Design, Modelling and Optimization of a Novel Concentrated Solar Powered (CSP) Flash Desalination System Involving Direct Heating and Pressure Modulation Using Response Surface Methodology (RSM)

Abstract

The main problem with existing desalination technologies is that they consume high input energy to generate fresh water. Secondly, this energy demand is usually met by conventional sources of energy such as fossil fuels. With limited conventional energy reserves predicted for the future, the focus is on the utilization of renewable sources of energy such as solar, wind, and geothermal energy for powering desalination systems. Such a transformation would make the desalination systems more energy efficient, sustainable, and economical. In this paper, a novel concentrated solar powered (CSP) flash desalination system with direct heating and pressure modulation is presented. A lab-scale prototype was designed, manufactured, and tested for feed water collected from the Arabian Sea and in climatic conditions of Al-Khobar city in Saudi Arabia. The effect of three process parameters, namely, feed water temperature (30–40 °C), feed water flow rate (0.003–0.006 kg/s), and vacuum pressure (0.1–0.3 bar) on distillate production, was investigated. System modelling and optimization were done using Design Expert software and Response Surface Methodology (RSM). The central composite design technique was employed for the optimization of process parameters. The adequacy of the developed distillate production model was verified by ANOVA. The optimum values of feed water temperature, flow rate, and vacuum pressure are reported to be 40 °C, 0.005 kg/s, and 0.1 bar, respectively, resulting in distillate production of 0.001 kg/s.

Application of response surface methodology and neural networks in pyramid solar still for seawater desalination: An optimization and prediction strategy

“…The probability of obtaining an elevated number due to noise is very little, namely 0.01 percent. The model was considered statistically significant when the P-value was below 0.05 (Ahmed et al 2022). The R 2 values that were predicted and adjusted are 0.9453 and 0.9727, respectively.…”

“…In the presence of system curvature, employing a higherdegree polynomial model, such as the second-order model, is necessary. The quadratic polynomial regression model is used (Ahmed et al 2022).…”

A Combinatorial Optimization Strategy for Performance Improvement of Stratum Ventilation Considering Outdoor Weather Changes and Metabolic Rate Differences: Energy Consumption and Sensitivity Analysis

“…Figure 5 shows that four criteria from the RSM models have a comparison with those from CFD simulations for 25 cases. Therefore, the development of RSM model is statistically reliable [56,57].…”