Inverse Properties Estimation of Methanol Adsorption in Activated Carbon to Utilise in Adsorption Cooling Applications: An Experimental and Numerical Study

The precise estimation of influential parameters in adsorption is a key point in conducting simulations for the sensitivity analysis and optimal design of cooling systems. This study explores the critical role of a new type of granular activated carbon (GAC-208C) in adsorption refrigeration systems. By fitting experimental and numerical models to the thermophysical properties of GAC/methanol as a working pair, an advanced methodology is established for the thermal analysis of the adsorption bed, addressing the various operating conditions overlooked in prior studies. The physical properties of the studied carbon sample are determined in a laboratory using surface area and pore volume tests, thermal adsorption analysis, and weight loss. To determine the thermal properties of GAC/methanol, the adsorption process is experimentally tested inside an isolated heat exchanger. A three-dimensional (3D) model is created to simulate the procedure and then coupled with the particle swarm optimisation (PSO) algorithm in MATLAB. The optimal thermal parameters for adsorption are determined by minimising the mean square error (MSE) of the adsorption bed temperature between the numerical and experimental data. The laboratory studies yielded accurate results for the physical properties of GAC, including adsorption capacity, porosity, permeability, specific heat capacity, density, activation energy, and the heat of adsorption. The thermal analysis of the adsorption process identified the ideal values for the Dubinin–Astakhov equation constants, diffusion coefficients, heat transfer coefficients, and contact resistance. The numerical model demonstrated strong agreement with the experimental results, and the dynamic behaviour of pressure and uptake distribution showed good agreement with 1.2% relative error. This research study contributes to the improved estimation of adsorption parameters to conduct more accurate numerical simulations and design new adsorption systems with enhanced performance under different operating conditions.