Optimization of Heat Transfer Coefficient in Fluidized Adsorption Bed By Gene Expression Programming Approach

Adsorption cooling and desalination techniques in adsorption chillers (AC) are one of the most promising areas in energy technologies. However, the main disadvantages of conventional packed-bed ACs are the low coefficient of performance and bulkiness. These are mainly due to the sorbent beds' high voidage, leading to low heat transfer coefficients. Despite many attempts, no practical solution has been deployed to handle this problem.

To fill this gap, we proposed a novel idea to employ fluidized adsorbent bed instead of the conventional, packed bed commonly used in traditional ACs. Furthermore, gene expression programming (GEP) was introduced as a novel artificial intelligence approach to optimize the heat transfer coefficient in the adsorption bed. The current studies, which include both calculations and model validation, are performed for an intensified heat transfer adsorption bed reactor designed for low-pressure adsorption processes. The adsorption bed is fluidized with water vapour generated in the evaporator. Silica gel as the parent adsorption material and carbon nanotubes and aluminum particles as two additives with different shares were applied in the tests. The heat transfer coefficient, measured during experiments and predicted by the developed model, is investigated and compared. The data evaluated by the model agrees well with the experimental results. Simulations showed that the performed GEP-based model correctly describes the heat transfer coefficient and can be applied to study the fluidized adsorption bed reactor and optimize the bed's operating strategy.

The described investigations are a reference point for further simulations of the intensified heat transfer adsorption bed reactor since they constitute a part of the work scheduled in project No. 2018/29/B/ST8/00442, "Research on sorption process intensification methods in modified construction of adsorbent beds," funded by the National Science Center, Poland.