A LBM–DEM solver for fast discrete particle simulation of particle–fluid flows View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-11

AUTHORS

Qingang Xiong, Ehsan Madadi-Kandjani, Giulio Lorenzini

ABSTRACT

The lattice Boltzmann method (LBM) for simulating fluid phases was coupled with the discrete element method (DEM) for studying solid phases to formulate a novel solver for fast discrete particle simulation (DPS) of particle–fluid flows. The fluid hydrodynamics was obtained by solving LBM equations instead of solving the Navier–Stokes equation by the finite volume method (FVM). Interparticle and particle–wall collisions were determined by DEM. The new DPS solver was validated by simulating a three-dimensional gas–solid bubbling fluidized bed. The new solver was found to yield results faster than its FVM–DEM counterpart, with the increase in the domain-averaged gas volume fraction. Additionally, the scalability of the LBM–DEM DPS solver was superior to that of the FVM–DEM DPS solver in parallel computing. Thus, the LBM–DEM DPS solver is highly suitable for use in simulating dilute and large-scale particle–fluid flows. More... »

PAGES

907-917

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00161-014-0351-z

DOI

http://dx.doi.org/10.1007/s00161-014-0351-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044574450


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": "Iowa State University", 
          "id": "https://www.grid.ac/institutes/grid.34421.30", 
          "name": [
            "Department of Mechanical Engineering, Iowa State University, 50011, Ames, IA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xiong", 
        "givenName": "Qingang", 
        "id": "sg:person.012357251401.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012357251401.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Iowa State University", 
          "id": "https://www.grid.ac/institutes/grid.34421.30", 
          "name": [
            "Department of Mechanical Engineering, Iowa State University, 50011, Ames, IA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Madadi-Kandjani", 
        "givenName": "Ehsan", 
        "id": "sg:person.014336762431.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014336762431.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Parma", 
          "id": "https://www.grid.ac/institutes/grid.10383.39", 
          "name": [
            "Department of Industrial Engineering, University of Parma, 43124, Parma, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lorenzini", 
        "givenName": "Giulio", 
        "id": "sg:person.013714140501.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013714140501.81"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1017/jfm.2013.268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004933602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/jfm.2013.268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004933602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2010.03.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007094057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2011.09.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007598708"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cej.2014.01.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009462283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2013.09.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011754505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2006.12.089", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014566639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.fluid.30.1.329", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022436194"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.camwa.2011.03.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027899692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2012.04.052", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028536231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cma.2012.03.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030802978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compfluid.2012.08.026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036060427"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/aic.11481", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040275779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2012.12.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043866239"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.partic.2013.07.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043953667"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2008.08.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047166022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2011.10.059", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047331434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ces.2013.08.037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048234308"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.powtec.2013.04.049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048998758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.partic.2012.02.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049037055"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcp.2013.04.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050750482"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112094001771", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053912624"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112094001783", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053995403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s002211201000306x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054001012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s002211201000306x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054001012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ie800283b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055642988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ie800283b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055642988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4770310", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058064865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.65.046308", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728338"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.65.046308", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728338"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.035301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728992"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.035301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060728992"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.67.036302", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060729826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.67.036302", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060729826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.71.045301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060732831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.71.045301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060732831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1209/0295-5075/17/6/001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064228747"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1680/geot.1979.29.1.47", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068209785"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-11", 
    "datePublishedReg": "2014-11-01", 
    "description": "The lattice Boltzmann method (LBM) for simulating fluid phases was coupled with the discrete element method (DEM) for studying solid phases to formulate a novel solver for fast discrete particle simulation (DPS) of particle\u2013fluid flows. The fluid hydrodynamics was obtained by solving LBM equations instead of solving the Navier\u2013Stokes equation by the finite volume method (FVM). Interparticle and particle\u2013wall collisions were determined by DEM. The new DPS solver was validated by simulating a three-dimensional gas\u2013solid bubbling fluidized bed. The new solver was found to yield results faster than its FVM\u2013DEM counterpart, with the increase in the domain-averaged gas volume fraction. Additionally, the scalability of the LBM\u2013DEM DPS solver was superior to that of the FVM\u2013DEM DPS solver in parallel computing. Thus, the LBM\u2013DEM DPS solver is highly suitable for use in simulating dilute and large-scale particle\u2013fluid flows.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00161-014-0351-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1135936", 
        "issn": [
          "0935-1175", 
          "1432-0959"
        ], 
        "name": "Continuum Mechanics and Thermodynamics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "26"
      }
    ], 
    "name": "A LBM\u2013DEM solver for fast discrete particle simulation of particle\u2013fluid flows", 
    "pagination": "907-917", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d452d05b7d50aa961f4904e5af7e90165476c64c0259d61395558d5c909d8b21"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00161-014-0351-z"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1044574450"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00161-014-0351-z", 
      "https://app.dimensions.ai/details/publication/pub.1044574450"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T10:19", 
    "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/v90/0000000348_0000000348/records_54325_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs00161-014-0351-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/s00161-014-0351-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/s00161-014-0351-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00161-014-0351-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00161-014-0351-z'


