Performance testing of a cross-flow membrane-based liquid desiccant dehumidification system

Bai, Hongyu; Zhu, Jun; Chen, Ziwei; Ma, Lei; Wang, Ruzhu; Li, Tingxian

doi:10.1016/j.applthermaleng.2017.03.058

Cited by 47 publications

(8 citation statements)

References 33 publications

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“…Su et al [16] proposed a solarpowered absorption chiller combined with a liquid desiccant dehumidifier for space cooling and fresh water production, and their results reveals that the exergy efficiency for the proposed system is 2.97% higher than the reference system. Huang et al [17,18] studied the conjugate heat and mass transfer in a membrane parallel-plate contractor, and analysed the effects of local and mean friction factors, Nusselt number and Sherwood number. Apart from the dehumidifier in the dehumidification system, the regenerator is another crucial component since the diluted solution needs to be re-concentrated in the regenerator.…”

Section: Research Backgroundmentioning

confidence: 99%

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

et al. 2020

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A complete membrane-based liquid desiccant dehumidification system is investigated under the steady operating condition, which mainly consists of a dehumidifier, a regenerator, three heat exchangers, a cold and a hot water supply units. A finite difference mathematical model is developed for the complete system to investigate the system dehumidification performance and energy requirement, and validated by experimental data. The dehumidification performance is evaluated by the system sensible and latent effectiveness and moisture flux rate, while its energy performance is assessed by the total cooling capacity and coefficient of performance. It is found that the number of heat transfer units in the dehumidifier side and solution to air mass flow rate ratio have the most considerable impact on the system performance, while the number of heat transfer units in the regenerator side and solution inlet concentration in the dehumidifier have comparatively weak influences. The system sensible and latent effectiveness can be improved by increasing the dehumidifier side number of heat transfer units before reaching its critical value of 6. However, the amount of moisture being absorbed, total cooling capacity and coefficient of performance decrease with the dehumidifier side number of heat transfer units at the low air flow rate. The critical value of solution to air mass flow rate ratio varies with number of heat transfer units, and it is preferable to keep the flow rate ratio at or below its critical value as further increasing solution flow rate would reduce the system coefficient of performance.

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Section: Research Backgroundmentioning

confidence: 99%

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

et al. 2020

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“…Cho et al [8] conducted a series of experiments and found that the cross-flow liquid desiccant dehumidifier has stable dehumidification performance regardless of the variations in operating parameters, but the crossflow dehumidifier performance is effected by temperature and humid process air conditions. Bai et al [9] experimentally investigated the performance of the membrane-based liquid desiccant dehumidification system with calcium chloride. The sensible, latent and total effectiveness in their study were recorded as 0.49, 0.55, and 0.53, respectively.…”

Section: E-mail Addressesmentioning

confidence: 99%

Statistical investigation of a dehumidification system performance using Gaussian process regression

Akhlaghi

Zhao

Shittu

et al. 2019

Energy and Buildings

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Swift performance assessment of dehumidification systems, in design stage and while operation of the system is of substantial importance for commercialization and wide implementation of this technology. This paper presents a novel statistical model, employing Gaussian Process Regression (GPR) to investigate performance of a solar/waste energy driven dehumidification/regeneration cycle with a solid adsorbent bed. The statistical model takes thousands of operating conditions derived from a numerical model to predict the performance of the system. This predictive tool directly correlates the main operating parameters with the performance parameters of the system. The operating parameters considered in this study are: temperature, relative humidity and flow rate of process air, temperature of regeneration air, length of the desiccant bed, solar radiation intensity and operating time, and the selected performance parameters are: moisture extraction efficiency for the dehumidification cycle and moisture removal efficiency for the regeneration cycle. The model is evaluated by three metrics, namely: root mean square error (RSME), mean absolute percentage error (MAPE), and coefficient of determination (R 2). The maximum RSME and MAPE for moisture extraction are only 0.045, 0.21%, and for moisture removal efficiencies are 0.082 and 0.39%, respectively, while the R 2 value is derived as 0.97. The developed model is used to investigate the impact of four selected operating parameters on system performance. Additionally, the system performance is predicted for randomly generated operating conditions as well as warm and humid climates. The developed GPR model provides a swift and highly accurate predictive tool for design of the dehumidification systems and for commercialization of the investigated dehumidification systems.

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“…Moghaddam et al [23] introduced a solution-side effectiveness to evaluate the impact of * on dehumidification and regeneration processes, and pointed out that the latent effectiveness difference between the air-side and the solution-side is can be neglected. Bai et al [24,25] experimentally and theoretically studied the operating characters of a parallel-plate membrane-based dehumidification system by focusing on various parameters, and identified the effects of and mass flow rate ratio ( * ) are interacted with each other. Some researchers developed different types of the membrane-based contractor.…”

Section: Introductionmentioning

confidence: 99%

Influences of the mixed LiCl-CaCl2 liquid desiccant solution on a membrane-based dehumidification system: Parametric analysis and mixing ratio selection

Bai¹,

Zhu²,

Chu³

et al. 2019

Energy and Buildings

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The membrane-based liquid desiccant dehumidification system has high energy efficiency without the traditional liquid system carry-over problem. The performance of such a system strongly depends on solution's temperature and concentration, which have direct relationship to the solution surface vapour pressure. Compared with the pure liquid desiccant solution, the mixed liquid desiccant solution has lower surface vapour pressure, better system performance and lower material cost. In this paper, the performance of a flat-plate membrane-based liquid desiccant dehumidification system with the mixed solution (LiCl and CaCl2) is investigated through theoretical and experimental approaches. A mathematical model is established to predict the system performance, while the electrolyte non-random two-liquid (NRTL) method is applied to calculate the mixed solution properties. The influences of the solution mixing ratio, temperature and concentration are evaluated, and it is found that the regeneration heat can be dramatically reduced by either applying a high concentration solution or increasing CaCl2 content in the mixed solution. Compared with the pure LiCl solution system, the mixed solution system COP can be improved up to 30.23% by increasing CaCl2 content for a 30% concentration solution. The optimum mixing ratio varies with the solution concentration. For the mixed LiCl-CaCl2 solution, the system highest COPs appear at the mixing ratios of 3:1, 2:1 and 1:1 for 20%, 30% and 40% concentrations respectively.

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Performance testing of a cross-flow membrane-based liquid desiccant dehumidification system

Cited by 47 publications

References 33 publications

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

Statistical investigation of a dehumidification system performance using Gaussian process regression

Influences of the mixed LiCl-CaCl2 liquid desiccant solution on a membrane-based dehumidification system: Parametric analysis and mixing ratio selection

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