Abstract: The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Abstract: Computational fluid dynamics (CFD) simulations
carried out in this paper show that spacer orientation has a major
influence on temperature patterns and on the heat transfer rates. The
local heat flux values significantly vary from high to very low values
at each filament when spacer touches the membrane surface. The
heat flux profile is more uniform when spacer filaments are not in
contact with the membrane thus making this arrangement more
beneficial. The temperature polarization is also found to be less in
this case when compared to the empty channel.