Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/73791
Title: Modeling and optimization of vacuumed regeneration process for liquid desiccant dehumidification system
Authors: Kulathunga S.M. Asiri Indrajith
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Kulathunga S.M. Asiri Indrajith. (2018). Modeling and optimization of vacuumed regeneration process for liquid desiccant dehumidification system. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Since the last few decades the world has been facing global warming due to the increased percentage of atmospheric CO2. Much attention is therefore devoted to building air conditioning and, mechanical ventilation (ACMV) systems to provide a comfortable environment to occupants of residential houses and buildings. Liquid Desiccant Dehumidification System (LDDS) has gained much attention due to the possibility of combining secondary level energy sources like renewable energy and waste heat as its main energy source. However, the regeneration process of LDDS absorbs a vast amount of heat to vaporize water from the weak desiccant solution. With proper study and investigation nevertheless, challenges such as the requirement of high temperature heat sources, inefficiency of the regeneration process, and the complexity of combining renewable energy sources with the regeneration system can be overcome. Thus, a new vacuumed regenerator was designed to improve key performance indices of the regeneration process, while taking important parameters into consideration, such as; evaporator and condenser heat, mass transfer mechanism and driving force, solution flow method through the heat exchanger, condenser tube arrangement and liquid desiccant properties. Vacuumed condition of the regenerator increases the mass transfer driving force and reduces the evaporation temperature of the water; thus lowering the required heat source temperature. Carry over effect of the liquid desiccant is prevented, by making the regenerator a fully closed system where liquid desiccant circulates internally, with no direct contact with other fluids. Data was collected by testing the system to study the regeneration performance, with respect to different parameter conditions like; hot water and chilled water temperatures and flow rates, solution flow rate, initial solution concentration and initial vacuum pressure. Mathematical models for the water vapour evaporation, and water vapour condensation processes of the regeneration system, were developed. Overall heat and mass transfer coefficients for evaporator were modeled, by considering external convection over a tube bank and internal convection of a cylindrical tube. Evaporator mass transfer Sherwood number was modeled as a function of two phases Reynolds number, Schmidt number, concentration gradient and heat flux. Both evaporator heat transfer and mass transfer models were validated within ±10% good agreement with actual results. Condensation process was modeled by considering external natural condensation over a tube bank and internal convection of a cylindrical tube. Heat transfer rate of the condensation process is a function of chilled water flow rate, mean temperature difference and the number of rows of tubes. The heat transfer and mass transfer models for the condensation process were validated within ±10% good agreement with actual values. This theoretical contribution can be equally applied to any kind of similar system by changing system dependent parameters. Finally, optimization for the developed model was conducted to identify the best operating condition of the system. Minimizing total energy consumption and maximizing heat and mass transfer of evaporation and condensation processes were set as objectives of the multi objective genetic algorithm optimization. MATLAB’s genetic algorithm tool was employed for the optimization calculation, and it was found that the optimum condition can be achieved by several combinations of constraint parameters. Hence, a suitable solution was selected from the optimum settings by considering the resource availability and economic factors. It was found that the optimum output can be achieved from a low temperature heat source around 38 0C, chilled water temperature of 8 0C with a vacuum condition of 695 Pa.
URI: http://hdl.handle.net/10356/73791
DOI: 10.32657/10356/73791
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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