Prediction Model of TBM Disc Cutter Wear During Tunnelling in Heterogeneous Ground View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11

AUTHORS

Dong-Jie Ren, Shui-Long Shen, Arul Arulrajah, Wen-Chieh Cheng

ABSTRACT

When shield tunnelling is constructed in complex geological conditions using a tunnel boring machine, the disc cutter in the cutterhead easily wears to the failure state, particularly when the ground conditions are heterogeneous. This paper summarises the failure modes of the disc cutter in heterogeneous ground conditions into three categories, based on the observed wear data from field: (1) uniform disc cutter wear, (2) non-uniform disc cutter wear, and (3) breakage of cutter ring. Subsequently, the stress state of a disc cutter in the heterogeneous ground was analysed and the effective factors were investigated. The relationships between friction energy during cutting, working status of the machine and the characteristics of the geological conditions were evaluated. Based on the stress analysis and friction energy, a prediction model was proposed. The proposed model was applied to two field case studies: pertaining to uniform and mixed-face ground conditions, for which the empirical coefficient k for energy transfer was also determined. The preliminary results from this research indicated that the proposed model was valid for both homogeneous and heterogeneous ground conditions. Further case studies provided by co-operators are expected to improve the effectiveness of the proposed model. More... »

PAGES

3599-3611

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00603-018-1549-3

DOI

http://dx.doi.org/10.1007/s00603-018-1549-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105564690


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Shanghai Jiao Tong University", 
          "id": "https://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China", 
            "Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ren", 
        "givenName": "Dong-Jie", 
        "id": "sg:person.014603037017.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014603037017.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Shanghai Jiao Tong University", 
          "id": "https://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China", 
            "Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shen", 
        "givenName": "Shui-Long", 
        "id": "sg:person.010735570166.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010735570166.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Swinburne University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.1027.4", 
          "name": [
            "Department of Civil and Construction Engineering, Swinburne University of Technology, 3122, Melbourne, VIC, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Arulrajah", 
        "givenName": "Arul", 
        "id": "sg:person.011021001047.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011021001047.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Shanghai Jiao Tong University", 
          "id": "https://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China", 
            "Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cheng", 
        "givenName": "Wen-Chieh", 
        "id": "sg:person.014376101655.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014376101655.99"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.oceaneng.2015.10.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001194939"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2007.02.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001707078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/t11-049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004041961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12665-016-5710-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005521032", 
          "https://doi.org/10.1007/s12665-016-5710-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12665-016-5710-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005521032", 
          "https://doi.org/10.1007/s12665-016-5710-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.crme.2014.02.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005952921"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compgeo.2011.10.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006986012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2013.10.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009946154"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2006.10.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011987317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.autcon.2010.07.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014510471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/geot.200800002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016664626"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2015.09.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017896763"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2007.05.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021678057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2013.06.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023426154"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2015.08.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023623338"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2015.08.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024382846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2012.06.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027004334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11440-016-0486-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029545630", 
          "https://doi.org/10.1007/s11440-016-0486-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11440-016-0486-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029545630", 
          "https://doi.org/10.1007/s11440-016-0486-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2014.07.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031033312"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rsta.1921.0006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033816692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2007.07.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034167408"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2006.07.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036925294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00603-016-1053-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037911634", 
