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dc.contributor.authorSkøien, Kristoffer Rist
dc.contributor.authorAlver, Morten
dc.contributor.authorAlfredsen, Jo Arve
dc.date.accessioned2019-09-16T06:30:21Z
dc.date.available2019-09-16T06:30:21Z
dc.date.created2019-01-08T15:58:31Z
dc.date.issued2018
dc.identifier.citationAquacultural Engineering. 2018, 82 1-11.nb_NO
dc.identifier.issn0144-8609
dc.identifier.urihttp://hdl.handle.net/11250/2616856
dc.description.abstractRotary feed spreaders are extensively used in large scale fish aquaculture and are tasked with distributing pelletized feed in a spatially uniform manner over the water surface. Questions have been raised with respect to the performance of classical spreader designs regarding the size and uniformity of the covered area as well as their inability to adapt to changing environmental conditions. This study presents a robotic model of rotary spreaders with experimental validations. Classic rotary spreaders are simulated as well as two alternative designs in the form of a spreader releasing pellets at an optimal initial ballistic angle and a motorized version to increase throw length and provide a more spatially homogeneous surface feed distribution. The alternative designs both yielded improved surface coverage without the need of higher conveying airspeed which may lead to increased pellet attrition. In addition, the motorized design may be used to position pellets at a given location within the sea cage, such as into the wind and current so that pellets can reside inside the sea cage for a prolonged period of time. The presented model may be of interest to researchers and equipment manufacturers who desire to explore performance of a given spreader design.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.titleModelling and simulation of rotary feed spreaders with application to sea cage aquaculture – A study of common and alternative designsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber1-11nb_NO
dc.source.volume82nb_NO
dc.source.journalAquacultural Engineeringnb_NO
dc.identifier.doi10.1016/j.aquaeng.2017.11.002
dc.identifier.cristin1652709
dc.description.localcodeThis article will not be available due to copyright restrictions (c) 2018 by Elseviernb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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