Explore the vast range of titles available.

The performance of heat exchangers is severely limited by airside thermal resistance. The effect of redirection louvers (RLs) on the airside thermal performance of a compact flat-tube louvered fin heat exchanger was investigated. A steady-state 3D numerical analysis was conducted for different fin configurations by varying the number of RLs (NRL = 1, 2, 3, and 5). Conjugate heat transfer analysis was performed at the low Re (50–450) for domestic and transport air-conditioning applications. Geometric parameters such as louver pitch, louver angle, fin pitch, and flow depth were set as 1.7 mm, 27°, 1.2 mm, and 20 mm, respectively. The effective heat transfer fin surface areas of different fin configurations were also kept identical for a comparative analysis. The influence of the RLs on the airside thermal–hydraulic performance was analysed by exploring the local and average Nusselt numbers, pressure drop, Colburn j factor, friction factor f, performance evaluation criteria (PEC), and flow efficiency of different fin configurations. The numerical results revealed that the asymmetric fin configuration with two RLs (NRL = 2) showed the best heat transfer performance for the entire Re range. It resulted in a 33% higher average Nusselt number, causing a 24% higher pressure drop compared to NRL=5. At low flow velocities (Re < 75), NRL = 3 showed better PEC; however, at high flow velocities (Re > 75), NRL = 1 outperformed other fin configurations. Finally, it was noted that increasing the number of RLs reduced the amplitude of the wavy-shaped flow formed between the neighbouring louvered fin, consequently deteriorating the flow efficiency.

Recently proposed organic flash cycles maintain lower irreversibility in the evaporator than traditional organic Rankine cycles. This study presented a novel combined heat and power system that was based on a regenerative organic flash cycle, in order to improve thermal efficiency. Parametric analyses for the proposed combined heat and power system were carried out, using six working fluids, and performed with heat source temperatures and heat sink temperatures that ranged from 130 °C to 170 °C, and from 20 °C to 40 °C, respectively. The results showed that the preferable working fluid was altered, with a change in the operating condition. Isopentane, R1234ze(Z), R1233zd(E), and R245fa performed better at a cooling water temperature of 20 °C. The system that used R245fa showed more promising performance when the heat source temperatures were set to 150 °C and 160 °C. R365mfc was determined to be the best working fluid at a heat source temperature of 150 °C, and at cooling water temperatures of 30–40 °C. Finally, the analyses evaluated the year-round system performance on the basis of monthly ambient and water temperatures in Daegu, Korea, as the system’s parameters. Compared to the single regenerative organic flash cycle, the thermal efficiency of the novel system improved significantly, from 8.37 % to 32.80% in August, and to 74.34% in February.

Sediment and cavitation erosion of the hydroelectric power turbine components are the fundamental problems in the rivers of Himalayas and Andes. In the present work, the latest research conducted in both the fields by various investigators and researchers are discussed and critically analyzed at different turbine components. Analysis shows that both types of erosion depends on flow characteristics, surface, and erodent material properties. Design optimization tools, coalesced effect (CE) of sediment and cavitation erosion and well conducted experiments will yield results that are beneficial for erosion identification and reduction. Although some researchers have done experimental work on the coalesced effect (CE) of sediment and cavitation erosion, very limited Computational Fluid Dynamics (CFD) work is available in literature. The present research work will be beneficial for practitioners and researchers in the future to address the erosion problem successfully.

The automotive industry is increasingly focused on developing more energy-efficient and eco-friendly air-conditioning systems. In this context, CO2 microchannel gas coolers (MCGCs) have emerged as promising alternatives due to their low global warming potential (GWP) and environmental benefits. This paper explores the application of machine learning (ML) algorithms to predict the thermohydraulic performance of MCGCs in automotive air-conditioning systems. Using data generated from an experimentally validated numerical model, this study compares various ML techniques, including both linear and nonlinear regression models, to forecast key performance metrics such as refrigerant outlet temperature, pressure drop, and heat transfer rate. Spearman’s correlation was employed to develop performance maps, whereas the R2 and MSE metrics were used to evaluate the models’ predictive accuracy. The linear models gave around 70% forecasting accuracy for pressure drop across the gas cooler and 97% accuracy for refrigerant outlet temperature, whereas the nonlinear models achieved more accurate predictions, with an accuracy ranging from 71% to 99%. This implies that nonlinear regression generally performs better than linear regression models in assessing the overall thermohydraulic performance of microchannel gas coolers. This research brings forth new ideas on how ML methods can be applied to enhance efficiency and effectiveness in gas coolers, contributing to the development of more eco-friendly automotive air-conditioning systems.

This paper presents the parameterization and optimization of two well-known airfoils. The aerodynamic shape optimization investigation includes the subsonic (NREL S-821) and transonic airfoils (RAE-2822). The class shape transformation is employed for parametrization while the genetic algorithm is used for optimization purposes. The absolute scheme of the optimization process is carried out for the minimization of the drag coefficient and maximization of lift to drag ratio. In-house MATLAB code is incorporated with a genetic algorithm to calculate the drag coefficient and lift to drag ratio of the resulting optimized airfoil. The panel method is utilized in genetic algorithm optimization code to calculate pressure distribution, lift coefficient, and lift to drag ratio for optimized airfoil shapes and validates with XFOIL and NREL experimental data. Furthermore, CFD analysis is conducted for both the original (NREL S-821) and optimized airfoil obtained. The present method shows that the optimized airfoil achieved an improvement in lift to drag ratio by 7.4% and 15.9% of S-821 and RAE-2822 airfoil, respectively, by the panel technique method and provides high design desirable stability parameters. These features significantly improve the overall aerodynamic performance of the newly optimized airfoils. Finally, the improved aerodynamics results are reported for the design of turbulence modeling and NREL phase II, Phase III, and Phase VI HAWT blades.