          "https://doi.org/10.1007/s00603-016-1053-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00603-016-1053-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037911634", 
          "https://doi.org/10.1007/s00603-016-1053-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2008.12.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038036149"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2010.09.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040554730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2004.03.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043090945"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrmms.2014.12.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043350563"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2009.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049163866"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)0733-9410(1993)119:1(69)", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057587547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)0733-947x(1985)111:6(633)", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057602507"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0000433", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057632404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0000709", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057632679"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0001166", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057633135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0001441", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057633410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)gt.1943-5606.0001611", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057633575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1680/geot.14.p.024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068208498"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00603-017-1176-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074235922", 
          "https://doi.org/10.1007/s00603-017-1176-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00603-017-1176-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074235922", 
          "https://doi.org/10.1007/s00603-017-1176-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)cf.1943-5509.0001058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084867227"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2017.05.028", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085961158"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/nag.2714", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090372647"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compgeo.2017.07.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090919589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1061/(asce)cf.1943-5509.0001082", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090972021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/cgj-2017-0355", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092525617"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/nag.2760", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093092737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2017.12.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100073603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/su10020304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100590070"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scitotenv.2018.01.138", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101113021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.engfailanal.2018.02.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101402636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tust.2018.04.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103668782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jhydrol.2018.06.075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105193640"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-11", 
    "datePublishedReg": "2018-11-01", 
    "description": "When shield tunnelling is constructed in complex geological conditions using a tunnel boring machine, the disc cutter in the cutterhead easily wears to the failure state, particularly when the ground conditions are heterogeneous. This paper summarises the failure modes of the disc cutter in heterogeneous ground conditions into three categories, based on the observed wear data from field: (1) uniform disc cutter wear, (2) non-uniform disc cutter wear, and (3) breakage of cutter ring. Subsequently, the stress state of a disc cutter in the heterogeneous ground was analysed and the effective factors were investigated. The relationships between friction energy during cutting, working status of the machine and the characteristics of the geological conditions were evaluated. Based on the stress analysis and friction energy, a prediction model was proposed. The proposed model was applied to two field case studies: pertaining to uniform and mixed-face ground conditions, for which the empirical coefficient k for energy transfer was also determined. The preliminary results from this research indicated that the proposed model was valid for both homogeneous and heterogeneous ground conditions. Further case studies provided by co-operators are expected to improve the effectiveness of the proposed model.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00603-018-1549-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1052698", 
        "issn": [
          "0723-2632", 
          "1434-453X"
        ], 
        "name": "Rock Mechanics and Rock Engineering", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "11", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "51"
      }
    ], 
    "name": "Prediction Model of TBM Disc Cutter Wear During Tunnelling in Heterogeneous Ground", 
    "pagination": "3599-3611", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "3c6dfc6ddbcf88602cbbad96054c49848c1a2a6c82782f18ee6052c8e6d9991f"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00603-018-1549-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1105564690"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00603-018-1549-3", 
      "https://app.dimensions.ai/details/publication/pub.1105564690"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T02:32", 
    "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_8700_00000604.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs00603-018-1549-3"
  }
]
 

