Statistical discussions on skin frictional drag of turbulence over randomly distributed semi-spheres View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

Yusuke Kuwata, Yasuo Kawaguchi

ABSTRACT

The influence of dynamical effects of rough wall turbulence, namely velocity dispersion, drag force and turbulence, on rough wall skin friction coefficient is statistically discussed by performing direct numerical simulation of rough-walled open channel flows and analyzing spatial and Reynolds (double) averaged equations. Numerical calculations are conducted by the D3Q27 multiple-relaxation-time lattice Boltzmann method (MRT-LBM). For the rough surfaces, randomly distributed semi-spheres are considered. Analyzing an integrated double averaged momentum equation, a main contributor to the skin friction coefficient is found to be the turbulence contribution and a second contributor is the drag contribution, and the drag contribution particularly increases with increasing the equivalent roughness. Although the streamwise mean velocity dispersion is significantly induced by the acceleration/deceleration of the streamwise velocity due to the roughness elements, the wall-normal mean velocity dispersion is not significant. Consequently, the off-diagonal component of the dispersive covariant term is far smaller than the Reynolds shear stress and the velocity dispersion thus hardly contributes to an increase in the skin friction coefficient. More... »

PAGES

1-10

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12572-018-0223-z

DOI

http://dx.doi.org/10.1007/s12572-018-0223-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105608988


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": "Osaka Prefecture University", 
          "id": "https://www.grid.ac/institutes/grid.261455.1", 
          "name": [
            "Osaka Prefecture University, 1-1 Sakai, 599-8531, Osaka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kuwata", 
        "givenName": "Yusuke", 
        "id": "sg:person.015714576515.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015714576515.77"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo University of Science", 
          "id": "https://www.grid.ac/institutes/grid.143643.7", 
          "name": [
            "Tokyo University of Science, 2641 Yamazaki, 278-8510, Chiba, Noda, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kawaguchi", 
        "givenName": "Yasuo", 
        "id": "sg:person.013351527675.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013351527675.55"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.compfluid.2014.10.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001012421"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compfluid.2005.10.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002801092"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatfluidflow.2016.03.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003336893"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10955-015-1375-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003958633", 
          "https://doi.org/10.1007/s10955-015-1375-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/3.10427", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004919661"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00348-004-0903-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006242509", 
          "https://doi.org/10.1007/s00348-004-0903-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00348-004-0903-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006242509", 
          "https://doi.org/10.1007/s00348-004-0903-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/jfm.2016.680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011377841"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/jfm.2016.680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011377841"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatfluidflow.2015.05.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011682510"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.camwa.2015.01.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012365331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.camwa.2015.01.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012365331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compfluid.2015.04.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012930998"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2014.10.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015700565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cam.2009.08.100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015995273"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatfluidflow.2016.05.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017346095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4208/aamm.2014.m468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019342564"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rsta.2001.0955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022491816"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2012.07.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023080810"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/6.1973-763", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025021727"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10494-016-9759-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028233800", 
          "https://doi.org/10.1007/s10494-016-9759-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10494-016-9759-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028233800", 
          "https://doi.org/10.1007/s10494-016-9759-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2013.06.037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030698513"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2016.02.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030934246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2011.04.031", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037653539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/3.5386", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038453002"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compfluid.2016.10.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041691075"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177706645", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043005266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.procs.2011.04.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048742046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/aic.14232", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053401947"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112008003571", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053790762"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112008003571", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053790762"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112092000594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053820741"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112010002740", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053947602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112010002740", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053947602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/jfm.2011.268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054001833"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/jfm.2011.268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054001833"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1399290", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057702818"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1516779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057715228"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.67.066707", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060730258"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.67.066707", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060730258"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.94.043304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060750724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.94.043304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060750724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1115/1.1486222", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062070829"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1115/1.3242406", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062110639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1115/1.4001492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062141846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1504/pcfd.2009.024820", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067506221"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2174/1877729500901010035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069241067"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compfluid.2017.07.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090666269"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/tcsme-1980-0001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103552059"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/tcsme-1980-0001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103552059"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "The influence of dynamical effects of rough wall turbulence, namely velocity dispersion, drag force and turbulence, on rough wall skin friction coefficient is statistically discussed by performing direct numerical simulation of rough-walled open channel flows and analyzing spatial and Reynolds (double) averaged equations. Numerical calculations are conducted by the D3Q27 multiple-relaxation-time lattice Boltzmann method (MRT-LBM). For the rough surfaces, randomly distributed semi-spheres are considered. Analyzing an integrated double averaged momentum equation, a main contributor to the skin friction coefficient is found to be the turbulence contribution and a second contributor is the drag contribution, and the drag contribution particularly increases with increasing the equivalent roughness. Although the streamwise mean velocity dispersion is significantly induced by the acceleration/deceleration of the streamwise velocity due to the roughness elements, the wall-normal mean velocity dispersion is not significant. Consequently, the off-diagonal component of the dispersive covariant term is far smaller than the Reynolds shear stress and the velocity dispersion thus hardly contributes to an increase in the skin friction coefficient.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12572-018-0223-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5916005", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.6840013", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1050051", 
        "issn": [
          "0975-0770", 
          "0975-5616"
        ], 
        "name": "International Journal of Advances in Engineering Sciences and Applied Mathematics", 
        "type": "Periodical"
      }
    ], 
    "name": "Statistical discussions on skin frictional drag of turbulence over randomly distributed semi-spheres", 
    "pagination": "1-10", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "49b24fb920b42729b6e69d4ba7e513c31df8c2c567367b4f26feae88028c8561"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12572-018-0223-z"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1105608988"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12572-018-0223-z", 
      "https://app.dimensions.ai/details/publication/pub.1105608988"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:45", 
    "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_8664_00000485.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s12572-018-0223-z"
  }
]
 

