Experimental analysis and numerical modelling of an AQSOA zeolite desiccant wheel. (5th April 2015)

• Record Type: Journal Article
• Authors: Intini, Manuel; Goldsworthy, Mark; White, Stephen; Joppolo, Cesare Maria
• Is Part Of: Applied thermal engineering. Volume 80(2015:Apr.)
• Page Start: 20
• Page End: 30
• Publication Date: 2015-04-05
• Subjects: Desiccant wheel -- AQSOA -- Zeolite -- Molecular sieve -- Dwell time; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2015.01.036
• Languages: English
• ISSNs: 1359-4311

Abstract

Abstract: An AQSOA zeolite based-desiccant wheel is experimentally and numerically investigated in the present work. The synthetic zeolite AQSOA benefits from a favourable S-shape isotherm whose steepest gradient zone is shifted towards higher vapour partial pressure values. An AQSOA-based desiccant wheel is experimentally characterized over a wide range of process and regeneration air inlet conditions. A one-dimensional, time-dependent numerical model is developed and calibrated using the experimental data with root mean square deviation of 0.66 g/kg and 0.99 °C for process outlet humidity ratio and temperature respectively. The model is used to investigate the influence of area ratio, process inlet temperature, humidity and air face velocity on performance. It is found that equal area split is essential to achieve maximum moisture removal capacity, while higher process area ratio leads to higher latent cooling, but only in the high regeneration temperature range, and moisture removal efficiency strongly depends on inlet humidity ratio with a weak dependence on process inlet temperature. Non dimensional analysis is shown to be useful for identifying optimal revolution speed as a function of inlet face velocity. Highlights: Experimental tests of a recently developed zeolite desiccant wheel. Effect of air stream quantities out of experimental testing range conditions. Identification of non-dimensional parameters to predict optimal revolution speed.