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This study reports the thermal performance of Al2O3 and TiO2 nanofluids (NFs) flowing inside a compact plate heat exchanger (CPHE) by comparing the experimental and numerical investigations. The NF samples were prepared for five concentrations each of Al2O3 and TiO2 nanoparticles dispersed in distilled water (DW) as a base fluid (BF). The stability of NF samples was ensured, and their viscosity and thermal conductivity were measured. Firstly, the experimental measurements were performed for the heat transfer and fluid flow of the NFs in the plate heat exchanger (PHE) system and then the numerical investigation method was developed for the same PHE dimensions and operation conditions of the experimental investigation. A finite volume method (FVM) and single-phase fluid were used for numerical modelling. The obtained experimental and numerical results show that the thermal performance of the CPHE enhances by adding nanoparticles to the BFs. Furthermore, numerical predictions present lower values of convection heat transfer coefficients than the experimental measurements with a maximum deviation of 12% at the highest flow rate. Nevertheless, the numerical model is suitable with acceptable accuracy for the prediction of NFs through PHE and it becomes better for relatively small particles’ concentrations and low flow rates.

The corrosion behavior of brass in TiO2 and Al2O3 nanofluids using a simulated cooling water (SCW) as the base solution and sodium dodecyl benzene sulfonate (SDBS) as the dispersant was studied by electrochemical measurements and surface analysis in this paper. It was found that SDBS could be adsorbed on the brass surface to form a protective film and have a corrosion inhibition effect on brass in SCW. In the SCW-SDBS-TiO2 nanofluid, some negatively charged TiO2 nanoparticles were attached to the brass surface and no obvious SDBS adsorption film was found, and the SDBS in this nanofluid had almost no corrosion inhibition on brass. In the SCW-SDBS-Al2O3 nanofluid, the brass surface was covered by a uniformly distributed SDBS film containing some Al2O3 nanoparticles which were positively charged, and the corrosion inhibition of brass was significantly improved in this nanofluid. It is concluded that the adsorption of SDBS on the brass surface in nanofluids is related to the charge status of the nanoparticles, which makes brass have different corrosion resistance in various nanofluids.

This study presents an integrated experimental and computational investigation into the thermal and hydraulic performance of three oxide-based nanofluids: aluminum oxide (Al2O3), titanium dioxide (TiO2), and copper oxide (CuO) for advanced engine cooling applications. A custom-built test rig was used to assess nanofluid behavior under varying flow rates, nanoparticle volume fractions, and temperature gradients, replicating realistic engine conditions. According to the results, at ideal concentrations, CuO nanofluids continuously demonstrate better heat transfer properties, outperforming TiO2 by up to 15% and AlO3 by 7%. However, performance plateaus beyond 1.5% volume fraction due to increased viscosity and pressure drop. A multilayer feedforward artificial neural network (ANN) model was developed to predict convective heat transfer coefficients and friction factors based on experimental inputs, achieving a mean absolute percentage error below 5% and a coefficient of determination (R2) exceeding 0.98. The ANN demonstrated robust generalization across varying operating conditions and nanoparticle types, confirming its utility for surrogate modeling and optimization. This work is distinguished by its dual focus on thermal efficiency and hydraulic stability, as well as its use of data-driven modeling validated by empirical results. The findings provide actionable insights for thermal management system design in internal combustion, hybrid, and electric vehicles, where efficient, compact, and reliable cooling solutions are increasingly vital. The study advances the practical application of nanofluids by offering a comparative, ANN-validated framework that bridges the gap between lab-scale performance and real-world automotive cooling demands.

The present study presents a semi-numerical simulation to investigate the flow behaviour and energy transfer of a ternary hybrid nanofluid (THNF) over a stretching surface, accounting for viscous dispersion and thermal radiation. To improve its thermal and rheological performance, the model combines curvature, couple stress, and higher thermal conductivity. This is achieved by suspending three different nanoparticles – Alumina oxide, Ag,TiO2,Al2O3 in a blood non-Newtonian base fluid. The authors reduce the controlling partial differential equation to a system of nonlinear ordinary differential equation via similarity transformations. After that, semi-numerical solutions are obtained using the homotopy analysis method, which provides flexibility in controlling convergence. The impact of several significant parameters on the velocity and energy fields is thoroughly examined, including the couple-stress parameter, nanoparticle volume fractions, radiation, curvature parameter, magneto-hydrodynamics parameter, and Eckert number. The results show that, while pair stress effects tend to lower flow resistance, the addition of ternary hybrid nanoparticles significantly improves heat transfer performance compared to traditional nanofluids. It is also discovered that the thickness of the thermal boundary layer is influenced by the surface’s curvature. These results provide new insights into optimising energy transfer processes in advanced thermal systems using tailored nanofluids.

During the last decade, second law analysis via entropy generation has become important in terms of entropy generation minimization (EGM), thermal engineering system design, irreversibility, and energy saving. In this study, heat transfer and entropy generation characteristics of flows of multi-walled carbon nanotube-based nanofluids were investigated in horizontal minitubes with outer and inner diameters of ~1067 and ~889 µm, respectively. Carbon nanotubes (CNTs) with outer diameter of 10–20 nm and length of 1–2 µm were used for nanofluid preparation, and water was considered as the base fluid. The entropy generation based on the experimental data, a significant parameter in thermal design system, was examined for CNTs/water nanofluids. The change in the entropy generation was only seen at low mass fractions (0.25 wt.% and 0.5 wt.%). Moreover, to have more insight on the entropy generation of nanofluids based on the experimental data, a further analysis was performed on Al2O3 and TiO2 nanoparticles/water nanofluids from the experimental database of the previous study of the authors. The corresponding results disclosed a remarkable increase in the entropy generation rate when Al2O3 and TiO2 nanoparticles were added to the base fluid.