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超声辅助再生活性氧化铝的性能和能耗特性的实验和预测研究。

Experimental and predictive study on the performance and energy consumption characteristics for the regeneration of activated alumina assisted by ultrasound.

机构信息

School of Energy and Environment, Southeast University, Nanjing, PR China.

School of Energy and Environment, Southeast University, Nanjing, PR China; Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, PR China.

出版信息

Ultrason Sonochem. 2021 Jan;70:105314. doi: 10.1016/j.ultsonch.2020.105314. Epub 2020 Aug 24.

Abstract

Activated alumina used in dehumidification should be regenerated at more than 110 °C temperature, resulting in excessive energy consumption. Comparative experiments were conducted to study the feasibility and performance of ultrasonic assisted regeneration so as to lower the regeneration temperature and raise the efficiency. The mean regeneration speed, regeneration degree, and enhanced rate were used to evaluate the contribution of ultrasound in regeneration. The effective moisture diffusivity and desorption apparent activation energy were calculated by theoretical models, revealed the enhanced mechanism caused by ultrasound. Also, we proposed some specific indexes such as unit energy consumption and energy-saving ratio to assess the energy-saving characteristics of this process. The unit energy consumption was predicted by artificial neural network (ANN), and the recovered moisture adsorption of activated alumina was measured by the dynamic adsorption test. Our analysis illustrates that the introduction of power ultrasound in the process of regeneration can reduce the unit energy consumption and improve the recovered moisture adsorption, the unit energy consumption was decreased by 68.69% and the recovered moisture adsorption was improved by 16.7% under 180 W power ultrasound compared with non-ultrasonic assisted regeneration at 70 °C when initial moisture adsorption was 30%. Meanwhile, an optimal regeneration condition around the turning point could be obtained according to the predictive results of ANN, which can minimize the unit energy consumption. Moreover, it was found that a larger specific surface area of activated alumina induced by ultrasound contributed to a better recovered moisture adsorption.

摘要

用于除湿的活性氧化铝应在 110°C 以上的温度下再生,这会导致过高的能源消耗。进行了对比实验,以研究超声辅助再生的可行性和性能,从而降低再生温度并提高效率。平均再生速度、再生程度和增强率用于评估超声在再生中的贡献。通过理论模型计算有效水分扩散系数和脱附表观活化能,揭示了超声增强的机制。此外,我们还提出了一些特定的指标,如单位能耗和节能率,以评估该过程的节能特性。通过人工神经网络(ANN)预测单位能耗,并通过动态吸附试验测量活性氧化铝的回收水分吸附量。我们的分析表明,在再生过程中引入功率超声可以降低单位能耗并提高回收水分吸附量,与 70°C 下非超声辅助再生相比,当初始水分吸附量为 30%时,180W 功率超声可将单位能耗降低 68.69%,回收水分吸附量提高 16.7%。同时,根据 ANN 的预测结果可以得到一个接近转折点的最佳再生条件,从而可以最小化单位能耗。此外,发现超声诱导的更大的活性氧化铝比表面积有助于更好的回收水分吸附。

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