Imperial College London


Faculty of EngineeringDepartment of Chemical Engineering

Professor of Clean Energy Technologies



+44 (0)20 7594 1601c.markides Website




404ACE ExtensionSouth Kensington Campus






BibTex format

author = {Harraz, AA and Freeman, J and Wang, K and Mac, Dowell N and Markides, CN},
doi = {10.1016/j.egypro.2019.01.284},
journal = {Energy Procedia},
pages = {2360--2365},
title = {Diffusion-absorption refrigeration cycle simulations in gPROMS using SAFT-γ Mie},
url = {},
volume = {158},
year = {2019}

RIS format (EndNote, RefMan)

AB - Diffusion-absorption refrigeration (DAR) is a clean thermally-powered refrigeration technology that can readily be activated by low- to medium-grade renewable heat. There is an ongoing interest in identifying or designing new working fluids for performance improvement, particularly in solar applications with non-concentrating solar collectors providing heat at temperatures < 150 °C. In this work, the state-of-the-art statistical associating fluid theory (SAFT) is adopted for predicting the thermodynamic properties of suitable DAR working fluids. A first-law thermodynamic analysis is performed in the software environment gPROMS for a DAR cycle using ammonia as the refrigerant, water as the absorbent and hydrogen as the auxiliary gas. The simulation results show good agreement with experimental data generated in a prototype DAR system with a nominal cooling capacity of 100 W. In particular, at a charge pressure of 17 bar and when delivering cooling at 5 °C, the model results agree with experimental COP data to within ± 7 % over a range of heat inputs from 150 to 500 W. The maximum coefficient of performance (COP) is estimated to be 0.24 at a heat input of 250 W. The group-contribution SAFT-γ Mie equation of state is of particular interest as it offers good agreement with experimental data and provides flexibility in extending the model to test different working fluids with a high degree of fidelity. A methodology is also presented that allows the DAR thermodynamic analysis and working-fluid modelling to be integrated into a more general technology optimisation framework.
AU - Harraz,AA
AU - Freeman,J
AU - Wang,K
AU - Mac,Dowell N
AU - Markides,CN
DO - 10.1016/j.egypro.2019.01.284
EP - 2365
PY - 2019///
SN - 1876-6102
SP - 2360
TI - Diffusion-absorption refrigeration cycle simulations in gPROMS using SAFT-γ Mie
T2 - Energy Procedia
UR -
UR -
VL - 158
ER -