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/s00603-018-1549-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00603-018-1549-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00603-018-1549-3'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00603-018-1549-3'


 

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

237 TRIPLES      21 PREDICATES      76 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00603-018-1549-3 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N5327cf28a8c3437d86b3bb59bc1e97e4
4 schema:citation sg:pub.10.1007/s00603-016-1053-6
5 sg:pub.10.1007/s00603-017-1176-4
6 sg:pub.10.1007/s11440-016-0486-0
7 sg:pub.10.1007/s12665-016-5710-6
8 https://doi.org/10.1002/geot.200800002
9 https://doi.org/10.1002/nag.2714
10 https://doi.org/10.1002/nag.2760
11 https://doi.org/10.1016/j.autcon.2010.07.009
12 https://doi.org/10.1016/j.compgeo.2011.10.004
13 https://doi.org/10.1016/j.compgeo.2017.07.014
14 https://doi.org/10.1016/j.crme.2014.02.002
15 https://doi.org/10.1016/j.engfailanal.2018.02.015
16 https://doi.org/10.1016/j.ijrmms.2004.03.007
17 https://doi.org/10.1016/j.ijrmms.2006.07.007
18 https://doi.org/10.1016/j.ijrmms.2007.02.005
19 https://doi.org/10.1016/j.ijrmms.2010.09.014
20 https://doi.org/10.1016/j.ijrmms.2014.07.022
21 https://doi.org/10.1016/j.ijrmms.2014.12.007
22 https://doi.org/10.1016/j.ijrmms.2015.09.019
23 https://doi.org/10.1016/j.jhydrol.2018.06.075
24 https://doi.org/10.1016/j.oceaneng.2015.10.011
25 https://doi.org/10.1016/j.scitotenv.2018.01.138
26 https://doi.org/10.1016/j.tust.2006.10.002
27 https://doi.org/10.1016/j.tust.2007.05.008
28 https://doi.org/10.1016/j.tust.2007.07.001
29 https://doi.org/10.1016/j.tust.2008.12.005
30 https://doi.org/10.1016/j.tust.2009.11.007
31 https://doi.org/10.1016/j.tust.2012.06.001
32 https://doi.org/10.1016/j.tust.2013.06.001
33 https://doi.org/10.1016/j.tust.2013.10.013
34 https://doi.org/10.1016/j.tust.2015.08.001
35 https://doi.org/10.1016/j.tust.2015.08.003
36 https://doi.org/10.1016/j.tust.2017.05.028
37 https://doi.org/10.1016/j.tust.2017.12.021
38 https://doi.org/10.1016/j.tust.2018.04.009
39 https://doi.org/10.1061/(asce)0733-9410(1993)119:1(69)
40 https://doi.org/10.1061/(asce)0733-947x(1985)111:6(633)
41 https://doi.org/10.1061/(asce)cf.1943-5509.0001058
42 https://doi.org/10.1061/(asce)cf.1943-5509.0001082
43 https://doi.org/10.1061/(asce)gt.1943-5606.0000433
44 https://doi.org/10.1061/(asce)gt.1943-5606.0000709
45 https://doi.org/10.1061/(asce)gt.1943-5606.0001166
46 https://doi.org/10.1061/(asce)gt.1943-5606.0001441
47 https://doi.org/10.1061/(asce)gt.1943-5606.0001611
48 https://doi.org/10.1098/rsta.1921.0006
49 https://doi.org/10.1139/cgj-2017-0355
50 https://doi.org/10.1139/t11-049
51 https://doi.org/10.1680/geot.14.p.024
52 https://doi.org/10.3390/su10020304
53 schema:datePublished 2018-11
54 schema:datePublishedReg 2018-11-01
55 schema:description When shield tunnelling is constructed in complex geological conditions using a tunnel boring machine, the disc cutter in the cutterhead easily wears to the failure state, particularly when the ground conditions are heterogeneous. This paper summarises the failure modes of the disc cutter in heterogeneous ground conditions into three categories, based on the observed wear data from field: (1) uniform disc cutter wear, (2) non-uniform disc cutter wear, and (3) breakage of cutter ring. Subsequently, the stress state of a disc cutter in the heterogeneous ground was analysed and the effective factors were investigated. The relationships between friction energy during cutting, working status of the machine and the characteristics of the geological conditions were evaluated. Based on the stress analysis and friction energy, a prediction model was proposed. The proposed model was applied to two field case studies: pertaining to uniform and mixed-face ground conditions, for which the empirical coefficient k for energy transfer was also determined. The preliminary results from this research indicated that the proposed model was valid for both homogeneous and heterogeneous ground conditions. Further case studies provided by co-operators are expected to improve the effectiveness of the proposed model.
