A solar air heater system design for air handling units and domestic hot water

In the thesis study, dimensioning optimization is performed for a solar air heater (SAH) system utilized in a representative building. This study incorporates five different methods: building energy modeling (BEM), computational fluid dynamics (CFD), design of experiment (DOE), response surface method (RSM), and multi-objective genetic algorithm (MOGA). BEM is used for three purposes: determining optimal panel area, analysis of climate-system appropriateness, and examination of SAH for summer-winter mode. In the first part, it is revealed that beyond a certain size, enlarging the SAH panel does not yield significant benefits and based on this finding, the optimal panel area is determined. In the second part of the thesis, the hourly calculations are further extended to compute the obtained energy of the SAH system for six different regions of the world, selected according to the Köppen climate zone system. It is computed that the usage of buildingintegrated SAH systems is more suitable in regions with high solar radiation and cold climates. In the third part of the thesis, the system design that allows for the utilization of the SAH system for domestic hot water and air handling unit heating is analyzed. The outcomes reveal that the system can be more effectively utilized with this design compared to conventional panels. In the final part of the thesis, a combination of CFD, DOE, RSM, and MOGA methods is employed for the dimensioning optimization of three-panel parameters: panel depth, corrugation depth, and side inlet diameter. According to the results, corrugation depth is the most influential parameter on panel efficiency, leading to an increase in efficiency compared to flat surfaces. The second effective parameter is panel depth, which results in increased air velocity and turbulence as it decreases. While the increase in velocity has a negative impact, turbulence acts as a beneficial factor for efficiency. Therefore, the optimal panel depth dimension is computed by considering these factors. Side inlet diameter has less effect and the optimum size of this parameter is determined by considering the turbulence and panel area effects. The combined parameter graphs are generated with RSM, and dimensioning optimization is conducted with MOGA.