Optimization Of Solar Air Heaters Research Articles

Parametric optimization of solar air heaters with dimples on absorber plates using metaheuristic approaches

The performance optimization analysis of artificially roughened solar air heaters (SAH) becomes complex due to the inherent difficulties of the optimization analytical processes. Metaheuristic algorithms can be employed as optimization methodologies to handle complex engineering problems with minimal computational efforts and high accuracy. However, due to their stochastic nature, only some metaheuristic algorithms are suitable for solving a specific problem. Hence, there is a need to perform a comparative performance analysis of different metaheuristic algorithms in optimizing SAH. The current paper presents a comparative performance analysis of four metaheuristics algorithms, i.e., Firefly algorithm (FA), Particle swarm optimization (PSO), Differential evolution (DE), and Teaching learning-based optimization (TLBO), in optimizing the system and operating parameters of SAH. Two types of artificially roughened SAH absorber plate design patterns have been taken: dimpled plate in a zig-zag pattern and straight-line pattern. Both single and multi-objective optimization techniques are carried out while viewing the maximization of Nusselt number (Nu) and minimization of friction factor (Ff) as two objective functions in single-objective optimization. Results showed that the TLBO algorithm delivered better optimal solutions for single and multi-objective optimization than the other three metaheuristic algorithms. In the single-objective optimization, the maximum improvement in Nu and Ff is 16.81 % and 3.61 %, respectively. In the multi-objective optimization of a zig-zag pattern, the suitable parametric setting is Re = 20000, S/e = 30.83, L/e = 30.83, and d/D = 0.2515 for the optimal value of Nu and Ff as 204.7034 and 0.0134, respectively. For a straight-line pattern, the optimal values for Nu and Ff are 108.6901 and 0.0237, respectively at Re = 12000, p/e = 12, and e/D = 0.0379.

Performance optimization of solar air heater using inclined ribs

Performance optimization of solar air heater using inclined ribs

Parametric optimization of solar air heater having sine wave baffles as turbulators

ABSTRACT The performance of a solar air heater roughened with sine wave baffles has been calculated in terms of effective and thermal efficiency. Relative baffle length ( relative roughness pitch , relative height angle of attack , Reynolds number , Insolation and Temperature rise parameter are the operational parameters. The sine wave roughened solar air heater has a higher effective and thermal efficiency than the smooth air heater. The thermal efficiency has boosted to 78%, and the effective efficiency has been improved to 70.8%. A parametric analysis has been carried out to determine the best set of parameters.

Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects

A transition to solar energy systems is considered one of the most important alternatives to conventional fossil fuels. Until recently, solar air heaters (SAHs) were among the other solar energy systems that have been widely used in various households and industrial applications. However, the recent literature reveals that efficiencies of SAHs are still low. Some metaheuristic algorithms have been used to enhance the efficiencies of these SAH systems. In the paper, we do not only discuss the techniques used to enhance the performance of SAHs, but we also reviewed a majority of published papers on the applications of SAH optimization. The metaheuristic algorithms include simulated annealing (SA), particle swarm optimization (PSO), genetic algorithm (GA), artificial bee colony (ABC), teaching-learning-based optimization (TLBO), and elitist teaching-learning-based optimization (ETLBO). For this research, it should be noted that this study is mostly based on the literature published in the last ten years in good energy top journals. Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. Based on the past literature and on the outcomes of this paper, ETLBO is unquestionably more competitive than ABC, GA, PSO, SA, and TLBO for the optimization of SAHs for the same considered problem. Finally, based on the covered six state-of-the-art metaheuristic techniques, some perspectives and recommendations for the future outlook of SAH optimization are proposed. This paper is the first-ever attempt to present the current developments to a large audience on the applications of metaheuristic methods in SAH optimization. Thus, researchers can use this paper for further research and for the advancement of the proposed and other recommended algorithms to generate the best performance for the various SAHs.

