Ontology type: schema:ScholarlyArticle Open Access: True
2016-03
AUTHORSMohammad Javad Jalalnezhad, Vahid Kamali
ABSTRACTCrude oil transport is one important part of the oil industry. Wax deposition is a very complex phenomenon that in recent years is one of the major challenges in oil industry. Wax deposited on the inner surface of crude oil pipelines are capable to reduce or completely stop the oil flow and the oil industry imposing large costs. The main objective of this study was to present a novel approach for predication of wax deposition thickness in single-phase turbulent flow rate. Using experimental data set and Adaptive neural-fuzzy inference system (ANFIS) model was developed. From the results predicted by this model, it can be pointed out that the ANFIS model can be used as powerful tools for prediction of wax deposition thickness in single-phase turbulent flow rate with mean square error, absolute relative deviation error and average absolute deviation error which are 0.00077034, 0.015720 and 0.097961, respectively. More... »
PAGES129-133
http://scigraph.springernature.com/pub.10.1007/s13202-015-0160-3
DOIhttp://dx.doi.org/10.1007/s13202-015-0160-3
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1009822600
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0915",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Interdisciplinary Engineering",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Engineering",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Shahid Bahonar University of Kerman",
"id": "https://www.grid.ac/institutes/grid.412503.1",
"name": [
"Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman, Iran",
"Young Researchers Society, Shahid Bahonar University of Kerman, Kerman, Iran"
],
"type": "Organization"
},
"familyName": "Jalalnezhad",
"givenName": "Mohammad Javad",
"id": "sg:person.015254325375.21",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015254325375.21"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Shahid Bahonar University of Kerman",
"id": "https://www.grid.ac/institutes/grid.412503.1",
"name": [
"Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman, Iran"
],
"type": "Organization"
},
"familyName": "Kamali",
"givenName": "Vahid",
"id": "sg:person.011700774335.38",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011700774335.38"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1081/lft-120038726",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001124844"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.fuel.2012.10.004",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004905373"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1004-9541(06)60135-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009513697"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00033-004-3056-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015970819",
"https://doi.org/10.1007/s00033-004-3056-5"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijmultiphaseflow.2011.02.007",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019546013"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1081/lft-100001231",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024135338"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/00908310490448253",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025864444"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0895-7177(97)00031-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028277073"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690420120",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029145625"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0020-7373(75)80002-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033324589"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1088/0957-0233/22/7/075701",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040506262"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/ef700434h",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055481024"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/ef700434h",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055481024"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/ef900920x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055482474"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/ef900920x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055482474"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/21.256541",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061121711"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/mspec.1984.6370431",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061427448"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tsmc.1985.6313399",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061793740"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2118/2175-pa",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1068954495"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2118/8071-ms",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1096936758"
],
"type": "CreativeWork"
}
],
"datePublished": "2016-03",
"datePublishedReg": "2016-03-01",
"description": "Crude oil transport is one important part of the oil industry. Wax deposition is a very complex phenomenon that in recent years is one of the major challenges in oil industry. Wax deposited on the inner surface of crude oil pipelines are capable to reduce or completely stop the oil flow and the oil industry imposing large costs. The main objective of this study was to present a novel approach for predication of wax deposition thickness in single-phase turbulent flow rate. Using experimental data set and Adaptive neural-fuzzy inference system (ANFIS) model was developed. From the results predicted by this model, it can be pointed out that the ANFIS model can be used as powerful tools for prediction of wax deposition thickness in single-phase turbulent flow rate with mean square error, absolute relative deviation error and average absolute deviation error which are 0.00077034, 0.015720 and 0.097961, respectively.",
"genre": "research_article",
"id": "sg:pub.10.1007/s13202-015-0160-3",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1053339",
"issn": [
"2190-0558",
"2190-0566"
],
"name": "Journal of Petroleum Exploration and Production Technology",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "6"
}
],
"name": "Development of an intelligent model for wax deposition in oil pipeline",
"pagination": "129-133",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"2ecb951dca5cbd6ff8cf70af09f1d5408f0326cace35c95c248d6dc2cf6e1514"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s13202-015-0160-3"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1009822600"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s13202-015-0160-3",
"https://app.dimensions.ai/details/publication/pub.1009822600"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-10T17:33",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8672_00000520.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1007%2Fs13202-015-0160-3"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s13202-015-0160-3'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s13202-015-0160-3'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13202-015-0160-3'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13202-015-0160-3'
This table displays all metadata directly associated to this object as RDF triples.
124 TRIPLES
21 PREDICATES
45 URIs
19 LITERALS
7 BLANK NODES