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Development of modified airlift reactor (MALR) for improving oxygen transfer: optimize design and operation condition using ‘design of experiment’ methodology

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Version 2 2019-02-17, 21:15
Version 1 2019-02-11, 13:41
journal contribution
posted on 2019-02-17, 21:15 authored by Saret Bun, Kritchart Wongwailikhit, Nattawin Chawaloesphonsiya, Jenyuk Lohwacharin, Phaly Ham, Pisut Painmanakul

Oxygen scarcity may significantly affect the process performance since it has low aqueous solubility and high demand by chemical and biological processes. The oxygen mass transfer is therefore necessary to enhance. This work aimed to develop the gas-liquid reactor, named Modified Airlift Reactor (MALR) for improving the oxygen transfer efficiency in terms of internal configurations and aeration parameters by equipping a vertical baffle for creating liquid circulation phenomena, and installing slanted baffles in the reactor riser to extend air-bubbles retention time and to improve their distributions. Since extremum conditions of the investigated factors may inefficient, optimum levels are required to identify. 2k factorial and response surface design of Design of Experiment (DOE) methodology were applied to optimize these complex variables in terms of overall liquid mass transfer coefficient (KLa) of clean water. As a result, the main effective factors of MALR with their optimum value are amount of baffles (Nb ∼ 3 baffles), baffle angle (α ∼ 50°), position of base area (Yr ∼ 10 cm), open space on baffle (As ∼ 90 cm2), and gas flow (Qg). Increasing Qg resulted better KLa for the studied ranges (2–18 LPM). At the optimum condition, the improvement of MALR in terms of KLa coefficient was increased up to 97% and 28% compared to the regular bubble column and airlift reactor, respectively, at a certain gas flow without any extra energy. The correlation models of KLa coefficient with significant variables and power consumption were constructed for future estimation purposes.

Funding

This research has been supported by ASEAN University Network/Southeast Asia Engineering Education Development Network (AUN/SEED-Net) Program of Japan International Cooperation Agency (JICA) through Collaborative Research (CR) Program JFY 2015.

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