Multi-objective design optimization of solar air heater for food drying based on energy, exergy and improvement potential

Solar air heaters (SAHs) are commonly utilized in different applications due to their simple structure and low setup cost. Optimizing operating parameters of the SAH is highly linked to the desired application. The aim of this study is to determine the optimal geometric and operational parameters of finned SAH for food drying. In order to achieve this goal, response surface methodology was combined with an experimentally validated thermal model of the SAH system. Multi-objective optimization is carried out according to energy-exergy analysis, improvement potential (IP) and outlet temperature suitable for food drying (40–70 °C). Length/width ratio (L/W) (1–5), height of air duct (0.02–0.2), and number of fins (0-60) were the operating variables. The experimental tests were carried out on the indirect type solar dryer composed of SAH and the drying chamber. The developed code led to consistent numerical results that have been confirmed by experimental tests. The optimal parameters were defined as 1.28 L/W, 0.067 m air duct height and 49 fins. In these optimal conditions, the outlet temperature, thermal efficiency, and IP were 52 °C, 51.78% and 1397.34W, respectively. The optimal design improved the thermal efficiency by 15.76% and IP by 19.33%.

Numerical simulations and optimization of solar air heaters

Different surface modification techniques have been used for enhancement of heat transfer from absorber plates of solar air heaters. It is necessary to have accurate values of design parameters within the operational window while designing the heat transfer equipments. The present work is focused on the development of empirical correlations and evaluation of maximum thermohydraulic performance of a rectangular section ribs installed in solar air heaters considering all the design combinations within the given range of input parameters. It is prescribed by design of experiment algorithms particularly with response surface methodology considering four input parameters viz., Reynolds number ranging from 4000 to 20000, relative rib pitch ranging from 5 to 60, relative rib height ranging from 0.065 to 0.252 and relative rib width ranging from 0.5 to 10. The maximum THP obtained is 2.77 at Reynolds number 20000, relative rib pitch 17.22, relative rib height 0.044 and relative rib height 0.5. The optimal values of design parameters have been verified with CFD simulations and experiments. The errors are within acceptable limit proving the accuracy of empirical correlations used for the design of solar artificial air heater and proper selection of model equations.

Overall performance analysis and GRA optimization of solar air heater with truncated half conical vortex generators

The present numerical study using ANSYS FLUENT 18.1 is based on improving the thermohydraulic performance of a solar air heater by embedding truncated half conical vortex generators (THC-VGs) on the absorber plate. Grey relational analysis (GRA) optimization technique is employed to achieve the best configuration for the applicable range of Reynolds number (Re = 3500–16000). The THC-VGs are fixed on the absorber plate at a relative pitch ratio, P/e range of 2.67–6.67 and placed such that the angle of attack, α lies in between 0° and 90°. RNG k-ε turbulent model is employed to solve the complex governing equations of CFD. Results are analysed by computing different performance parameters like, Nusselt number, Nu, thermal enhancement factor, TEF, friction factor, f, friction factor enhancement factor, FEF and thermohydraulic performance parameter, THPP. A maximum percentage enhancement of 187% in Nu is noted for α = 60°, P/e = 2.67 and Re = 16000. Results are supported with proper justifications by using different contours derived from the post processing unit of the CFD code. Proper flow dynamics along with thermal behaviour due to the introduction of THC-VGs are explored. Correlations for Nu and f are developed as a function of Re, P/e and α.

Thermo-economic optimization of solar air heaters with arcuate-shaped obstacles

In this study, thermo-economic optimization of single-pass SAHs (solar air heaters) with obstacles of arcuate shape has been carried out. The research is conducted in order to compare the exergy efficiency of three different types of flat plate SAHs. Also, using NSGA-II (non-dominated sorting genetic algorithm) influencing factors were optimized. The SAHs were two different arcuate obstacles (type II and type III), and the other one had no obstacles (type I). All heater types with single and double glass cover were evaluated. The results showed that the heater with double glass cover and the obstacles (type III) had the highest function in both economic and exergetic aspects. Based on the NSGA-II results, collector with flow rate, area and the outlet temperature of 0.017 kg s−1, 2.6 m2 and 78 °C, respectively, had the best performance.

