In the present study, a simulation and response surface methodology (RSM) combined approach has been applied to investigate the thermal and thermo-hydraulic performance parameter (THPP) of solar air heater (SAH) with inclined fins. CFD based software (ANSYS Fluent v16.1) is used to simulate the SAH. RNG k-Ɛ turbulence model was selected to carry out a two-dimensional simulation modeling. Moreover, RSM is applied to analyze the results of finite volume method and to optimize the process parameters of SAH. A numerical model describing the heat transfer characteristics of SAH having inclined fins has been developed and employed to study the effects of various design of fins on the average Nusselt number, fiction factor as well as THPP. The study covered different length of fin in the range of 1.5-2.5 mm, different slant angle (α) of fin in the range of 30°-60°, different pitch (P) of fin in the range of 15-25 mm, and a range of 4000-24,000 for the Reynolds numbers. Based on results of the model, the optimized values of design parameters for the optimal operation of SAH to provide the optimal THPP of 1.928 were found to be; length of fin = 1.52 mm, the pitch of fin = 19.04 mm, slant angle = 49° and Reynolds number at 18243.5. According to the optimized values of design parameters, the enhancement ratio of Nusselt number and friction factor were found to be 2.53 and 2.22, respectively. Finally, the thermal performance of the proposed inclined fin in terms of THPP was compared to other roughness geometries, such as circle (THPP = 1.65), square-sectioned (THPP = 1.80) and L-shaped (THPP = 1.90). Accordingly, a better THPP of 1.928 was observed for the current study.
The world today is going through a phase of uncertainty in terms of provision of power and energy because of shortages of fossil fuels, and these issues are increasing the costs as well as developing uncertain economic conditions worldwide. Hence, there is a dire necessity to find a solution to this problem by finding sustainable alternative power and energy solutions. However, the thermal performance of the conventional SAH is found to be poor due to low convective heat transfer coefficient between the heat collecting surface and working fluid. Therefore, increasing the convection heat transfer coefficient is essential so that thermal system performance can also be increased. In the present research, a numerical evaluation was carried out on the heat transfer and the flow friction processes in a SAH coupled with inclined fins underneath the absorber plate. With a constant heat flux application (1000 W/m2), the average Nusselt number (Nu) and friction factor, as well as the thermo-hydraulic performance parameter (THPP), were comprehensively investigated. The research covered different slant angle (α) of fins in the range of 30°-75°, different pitch (P) of fin in the range of 15-25 mm and a range of 4000-24000 for the Reynolds numbers (Re). For the current CFD evaluation, ANSYS FLUENT (v16.1) with renormalization group turbulence model is selected for computational domain analysis. In general, a significant improvement of the heat transfer in a SAH having inclined fins has been achieved. Moreover, with a view to analyzing the total effect of the slant angle and pitch of fin, the THPP subjected to similar pumping power constraint was calculated. From the investigated range, a maximum THPP of 1.916 was achieved by utilizing fins with α = 45° and P = 20 mm at Re = 20,000. Finally, the proposed inclined fin's THPP was compared to other geometries such as, L-shaped (THPP = 1.90), square (THPP = 1.80), and circle (THPP = 1.65). As a result, a better THPP of 1.916 was observed for this study.
To preserve the environment and natural resources, steel slag recovery conserves natural resources and makes landfill space available. Steel slag as a waste material has been partially substituted for fine (sand) and coarse aggregate in concrete (gravel). Compressive strength (CS) is the most significant mechanical attribute for all forms of concrete composites. To save time, energy, and money, it is essential to create accurate models for forecasting the CS of normal concrete (NC). In addition, it offers essential information for organizing the building work and details the ideal time to remove the formwork. In total, 338 data points were gathered, processed, and modeled in total. During the modeling approach, the most influential elements impacting the compressive strength (CS) of concrete with steel slag replacement were addressed. According to the modeling method, the most effective parameter which affects the compressive strength of normal concrete is the curing time. This research employed a Multi Logistic Regression model (MLR), an Artificial Neural Network (ANN), a Full Quadratic model (FQ), an M5P‐tree model, and an Interaction model to predict the compressive strength of normal strength concrete (CS ranged from 10 to 55 MPa) with steel slag aggregate replacement. According to data from the literature, the steel slag concentration enhanced the compressive strength. Based on evaluations with statistical tools like the objective (OBJ) function, the scatter index, and the Taylar diagram, the ANN model with the lowest root mean square error did better at predicting compressive strength than the other models.
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