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/s12572-018-0223-z'

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/s12572-018-0223-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12572-018-0223-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12572-018-0223-z'


 

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

195 TRIPLES      21 PREDICATES      66 URIs      17 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12572-018-0223-z schema:about anzsrc-for:09
2 anzsrc-for:0915
3 schema:author N7fb94ff89b39405d864589832063bc24
4 schema:citation sg:pub.10.1007/s00348-004-0903-2
5 sg:pub.10.1007/s10494-016-9759-9
6 sg:pub.10.1007/s10955-015-1375-x
7 https://doi.org/10.1002/aic.14232
8 https://doi.org/10.1016/j.cam.2009.08.100
9 https://doi.org/10.1016/j.camwa.2015.01.010
10 https://doi.org/10.1016/j.ces.2013.06.037
11 https://doi.org/10.1016/j.compfluid.2005.10.002
12 https://doi.org/10.1016/j.compfluid.2014.10.012
13 https://doi.org/10.1016/j.compfluid.2015.04.008
14 https://doi.org/10.1016/j.compfluid.2016.10.007
15 https://doi.org/10.1016/j.compfluid.2017.07.005
16 https://doi.org/10.1016/j.ijheatfluidflow.2015.05.015
17 https://doi.org/10.1016/j.ijheatfluidflow.2016.03.006
18 https://doi.org/10.1016/j.ijheatfluidflow.2016.05.008
19 https://doi.org/10.1016/j.jcp.2011.04.031
20 https://doi.org/10.1016/j.jcp.2012.07.023
21 https://doi.org/10.1016/j.jcp.2014.10.002
22 https://doi.org/10.1016/j.jcp.2016.02.008
23 https://doi.org/10.1016/j.procs.2011.04.111
24 https://doi.org/10.1017/jfm.2011.268
25 https://doi.org/10.1017/jfm.2016.680
26 https://doi.org/10.1017/s0022112008003571
27 https://doi.org/10.1017/s0022112010002740
28 https://doi.org/10.1017/s0022112092000594
29 https://doi.org/10.1063/1.1399290
30 https://doi.org/10.1063/1.1516779
31 https://doi.org/10.1098/rsta.2001.0955
32 https://doi.org/10.1103/physreve.67.066707
33 https://doi.org/10.1103/physreve.94.043304
34 https://doi.org/10.1115/1.1486222
35 https://doi.org/10.1115/1.3242406
36 https://doi.org/10.1115/1.4001492
37 https://doi.org/10.1139/tcsme-1980-0001
38 https://doi.org/10.1214/aoms/1177706645
39 https://doi.org/10.1504/pcfd.2009.024820
40 https://doi.org/10.2174/1877729500901010035
41 https://doi.org/10.2514/3.10427
42 https://doi.org/10.2514/3.5386
43 https://doi.org/10.2514/6.1973-763
44 https://doi.org/10.4208/aamm.2014.m468
45 schema:datePublished 2018-12
46 schema:datePublishedReg 2018-12-01
47 schema:description The influence of dynamical effects of rough wall turbulence, namely velocity dispersion, drag force and turbulence, on rough wall skin friction coefficient is statistically discussed by performing direct numerical simulation of rough-walled open channel flows and analyzing spatial and Reynolds (double) averaged equations. Numerical calculations are conducted by the D3Q27 multiple-relaxation-time lattice Boltzmann method (MRT-LBM). For the rough surfaces, randomly distributed semi-spheres are considered. Analyzing an integrated double averaged momentum equation, a main contributor to the skin friction coefficient is found to be the turbulence contribution and a second contributor is the drag contribution, and the drag contribution particularly increases with increasing the equivalent roughness. Although the streamwise mean velocity dispersion is significantly induced by the acceleration/deceleration of the streamwise velocity due to the roughness elements, the wall-normal mean velocity dispersion is not significant. Consequently, the off-diagonal component of the dispersive covariant term is far smaller than the Reynolds shear stress and the velocity dispersion thus hardly contributes to an increase in the skin friction coefficient.
48 schema:genre research_article
49 schema:inLanguage en
50 schema:isAccessibleForFree false
51 schema:isPartOf sg:journal.1050051
52 schema:name Statistical discussions on skin frictional drag of turbulence over randomly distributed semi-spheres
53 schema:pagination 1-10
54 schema:productId N16f432edb3dc4f63946cc6560eaebba0
55 Na2e8d428d94b48fe8b0ac8e1f0b4be0e
56 Ne880db7f5c6b4ad384020950e1cf728f
57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105608988
58 https://doi.org/10.1007/s12572-018-0223-z