 

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

171 TRIPLES      21 PREDICATES      58 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00161-014-0351-z schema:about anzsrc-for:09
2 anzsrc-for:0915
3 schema:author Na8f9da4378d04206a9e7c89570054ae1
4 schema:citation https://doi.org/10.1002/aic.11481
5 https://doi.org/10.1016/j.camwa.2011.03.016
6 https://doi.org/10.1016/j.cej.2014.01.029
7 https://doi.org/10.1016/j.ces.2006.12.089
8 https://doi.org/10.1016/j.ces.2008.08.006
9 https://doi.org/10.1016/j.ces.2010.03.023
10 https://doi.org/10.1016/j.ces.2011.10.059
11 https://doi.org/10.1016/j.ces.2013.08.037
12 https://doi.org/10.1016/j.ces.2013.09.023
13 https://doi.org/10.1016/j.cma.2012.03.011
14 https://doi.org/10.1016/j.compfluid.2012.08.026
15 https://doi.org/10.1016/j.jcp.2012.12.015
16 https://doi.org/10.1016/j.jcp.2013.04.019
17 https://doi.org/10.1016/j.partic.2012.02.006
18 https://doi.org/10.1016/j.partic.2013.07.007
19 https://doi.org/10.1016/j.powtec.2011.09.021
20 https://doi.org/10.1016/j.powtec.2012.04.052
21 https://doi.org/10.1016/j.powtec.2013.04.049
22 https://doi.org/10.1017/jfm.2013.268
23 https://doi.org/10.1017/s002211201000306x
24 https://doi.org/10.1017/s0022112094001771
25 https://doi.org/10.1017/s0022112094001783
26 https://doi.org/10.1021/ie800283b
27 https://doi.org/10.1063/1.4770310
28 https://doi.org/10.1103/physreve.65.046308
29 https://doi.org/10.1103/physreve.66.035301
30 https://doi.org/10.1103/physreve.67.036302
31 https://doi.org/10.1103/physreve.71.045301
32 https://doi.org/10.1146/annurev.fluid.30.1.329
33 https://doi.org/10.1209/0295-5075/17/6/001
34 https://doi.org/10.1680/geot.1979.29.1.47
35 schema:datePublished 2014-11
36 schema:datePublishedReg 2014-11-01
37 schema:description The lattice Boltzmann method (LBM) for simulating fluid phases was coupled with the discrete element method (DEM) for studying solid phases to formulate a novel solver for fast discrete particle simulation (DPS) of particle–fluid flows. The fluid hydrodynamics was obtained by solving LBM equations instead of solving the Navier–Stokes equation by the finite volume method (FVM). Interparticle and particle–wall collisions were determined by DEM. The new DPS solver was validated by simulating a three-dimensional gas–solid bubbling fluidized bed. The new solver was found to yield results faster than its FVM–DEM counterpart, with the increase in the domain-averaged gas volume fraction. Additionally, the scalability of the LBM–DEM DPS solver was superior to that of the FVM–DEM DPS solver in parallel computing. Thus, the LBM–DEM DPS solver is highly suitable for use in simulating dilute and large-scale particle–fluid flows.
38 schema:genre research_article
39 schema:inLanguage en
40 schema:isAccessibleForFree false
41 schema:isPartOf N6a4041567bce4607bec698445b3db9d3
42 Nc2416c586fae41709b25d206d7904807
43 sg:journal.1135936
44 schema:name A LBM–DEM solver for fast discrete particle simulation of particle–fluid flows
45 schema:pagination 907-917
46 schema:productId N09b554c67ac34c3e80d610271c5433e1
47 N2bb545ab45c24d20a18efb78888ca291
48 Nbda3a112c4654d639a1dd538fd36ca02
49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044574450
50 https://doi.org/10.1007/s00161-014-0351-z
51 schema:sdDatePublished 2019-04-11T10:19
52 schema:sdLicense https://scigraph.springernature.com/explorer/license/
53 schema:sdPublisher Ndabc9fa73e144a5e81bec2b2a2f0288a
54 schema:url https://link.springer.com/10.1007%2Fs00161-014-0351-z
55 sgo:license sg:explorer/license/
56 sgo:sdDataset articles
57 rdf:type schema:ScholarlyArticle
58 N09b554c67ac34c3e80d610271c5433e1 schema:name doi
59 schema:value 10.1007/s00161-014-0351-z
60 rdf:type schema:PropertyValue
61 N1770b5c7b80042ba8f25c7dce4a3c410 rdf:first sg:person.014336762431.98
62 rdf:rest Nd75a474b903742d4a257f7e389667447
63 N2bb545ab45c24d20a18efb78888ca291 schema:name readcube_id
64 schema:value d452d05b7d50aa961f4904e5af7e90165476c64c0259d61395558d5c909d8b21
65 rdf:type schema:PropertyValue
66 N6a4041567bce4607bec698445b3db9d3 schema:issueNumber 6
67 rdf:type schema:PublicationIssue
68 Na8f9da4378d04206a9e7c89570054ae1 rdf:first sg:person.012357251401.29
69 rdf:rest N1770b5c7b80042ba8f25c7dce4a3c410
70 Nbda3a112c4654d639a1dd538fd36ca02 schema:name dimensions_id
71 schema:value pub.1044574450
72 rdf:type schema:PropertyValue
73 Nc2416c586fae41709b25d206d7904807 schema:volumeNumber 26
74 rdf:type schema:PublicationVolume
75 Nd75a474b903742d4a257f7e389667447 rdf:first sg:person.013714140501.81
76 rdf:rest rdf:nil
77 Ndabc9fa73e144a5e81bec2b2a2f0288a schema:name Springer Nature - SN SciGraph project
78 rdf:type schema:Organization
79 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
80 schema:name Engineering
81 rdf:type schema:DefinedTerm
82 anzsrc-for:0915 schema:inDefinedTermSet anzsrc-for:
83 schema:name Interdisciplinary Engineering
84 rdf:type schema:DefinedTerm
85 sg:journal.1135936 schema:issn 0935-1175
86 1432-0959
87 schema:name Continuum Mechanics and Thermodynamics
88 rdf:type schema:Periodical
89 sg:person.012357251401.29 schema:affiliation https://www.grid.ac/institutes/grid.34421.30
90 schema:familyName Xiong
91 schema:givenName Qingang
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012357251401.29
