Advanced RTD Prediction and Optimization in Three- Phase Bubble Column Reactors- Leveraging Deep Learning for Enhanced Industrial Efficiency

Goddindla Sreenivasulu, R Ramakoteswara Rao, B Sarath Babu, P Akhila Swathantra and Asadi Srinivasulu
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P Akhila Swathantra: Department of Chemical Engineering, Sri Venkateswara University, India
Asadi Srinivasulu: Department of crcCARE, Newcastle, University of Newcastle, Australia

Biomedical Journal of Scientific & Technical Research, 2024, vol. 59, issue 5, 51965-51976

Abstract: This research aims to improve industrial efficiency by focusing on bubble column reactors, which are critical to many industrial processes. However, predicting residence time distribution (RTD) and optimizing reactor performance is challenging due to the complex interplay of factors like gas and liquid flow rates, particle size, reactor pressure, and temperature. To tackle these challenges, a Convolutional Neural Network (CNN) model is employed to analyze and optimize RTD in these reactors.

Keywords: Journals on Medical Drug and Therapeutics; Journals on Emergency Medicine; Physical Medicine and Rehabilitation; Journals on Infectious Diseases Addiction Science and Clinical Pathology; Open Access Clinical and Medical Journal; Journals on Biomedical Science; List of Open Access Medical Journal; Journals on Biomedical Engineering; Open Access Medical Journal; Biomedical Science Articles; Journal of Scientific and Technical Research (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:59:y:2024:i:5:p:51965-51976

DOI: 10.26717/BJSTR.2024.59.009364

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