Research on establishing numerical model of geo material based on CT image analysis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Gang Luo, Shaokang Pan, Yulong Zhang, Hanghang Jia, Liang Chen

ABSTRACT

Geotechnical engineering material is a kind of heterogeneous composite material. The stone, mineral, gravel, hole, and crack contained in it have different physical and mechanical properties, and their responses to external forces are very different. For example, stress distribution, crack propagation, and failure mode are closely related to material heterogeneity and microstructure. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. The theory of digital image processing is applied to geotechnical CT image processing to realize pseudo-color enhancement of CT image, and the histograms of different geotechnical CT numbers are obtained. Canny operator is used to detect the edge of geotechnical CT image, and the binary image of geotechnical microstructure is obtained. According to the color change of pseudo-color enhanced image and CT histogram, the meso-structure and variation of rock and soil can be quantitatively analyzed. The finite element model established by this method can fully consider the heterogeneity of geotechnical materials, especially the effect of void distribution on the mechanical properties of geotechnical materials. More... »

PAGES

36

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13640-019-0421-z

DOI

http://dx.doi.org/10.1186/s13640-019-0421-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111954612


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/2008/0912", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Materials 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": "Chang'an University", 
          "id": "https://www.grid.ac/institutes/grid.440661.1", 
          "name": [
            "School of Highway, Chang\u2019an University, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Luo", 
        "givenName": "Gang", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Chang'an University", 
          "id": "https://www.grid.ac/institutes/grid.440661.1", 
          "name": [
            "School of Highway, Chang\u2019an University, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pan", 
        "givenName": "Shaokang", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Chang'an University", 
          "id": "https://www.grid.ac/institutes/grid.440661.1", 
          "name": [
            "School of Highway, Chang\u2019an University, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Yulong", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Chang'an University", 
          "id": "https://www.grid.ac/institutes/grid.440661.1", 
          "name": [
            "School of Highway, Chang\u2019an University, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jia", 
        "givenName": "Hanghang", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Guangxi Communications Investment Group Co., Ltd., Nanning, Guangxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Liang", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.wear.2014.07.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000810524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tcs.2005.11.038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004732705"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10064-014-0673-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005297201", 
          "https://doi.org/10.1007/s10064-014-0673-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11240-014-0596-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007142636", 
          "https://doi.org/10.1007/s11240-014-0596-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11709-007-0008-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010717332", 
          "https://doi.org/10.1007/s11709-007-0008-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.conbuildmat.2014.03.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011455023"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4942896", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017712571"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/amt-8-183-2015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019761701"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00603-014-0679-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024411417", 
          "https://doi.org/10.1007/s00603-014-0679-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neucom.2011.12.061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025365814"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compgeo.2016.11.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025747215"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.3901/cjme.2014.01.171", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029469672", 
          "https://doi.org/10.3901/cjme.2014.01.171"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jrmge.2016.06.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029939923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1520-684x(199701)28:1<74::aid-scj8>3.0.co;2-p", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038621678"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11666-015-0238-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041997803", 
          "https://doi.org/10.1007/s11666-015-0238-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.actamat.2015.09.026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043893217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1515/oere-2015-0014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050091207"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.sjbs.2017.01.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074192902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.conbuildmat.2017.03.037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084068036"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10706-017-0241-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085074073", 
          "https://doi.org/10.1007/s10706-017-0241-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10706-017-0241-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085074073", 
          "https://doi.org/10.1007/s10706-017-0241-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ins.2017.08.048", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091209225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11242-018-1110-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105220116", 
          "https://doi.org/10.1007/s11242-018-1110-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11242-018-1110-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105220116", 
          "https://doi.org/10.1007/s11242-018-1110-6"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Geotechnical engineering material is a kind of heterogeneous composite material. The stone, mineral, gravel, hole, and crack contained in it have different physical and mechanical properties, and their responses to external forces are very different. For example, stress distribution, crack propagation, and failure mode are closely related to material heterogeneity and microstructure. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. The theory of digital image processing is applied to geotechnical CT image processing to realize pseudo-color enhancement of CT image, and the histograms of different geotechnical CT numbers are obtained. Canny operator is used to detect the edge of geotechnical CT image, and the binary image of geotechnical microstructure is obtained. According to the color change of pseudo-color enhanced image and CT histogram, the meso-structure and variation of rock and soil can be quantitatively analyzed. The finite element model established by this method can fully consider the heterogeneity of geotechnical materials, especially the effect of void distribution on the mechanical properties of geotechnical materials.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13640-019-0421-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1038561", 
        "issn": [
          "1687-5176", 
          "1687-5281"
        ], 
        "name": "EURASIP Journal on Image and Video Processing", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2019"
      }
    ], 
    "name": "Research on establishing numerical model of geo material based on CT image analysis", 
    "pagination": "36", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6b4b0b45fee7a726933e7bf225b921521b962a40e5081eda22d0b9298a50afcc"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13640-019-0421-z"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111954612"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13640-019-0421-z", 
      "https://app.dimensions.ai/details/publication/pub.1111954612"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:02", 
    "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/v90/0000000331_0000000331/records_105433_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs13640-019-0421-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.10.1186/s13640-019-0421-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.10.1186/s13640-019-0421-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13640-019-0421-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13640-019-0421-z'


