Effect of magnetic field on laminar forced convective heat transfer of MWCNT–Fe3O4/water hybrid nanofluid in a heated tube View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-20

AUTHORS

Jalal Alsarraf, Reza Rahmani, Amin Shahsavar, Masoud Afrand, Somchai Wongwises, Minh Duc Tran

ABSTRACT

A numerical investigation is carried out to assess the hydrothermal performance of a water-based hybrid nanofluid containing both Fe3O4 (magnetite) nanoparticles and carbon nanotubes (CNTs) in a heated tube in the presence of a constant non-uniform magnetic field. The magnetic field is created by three pairs of permanent magnets. The effects of Reynolds number, magnetite, and CNT volume concentrations as well as magnetic field strength are investigated. The acquired data for the case of without magnetic field confirmed higher values of heat transfer and pressure drop as a result of utilizing nanofluid compared with water. Additionally, it was found that the Nusselt number and pressure drop of the studied nanofluid samples increase significantly under the magnetic field. Moreover, the influence of magnetic field increases with an increase in the nanoparticle concentrations and magnetic field strength and decrease in the Reynolds number. The maximum increments of 109.31% and 25.02% in comparison with the case of without field were obtained in the average Nusselt number and pressure drop for hybrid nanofluid containing 0.9% magnetite and 1.35% CNT at Reynolds number of 500. More... »

PAGES

1-17

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10973-019-08078-y

DOI

http://dx.doi.org/10.1007/s10973-019-08078-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112262039


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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": "Public Authority for Applied Education and Training", 
          "id": "https://www.grid.ac/institutes/grid.459471.a", 
          "name": [
            "Automotive and Marine Engineering Department, College of Technological Studies (CTS), Public Authority for Applied Education and Training (PAAET), 70654, Shuwaikh, Kuwait"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alsarraf", 
        "givenName": "Jalal", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kermanshah University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.459724.9", 
          "name": [
            "Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rahmani", 
        "givenName": "Reza", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kermanshah University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.459724.9", 
          "name": [
            "Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shahsavar", 
        "givenName": "Amin", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Islamic Azad University of Najafabad", 
          "id": "https://www.grid.ac/institutes/grid.468905.6", 
          "name": [
            "Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Afrand", 
        "givenName": "Masoud", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "King Mongkut's University of Technology Thonburi", 
          "id": "https://www.grid.ac/institutes/grid.412151.2", 
          "name": [
            "Fluid Mechanics, Thermal Engineering and Multiphase Flow Research Lab. (FUTURE), Department of Mechanical Engineering, Faculty of Engineering, King Mongkut\u2019s University of Technology Thonburi, 10140, Bangmod, Bangkok, Thailand", 
            "The Academy of Science, The Royal Society of Thailand, Sanam Suea Pa, 10300, Dusit, Bangkok, Thailand"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wongwises", 
        "givenName": "Somchai", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ton Duc Thang University", 
          "id": "https://www.grid.ac/institutes/grid.444812.f", 
          "name": [
            "Division of Computational Mechatronics, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam", 
            "Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tran", 
        "givenName": "Minh Duc", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.ijheatfluidflow.2016.01.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000816193"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2015.01.031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002390340"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.synthmet.2007.05.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003540646"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.expthermflusci.2013.04.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004103466"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.expthermflusci.2015.07.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004721374"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physleta.2016.12.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018476714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.applthermaleng.2016.09.091", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020996580"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.icheatmasstransfer.2014.01.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022541023"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.icheatmasstransfer.2016.05.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023105198"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2009.04.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026025479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2013.09.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026586549"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00231-015-1743-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030682399", 
          "https://doi.org/10.1007/s00231-015-1743-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molliq.2016.12.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031909609"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01447973", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032571512", 
          "https://doi.org/10.1007/bf01447973"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tca.2015.08.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039111966"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.expthermflusci.2016.03.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039242810"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmmm.2003.09.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039838438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmmm.2003.09.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039838438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmmm.2016.12.129", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044099903"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.icheatmasstransfer.2016.09.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044473735"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.apt.2016.05.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051499826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pssb.200572720", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052678737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ed076p943", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055465321"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3642974", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057990499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.89.022310", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060745857"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.89.022310", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060745857"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cep.2017.03.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084064724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2017.06.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086031837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.applthermaleng.2017.07.100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090678964"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.enconman.2017.08.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091084616"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.applthermaleng.2017.09.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091492671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.expthermflusci.2017.09.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091895588"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2018.09.052", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107169703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2018.11.069", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110101435"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physrep.2018.11.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110373958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physrep.2018.11.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110373958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physrep.2018.11.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110397989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molliq.2018.12.055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110582692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molliq.2018.12.055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110582692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molliq.2018.12.055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110582692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00231-018-02558-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111153600", 
          "https://doi.org/10.1007/s00231-018-02558-x"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-02-20", 
    "datePublishedReg": "2019-02-20", 
    "description": "A numerical investigation is carried out to assess the hydrothermal performance of a water-based hybrid nanofluid containing both Fe3O4 (magnetite) nanoparticles and carbon nanotubes (CNTs) in a heated tube in the presence of a constant non-uniform magnetic field. The magnetic field is created by three pairs of permanent magnets. The effects of Reynolds number, magnetite, and CNT volume concentrations as well as magnetic field strength are investigated. The acquired data for the case of without magnetic field confirmed higher values of heat transfer and pressure drop as a result of utilizing nanofluid compared with water. Additionally, it was found that the Nusselt number and pressure drop of the studied nanofluid samples increase significantly under the magnetic field. Moreover, the influence of magnetic field increases with an increase in the nanoparticle concentrations and magnetic field strength and decrease in the Reynolds number. The maximum increments of 109.31% and 25.02% in comparison with the case of without field were obtained in the average Nusselt number and pressure drop for hybrid nanofluid containing 0.9% magnetite and 1.35% CNT at Reynolds number of 500.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10973-019-08078-y", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1294862", 
        "issn": [
          "1388-6150", 
          "1572-8943"
        ], 
        "name": "Journal of Thermal Analysis and Calorimetry", 
        "type": "Periodical"
      }
    ], 
    "name": "Effect of magnetic field on laminar forced convective heat transfer of MWCNT\u2013Fe3O4/water hybrid nanofluid in a heated tube", 
    "pagination": "1-17", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "51a56543b43b68e899e8a7a870cb10666ef70a959da75bf414a57f2db2437e79"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10973-019-08078-y"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112262039"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10973-019-08078-y", 
      "https://app.dimensions.ai/details/publication/pub.1112262039"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:31", 
    "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/v90/0000000346_0000000346/records_99803_00000004.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10973-019-08078-y"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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/s10973-019-08078-y'