59 schema:sdDatePublished 2019-04-10T15:45
60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
61 schema:sdPublisher N81e3d302323246d9826a54eb403676d1
62 schema:url http://link.springer.com/10.1007/s12572-018-0223-z
63 sgo:license sg:explorer/license/
64 sgo:sdDataset articles
65 rdf:type schema:ScholarlyArticle
66 N0d59a54c81f04fe68ce63242f7adde7f rdf:first sg:person.013351527675.55
67 rdf:rest rdf:nil
68 N16f432edb3dc4f63946cc6560eaebba0 schema:name readcube_id
69 schema:value 49b24fb920b42729b6e69d4ba7e513c31df8c2c567367b4f26feae88028c8561
70 rdf:type schema:PropertyValue
71 N7fb94ff89b39405d864589832063bc24 rdf:first sg:person.015714576515.77
72 rdf:rest N0d59a54c81f04fe68ce63242f7adde7f
73 N81e3d302323246d9826a54eb403676d1 schema:name Springer Nature - SN SciGraph project
74 rdf:type schema:Organization
75 Na2e8d428d94b48fe8b0ac8e1f0b4be0e schema:name doi
76 schema:value 10.1007/s12572-018-0223-z
77 rdf:type schema:PropertyValue
78 Ne880db7f5c6b4ad384020950e1cf728f schema:name dimensions_id
79 schema:value pub.1105608988
80 rdf:type schema:PropertyValue
81 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
82 schema:name Engineering
83 rdf:type schema:DefinedTerm
84 anzsrc-for:0915 schema:inDefinedTermSet anzsrc-for:
85 schema:name Interdisciplinary Engineering
86 rdf:type schema:DefinedTerm
87 sg:grant.5916005 http://pending.schema.org/fundedItem sg:pub.10.1007/s12572-018-0223-z
88 rdf:type schema:MonetaryGrant
89 sg:grant.6840013 http://pending.schema.org/fundedItem sg:pub.10.1007/s12572-018-0223-z
90 rdf:type schema:MonetaryGrant
91 sg:journal.1050051 schema:issn 0975-0770
92 0975-5616
93 schema:name International Journal of Advances in Engineering Sciences and Applied Mathematics
94 rdf:type schema:Periodical
95 sg:person.013351527675.55 schema:affiliation https://www.grid.ac/institutes/grid.143643.7
96 schema:familyName Kawaguchi
97 schema:givenName Yasuo
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013351527675.55
99 rdf:type schema:Person
100 sg:person.015714576515.77 schema:affiliation https://www.grid.ac/institutes/grid.261455.1
101 schema:familyName Kuwata
102 schema:givenName Yusuke
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015714576515.77
104 rdf:type schema:Person
105 sg:pub.10.1007/s00348-004-0903-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006242509
106 https://doi.org/10.1007/s00348-004-0903-2
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/s10494-016-9759-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028233800
109 https://doi.org/10.1007/s10494-016-9759-9
110 rdf:type schema:CreativeWork
111 sg:pub.10.1007/s10955-015-1375-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1003958633
112 https://doi.org/10.1007/s10955-015-1375-x
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1002/aic.14232 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053401947
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.cam.2009.08.100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015995273
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/j.camwa.2015.01.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012365331
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.ces.2013.06.037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030698513
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.compfluid.2005.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002801092
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.compfluid.2014.10.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001012421
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/j.compfluid.2015.04.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012930998
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.compfluid.2016.10.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041691075
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.compfluid.2017.07.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090666269
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.ijheatfluidflow.2015.05.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011682510
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.ijheatfluidflow.2016.03.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003336893
