Particle Movement and Separation Phenomena for a Gravity Separator: II. Experimental Data and Performance of Distance-Transition Markov Models

dc.contributor.author Balascio, Carmine
dc.contributor.author Misra, Manjit
dc.contributor.author Misra, Manjit
dc.contributor.author Johnson, Howard
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2018-02-14T13:40:33.000
dc.date.accessioned 2020-06-29T22:40:43Z
dc.date.available 2020-06-29T22:40:43Z
dc.date.copyright Thu Jan 01 00:00:00 UTC 1987
dc.date.embargo 2014-09-08
dc.date.issued 1987
dc.description.abstract <p>Linear programming procedures are used to fit stationary and nonstationary distance-transition Markov probability models to experimentally obtained particle distribution data from the deck of a gravity separator. Particle movement modeled is that of a light discard fraction. Performance of the models is examined by comparing predicted "typical'' particle pathways with observed particle pathways. The Markov process is found to be an appropriate model of particle movement.</p>
dc.description.comments <p>This article is from <em>Transactions of the ASAE</em> 30 (1987): 1840–1847, doi:<a href="http://dx.doi.org/10.13031/2013.30647" target="_blank">10.13031/2013.30647</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/544/
dc.identifier.articleid 1826
dc.identifier.contextkey 6092565
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/544
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/1322
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/544/1987_Balascio_ParticleMovementII.pdf|||Sat Jan 15 00:53:59 UTC 2022
dc.source.uri 10.13031/2013.30647
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.keywords Seed Science Center
dc.title Particle Movement and Separation Phenomena for a Gravity Separator: II. Experimental Data and Performance of Distance-Transition Markov Models
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication a1d94dd4-52b8-4e60-b8a8-e742eefa9a59
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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