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/s10973-019-08078-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10973-019-08078-y'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10973-019-08078-y'


 

This table displays all metadata directly associated to this object as RDF triples.

209 TRIPLES      21 PREDICATES      60 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10973-019-08078-y schema:about anzsrc-for:09
2 anzsrc-for:0915
3 schema:author Necb4ad7e802044948b9a51a5fea79652
4 schema:citation sg:pub.10.1007/bf01447973
5 sg:pub.10.1007/s00231-015-1743-8
6 sg:pub.10.1007/s00231-018-02558-x
7 https://doi.org/10.1002/pssb.200572720
8 https://doi.org/10.1016/j.applthermaleng.2016.09.091
9 https://doi.org/10.1016/j.applthermaleng.2017.07.100
10 https://doi.org/10.1016/j.applthermaleng.2017.09.009
11 https://doi.org/10.1016/j.apt.2016.05.015
12 https://doi.org/10.1016/j.cep.2017.03.018
13 https://doi.org/10.1016/j.enconman.2017.08.007
14 https://doi.org/10.1016/j.expthermflusci.2013.04.018
15 https://doi.org/10.1016/j.expthermflusci.2015.07.002
16 https://doi.org/10.1016/j.expthermflusci.2016.03.010
17 https://doi.org/10.1016/j.expthermflusci.2017.09.018
18 https://doi.org/10.1016/j.icheatmasstransfer.2014.01.012
19 https://doi.org/10.1016/j.icheatmasstransfer.2016.05.029
20 https://doi.org/10.1016/j.icheatmasstransfer.2016.09.015
21 https://doi.org/10.1016/j.ijheatfluidflow.2016.01.009
22 https://doi.org/10.1016/j.ijheatmasstransfer.2009.04.029
23 https://doi.org/10.1016/j.ijheatmasstransfer.2013.09.011
24 https://doi.org/10.1016/j.ijheatmasstransfer.2018.11.069
25 https://doi.org/10.1016/j.jmmm.2003.09.015
26 https://doi.org/10.1016/j.jmmm.2016.12.129
27 https://doi.org/10.1016/j.molliq.2016.12.013
28 https://doi.org/10.1016/j.molliq.2018.12.055
29 https://doi.org/10.1016/j.physleta.2016.12.017
30 https://doi.org/10.1016/j.physrep.2018.11.003
31 https://doi.org/10.1016/j.physrep.2018.11.004
32 https://doi.org/10.1016/j.powtec.2015.01.031
33 https://doi.org/10.1016/j.powtec.2017.06.023
34 https://doi.org/10.1016/j.powtec.2018.09.052
35 https://doi.org/10.1016/j.synthmet.2007.05.009
36 https://doi.org/10.1016/j.tca.2015.08.025
37 https://doi.org/10.1021/ed076p943
38 https://doi.org/10.1063/1.3642974
39 https://doi.org/10.1103/physreve.89.022310
40 schema:datePublished 2019-02-20
41 schema:datePublishedReg 2019-02-20
42 schema:description A numerical investigation is carried out to assess the hydrothermal performance of a water-based hybrid nanofluid containing both Fe3O4 (magnetite) nanoparticles and carbon nanotubes (CNTs) in a heated tube in the presence of a constant non-uniform magnetic field. The magnetic field is created by three pairs of permanent magnets. The effects of Reynolds number, magnetite, and CNT volume concentrations as well as magnetic field strength are investigated. The acquired data for the case of without magnetic field confirmed higher values of heat transfer and pressure drop as a result of utilizing nanofluid compared with water. Additionally, it was found that the Nusselt number and pressure drop of the studied nanofluid samples increase significantly under the magnetic field. Moreover, the influence of magnetic field increases with an increase in the nanoparticle concentrations and magnetic field strength and decrease in the Reynolds number. The maximum increments of 109.31% and 25.02% in comparison with the case of without field were obtained in the average Nusselt number and pressure drop for hybrid nanofluid containing 0.9% magnetite and 1.35% CNT at Reynolds number of 500.
43 schema:genre research_article
44 schema:inLanguage en
45 schema:isAccessibleForFree false
46 schema:isPartOf sg:journal.1294862
47 schema:name Effect of magnetic field on laminar forced convective heat transfer of MWCNT–Fe3O4/water hybrid nanofluid in a heated tube
48 schema:pagination 1-17
49 schema:productId N19d97de975f746ad8e794597c6b5171b
50 N458c2e8cc855433d943c8ceb06576e23
51 Nbdb36374417248d09bb0e2d9e19bdbef
52 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112262039
53 https://doi.org/10.1007/s10973-019-08078-y
54 schema:sdDatePublished 2019-04-11T09:31
55 schema:sdLicense https://scigraph.springernature.com/explorer/license/
56 schema:sdPublisher N1414c07e86ae4b8085ce99277ea27b98
57 schema:url https://link.springer.com/10.1007%2Fs10973-019-08078-y
58 sgo:license sg:explorer/license/
59 sgo:sdDataset articles
60 rdf:type schema:ScholarlyArticle
61 N14099f83cd46489b93f93599bc5a49bb schema:affiliation https://www.grid.ac/institutes/grid.459724.9
62 schema:familyName Rahmani
63 schema:givenName Reza