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.ijheatfluidflow.2016.05.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017346095
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.jcp.2011.04.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037653539
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/j.jcp.2012.07.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023080810
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.jcp.2014.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015700565
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/j.jcp.2016.02.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030934246
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/j.procs.2011.04.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048742046
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1017/jfm.2011.268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054001833
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1017/jfm.2016.680 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011377841
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1017/s0022112008003571 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053790762
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1017/s0022112010002740 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053947602
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1017/s0022112092000594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053820741
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1063/1.1399290 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057702818
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1063/1.1516779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057715228
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1098/rsta.2001.0955 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022491816
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1103/physreve.67.066707 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060730258
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1103/physreve.94.043304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060750724
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1115/1.1486222 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062070829
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1115/1.3242406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062110639
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1115/1.4001492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062141846
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1139/tcsme-1980-0001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103552059
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1214/aoms/1177706645 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043005266
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1504/pcfd.2009.024820 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067506221
179 rdf:type schema:CreativeWork
180 https://doi.org/10.2174/1877729500901010035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069241067
181 rdf:type schema:CreativeWork
182 https://doi.org/10.2514/3.10427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004919661
183 rdf:type schema:CreativeWork
184 https://doi.org/10.2514/3.5386 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038453002
185 rdf:type schema:CreativeWork
186 https://doi.org/10.2514/6.1973-763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025021727
187 rdf:type schema:CreativeWork
188 https://doi.org/10.4208/aamm.2014.m468 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019342564
189 rdf:type schema:CreativeWork
190 https://www.grid.ac/institutes/grid.143643.7 schema:alternateName Tokyo University of Science
191 schema:name Tokyo University of Science, 2641 Yamazaki, 278-8510, Chiba, Noda, Japan
192 rdf:type schema:Organization
193 https://www.grid.ac/institutes/grid.261455.1 schema:alternateName Osaka Prefecture University
194 schema:name Osaka Prefecture University, 1-1 Sakai, 599-8531, Osaka, Japan
195 rdf:type schema:Organization
 




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


...