 

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

160 TRIPLES      21 PREDICATES      49 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13640-019-0421-z schema:about anzsrc-for:09
2 anzsrc-for:0912
3 schema:author Nce72939b114645478e7538fedbd2e413
4 schema:citation sg:pub.10.1007/s00603-014-0679-5
5 sg:pub.10.1007/s10064-014-0673-x
6 sg:pub.10.1007/s10706-017-0241-9
7 sg:pub.10.1007/s11240-014-0596-z
8 sg:pub.10.1007/s11242-018-1110-6
9 sg:pub.10.1007/s11666-015-0238-y
10 sg:pub.10.1007/s11709-007-0008-0
11 sg:pub.10.3901/cjme.2014.01.171
12 https://doi.org/10.1002/(sici)1520-684x(199701)28:1<74::aid-scj8>3.0.co;2-p
13 https://doi.org/10.1016/j.actamat.2015.09.026
14 https://doi.org/10.1016/j.compgeo.2016.11.015
15 https://doi.org/10.1016/j.conbuildmat.2014.03.005
16 https://doi.org/10.1016/j.conbuildmat.2017.03.037
17 https://doi.org/10.1016/j.ins.2017.08.048
18 https://doi.org/10.1016/j.jrmge.2016.06.011
19 https://doi.org/10.1016/j.neucom.2011.12.061
20 https://doi.org/10.1016/j.sjbs.2017.01.027
21 https://doi.org/10.1016/j.tcs.2005.11.038
22 https://doi.org/10.1016/j.wear.2014.07.007
23 https://doi.org/10.1063/1.4942896
24 https://doi.org/10.1515/oere-2015-0014
25 https://doi.org/10.5194/amt-8-183-2015
26 schema:datePublished 2019-12
27 schema:datePublishedReg 2019-12-01
28 schema:description Geotechnical engineering material is a kind of heterogeneous composite material. The stone, mineral, gravel, hole, and crack contained in it have different physical and mechanical properties, and their responses to external forces are very different. For example, stress distribution, crack propagation, and failure mode are closely related to material heterogeneity and microstructure. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. The theory of digital image processing is applied to geotechnical CT image processing to realize pseudo-color enhancement of CT image, and the histograms of different geotechnical CT numbers are obtained. Canny operator is used to detect the edge of geotechnical CT image, and the binary image of geotechnical microstructure is obtained. According to the color change of pseudo-color enhanced image and CT histogram, the meso-structure and variation of rock and soil can be quantitatively analyzed. The finite element model established by this method can fully consider the heterogeneity of geotechnical materials, especially the effect of void distribution on the mechanical properties of geotechnical materials.
29 schema:genre research_article
30 schema:inLanguage en
31 schema:isAccessibleForFree false
32 schema:isPartOf N5f80b88f01a24987a7216cbcf945e9e8
33 Nfc6ee6d09ec94ed38203e98995f6087c
34 sg:journal.1038561
35 schema:name Research on establishing numerical model of geo material based on CT image analysis
36 schema:pagination 36
37 schema:productId N287f26d9910d4265b52f6c1dfb650934
38 N2b153bff3a894cb9a838afa46928d947
39 Ncf137155057645d8a9c6a24d306f6000
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111954612
41 https://doi.org/10.1186/s13640-019-0421-z
42 schema:sdDatePublished 2019-04-11T09:02
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher N4744b2691b4a43c49829d878ef0f4640
45 schema:url https://link.springer.com/10.1186%2Fs13640-019-0421-z
46 sgo:license sg:explorer/license/
47 sgo:sdDataset articles
48 rdf:type schema:ScholarlyArticle
49 N0269c374f7024ac4a3690a77ddf58e7d rdf:first Nfc4e5d18df714a94ba570150a1515326
50 rdf:rest Nd0681358117b4cdca355632ba40accb7
51 N166bbc0c43a84fb99201788070b6bc08 schema:affiliation N189bbc8182f14df4bd14b4f0024655fc
52 schema:familyName Chen
53 schema:givenName Liang
54 rdf:type schema:Person
55 N189bbc8182f14df4bd14b4f0024655fc schema:name Guangxi Communications Investment Group Co., Ltd., Nanning, Guangxi, China
56 rdf:type schema:Organization
57 N287f26d9910d4265b52f6c1dfb650934 schema:name readcube_id
58 schema:value 6b4b0b45fee7a726933e7bf225b921521b962a40e5081eda22d0b9298a50afcc
59 rdf:type schema:PropertyValue
60 N2b153bff3a894cb9a838afa46928d947 schema:name dimensions_id
61 schema:value pub.1111954612
62 rdf:type schema:PropertyValue
63 N34b5be3261a0487aae88b42e122abd51 schema:affiliation https://www.grid.ac/institutes/grid.440661.1
64 schema:familyName Luo
65 schema:givenName Gang
66 rdf:type schema:Person
67 N4744b2691b4a43c49829d878ef0f4640 schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 N5269c49410594d5c995562d081cd683f rdf:first Ne958b547f516442fbdd882b59ff2ce8d
70 rdf:rest Nc16dff25a16d4fd4a3cf510e5ac7422e
71 N5f80b88f01a24987a7216cbcf945e9e8 schema:volumeNumber 2019
72 rdf:type schema:PublicationVolume
73 Nc16dff25a16d4fd4a3cf510e5ac7422e rdf:first N166bbc0c43a84fb99201788070b6bc08
74 rdf:rest rdf:nil
75 Nce72939b114645478e7538fedbd2e413 rdf:first N34b5be3261a0487aae88b42e122abd51
76 rdf:rest N0269c374f7024ac4a3690a77ddf58e7d
77 Ncf137155057645d8a9c6a24d306f6000 schema:name doi
