Statistical Analysis and Optimization of a Single-Effect Vapor Absorption Refrigeration Cycle

Abstract

This study employs Response Surface Methodology (RSM) with a Box-Behnken design to optimize the Coefficient of Performance (COP) in a Single-Effect Vapor Absorption System. The thermodynamic model considers a 1-ton refrigeration (TR) system utilizing Lithium bromide-water as the refrigerant, and simulations are conducted using the Engineering Equation Solver (EES). The optimization process identifies optimal values for the generator, absorber, condenser, and evaporator temperatures, set at 90°C, 33°C, 33°C, and -5°C, respectively, resulting in an achieved optimum COP of 0.716. Statistical analysis through ANOVA of the quadratic regression model reveals a significant F-value of 110.62, with a low probability value (p=0.0003), attesting to the model's robustness. Key statistical metrics for the model encompass a standard deviation (Std. Dev.) of 0.0059, a mean of 0.8956, a coefficient of variation (C.V. %) of 0.6559, an R² of 0.9901, an adjusted R² of 0.9811, a predicted R² of 0.9159, and an adequate precision of 38.2967. This research offers crucial insights into enhancing the performance of a Single-Effect Vapor Absorption System, thereby contributing to the advancement of energy-efficient refrigeration technologies