Loading…

Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation

A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is opt...

Full description

Saved in:
Bibliographic Details
Published in:Hydrometallurgy 2003-10, Vol.71 (1), p.89-96
Main Authors: Gatti, M.N., Milocco, R.H., Giaveno, A.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3
cites cdi_FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3
container_end_page 96
container_issue 1
container_start_page 89
container_title Hydrometallurgy
container_volume 71
creator Gatti, M.N.
Milocco, R.H.
Giaveno, A.
description A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is optimal in the sense of minimum variance. The results obtained improve the prediction error associated to the use of the current “knowledge-based” models. Results on modeling the kinetics of the bacterium Acidithiobacillus ferrooxidans, previously called Thiobacillus ferrooxidans, growing in ferrous iron as energy source in a batch airlift reactor are presented. The prediction error bound associated with the model is deduced theoretically and calculated for the application case.
doi_str_mv 10.1016/S0304-386X(03)00177-4
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_27853426</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0304386X03001774</els_id><sourcerecordid>27853426</sourcerecordid><originalsourceid>FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3</originalsourceid><addsrcrecordid>eNqFkDlPxDAQhS0EEsvxE5DSgKAI-EjsbIUQ4pJAFFDQWY49gQETL3aW49_jzSIoqZ5G8703mkfIDqOHjDJ5dEcFrUrRyId9Kg4oZUqV1QqZsEZNS8bqZpVMfpF1spHSM6VUCsUmZHYTHHjsH4vhCYrW2AEiGl-ET3RmwNAXoSs6iDHMU4Exzx84PBUnFl1WDNmB3ufdyIyuPhXztEh8ifi4UOxz6Cz4MW-LrHXGJ9j-0U1yf352f3pZXt9eXJ2eXJdWyGYoTeccp1VbOVsx2YKoueFT2XS1sKAUNFxYXgOvW1BuypkBzttOVlIZCdyJTbK3jJ3F8DaHNOhXTBa8Nz3kVzRXTS0qLjNYL0EbQ0oROj2L-Gril2ZUL-rVY7160Z2mQo_16ir7dn8OmGSN76LpLaY_c81FLrjJ3PGSg_zsO0LUySL0FhxGsIN2Af-59A0XipKe</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>27853426</pqid></control><display><type>article</type><title>Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation</title><source>Elsevier</source><creator>Gatti, M.N. ; Milocco, R.H. ; Giaveno, A.</creator><creatorcontrib>Gatti, M.N. ; Milocco, R.H. ; Giaveno, A.</creatorcontrib><description>A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is optimal in the sense of minimum variance. The results obtained improve the prediction error associated to the use of the current “knowledge-based” models. Results on modeling the kinetics of the bacterium Acidithiobacillus ferrooxidans, previously called Thiobacillus ferrooxidans, growing in ferrous iron as energy source in a batch airlift reactor are presented. The prediction error bound associated with the model is deduced theoretically and calculated for the application case.</description><identifier>ISSN: 0304-386X</identifier><identifier>EISSN: 1879-1158</identifier><identifier>DOI: 10.1016/S0304-386X(03)00177-4</identifier><identifier>CODEN: HYDRDA</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applied sciences ; Bioleaching ; Biooxidation ; Exact sciences and technology ; Ferrous iron oxidation ; Hydrometallurgy ; Kriging interpolation ; Metals. Metallurgy ; Production of metals ; Production of non ferrous metals. Process materials</subject><ispartof>Hydrometallurgy, 2003-10, Vol.71 (1), p.89-96</ispartof><rights>2003</rights><rights>2003 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3</citedby><cites>FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,776,780,785,786,23909,23910,25118,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=15233718$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Gatti, M.N.</creatorcontrib><creatorcontrib>Milocco, R.H.</creatorcontrib><creatorcontrib>Giaveno, A.</creatorcontrib><title>Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation</title><title>Hydrometallurgy</title><description>A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is optimal in the sense of minimum variance. The results obtained improve the prediction error associated to the use of the current “knowledge-based” models. Results on modeling the kinetics of the bacterium Acidithiobacillus ferrooxidans, previously called Thiobacillus ferrooxidans, growing in ferrous iron as energy source in a batch airlift reactor are presented. The prediction error bound associated with the model is deduced theoretically and calculated for the application case.