78 schema:value 10.1186/s13640-019-0421-z
79 rdf:type schema:PropertyValue
80 Nd0681358117b4cdca355632ba40accb7 rdf:first Ne799d130cbf54a85a3f73c8bc17e853b
81 rdf:rest N5269c49410594d5c995562d081cd683f
82 Ne799d130cbf54a85a3f73c8bc17e853b schema:affiliation https://www.grid.ac/institutes/grid.440661.1
83 schema:familyName Zhang
84 schema:givenName Yulong
85 rdf:type schema:Person
86 Ne958b547f516442fbdd882b59ff2ce8d schema:affiliation https://www.grid.ac/institutes/grid.440661.1
87 schema:familyName Jia
88 schema:givenName Hanghang
89 rdf:type schema:Person
90 Nfc4e5d18df714a94ba570150a1515326 schema:affiliation https://www.grid.ac/institutes/grid.440661.1
91 schema:familyName Pan
92 schema:givenName Shaokang
93 rdf:type schema:Person
94 Nfc6ee6d09ec94ed38203e98995f6087c schema:issueNumber 1
95 rdf:type schema:PublicationIssue
96 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
97 schema:name Engineering
98 rdf:type schema:DefinedTerm
99 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
100 schema:name Materials Engineering
101 rdf:type schema:DefinedTerm
102 sg:journal.1038561 schema:issn 1687-5176
103 1687-5281
104 schema:name EURASIP Journal on Image and Video Processing
105 rdf:type schema:Periodical
106 sg:pub.10.1007/s00603-014-0679-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024411417
107 https://doi.org/10.1007/s00603-014-0679-5
108 rdf:type schema:CreativeWork
109 sg:pub.10.1007/s10064-014-0673-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1005297201
110 https://doi.org/10.1007/s10064-014-0673-x
111 rdf:type schema:CreativeWork
112 sg:pub.10.1007/s10706-017-0241-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085074073
113 https://doi.org/10.1007/s10706-017-0241-9
114 rdf:type schema:CreativeWork
115 sg:pub.10.1007/s11240-014-0596-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1007142636
116 https://doi.org/10.1007/s11240-014-0596-z
117 rdf:type schema:CreativeWork
118 sg:pub.10.1007/s11242-018-1110-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105220116
119 https://doi.org/10.1007/s11242-018-1110-6
120 rdf:type schema:CreativeWork
121 sg:pub.10.1007/s11666-015-0238-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1041997803
122 https://doi.org/10.1007/s11666-015-0238-y
123 rdf:type schema:CreativeWork
124 sg:pub.10.1007/s11709-007-0008-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010717332
125 https://doi.org/10.1007/s11709-007-0008-0
126 rdf:type schema:CreativeWork
127 sg:pub.10.3901/cjme.2014.01.171 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029469672
128 https://doi.org/10.3901/cjme.2014.01.171
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1002/(sici)1520-684x(199701)28:1<74::aid-scj8>3.0.co;2-p schema:sameAs https://app.dimensions.ai/details/publication/pub.1038621678
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.actamat.2015.09.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043893217
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.compgeo.2016.11.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025747215
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.conbuildmat.2014.03.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011455023
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.conbuildmat.2017.03.037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084068036
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/j.ins.2017.08.048 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091209225
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.jrmge.2016.06.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029939923
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/j.neucom.2011.12.061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025365814
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/j.sjbs.2017.01.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074192902
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1016/j.tcs.2005.11.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004732705
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1016/j.wear.2014.07.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000810524
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1063/1.4942896 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017712571
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1515/oere-2015-0014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050091207
155 rdf:type schema:CreativeWork
156 https://doi.org/10.5194/amt-8-183-2015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019761701
157 rdf:type schema:CreativeWork
158 https://www.grid.ac/institutes/grid.440661.1 schema:alternateName Chang'an University
159 schema:name School of Highway, Chang’an University, Xi’an, Shaanxi, China
160 rdf:type schema:Organization
 




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


...