Performance evaluation and multi-objective optimization of a tubular indirect evaporative cooler integrated with moisture-conducting fibers

Indirect evaporative cooling (IEC) technology is an energy-efficient approach for regulating the indoor thermal environment of buildings. The conventional tubular indirect evaporative cooler (TIEC) may have a relatively low cooling efficiency due to poor wettability issues. The application of moisture-conducting fibers provides a feasible way to solve the above problem. However, the integration of moisture-conducting fibers with TIEC is still in the exploratory stage. This study proposed a novel moisture-conducting fiber-assisted TIEC and conducted a multi-objective optimization. An experimental facility and theoretical model of the proposed moisture- conducting fiber-assisted TIEC were developed. Based on the numerical model validated by experiments and response surface methodology (RSM), the regression models for performance prediction of the cooler were established. Eight input parameters including inlet air parameters, operating parameters and geometric parameters were selected, and four performance evaluation indicators were chosen as output responses. The parameter sensitivity of the regression models was analyzed. The multi-objective optimization was performed by considering the influence of different relative weights assigned to the output responses. Furthermore, the performance of the optimized cooler applied in different climate zones was predicted. The results showed that the product air temperature drop could achieve 8.8-11.3 degrees C after cooling by the cooler. The established regression models can predict the performance of the moisture-conducting fiber-assisted TIEC conveniently and effectively, which is expected to guide the design and optimization of engineering practices.