Abstract
Engineering applications including food processing, wastewater treatment, home heating, commercial heating, and institutional heating successfully use unglazed transpired solar collectors (UTCs). Trapping of solar energy is the prime goal of developing an unglazed transpired solar collector. The UTC is usually developed in and around the walls of the building and absorbs the solar energy to heat the air. One of the key challenges faced by the UTC designer is the prediction of performance and its warranty under uncertain operating conditions of flow variables. Some of the flow features are the velocity distribution, plate temperature, exit temperature and perforation location. The objective of the present study was to establish correlations among these flow features and demonstrate a method of predicting the performance of the UTC. Hence, a correlation matrix was generated from the dataset prepared after solving the airflow over a perforated flat UTC. Further, both strong and weak correlations of flow features were captured through Pearson's correlation coefficient. A comparison between the outcomes from a linear regression model and that of computational simulation was showcased. The performance probability for the UTC was interlinked with correlation matrix data. The Monte Carlo simulation was used to predict the performance from random values of the flow parameters. The study showed that the difference between the free stream value of temperature and the value of temperature inside the UTC's chamber varied between 15 and 20 degrees C. The probability of achieving system efficiency greater than 35% was 55.2%. This has raised the hope of recommending the UTC for drying and heating where the required temperature differential is within 20 degrees C.