Flat tubes are vital components of various technical applications including modern heat exchangers, thermal power plants, and automotive radiators. This paper presents the hybridization of computational fluid dynamic (CFD) and artificial neural network (ANN) approach to predict the thermal-hydraulic characteristics of in-line flat tubes heat exchangers. A 2D steady state and an incompressible laminar flow in a tube configuration are considered for numerical analysis. Finite volume technique and body-fitted coordinate system are used to solve the Navier-Stokes and energy equations. The Reynolds number based on outer hydraulic diameter varies between 10 and 320. Heat transfer coefficient and friction are analyzed for various tube configurations including transverse and longitudinal pitches. The numerical results from CFD analysis are used in the training and testing of the ANN for predicting thermal characteristics and friction factors. The predicted results revealed a satisfactory performance, with the mean relative error ranging from 0.39% to 5.57%, the root-mean-square error ranging from 0.00367 to 0.219, and the correlation coefficient (R 2) ranging from 99.505% to 99.947%. Thus, this study verifies the effectiveness of using ANN in predicting the performance of thermal-hydraulic systems in engineering applications such as heat transfer modeling and fluid flow in tube bank heat exchangers.

Heat transfer coefficients and pressure drop are studied experimentally for airflow over aligned round and flattened tube configurations. The Reynolds number is based on the outer diameter of the round tube or the outside transverse diameter of the flattened tube, which is used for various flows, ranging from 133 to 800 with a constant input heat flux. In the present work, a total of 30 samples of round and flattened tubes heat exchangers with three transverse pitches, 2.0, 3.0, and 4.5, were studied to investigate their thermal performance. The results indicate that the relative gain in the overall Nusselt number is about 32.5 to 60.6% in flattened tubes, while the reduction range in the friction factor is about 11 to 30.6%. Correlations are proposed for the overall Nusselt number, friction factor, and Colburn j–factor for both round and flattened tube banks. A higher value means that a deviation error of 9.9% in the round tube banks and 10.1% in the flattened tube banks are expected. In addition, the best value for thermal performance for the flattened tube bundle was found to be coincident with a smaller Reynolds number.

Welding of aluminum alloys by traditional welding methods creates some defects such as hot cracks, porosity, and void that led to decreasing of mechanical properties. Friction Stir Welding (FSW) gives good mechanical properties of aluminum alloy welds. In this paper, FSW worked in 4 mm thick plate of 6061-T4 aluminum alloy, with two welding parameters are used (tool rotational speed and feed rate) was investigated, were analyzed the microstructure and mechanical properties by carried out microstructural, micro-hardness, and tensile strength tests. From results are found defect-free of welds at a wide range of parameters. Stir zone shows a fine-equiaxed grain and high hardness, not significantly change between heat affected zone and base metal in size grain. Tensile strength of welds was lower than base metal and fracture location was occurred at a low hardness region for the welds.

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