64 rdf:type schema:Person
65 N1414c07e86ae4b8085ce99277ea27b98 schema:name Springer Nature - SN SciGraph project
66 rdf:type schema:Organization
67 N19d97de975f746ad8e794597c6b5171b schema:name readcube_id
68 schema:value 51a56543b43b68e899e8a7a870cb10666ef70a959da75bf414a57f2db2437e79
69 rdf:type schema:PropertyValue
70 N1f168f23183940a2b1466861a6a8fae6 rdf:first Nfe7e77103aa443ae8d406dafe4b22c17
71 rdf:rest N490d6cdd194d405f989d0976b506e0ff
72 N3a10ce14153a40c291a5289e078973f8 rdf:first N8b0e1db6c5154c6aa6976e5d9a0f8148
73 rdf:rest Nee346405da154a9282efd19f3ffa2e22
74 N458c2e8cc855433d943c8ceb06576e23 schema:name doi
75 schema:value 10.1007/s10973-019-08078-y
76 rdf:type schema:PropertyValue
77 N490d6cdd194d405f989d0976b506e0ff rdf:first Nc9104e132d4e439ebf46110233053f99
78 rdf:rest rdf:nil
79 N62662dfc0f4c41f49bad166364a6b7c5 schema:affiliation https://www.grid.ac/institutes/grid.468905.6
80 schema:familyName Afrand
81 schema:givenName Masoud
82 rdf:type schema:Person
83 N71816e83cc974dadbf4f15b68a93677a rdf:first N14099f83cd46489b93f93599bc5a49bb
84 rdf:rest N3a10ce14153a40c291a5289e078973f8
85 N8b0e1db6c5154c6aa6976e5d9a0f8148 schema:affiliation https://www.grid.ac/institutes/grid.459724.9
86 schema:familyName Shahsavar
87 schema:givenName Amin
88 rdf:type schema:Person
89 Na7b3f7ef7a884410a7621e6f9c129f68 schema:affiliation https://www.grid.ac/institutes/grid.459471.a
90 schema:familyName Alsarraf
91 schema:givenName Jalal
92 rdf:type schema:Person
93 Nbdb36374417248d09bb0e2d9e19bdbef schema:name dimensions_id
94 schema:value pub.1112262039
95 rdf:type schema:PropertyValue
96 Nc9104e132d4e439ebf46110233053f99 schema:affiliation https://www.grid.ac/institutes/grid.444812.f
97 schema:familyName Tran
98 schema:givenName Minh Duc
99 rdf:type schema:Person
100 Necb4ad7e802044948b9a51a5fea79652 rdf:first Na7b3f7ef7a884410a7621e6f9c129f68
101 rdf:rest N71816e83cc974dadbf4f15b68a93677a
102 Nee346405da154a9282efd19f3ffa2e22 rdf:first N62662dfc0f4c41f49bad166364a6b7c5
103 rdf:rest N1f168f23183940a2b1466861a6a8fae6
104 Nfe7e77103aa443ae8d406dafe4b22c17 schema:affiliation https://www.grid.ac/institutes/grid.412151.2
105 schema:familyName Wongwises
106 schema:givenName Somchai
107 rdf:type schema:Person
108 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
109 schema:name Engineering
110 rdf:type schema:DefinedTerm
111 anzsrc-for:0915 schema:inDefinedTermSet anzsrc-for:
112 schema:name Interdisciplinary Engineering
113 rdf:type schema:DefinedTerm
114 sg:journal.1294862 schema:issn 1388-6150
115 1572-8943
116 schema:name Journal of Thermal Analysis and Calorimetry
117 rdf:type schema:Periodical
118 sg:pub.10.1007/bf01447973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032571512
119 https://doi.org/10.1007/bf01447973
120 rdf:type schema:CreativeWork
121 sg:pub.10.1007/s00231-015-1743-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030682399
122 https://doi.org/10.1007/s00231-015-1743-8
123 rdf:type schema:CreativeWork
124 sg:pub.10.1007/s00231-018-02558-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1111153600
125 https://doi.org/10.1007/s00231-018-02558-x
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1002/pssb.200572720 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052678737
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.applthermaleng.2016.09.091 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020996580
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.applthermaleng.2017.07.100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090678964
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.applthermaleng.2017.09.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091492671
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.apt.2016.05.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051499826
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.cep.2017.03.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084064724
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.enconman.2017.08.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091084616
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.expthermflusci.2013.04.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004103466
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.expthermflusci.2015.07.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004721374
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.expthermflusci.2016.03.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039242810
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.expthermflusci.2017.09.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091895588
