluid dynamics analysis on Fe3O4-H2O based nanofluid axisymmetric flow over a rotating disk with heat transfer enhancement

Four-stage Lobatto analysis on 3D magneto-hydrodynamic radiative non-newtonian nanofluid flow and heat transportation over a stretchable surface under Brownian motion and thermophorsis impact

Viscous dissipation and thermal radiation are essential in governing the dynamics of boundary layer flow, particularly in high-temperature engineering systems such as gas turbines, combustion engines, and industrial furnaces. Thermal radiation emerges as a primary factor of heat transfer under such conditions, while viscous dissipation contributes to the transformation of kinetic energy into thermal energy through internal frictional forces within the fluid. The present study investigates the three dimensional magneto-hydrodynamic (MHD) flow of a radiative Eyring-Powell nanofluid towards a stretchable, porous surface. The governing equations, initially formulated as partial differential equations (PDEs), are reduced to a set of coupled ordinary differential equations (ODEs) through similarity transformations. These transformed equations are numerically solved using MATLAB bvp5c solver. A detailed parametric analysis is performed to examine the impact of key dimensionless quantities, including slip parameter, Lewis number, Eckert number, thermophoresis parameter, magnetic field strength and Brownian motion parameter, on velocity profile, temperature profile and concentration distributions. The analysis reveals that the fluid velocity decreases with an increase in the magnetic field strength, whereas it exhibits an increasing trend with higher values of the Eyring-Powell fluid parameter. This paper convers the following key points:•Modeled the dynamical flow equation for hybrid Eyring-Powell nanofluid.•Analyzed the magnetic force impact on the velocity curve.•Graphical interpretations are presented, highlighting the effects of physical parameters.

Mixed and forced convection heat transfer and pressure drop in inclined tube with twisted tape in transition flow

Understanding the influence of angular orientation on mixed convection heat transfer and pressure drop in circular tubes with swirl generators is crucial for optimizing thermal performance in various engineering applications, including heat exchangers and energy systems. This study aims to investigate the impact of angular orientation on heat transfer enhancement and pressure drop characteristics in a uniformly heated circular tube equipped with a twisted-tape longitudinal swirl generator. An experimental approach was employed, varying key parameters such as Reynolds number (435-10,130), heat flux (2, 3, and 4 kW/m²), twist ratio (P/D = 3, 4, and 5), and angular orientation (15° and 30°). The setup was validated against established correlations for Nusselt number and friction factor, demonstrating strong agreement. The results reveal that angular orientation significantly affects heat transfer and pressure drop at Reynolds numbers up to ~ 1000, where mixed convection plays a dominant role. Beyond this, forced convection prevails. In a plain channel, the transition from laminar to transitional flow occurs at Reynolds numbers of 2924-4088 for a 15° angle of inclination (AoI) and 3001-4274 for a 30° AoI, with the transition occurring slightly earlier at the lower angle. The Richardson number varied from 2.5 in the low laminar regime to 0.0087 in the turbulent regime, with additional variations observed when turbulators were introduced.

Mixed convective nanofluid flow and heat transfer induced by a stretchable rotating disk in porous medium

Enhancement of “heat transfer” using “nanofluid” has diverse potential applications in heat exchangers, thermal management of electric devices, cooling of tractors, solar thermal systems, manufacturing of paper, and many others. Hence, the aim of the current investigation is to explore the impacts of “mixed convection” on “nanofluid flow” over a permeable rotating disk, which is stretched radially in a porous medium. Variable wall “temperature” and “convective boundary conditions” are also considered here. This makes the present investigation different from others. The suitable “similarity transformations” are imposed to alter the governing partial differential equations into a set of coupled ordinary differential equations (ODEs). Then, these ODEs are solved numerically by the “4th order Runge‐Kutta method” using the “shooting technique” with the help of the bvp4c package in MATLAB software. The effects of fluid controlling “parameters” on “flow and thermal fields” as well as “skin friction coefficient” and “Nusselt number” are presented graphically and explained physically. Due to enhanced rotation of the disk, the radial and azimuthal velocity of the fluid increase and the temperature of the fluid decreases. Most importantly, it is observed that when the disk rotates faster than the stretching rate, the temperature of the nanofluid decreases rapidly, which has wider applications for cooling purposes. It is also noted that when the suction parameter increases its value from −1 to 1, for Ag–water nanofluid, the “skin friction coefficient” decreases by 73.56%, and the Nusselt number also decreases by 24.11%, and for Fe3O4–water nanofluids, the “skin friction coefficient” decreases by 71.25% and the Nusselt number decreases by 24.47%.

Thermal and flow dynamics of an inclined air heat exchanger equipped with spring turbulators in the transition flow regime

The research involves an experimental investigation into the performance of a flow assisting air heat exchanger under varying angular orientation and uniform external heat fluxes without and with spring turbulators. The investigation was performed for Reynolds numbers ranging from 511 to 9676 and inclination angle 15° and 30°. Three heat fluxes (2, 3, and 4 kW/m2) were applied to the test section to investigate the effect of external surface heating on the range of transition flow regime and thermohydraulic performance. Transition from laminar to turbulent flow for plain channel at different heat fluxes and inclinations occurs within specific Reynolds number ranges: 2436-4446 for 15° inclination at 4 kW/m2, 2574-4289 at 3 kW/m2, and 2850-4152 at 2 kW/m2; for 30° inclination, the ranges are 2518-4151, 2712-4361, and 2992-4346 at the respective heat fluxes. When it comes to the effect of inclination on Nusselt number, the transition occurs sooner at lower angles, but is delayed as the angle increases. Additionally, the Nusselt number decreases as the angle of inclination increases. When comparing the Nusselt numbers of plain tubes to those with spring turbulators, the latter shows a significantly greater enhancement. In laminar flow, a maximum 100% deviation exists between highest and lowest friction factors, decreasing to 75% with increasing Reynolds number; all insert configurations exhibit highest friction factor at 15° due to stronger buoyancy forces.

