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Keywords
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ANOVA, fresh air temperature, gray relational grade, HMBAC system, input power, Taguchi method
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Abstract
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Various parameters have an impact on the fresh air temperature and input power of
a hybrid membrane-based air conditioning (HMBAC) system, such as pressure ratio,
membrane selectivity, membrane permeance, membrane area, air flowrate of the
dehumidification unit, and module length, number of fibers, and fiber outer diameter
of the humidification unit, which comprise both operational and structural parame-
ters. Therefore, in this study, the effects of these parameters on the system perfor-
mance are examined separately based on a statistical approach. The importance
order of each parameter and its contribution ratio are determined by using Taguchi
method and ANOVA analysis. The optimum level for each input parameter is deter-
mined using statistical analysis for the fresh air temperature and input power. Then,
for the simultaneous minimization of fresh air temperature and input power Taguchi-
gray relational grade (GRG) is used. GRG revealed that membrane selectivity, pres-
sure ratio, and membrane permeance with the contribution ratio of 37.87%, 32.51%,
and 10.55%, respectively, are the most critical parameters of the multiperformance
of an HMBAC system. Interestingly dehumidification from a humid airflow can be
more effective when membranes with low selectivity and high permeability are used.
In conclusion, the optimization outputs disclosed that both structural and operational
parameters have significant effects on the performance of the HMBAC system and
this optimization can be a helpful tool for designing a HMBAC systems to cover the
optimal conditions to develop a sustainable membrane-based air conditioning
system.
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