Optimization and Modeling of Flow Characteristics of Low-Oil DDGS Using Regression Techniques

dc.citation.doi10.13031/trans.11928en_US
dc.citation.epage258en_US
dc.citation.issn0001-2351en_US
dc.citation.issue1en_US
dc.citation.jtitleTransactions of the ASABEen_US
dc.citation.spage249en_US
dc.citation.volume60en_US
dc.contributor.authorBhadra, Rumela
dc.contributor.authorAmbrose, R.P. Kingsly
dc.contributor.authorCasada, Mark E.
dc.contributor.authorSimsek, Senay
dc.contributor.authorSiliveru, Kaliramesh
dc.contributor.authoreidrbhadraen_US
dc.date.accessioned2017-03-17T20:27:46Z
dc.date.available2017-03-17T20:27:46Z
dc.date.issued2017-04-01
dc.date.published2017en_US
dc.descriptionCitation: R. Bhadra, R. P. K. Ambrose, M. E. Casada, S. Simsek, K. Siliveru. (2017). Optimization and Modeling of Flow Characteristics of Low-Oil DDGS Using Regression Techniques. Transactions of the ASABE. 60(1): 249-258. (doi: 10.13031/trans.11928)
dc.description.abstractStorage conditions, such as temperature, relative humidity (RH), consolidation pressure (CP), and time, affect the flow behavior of bulk solids such as distillers dried grains with solubles (DDGS), which is widely used as animal feed by the U.S. cattle and swine industries. The typical dry-grind DDGS production process in most corn ethanol plants has been adapted to facilitate oil extraction from DDGS for increased profits, resulting in production of low-oil DDGS. Many studies have shown that caking, and thus flow, of regular DDGS is an issue during handling and transportation. This study measured the dynamic flow properties of low-oil DDGS. Flow properties such as stability index (SI), basic flow energy (BFE), flow rate index (FRI), cohesion, Jenike flow index, and wall friction angle were measured at varying temperature (20°C, 40°C, 60°C), RH (40%, 60%, 80%), moisture content (MC; 8%, 10%, 12% w.b.), CP (generated by 0, 10, and 20 kg overbearing loads), and consolidation time (CT; 2, 4, 6, 8 days) for low-oil DDGS. Response surface modeling (RSM) and multivariate analysis showed that MC, temperature, and RH were the most influential variables on flow properties. The dynamic flow properties as influenced by environmental conditions were modeled using the RSM technique. Partial least squares regression yielded models with R2 values greater than 0.80 for SI, BFE, and cohesion as a function of MC, temperature, RH, CP, and CT using two principal components. These results provide critical information for quantifying and predicting the flow behavior of low-oil DDGS during commercial handling and transportation.en_US
dc.identifier.urihttp://hdl.handle.net/2097/35289
dc.language.isoen_USen_US
dc.relation.urihttps://doi.org/10.13031/trans.11928en_US
dc.relation.urihttp://www.sherpa.ac.uk/romeo/issn/0001-2351/
dc.rightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).en_US
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/?language=en
dc.subjectDynamic flow propertiesen_US
dc.subjectFlowabiltyen_US
dc.subjectLow-oil DDGSen_US
dc.subjectMultivariate modelingen_US
dc.titleOptimization and Modeling of Flow Characteristics of Low-Oil DDGS Using Regression Techniquesen_US
dc.typeArticle (publisher version)en_US

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