Simulation and Optimization: A New Direction in Supercritical Technology Based Nanomedicine

In recent years, nanomedicines prepared using supercritical technology have garnered widespread research attention due to their inherent attributes, including structural stability, high bioavailability, and commendable safety profiles. The preparation of these nanomedicines relies upon drug solubility and mixing efficiency within supercritical fluids (SCFs). Solubility is closely intertwined with operational parameters such as temperature and pressure while mixing efficiency is influenced not only by operational conditions but also by the shape and dimensions of the nozzle. Due to the special conditions of supercriticality, these parameters are difficult to measure directly, thus presenting significant challenges for the preparation and optimization of nanomedicines. Mathematical models can, to a certain extent, prognosticate solubility, while simulation models can visualize mixing efficiency during experimental procedures, offering novel avenues for advancing supercritical nanomedicines. Consequently, within the framework of this endeavor, we embark on an extensive review encompassing the application of mathematical models, artificial intelligence (AI) methodologies, and computational fluid dynamics (CFD) techniques within the medical domain of supercritical technology. We undertake the synthesis and discourse of methodologies for calculating drug solubility in SCFs, as well as the influence of operational conditions and experimental apparatus upon the outcomes of nanomedicine preparation using supercritical technology. Through this comprehensive review, we elucidate the implementation procedures and commonly employed models of diverse methodologies, juxtaposing the merits and demerits of these models. Furthermore, we assert the dependability of employing models to compute drug solubility in SCFs and simulate the experimental processes, with the capability to serve as valuable tools for aiding and optimizing experiments, as well as providing guidance in the selection of appropriate operational conditions. This, in turn, fosters innovative avenues for the development of supercritical pharmaceuticals.

A novel hermit crab optimization algorithm

High-dimensional optimization has numerous potential applications in both academia and industry. It is a major challenge for optimization algorithms to generate very accurate solutions in high-dimensional search spaces. However, traditional search tools are prone to dimensional catastrophes and local optima, thus failing to provide high-precision results. To solve these problems, a novel hermit crab optimization algorithm (the HCOA) is introduced in this paper. Inspired by the group behaviour of hermit crabs, the HCOA combines the optimal search and historical path search to balance the depth and breadth searches. In the experimental section of the paper, the HCOA competes with 5 well-known metaheuristic algorithms in the CEC2017 benchmark functions, which contain 29 functions, with 23 of these ranking first. The state of work BPSO-CM is also chosen to compare with the HCOA, and the competition shows that the HCOA has a better performance in the 100-dimensional test of the CEC2017 benchmark functions. All the experimental results demonstrate that the HCOA presents highly accurate and robust results for high-dimensional optimization problems.

Comparative study of ternary hybrid nanofluids with role of thermal radiation and Cattaneo-Christov heat flux between double rotating disks

Heat and mass transfer are crucial to numerous technical and commercial operations, including air conditioning, machinery power collectors, crop damage, processing food, heat transfer mechanisms, and cooling, among numerous others. The fundamental purpose of this research is to use the Cattaneo-Christov heat flux model to disclose an MHD flow of ternary hybrid nanofluid through double discs. The results of a heat source and a magnetic field are therefore included in a system of PDEs that model the occurrences. These are transformed into an ODE system using similarity replacements. The first-order differential equations that emerge are then handled using the computational technique Bvp4c shooting scheme. The Bvp4c function in MATLAB is used to numerically solve the governing equations. The influence of the key important factors on velocity, temperature, nanoparticles concentration, and is illustrated visually. Furthermore, increasing the volume fraction of nanoparticles improves thermal conduction, increasing the heat transfer rate at the top disc. The graph indicates that a slight increase in melting parameter rapidly declines the velocity distribution profile of nanofluid. The temperature profile was boosted due to the growing outcomes of the Prandtl number. The increasing variations of the thermal relaxation parameter decline the thermal distribution profile. Furthermore, for some exceptional instances, the obtained numerical answers were compared to previously disclosed data, yielding a satisfactory compromise. We believe that this discovery will have far-reaching ramifications in engineering, medicine, and the field of biomedical technology. Additionally, this model can be used to examine biological mechanisms, surgical techniques, nano-pharmacological drug delivery systems, and the therapy of diseases like cholesterol using nanotechnology.

An efficient quantum partial differential equation solver with chebyshev points

Differential equations are the foundation of mathematical models representing the universe's physics. Hence, it is significant to solve partial and ordinary differential equations, such as Navier-Stokes, heat transfer, convection-diffusion, and wave equations, to model, calculate and simulate the underlying complex physical processes. However, it is challenging to solve coupled nonlinear high dimensional partial differential equations in classical computers because of the vast amount of required resources and time. Quantum computation is one of the most promising methods that enable simulations of more complex problems. One solver developed for quantum computers is the quantum partial differential equation (PDE) solver, which uses the quantum amplitude estimation algorithm (QAEA). This paper proposes an efficient implementation of the QAEA by utilizing Chebyshev points for numerical integration to design robust quantum PDE solvers. A generic ordinary differential equation, a heat equation, and a convection-diffusion equation are solved. The solutions are compared with the available data to demonstrate the effectiveness of the proposed approach. We show that the proposed implementation provides a two-order accuracy increase with a significant reduction in solution time.