Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55039
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dc.contributor.authorP. Satjaritanunen_US
dc.contributor.authorY. Khunatornen_US
dc.contributor.authorN. Vorayosen_US
dc.contributor.authorS. Shimpaleeen_US
dc.contributor.authorE. Bringleyen_US
dc.date.accessioned2018-09-05T02:51:11Z-
dc.date.available2018-09-05T02:51:11Z-
dc.date.issued2016-03-01en_US
dc.identifier.issn18732909en_US
dc.identifier.issn09619534en_US
dc.identifier.other2-s2.0-84956662790en_US
dc.identifier.other10.1016/j.biombioe.2016.01.018en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84956662790&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55039-
dc.description.abstract© 2016 Elsevier Ltd. The objective of this work is to conduct a parametric study on the design variables and flow distribution of a Continuous Stirred Tank Reactor (CSTR). The numerical solutions were obtained by using Lattice Boltzmann Method (LBM) technique. Three different designs of CSTR with Napier grass as substance were evaluated for mixing efficiency, vorticity, and flow behavior, Model 1: one propeller no baffle tank, Model 2: one propeller with baffles tank, and Model 3: double propellers with baffles tank. The results show that the fluid velocity and the direction of fluid motion play the major role on the mixing characteristic. The propellers, baffles plates, and stirring speeds are significant factors on the fluid direction and thus the mixing performance. The solid-liquid mixing efficiency can be calculated from the numerical results of Discrete Phase Model (DPM) by image analysis technique. The mixing efficiency of Models 1, 2, and 3 are 10.08%, 23.77% and 34.66%, respectively. The power numbers which indicate the power consumption of the system of Models 1, 2, and 3 are 0.91, 1.20 and 2.00, respectively. Therefore, Model 3 gives the best mixing efficiency but requires higher energy consumption. This work also characterized the mixing quality in various depth levels. The predictions implement along with the mixing efficiency in order to evaluate mixing efficiency of the system completely.en_US
dc.subjectAgricultural and Biological Sciencesen_US
dc.subjectEnergyen_US
dc.subjectEnvironmental Scienceen_US
dc.titleNumerical analysis of the mixing characteristic for napier grass in the continuous stirring tank reactor for biogas productionen_US
dc.typeJournalen_US
article.title.sourcetitleBiomass and Bioenergyen_US
article.volume86en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsUniversity of South Carolinaen_US
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