RESUMO
In this Paper solar desiccant air conditioning system integrated with cross flow Maisotsenko cycle (M-cycle) indirect evaporative cooler is used to investigate the performance of whole system in different range of parameters. Solar evacuated tube electric heater is used to supply the regeneration temperature to the desiccant wheel, whereas, Desiccant Wheel (DW) and M-cycle is used to handle latent load and sensible load separately. Major contribution of this research is to predict system level performance parameters of a Solar Assisted Desiccant Air Conditioning (Sol-DAC) system using Radial Basis Function Neural Network (RBF-NN) under real transient experimental inlet conditions. Nine parameters are mainly considered as input parameters to train the RBF-NN model, which are, supply Air temperature at the process side of desiccant wheel, supply air humidity ratio at process side of the desiccant wheel, outlet temperature from the desiccant wheel at process side, outlet humidity ratio from the desiccant wheel at process side, regeneration temperature at regeneration side of the DW, outlet temperature from the heat recovery wheel at process side, outlet humidity ratio out from the Heat Recovery Wheel (HRW) at process side, temperature before heat recovery wheel regeneration side of the system, humidity ratio before heat recovery wheel regeneration side of the system. Four parameters are considered as the output of the RBF-NN model, namely: output temperature, output humidity, Cooling Capacity (CC), and Coefficient of Performance (COP). The results of the RBF-NN model shows that the best Mean Squared Error (MSE) and Regression coefficient (R) for outlet temperature prediction are 0.00998279 and 0.99832 when regeneration temperature is 70 °C and inlet humidity at 18 g/kg. Best MSE and R for predication of outlet humidity are 0.0102932 and 0.99485 when the regeneration temperature is 70 °C and inlet humidity at 16 g/kg. Best MSE and R for predication of COP are 0.0106691 and 0.9981 when the regeneration temperature is 70 °C and inlet humidity 12 g/kg. Best MSE and R for predication of CC are 0.0144943 and 0.99711 when the regeneration temperature is 70 °C and inlet humidity 14 g/kg. Experimental and predicted performance parameters were in close agreement and showed minimal deviation. Investigations of predicted results revealed that trained RBF-NN model was capable of predicting the trend of output result under the varying input condition.
RESUMO
The use of solar energy is one of the most prominent strategies for addressing the present energy management challenges. Solar energy is used in numerous residential sectors through flat plate solar collectors. The thermal efficiency of flat plate solar collectors is improved when conventional heat transfer fluids are replaced with nanofluids because they offer superior thermo-physical properties to conventional heat transfer fluids. Concentrated chemicals are utilized in nanofluids' conventional synthesis techniques, which produce hazardous toxic bi-products. The present research investigates the effects of novel green covalently functionalized gallic acid-treated multiwall carbon nanotubes-water nanofluid on the performance of flat plate solar collectors. GAMWCNTs are highly stable in the base fluid, according to stability analysis techniques, including ultraviolet-visible spectroscopy and zeta potential. Experimental evaluation shows that the thermo-physical properties of nanofluid are better than those of base fluid deionized water. The energy, exergy and economic analysis are performed using 0.025%, 0.065% and 0.1% weight concentrations of GAMWCNT-water at varying mass flow rates 0.010, 0.0144, 0.0188 kg/s. The introduction of GAMWCNT nanofluid enhanced the thermal performance of flat plate solar collectors in terms of energy and exergy efficiency. There is an enhancement in efficiency with the rise in heat flux, mass flow rate and weight concentration, but a decline is seen as inlet temperature increases. As per experimental findings, the highest improvement in energy efficiency is 30.88% for a 0.1% weight concentration of GAMWCNT nanofluid at 0.0188 kg/s compared to the base fluid. The collector's exergy efficiency increases with the rise in weight concentration while it decreases with an increase in flow rate. The highest exergy efficiency is achieved at 0.1% GAMWCNT concentration and 0.010 kg/s mass flow rate. GAMWCNT nanofluids have higher values for friction factor compared to the base fluid. There is a small increment in relative pumping power with increasing weight concentration of nanofluid. Performance index values of more than 1 are achieved for all GAMWCNT concentrations. When the solar thermal collector is operated at 0.0188 kg/s and 0.1% weight concentration of GAMWCNT nanofluid, the highest size reduction, 27.59%, is achieved as compared to a flat plate solar collector with water as a heat transfer fluid.
