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Sustainable development policy focuses on reducing the carbon footprint generated by the global industry and energy sector. Replacing conventional energy sources with environmentally friendly ones requires advanced research to increase energy efficiency and reduce the instability and intermittence of renewable sources. Moreover, adsorption chillers are an opportunity to introduce net-zero emission technologies to the refrigeration, air-conditioning, and desalination industries. Adsorption devices could be popularized if a method of effective heat transfer in the volume of the adsorption bed is developed. The innovative concept of introducing fluidized beds into the adsorption system can achieve the most promising results in improving energy efficiency. To confirm the adopted assumption, heat transfer coefficient calculations for the packed and fluidized bed were carried out in this paper based on experimental tests and literature data. The empirical research aims to extend the fundamental knowledge in the implementation of fluidization under low-pressure conditions, characteristic of the adsorption systems' working cycle. Experiments were conducted on a unique test stand equipped with the Intensified Heat Transfer Adsorption Bed (IHTAB) reactor prototype. Five adsorption bed samples were analyzed. The reference sample consisted only of silica gel, and the subsequent ones contained aluminum or carbon nanotubes with 5 and 10% additions. In the case of samples with admixtures, the fluidized state increased the heat transfer coefficient on average from approx. 36.9 W/m2 K to approx. 245.4 W/m2 K. [ABSTRACT FROM AUTHOR]

The idea of fluidised bed application allows a significantly increased heat transfer coefficient between adsorption bed and the surface of a heat exchanger, improving the performance of adsorption cooling and desalination systems [[11]]. The results confirmed the effect of the duration of adsorption and desorption on the COP and SCP of the adsorption chiller. The paper [[9]] presents experimental results of the metal-based and carbon nanotube additives influence on sorption kinetics of a silica-gel-based adsorption bed in an adsorption chiller. The authors in [[8]] conducted energy and exergy analyses of an adsorption chiller to investigate the effect of recooling-water temperatures on the cooling capacity and COP with variable cycle modes. [Extracted from the article]

One of the main disadvantages of conventional fixed-bed adsorption chillers is the low coefficient of performance due to the high voidage of the sorbent beds. The common method, which can help to handle this problem, is modifying the beds' design, including the application of fluidization. An innovative idea, shown in the article, constitutes in the use of the fluidized bed of sorbent, instead of the conventional, fixed-bed, commonly used nowadays in the adsorption chillers. Bed-to-wall heat transfer coefficients for fixed and fluidized beds of adsorbent are determined in the study. Effects of Sorbent particles diameters and velocities of fluidizing gas are discussed in the study. The calculations confirmed that the bed-to-wall heat transfer coefficient in the fluidized bed of adsorbent is much higher than that in a conventional bed. The proposed idea allows significantly reducing the size of a chiller and overcome the main reason for the limited dissemination of the adsorption cooling technology. [ABSTRACT FROM AUTHOR]

Since the adsorption chillers do not use primary energy as driving source the possibility to employ low temperature waste heat sources in cooling energy production receives nowadays much attention of the industry and science community. However, the performance of the thermally driven adsorption systems is lower than that of other heat driven heating/cooling systems. Low coefficients of performance are one of the main disadvantages of adsorption coolers. It is the result of a poor heat transfer coefficient between the bed and the immersed heating surfaces of a built-in heat exchanger system. The purpose of this work is to study the effect of thermal conductance values of sorption elements and evaporator as well as other design parameters on the performance of a re-heat two-stage adsorption chiller. One of the main energy efficiency factors in cooling production, i. e. cooling capacity for wide-range of both design and operating parameters is analyzed in the paper. Moreover, the work introduces artificial intelligence approach for the optimization study of the adsorption cooler. The ANFIS was employed in the work. The increase in both the bed and evaporator conductance provides better performance of the considered innovative adsorption chiller. The highest obtained value of cooling capacity is 21.7 kW and it can be achieved for the following design and operational parameters of the considered re-heat twostage adsorption chiller: Msorb = 40 kg, t = 1300 s, T = 80 ºC, Csorb/Cmet = 50, hAsorb = 4000 W/K, hAevap = 4000 W/K. [ABSTRACT FROM AUTHOR]

The paper introduces the artificial intelligence (AI) approach for modeling fluidized adsorption beds. The idea of fluidized bed application allows a significantly increased heat transfer coefficient between adsorption bed and the surface of a heat exchanger, improving the performance of adsorption cooling and desalination systems. The Long Short-Term Memory (LSTM) network algorithm was used, classified as a deep learning method, to predict the vapor mass quantity in the adsorption bed. The research used an LSTM network with two hidden layers. The network used in the study is composed of seven inputs (absolute pressures in the adsorption chamber and evaporator, the temperatures in adsorption chamber and evaporator, relative pressure, the temperatures in the center of adsorption bed and 25 mm from the bed center, the kind of the solids mixture, the percentage value of the addition) and one output (mass of the sorption bed). The paper presents numerical research concerning mass prediction with the algorithm mentioned above for three sorbents in fixed ad fluidized beds. The results obtained by the developed algorithm of the LSTM network and the experimental tests are in good agreement of the matching the results above 0.95. [ABSTRACT FROM AUTHOR]