93 rdf:type schema:Person
94 sg:person.013714140501.81 schema:affiliation https://www.grid.ac/institutes/grid.10383.39
95 schema:familyName Lorenzini
96 schema:givenName Giulio
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013714140501.81
98 rdf:type schema:Person
99 sg:person.014336762431.98 schema:affiliation https://www.grid.ac/institutes/grid.34421.30
100 schema:familyName Madadi-Kandjani
101 schema:givenName Ehsan
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014336762431.98
103 rdf:type schema:Person
104 https://doi.org/10.1002/aic.11481 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040275779
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1016/j.camwa.2011.03.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027899692
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1016/j.cej.2014.01.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009462283
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1016/j.ces.2006.12.089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014566639
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.ces.2008.08.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047166022
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/j.ces.2010.03.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007094057
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.ces.2011.10.059 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047331434
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/j.ces.2013.08.037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048234308
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.ces.2013.09.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011754505
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.cma.2012.03.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030802978
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.compfluid.2012.08.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036060427
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/j.jcp.2012.12.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043866239
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.jcp.2013.04.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050750482
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.partic.2012.02.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049037055
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.partic.2013.07.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043953667
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.powtec.2011.09.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007598708
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.powtec.2012.04.052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028536231
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.powtec.2013.04.049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048998758
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1017/jfm.2013.268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004933602
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1017/s002211201000306x schema:sameAs https://app.dimensions.ai/details/publication/pub.1054001012
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1017/s0022112094001771 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053912624
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1017/s0022112094001783 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053995403
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1021/ie800283b schema:sameAs https://app.dimensions.ai/details/publication/pub.1055642988
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1063/1.4770310 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058064865
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1103/physreve.65.046308 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060728338
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1103/physreve.66.035301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060728992
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1103/physreve.67.036302 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060729826
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1103/physreve.71.045301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060732831
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1146/annurev.fluid.30.1.329 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022436194
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1209/0295-5075/17/6/001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064228747
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1680/geot.1979.29.1.47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068209785
165 rdf:type schema:CreativeWork
166 https://www.grid.ac/institutes/grid.10383.39 schema:alternateName University of Parma
167 schema:name Department of Industrial Engineering, University of Parma, 43124, Parma, Italy
168 rdf:type schema:Organization
169 https://www.grid.ac/institutes/grid.34421.30 schema:alternateName Iowa State University
170 schema:name Department of Mechanical Engineering, Iowa State University, 50011, Ames, IA, USA
171 rdf:type schema:Organization
 




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


...