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.icheatmasstransfer.2014.01.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022541023
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.icheatmasstransfer.2016.05.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023105198
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.icheatmasstransfer.2016.09.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044473735
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.ijheatfluidflow.2016.01.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000816193
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.ijheatmasstransfer.2009.04.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026025479
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/j.ijheatmasstransfer.2013.09.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026586549
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/j.ijheatmasstransfer.2018.11.069 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110101435
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.jmmm.2003.09.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039838438
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.jmmm.2016.12.129 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044099903
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.molliq.2016.12.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031909609
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/j.molliq.2018.12.055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110582692
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/j.physleta.2016.12.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018476714
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.physrep.2018.11.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110373958
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/j.physrep.2018.11.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110397989
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/j.powtec.2015.01.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002390340
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/j.powtec.2017.06.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086031837
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/j.powtec.2018.09.052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107169703
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/j.synthmet.2007.05.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003540646
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1016/j.tca.2015.08.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039111966
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1021/ed076p943 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055465321
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1063/1.3642974 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057990499
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1103/physreve.89.022310 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060745857
192 rdf:type schema:CreativeWork
193 https://www.grid.ac/institutes/grid.412151.2 schema:alternateName King Mongkut's University of Technology Thonburi
194 schema:name Fluid Mechanics, Thermal Engineering and Multiphase Flow Research Lab. (FUTURE), Department of Mechanical Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, 10140, Bangmod, Bangkok, Thailand
195 The Academy of Science, The Royal Society of Thailand, Sanam Suea Pa, 10300, Dusit, Bangkok, Thailand
196 rdf:type schema:Organization
197 https://www.grid.ac/institutes/grid.444812.f schema:alternateName Ton Duc Thang University
198 schema:name Division of Computational Mechatronics, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
199 Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
200 rdf:type schema:Organization
201 https://www.grid.ac/institutes/grid.459471.a schema:alternateName Public Authority for Applied Education and Training
202 schema:name Automotive and Marine Engineering Department, College of Technological Studies (CTS), Public Authority for Applied Education and Training (PAAET), 70654, Shuwaikh, Kuwait
203 rdf:type schema:Organization
204 https://www.grid.ac/institutes/grid.459724.9 schema:alternateName Kermanshah University of Technology
205 schema:name Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran
206 rdf:type schema:Organization
207 https://www.grid.ac/institutes/grid.468905.6 schema:alternateName Islamic Azad University of Najafabad
208 schema:name Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
209 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...