Literature DB >> 32890986

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

Xinzhu Mou1, Zhenqian Chen2.   

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.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Activated alumina; Artificial neural network; Energy consumption; Moisture adsorption; Regeneration; Ultrasonic

Year:  2020        PMID: 32890986      PMCID: PMC7786628          DOI: 10.1016/j.ultsonch.2020.105314

Source DB:  PubMed          Journal:  Ultrason Sonochem        ISSN: 1350-4177            Impact factor:   7.491


  12 in total

1.  Comparison of ultrasonic with stirrer performance for removal of sunset yellow (SY) by activated carbon prepared from wood of orange tree: artificial neural network modeling.

Authors:  A M Ghaedi; M Ghaedi; P Karami
Journal:  Spectrochim Acta A Mol Biomol Spectrosc       Date:  2014-11-13       Impact factor: 4.098

Review 2.  Application of airborne ultrasound in the convective drying of fruits and vegetables: A review.

Authors:  Kai Fan; Min Zhang; Arun S Mujumdar
Journal:  Ultrason Sonochem       Date:  2017-04-04       Impact factor: 7.491

3.  Evaluation on the air-borne ultrasound-assisted hot air convection thin-layer drying performance of municipal sewage sludge.

Authors:  G Y Sun; M Q Chen; Y W Huang
Journal:  Ultrason Sonochem       Date:  2016-06-24       Impact factor: 7.491

4.  Ultrasound assisted co-precipitation synthesis and catalytic performance of mesoporous nanocrystalline NiO-Al2O3 powders.

Authors:  Farnaz Rahbar Shamskar; Fereshteh Meshkani; Mehran Rezaei
Journal:  Ultrason Sonochem       Date:  2016-06-20       Impact factor: 7.491

Review 5.  Applications of artificial neural networks for adsorption removal of dyes from aqueous solution: A review.

Authors:  Abdol Mohammad Ghaedi; Azam Vafaei
Journal:  Adv Colloid Interface Sci       Date:  2017-04-26       Impact factor: 12.984

6.  Rapid and high-capacity ultrasonic assisted adsorption of ternary toxic anionic dyes onto MOF-5-activated carbon: Artificial neural networks, partial least squares, desirability function and isotherm and kinetic study.

Authors:  Hanieh Askari; Mehrorang Ghaedi; Kheibar Dashtian; Mohammad Hossein Ahmadi Azghandi
Journal:  Ultrason Sonochem       Date:  2016-11-01       Impact factor: 7.491

7.  Effect of ultrasound-assisted osmotic dehydration pretreatment on the convective drying of strawberry.

Authors:  Ezzeddine Amami; Wissal Khezami; Salma Mezrigui; Laxmikant S Badwaik; Asma Kammoun Bejar; Carmen Tellez Perez; Nabil Kechaou
Journal:  Ultrason Sonochem       Date:  2016-12-07       Impact factor: 7.491

Review 8.  Enhancement of mass transfer by ultrasound: Application to adsorbent regeneration and food drying/dehydration.

Authors:  Ye Yao
Journal:  Ultrason Sonochem       Date:  2016-02-02       Impact factor: 7.491

9.  Effects of ultrasonic pretreatments on quality, energy consumption and sterilization of barley grass in freeze drying.

Authors:  Xiaohuang Cao; Min Zhang; Arun S Mujumdar; Qifeng Zhong; Zhushang Wang
Journal:  Ultrason Sonochem       Date:  2017-06-19       Impact factor: 7.491

10.  Optimization and modeling of simultaneous ultrasound-assisted adsorption of ternary dyes using copper oxide nanoparticles immobilized on activated carbon using response surface methodology and artificial neural network.

Authors:  Abdol Mohammad Ghaedi; Shahnaz Karamipour; Azam Vafaei; Mohammad Mehdi Baneshi; Vahid Kiarostami
Journal:  Ultrason Sonochem       Date:  2018-10-06       Impact factor: 7.491

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