Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network
[Display omitted] •Carbon coated carriers and PU-foam frame in A/O MBBR enhanced biomass adhesion.•>95 % COD and ∼98 % NH4-N removals were observed at C/N ratios ≥ 6.75 and 3.5.•Maximum total nitrogen and PO43-- P removals were observed as 87.9% and 93%.•FF-BP-NN model was developed for accurate...
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Veröffentlicht in: | Bioresource technology 2023-03, Vol.371, p.128641-128641, Article 128641 |
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creator | Saidulu, Duduku Srivastava, Ashish Gupta, Ashok Kumar |
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•Carbon coated carriers and PU-foam frame in A/O MBBR enhanced biomass adhesion.•>95 % COD and ∼98 % NH4-N removals were observed at C/N ratios ≥ 6.75 and 3.5.•Maximum total nitrogen and PO43-- P removals were observed as 87.9% and 93%.•FF-BP-NN model was developed for accurate prediction of reactor performance.•Optimal operational conditions were evaluated using validated ANN model.
A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH4-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH4-N (∼98 %) and PO43--P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed. |
doi_str_mv | 10.1016/j.biortech.2023.128641 |
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•Carbon coated carriers and PU-foam frame in A/O MBBR enhanced biomass adhesion.•>95 % COD and ∼98 % NH4-N removals were observed at C/N ratios ≥ 6.75 and 3.5.•Maximum total nitrogen and PO43-- P removals were observed as 87.9% and 93%.•FF-BP-NN model was developed for accurate prediction of reactor performance.•Optimal operational conditions were evaluated using validated ANN model.
A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH4-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH4-N (∼98 %) and PO43--P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed.</description><identifier>ISSN: 0960-8524</identifier><identifier>EISSN: 1873-2976</identifier><identifier>DOI: 10.1016/j.biortech.2023.128641</identifier><identifier>PMID: 36681347</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Artificial neural network ; Biofilms ; Bioreactors ; Carriers ; Denitrification ; Integrated moving bed biofilm reactor ; Neural Networks, Computer ; Nitrification ; Nitrogen - analysis ; Waste Disposal, Fluid ; Waste Products ; Wastewater</subject><ispartof>Bioresource technology, 2023-03, Vol.371, p.128641-128641, Article 128641</ispartof><rights>2023 Elsevier Ltd</rights><rights>Copyright © 2023 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-a06876c9d7353e7d5bee078c25a31c82b52dd3b2923f1055f3b3b451cac80a9f3</citedby><cites>FETCH-LOGICAL-c368t-a06876c9d7353e7d5bee078c25a31c82b52dd3b2923f1055f3b3b451cac80a9f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0960852423000676$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36681347$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Saidulu, Duduku</creatorcontrib><creatorcontrib>Srivastava, Ashish</creatorcontrib><creatorcontrib>Gupta, Ashok Kumar</creatorcontrib><title>Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network</title><title>Bioresource technology</title><addtitle>Bioresour Technol</addtitle><description>[Display omitted]
•Carbon coated carriers and PU-foam frame in A/O MBBR enhanced biomass adhesion.•>95 % COD and ∼98 % NH4-N removals were observed at C/N ratios ≥ 6.75 and 3.5.•Maximum total nitrogen and PO43-- P removals were observed as 87.9% and 93%.•FF-BP-NN model was developed for accurate prediction of reactor performance.•Optimal operational conditions were evaluated using validated ANN model.
A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH4-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH4-N (∼98 %) and PO43--P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed.</description><subject>Artificial neural network</subject><subject>Biofilms</subject><subject>Bioreactors</subject><subject>Carriers</subject><subject>Denitrification</subject><subject>Integrated moving bed biofilm reactor</subject><subject>Neural Networks, Computer</subject><subject>Nitrification</subject><subject>Nitrogen - analysis</subject><subject>Waste Disposal, Fluid</subject><subject>Waste Products</subject><subject>Wastewater</subject><issn>0960-8524</issn><issn>1873-2976</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUctu1DAUtRCIDoVfqLxkk6kfieOwoqpKi1SJDawtx76ZeprYwXZa4PP4MhzSsmVjS_eel30QOqNkTwkV58d970LMYO72jDC-p0yKmr5AOypbXrGuFS_RjnSCVLJh9Ql6k9KREMJpy16jEy6EpLxud-j31bgYZ3V2_oDzHeAZ4hDipL0BHAbsfIZD1Bks1j78cOZ8PfAUHlZCX8Ylx-DGCUfQJof4AV-kBClN4PMqEOJBe2dSoVvslxxdWaSCLhJ6_DsNc3aT-1UyBI-XtAoPUJRLjkcdi4M293iOYdaHDeNhiYXrIT-GeP8WvRr0mODd032Kvn26-np5U91-uf58eXFbGS5krjQRshWmsy1vOLS26QFIKw1rNKdGsr5h1vKedYwPlDTNwHve1w012kiiu4GfovebbonyfYGU1eSSgXHUHsKSFGuFZDURTBSo2KAmhpQiDGqObtLxp6JErf2po3ruT639qa2_Qjx78lj6Cew_2nNhBfBxA0B56YODqJIpP2rAuggmKxvc_zz-ACf6tYc</recordid><startdate>202303</startdate><enddate>202303</enddate><creator>Saidulu, Duduku</creator><creator>Srivastava, Ashish</creator><creator>Gupta, Ashok Kumar</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202303</creationdate><title>Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network</title><author>Saidulu, Duduku ; Srivastava, Ashish ; Gupta, Ashok Kumar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-a06876c9d7353e7d5bee078c25a31c82b52dd3b2923f1055f3b3b451cac80a9f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial neural network</topic><topic>Biofilms</topic><topic>Bioreactors</topic><topic>Carriers</topic><topic>Denitrification</topic><topic>Integrated moving bed biofilm reactor</topic><topic>Neural Networks, Computer</topic><topic>Nitrification</topic><topic>Nitrogen - analysis</topic><topic>Waste Disposal, Fluid</topic><topic>Waste Products</topic><topic>Wastewater</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saidulu, Duduku</creatorcontrib><creatorcontrib>Srivastava, Ashish</creatorcontrib><creatorcontrib>Gupta, Ashok Kumar</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Bioresource technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saidulu, Duduku</au><au>Srivastava, Ashish</au><au>Gupta, Ashok Kumar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network</atitle><jtitle>Bioresource technology</jtitle><addtitle>Bioresour Technol</addtitle><date>2023-03</date><risdate>2023</risdate><volume>371</volume><spage>128641</spage><epage>128641</epage><pages>128641-128641</pages><artnum>128641</artnum><issn>0960-8524</issn><eissn>1873-2976</eissn><abstract>[Display omitted]
•Carbon coated carriers and PU-foam frame in A/O MBBR enhanced biomass adhesion.•>95 % COD and ∼98 % NH4-N removals were observed at C/N ratios ≥ 6.75 and 3.5.•Maximum total nitrogen and PO43-- P removals were observed as 87.9% and 93%.•FF-BP-NN model was developed for accurate prediction of reactor performance.•Optimal operational conditions were evaluated using validated ANN model.
A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH4-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH4-N (∼98 %) and PO43--P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>36681347</pmid><doi>10.1016/j.biortech.2023.128641</doi><tpages>1</tpages></addata></record> |
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subjects | Artificial neural network Biofilms Bioreactors Carriers Denitrification Integrated moving bed biofilm reactor Neural Networks, Computer Nitrification Nitrogen - analysis Waste Disposal, Fluid Waste Products Wastewater |
title | Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network |
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