</description><subject>Applied sciences</subject><subject>Bioleaching</subject><subject>Biooxidation</subject><subject>Exact sciences and technology</subject><subject>Ferrous iron oxidation</subject><subject>Hydrometallurgy</subject><subject>Kriging interpolation</subject><subject>Metals. Metallurgy</subject><subject>Production of metals</subject><subject>Production of non ferrous metals. Process materials</subject><issn>0304-386X</issn><issn>1879-1158</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><recordid>eNqFkDlPxDAQhS0EEsvxE5DSgKAI-EjsbIUQ4pJAFFDQWY49gQETL3aW49_jzSIoqZ5G8703mkfIDqOHjDJ5dEcFrUrRyId9Kg4oZUqV1QqZsEZNS8bqZpVMfpF1spHSM6VUCsUmZHYTHHjsH4vhCYrW2AEiGl-ET3RmwNAXoSs6iDHMU4Exzx84PBUnFl1WDNmB3ufdyIyuPhXztEh8ifi4UOxz6Cz4MW-LrHXGJ9j-0U1yf352f3pZXt9eXJ2eXJdWyGYoTeccp1VbOVsx2YKoueFT2XS1sKAUNFxYXgOvW1BuypkBzttOVlIZCdyJTbK3jJ3F8DaHNOhXTBa8Nz3kVzRXTS0qLjNYL0EbQ0oROj2L-Gril2ZUL-rVY7160Z2mQo_16ir7dn8OmGSN76LpLaY_c81FLrjJ3PGSg_zsO0LUySL0FhxGsIN2Af-59A0XipKe</recordid><startdate>20031001</startdate><enddate>20031001</enddate><creator>Gatti, M.N.</creator><creator>Milocco, R.H.</creator><creator>Giaveno, A.</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope></search><sort><creationdate>20031001</creationdate><title>Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation</title><author>Gatti, M.N. ; Milocco, R.H. ; Giaveno, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Applied sciences</topic><topic>Bioleaching</topic><topic>Biooxidation</topic><topic>Exact sciences and technology</topic><topic>Ferrous iron oxidation</topic><topic>Hydrometallurgy</topic><topic>Kriging interpolation</topic><topic>Metals. Metallurgy</topic><topic>Production of metals</topic><topic>Production of non ferrous metals. Process materials</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gatti, M.N.</creatorcontrib><creatorcontrib>Milocco, R.H.</creatorcontrib><creatorcontrib>Giaveno, A.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><jtitle>Hydrometallurgy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gatti, M.N.</au><au>Milocco, R.H.</au><au>Giaveno, A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation</atitle><jtitle>Hydrometallurgy</jtitle><date>2003-10-01</date><risdate>2003</risdate><volume>71</volume><issue>1</issue><spage>89</spage><epage>96</epage><pages>89-96</pages><issn>0304-386X</issn><eissn>1879-1158</eissn><coden>HYDRDA</coden><abstract>A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is optimal in the sense of minimum variance. The results obtained improve the prediction error associated to the use of the current “knowledge-based” models. Results on modeling the kinetics of the bacterium Acidithiobacillus ferrooxidans, previously called Thiobacillus ferrooxidans, growing in ferrous iron as energy source in a batch airlift reactor are presented. The prediction error bound associated with the model is deduced theoretically and calculated for the application case.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0304-386X(03)00177-4</doi><tpages>8</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0304-386X
ispartof Hydrometallurgy, 2003-10, Vol.71 (1), p.89-96
issn 0304-386X
1879-1158
language eng
recordid cdi_proquest_miscellaneous_27853426
source Elsevier
subjects Applied sciences
Bioleaching
Biooxidation
Exact sciences and technology
Ferrous iron oxidation
Hydrometallurgy
Kriging interpolation
Metals. Metallurgy
Production of metals
Production of non ferrous metals. Process materials
title Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-22T16%3A24%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modeling%20the%20bacterial%20oxidation%20of%20ferrous%20iron%20with%20Acidithiobacillus%20ferrooxidans%20using%20kriging%20interpolation&rft.jtitle=Hydrometallurgy&rft.au=Gatti,%20M.N.&rft.date=2003-10-01&rft.volume=71&rft.issue=1&rft.spage=89&rft.epage=96&rft.pages=89-96&rft.issn=0304-386X&rft.eissn=1879-1158&rft.coden=HYDRDA&rft_id=info:doi/10.1016/S0304-386X(03)00177-4&rft_dat=%3Cproquest_cross%3E27853426%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c368t-afdd204b4dc416be352a2968f53ce77e823c25e25be7d921ae22bf6467a6e2d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=27853426&rft_id=info:pmid/&rfr_iscdi=true