Search

This paper introduces a novel empirical correlation designed to predict the overall heat transfer coefficient (U) in concentric tube heat exchangers. The study utilizes a comprehensive dataset of 2700 data points from CFD simulations, examining the impact of critical variables including hot and cold fluid Reynolds numbers (Reh, Rec), Prandtl numbers (Prh, Prc), and heat exchanger dimensions (tube hydraulic diameter Dh, annular space hydraulic diameter Dc, and overall length L). The analysis incorporates a range of fluid combinations in the tube and annular sections – air–air, air–water, water-air, and water–water – across Reynolds number ranges from 1000 to 20000, covering both laminar and turbulent flow regimes. The correlation was developed using the Adam optimizer to minimize the Weighted Mean Squared Error (WMSE), achieving an impressive convergence to an average prediction error of 6.7% compared to actual U values. The model categorizes flow into four distinct categories, each corresponding to a combination of flow patterns in the tube and annular spaces regimes – Laminar–Laminar, Laminar–Turbulent, Turbulent–Laminar, and Turbulent–Turbulent – integrating both hydrodynamic and thermal entry effects to enhance prediction accuracy. Rigorous error analysis revealed a median error of 5.18%, substantially outperforming existing models. Notably, 10% of the predictions deviate by less than 1%, with 90th percentile errors staying below 15%. Parameters were finely tuned through extensive numerical simulations, ensuring accurate application of the correlation across diverse operational conditions. The study concludes by highlighting the model’s potential to significantly enhance the design and efficiency of heat exchangers and proposes future enhancements to further improve its predictive accuracy.

A microplate heat exchanger is one of the most compact types of heat exchanger used for cooling systems, and not much research was carried out to study the performance of this type of heat exchanger with hybrid nanofluids. In this regard, the performance analysis of the microplate heat exchanger is carried out by estimating the convective heat transfer coefficient in terms of Nusselt number using a hybrid nanofluid. In current research work, Microplate heat exchangers tested using TiO2/ethylene glycol, ZnO/ethylene glycol nanofluids, and a hybrid nanofluid with varied nanoparticle volume fractions. Based on the results, it was found that the thermal conductivity of hybrid nanofluids and the overall heat transfer coefficient by applying hybrid nanofluids show better enhancement than nanofluids. The maximum thermal conductivity ratio between the hybrid nanofluid and the base fluid is 2.10. The maximum Nusselt number of 35.8 was observed for hybrid (TiO2–ZnO/ethylene glycol) at 50 °C and a volume fraction of 4%.

The helical coil heat exchanger (HCHX) is one of the most popular heat transfer devices in heat pump water heaters. In this study, the Computational Fluid Dynamics (CFD) software, ANSYS FLUENT, was employed to predict the thermohydraulic performance of an HCHX, including the overall heat transfer coefficient and Fanning friction factor. Using different sizes of the HCHX, comparing the CFD results with experimental data or correlations available in the literature revealed that both results on thermohydraulic performance agreed well. The objective of this study was to choose the Taguchi method coupled with grey relational analysis (GRA) to optimize the HCHX design with the improvement of thermohydraulic performance. Among the selected three factors in the optimization process, it was found that the coil pitch and coil diameter were the two most important factors in influencing the thermohydraulic performance of HCHXs, while the outer diameter of the helical tube had little impact. Consequently, the optimal design of the HCHX increased the overall heat transfer coefficient by 131% and decreased the friction fanning factor by 6%, resulting in the increase of heat transfer rate by 47% and the reduction of pumping work by 72%. Moreover, the predicted optimal thermohydraulic performance was verified by the predictive formula of the Taguchi method.

Controlling heat transfer and managing heat flows in a building has become very important in recent years and is essential to ensure the thermal comfort of occupants, increase energy efficiency, and sustainable development. These measures reduce energy consumption in buildings, save resources and money and at the same time reduce pollution and CO2 emissions into the atmosphere, as the severity of the climate increases. The paper describes the analytical method used to analyse the one-dimensional, steady-state heat transfer through homogeneous walls and composite walls of buildings (wall structure may contain different construction materials, air spaces, insulation, etc.). The web application allows users to analyse one-dimensional and steady-state heat transfer through the building walls and calculate the heat flux density, total heat flux, overall heat transfer coefficient of the building wall, thermal resistance, temperature profile through the wall, the specific thermal resistances and the temperatures at the interface between wall layers. The user can analyse the one-dimensional, steady-state heat transfer through homogeneous and multilayer walls of buildings, being able to analyse a wall composed of a single layer, or one with a maximum of seven layers. The application allows the user, after defining the cross section’s geometry, materials properties, and boundary conditions, to determine the optimal insulation thickness, depending on its placement, on the inner or outer wall surface.

Prediction of heat exchangers performance is primordial in the world of machine design especially when the industrial environment becomes demanding in terms of size reducing or price lowering. The most common adopted procedure for this kind of investigation is defining the exchanger's overall heat transfer coefficient with a purely empiric way using interpolations and mathematical operations missing physical senses in the modeling. The present work offers a first step in theoretically modeling the heat transfer coefficient and presents a semi-empirical method which allows expressing the latter in function of the Reynolds' numbers of the fluids' flows when the variations of the Prandtl numbers of the two fluids are small. The method consists in an iterative technique based on a single test approach and allows the prediction of the heat exchanger performance for a large range of flowrates. Experimental validation of the method is performed for a cross-flow heat exchanger with water and air as working fluids, showing a relative error less than 1.6%. The relative error of the mathematical methods applied is less than 1.7%.

This work presents a case study of thermodynamic performance of a condenser used in a 210 MW thermal power station at Mejia in West Bengal, India. The analysis involves an improvement of actual overall heat transfer coefficient by varying tube materials and fouling resistance. Exergy Destruction Factor (EDF) is introduced to quantify the percentage of exergy loss from the condenser wall. From this study, it is revealed that the second law performance of the condenser increases with the increase in thermal conductivity of the tube materials, decreases with the increase in fouling resistance and decreases with the increase in condenser pressure at the turbine outlet. The actual overall heat transfer coefficient can be increased up to 6% by selecting better conducting tube materials. While the EDF decreases with the increase in cooling water temperature rise and increases with the increase in cooling water inlet temperature, EDF is found to decrease with the increased cooling water mass flow rate.

Aimed at biggish prediction error of the overall heat transfer coefficient caused by running parameters fluctuations, analyze the correlations between various elements including outlet oil temperature, oil physical properties, flow rate, environmental temperature, wax deposition rate as well as running time after pigging and the overall heat transfer coefficient. And four dimensionless number determining the laws of overall heat transfer coefficient was put forward. Simplified model came in the use of collinearity diagnosis theory and dimensionless experimental analysis, followed by determining the optimal functional form of prediction model and physical meaning for each dimensionless numbers, then establish a new prediction model. Prediction of the overall heat transfer coefficient for several pipelines came after applying Ten-fold Cross Validation to solve the model. The results showed that, compared with back calculation, the error of overall heat transfer coefficient reduces by 3.62%, and average relative error of end-point temperature lowers by 2.88%. The model is of good steadiness and generalization, and better characterization on heat transfer mechanism of overall heat transfer coefficient, to some degree, solving the biggish prediction error led by running parameters fluctuations.