Effect of upflow velocity and hydraulic retention time in anaerobic fluidized-bed reactors used for hydrogen production

The degradation of 2,4,6,-trichlorophenol (2,4,6-TCP), 2,3,4,6-tetra-chlorophenol (2,3,4,6-TeCP) and pentachlorophenol (PCP) was evaluated in oxic fluidized-bed reactors. The pseudo-steady-state reactor operation at a hydraulic retention time of 5 hours and feed concentrations of 54 mg/l of 2,4,6-TCP and 64 mg/l of 2,3,4,6-TeCP resulted in stable and effective removal performances on these compounds. GC/MS results indicated over 99 % removal of both 2,4,6-TCP and 2,3,4,6-TeCP. However, PCP degradation at 74 mg/l feed concentration was neglible under these conditions. Further, a denitrifying biofilm was developed which was able to use 4-chlorophenol (4-CP) as the sole electron donor in denitrification reactions. No anoxie biofilm able to degrade 2,4-dichlorophenol (2,4-DCP) or PCP degradation in the presence of potassium nitrate could be developed.

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Longitudinal dispersion and biomass hold-up of anaerobic fluidized bed reactors

Water Science & Technology ◽

10.2166/wst.1996.0583 ◽

1996 ◽

Vol 34 (5-6) ◽

pp. 461-468 ◽

Cited By ~ 1

Author(s):

M. Turan ◽

I. Öztürk

Keyword(s):

Fluidized Bed ◽

Retention Time ◽

Fluidized Beds ◽

Hydraulic Retention Time ◽

Biomass Concentration ◽

Pulse Response ◽

Longitudinal Dispersion ◽

Fluidized Bed Reactors ◽

Biofilm Growth ◽

Biological Growth

Longitudinal dispersion in fluidized bed reactors was studied using pulse-response techniques for both clean and anaerobic-biofilm coated media. A large number of experimental data on the longitudinal dispersion and biofilm growth in the anaerobic fluidized bed reactors (AFBRs) were investigated. Some correlations applicable to fluidized beds were obtained for both the hydraulic retention time and the biomass concentration versus the ratio Pe/Re. The biomass concentration tends to zero for a critical retention time in AFBRs. The biological growth in the bed causes an increase of Pe number.

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INFLUENCE OF HYDRAULIC RETENTION TIME ON HYDROGEN PRODUCTION BY TREATING CHEESE WHEY WASTEWATER IN ANAEROBIC FLUIDIZED BED BIOREACTOR - AN APPROACH FOR DEVELOPING COUNTRIES

Brazilian Journal of Chemical Engineering ◽

10.1590/0104-6632.20190363s20190075 ◽

2019 ◽

Vol 36 (3) ◽

pp. 1109-1117 ◽

Cited By ~ 1

Author(s):

Thiago D. Marques ◽

Williane V. Macêdo ◽

Fernanda S. Peiter ◽

Anna A. T. L. Bonfim ◽

Isabel K. Sakamoto ◽

...

Keyword(s):

Developing Countries ◽

Hydrogen Production ◽

Fluidized Bed ◽

Retention Time ◽

Cheese Whey ◽

Hydraulic Retention Time ◽

Fluidized Bed Bioreactor

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Effect of hydraulic retention time on metal precipitation in sulfate reducing inverse fluidized bed reactors

Journal of Chemical Technology & Biotechnology ◽

10.1002/jctb.4296 ◽

2014 ◽

Vol 90 (1) ◽

pp. 120-129 ◽

Cited By ~ 11

Author(s):

Denys Kristalia Villa Gomez ◽

Anne Marie Enright ◽

Eki Listya Rini ◽

Audrey Buttice ◽

Herman Kramer ◽

...

Keyword(s):

Fluidized Bed ◽

Retention Time ◽

Hydraulic Retention Time ◽

Fluidized Bed Reactors ◽

Sulfate Reducing ◽

Metal Precipitation ◽

Inverse Fluidized Bed

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Hydrogen Production by Fluidized Bed Reactors: A Quantitative Perspective Using the Supervised Machine Learning Approach

J ◽

10.3390/j4030022 ◽

2021 ◽

Vol 4 (3) ◽

pp. 266-287

Author(s):

Zheng Lian ◽

Yixiao Wang ◽

Xiyue Zhang ◽

Abubakar Yusuf ◽

Lord Famiyeh ◽

...

Keyword(s):

Machine Learning ◽

Hydrogen Production ◽

Fluidized Bed ◽

Biomass Gasification ◽

Supervised Machine Learning ◽

Fluidized Bed Reactors ◽

Hydrogen Yield ◽

Carbon Conversion ◽

Operational Parameters ◽

Operational Conditions

The current hydrogen generation technologies, especially biomass gasification using fluidized bed reactors (FBRs), were rigorously reviewed. There are involute operational parameters in a fluidized bed gasifier that determine the anticipated outcomes for hydrogen production purposes. However, limited reviews are present that link these parametric conditions with the corresponding performances based on experimental data collection. Using the constructed artificial neural networks (ANNs) as the supervised machine learning algorithm for data training, the operational parameters from 52 literature reports were utilized to perform both the qualitative and quantitative assessments of the performance, such as the hydrogen yield (HY), hydrogen content (HC) and carbon conversion efficiency (CCE). Seven types of operational parameters, including the steam-to-biomass ratio (SBR), equivalent ratio (ER), temperature, particle size of the feedstock, residence time, lower heating value (LHV) and carbon content (CC), were closely investigated. Six binary parameters have been identified to be statistically significant to the performance parameters (hydrogen yield (HY)), hydrogen content (HC) and carbon conversion efficiency (CCE)) by analysis of variance (ANOVA). The optimal operational conditions derived from the machine leaning were recommended according to the needs of the outcomes. This review may provide helpful insights for researchers to comprehensively consider the operational conditions in order to achieve high hydrogen production using fluidized bed reactors during biomass gasification.

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