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Liquid Desiccant Dehumidification Systems (LDDS) have been gaining attention due to its great energy saving potential in buildings. The desiccant regeneration system in LDDS plays a vital role in the system as the major energy consumed is due to the heat energy supplied to regain the concentration of the desiccant solution. The high regeneration temperature prohibits the potential use of low-grade...
In this paper, CFD simulation of evaporative cooling pad, which is one kind of structured packing, has been carried out in Liquid Desiccant Dehumidification System (LDDS). Dry pressure drop and liquid distribution of two types of evaporative cooling pad are simulated and validated by the experimental data and Nusselt formula. For conducting the simulation, micro-scale representative element of evaporative...
In this paper, a dynamic analysis of mass transfer in liquid desiccant dehumidifier is proposed. This analysis is performed via the calculated results from a model, which can presents dynamic properties of the system. Hybrid method is introduced to simplify the model and estimate the model parameters. Dynamic properties are preserved in the procedure of model simplification so as to completely describe...
This paper presents a soft-sensing method for predicting the liquid desiccant concentration based on the Extreme learning machine (ELM). The soft-sensing method utilizes a blackbox model including eight inputs variables and one output to predict the concentration in real-time and is a better alternative to manual measurement or expensive and complex sensors. The soft-sensing method is verified with...
In this paper, a simplified, yet accurate hybrid model to predict the heat and mass transfer processes in a packed column liquid desiccant dehumidifier is developed. Starting from energy and mass balance principles, and by lumping the geometric parameters and fluids’ thermodynamic coefficients as constants, the derived model only requires two equations together with total seven parameters for predicting...
In this paper, an empirical model based on least square support vector machine (LSSVM) method to predict the output air conditions in a packed tower liquid desiccant dehumidifier is developed. By analysis of the coupled heat and mass transfer between the process air and desiccant solution, six variables are used as the inputs of the LSSVM model, namely: desiccant solution and air flow rates, desiccant...
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