The airborne wind turbine (AWT) employs a flying energy conversion to harvest the stronger winds blowing at higher altitudes. This study presents an aeroelastic evaluation of the AWT, which carries a flying rotor installed inside a buoyant shell. A considerable aerodynamic impact on the structural integrity of the full-scale system is modeled using a fluid–structure interaction (FSI) approach. Both the fluid and structure models are formulated separately and validated using a series of benchmark numerical data. To analyze the structural aeroelasticity, the aerodynamic loads from the fully resolved computational model are coupled using a one-way FSI on the structural model of the blade and shell to perform the non-linear static analysis. For a detailed investigation, various wind loads from the bare and shell rotor configurations are imposed on the flexible structure. The generated torque, aerodynamic loads, tip deflection, stress estimation and operational stability of the proposed energy system are computed. The tip deflection is 18% more in the shell rotor compared to the bare rotor at rated conditions, while an average increase of 54% more tip deflection was observed for every 4 m/s increase in wind speed. The non-linear aeroelastic characteristics in each case are found to be within the chosen design criteria, according to material, operational speed and structural limits. Most importantly, the significant power gain justifies the structural response of the blade to withstand the shell-induced loads at rated conditions in the shell configuration.

In this study, a numerical model of a microchannel gas cooler was developed using a segment-by-segment approach for thermohydraulic performance evaluation. State-of-the-art heat transfer and pressure drop correlations were used to determine the air and refrigerant side heat transfer coefficients and friction factors. The developed model was validated against a wide range of experimental data and was found to accurately predict the gas cooler capacity (Q) and pressure drop (ΔP) within an acceptable margin of error. Furthermore, advanced machine learning algorithms such as extreme gradient boosting (XGB), random forest (RF), support vector regression (SVR), k-nearest neighbors (KNNs), and artificial neural networks (ANNs) were employed to analyze their predictive capability. Over 11,000 data points from the numerical model were used, with 80% of the data for training and 20% for testing. The evaluation metrics, such as the coefficient of determination (R2, 0.99841–0.99836) and mean squared error values (0.09918–0.10639), demonstrated high predictive efficacy and accuracy, with only slight variations among the models. All models accurately predict the Q, with the XGB and ANN models showing superior performance in ΔP prediction. Notably, the ANN model emerges as the most accurate method for refrigerant and air outlet temperatures predictions. These findings highlight the potential of machine learning as a robust tool for optimizing thermal system performance and guiding the design of energy-efficient heat exchange technologies.

This study reports the thermodynamic analysis of a high-temperature recuperative organic Rankine cycle comprising a water heating system that can provide a net power of 585.7 kW and hot water for domestic use at 35 °C. The performance was analysed using seasonal ambient temperature and water temperature data from Seoul, South Korea. The working fluid was separated into two different mass fractions after emerging from the turbine 1 outlet; one fraction provided heat to recuperate the organic Rankine cycle, and the other fraction was transferred to the water heating system for heating water. Mass fractions were balanced based on the projected seasonal need for hot water. Four working fluids with high critical temperatures and five working fluids with low critical temperatures were examined for top and bottom cycles, respectively. Chlorobenzene was selected for the top cycle and R601 was selected for the bottom cycle. The system achievement in individual months was analysed using thermal efficiency and exergy efficiency. Moreover, the performances of the hottest (low hot water demand) and coldest (high hot water demand) months were analysed.

The realization of a comfortable thermal environment with low energy consumption and improved ventilation in a car has become the aim of manufacturers in recent decades. Novel ventilation concepts with more flexible cabin usage and layouts are appealing owing to their potential for improving passenger comfort and driving power. In this study, three variant ventilation concepts are investigated and their performance is compared with respect to energy efficiency and human comfort of the driver and passenger in front and a child in the rear compartment. FLUENT 16.0, a commercial three-dimensional (3D) software, are used for the simulation. A surface-to-surface radiation model is applied under transient conditions for a car parked in summer conditions with its engine in the running condition. The results for the standard Fanger’s model and modified Fanger’s model are analyzed, discussed, and compared for the driver, passenger, and child. The modified Fanger’s model determines the thermal sensation on the basis of mean arterial pressure.

This study investigates a combined power generation and cooling system comprising an organic Rankine cycle (ORC) and a vapor compression cycle (VCC). Thermodynamic analyses of the system were conducted for two operation modes, i.e., the basic ORC mode and the ORC–VCC mode, using six different working fluids: R245fa, R114, R600, R142b, R152a, and R1234yf. The results showed that the thermal efficiency of the combined ORC–VCC system was almost twice that of the basic ORC system. The effects of thermodynamic parameters, such as the turbine inlet temperature and pressure and the condensing temperature, on the system performance were discussed. The second-law efficiency, cooling capacity, and coefficient of performance were addressed by varying the condensing temperature.