Intelligent modeling of thermohydraulic behavior in solar air heaters with artificial neural networks

The artificial neural network was applied to map the thermohydraulic performance criteria of the solar air heater with constant values of geometric parameters. Along with intelligent prediction of friction factor and Nusselt number, the main idea behind the research was modeling the performance of solar air heater through the temperature and velocity features instead of geometric parameters which cause opportunity for comparison and investigation of the roughnesses based on the Nusselt number and the friction factor and consequently the thermohydraulic performance. Two approaches were selected for ANN methodology: separate networks for each smooth and roughened plate and integrated model for both. Comparison between the predicted and experimental data in all designed networks indicated that the ANN predicts the Nusselt number better than the friction factor. Parameters of the roughened plate were inserted as the test data to the best-determined smooth plate networks in order to generalize the networks. The better result was observed for the Nusselt number of the roughened plate rather than the friction factor, in the procedure of generalizing the smooth plate networks. The least MSE for the Nusselt number and the friction factor of roughened duct in method 1 was 2.4999e−06 and 2.70199e−04, respectively. 1.7681e−06 and 4.0819e−04 were the least magnitudes of the MSE for the Nusselt number and the friction factor related to the smooth plate. The proposed model can be strongly recommended as a replacement for exhaustive and massive experimental procedure in the optimization of solar air heaters.

Mathematical Modelling and Optimization of Solar Air Heater Using CFD

Mathematical Modelling and Optimization of Solar Air Heater Using CFD

Multi-objective optimization of solar air heater with obstacles on absorber plate

A multi-objective optimization of a solar air heater with obstacles on an absorber plate is performed for maximum heat transfer and minimum pressure loss. In this work, shape optimization is carried out in conjunction with three-dimensional Reynolds-averaged Navier–Stokes analysis and two basic surrogate models: the response surface approximation and the Kriging models. Three geometric variables (the ratio of the obstacle height to the height of the duct; the ratio of the transverse pitch to the base length of the obstacle; and the angle of attack) were used as design variables for the optimization. The average Nusselt number and friction factor were used to define the two objective functions. The Latin hypercube sampling method was used to select the design points in the design space. A hybrid multi-objective genetic algorithm coupled with the surrogate model was used to find the Pareto-optimal solutions. The representative Pareto-optimal solutions were selected to study the trade-off between the two objectives. The response surface approximation model leads to a better set of non-dominated solutions over a wide range of functional space than the Kriging model. The optimization results show that the objective functions are significantly affected by the design variables, and the constructed surrogate models show good prediction accuracies for the objective functions. A performance factor was used to study the thermal–hydraulic performance of the Pareto-optimal solutions.

Numerical optimization of solar air heaters having different types of roughness shapes on the heated plate – Technical note

This paper presents numerical optimization results for the thermal and effective efficiencies of a solar air heater duct as a function of various roughness geometries on the heated plate. A methodology for the prediction of thermal and effective efficiency of the SAH has been developed on the basis of heat transfer and friction factor correlations. Among the roughness geometries considered, the discrete multiple V-shaped rib results in the best thermal and effective efficiencies over the entire range of design conditions. This work also addresses the scope for future research in the area of roughened SAH ducts and will be helpful for researchers investigating new artificial shapes for SAH ducts to enhance the heat transfer.

Optimization of solar air heaters of different designs

The optimum flow channel depth and mass flow rate in 10 different designs of solar air heaters have been obtained. The design variations considered are flat absorber type with and without cover glazings; single, double and triple pass etc. It is found that there exists an optimum mass flow rate corresponding to an optimum flow channel depth, for each design considered. The thermal efficiency of each design is then obtained under the optimum conditions. It is found that a single glazing solar air heater operating under double flow configuration gives the best performance.