56 schema:genre research_article
57 schema:inLanguage en
58 schema:isAccessibleForFree false
59 schema:isPartOf Nbadc303871ba45178ad5a79b7c76cdda
60 Nd6c0d73afbae49748564357d67e0c5de
61 sg:journal.1052698
62 schema:name Prediction Model of TBM Disc Cutter Wear During Tunnelling in Heterogeneous Ground
63 schema:pagination 3599-3611
64 schema:productId N074e11feef6c4bb79e1e83938f43d8d9
65 N1f585b5a6cd84c48955dbc86cc0f713a
66 Na83e459ddfca4d05afff8191060ac0e8
67 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105564690
68 https://doi.org/10.1007/s00603-018-1549-3
69 schema:sdDatePublished 2019-04-11T02:32
70 schema:sdLicense https://scigraph.springernature.com/explorer/license/
71 schema:sdPublisher N42d303430dc343189f7e7081c6965c3f
72 schema:url https://link.springer.com/10.1007%2Fs00603-018-1549-3
73 sgo:license sg:explorer/license/
74 sgo:sdDataset articles
75 rdf:type schema:ScholarlyArticle
76 N074e11feef6c4bb79e1e83938f43d8d9 schema:name readcube_id
77 schema:value 3c6dfc6ddbcf88602cbbad96054c49848c1a2a6c82782f18ee6052c8e6d9991f
78 rdf:type schema:PropertyValue
79 N1f585b5a6cd84c48955dbc86cc0f713a schema:name doi
80 schema:value 10.1007/s00603-018-1549-3
81 rdf:type schema:PropertyValue
82 N42d303430dc343189f7e7081c6965c3f schema:name Springer Nature - SN SciGraph project
83 rdf:type schema:Organization
84 N5327cf28a8c3437d86b3bb59bc1e97e4 rdf:first sg:person.014603037017.25
85 rdf:rest N9edbf6347e15448ea3f4ab217d69c80f
86 N6b38bea153d640bcaa9e9b4249e776b4 rdf:first sg:person.011021001047.16
87 rdf:rest Nf4c0595303344ed293941cda55eb86ac
88 N9edbf6347e15448ea3f4ab217d69c80f rdf:first sg:person.010735570166.15
89 rdf:rest N6b38bea153d640bcaa9e9b4249e776b4
90 Na83e459ddfca4d05afff8191060ac0e8 schema:name dimensions_id
91 schema:value pub.1105564690
92 rdf:type schema:PropertyValue
93 Nbadc303871ba45178ad5a79b7c76cdda schema:issueNumber 11
94 rdf:type schema:PublicationIssue
95 Nd6c0d73afbae49748564357d67e0c5de schema:volumeNumber 51
96 rdf:type schema:PublicationVolume
97 Nf4c0595303344ed293941cda55eb86ac rdf:first sg:person.014376101655.99
98 rdf:rest rdf:nil
99 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
100 schema:name Information and Computing Sciences
101 rdf:type schema:DefinedTerm
102 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
103 schema:name Artificial Intelligence and Image Processing
104 rdf:type schema:DefinedTerm
105 sg:journal.1052698 schema:issn 0723-2632
106 1434-453X
107 schema:name Rock Mechanics and Rock Engineering
108 rdf:type schema:Periodical
109 sg:person.010735570166.15 schema:affiliation https://www.grid.ac/institutes/grid.16821.3c
110 schema:familyName Shen
111 schema:givenName Shui-Long
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010735570166.15
113 rdf:type schema:Person
114 sg:person.011021001047.16 schema:affiliation https://www.grid.ac/institutes/grid.1027.4
115 schema:familyName Arulrajah
116 schema:givenName Arul
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011021001047.16
118 rdf:type schema:Person
119 sg:person.014376101655.99 schema:affiliation https://www.grid.ac/institutes/grid.16821.3c
120 schema:familyName Cheng
121 schema:givenName Wen-Chieh
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014376101655.99
123 rdf:type schema:Person
124 sg:person.014603037017.25 schema:affiliation https://www.grid.ac/institutes/grid.16821.3c
125 schema:familyName Ren
126 schema:givenName Dong-Jie
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014603037017.25
128 rdf:type schema:Person
129 sg:pub.10.1007/s00603-016-1053-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037911634
130 https://doi.org/10.1007/s00603-016-1053-6
131 rdf:type schema:CreativeWork
132 sg:pub.10.1007/s00603-017-1176-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074235922
133 https://doi.org/10.1007/s00603-017-1176-4
134 rdf:type schema:CreativeWork
135 sg:pub.10.1007/s11440-016-0486-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029545630
136 https://doi.org/10.1007/s11440-016-0486-0
137 rdf:type schema:CreativeWork
138 sg:pub.10.1007/s12665-016-5710-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005521032
139 https://doi.org/10.1007/s12665-016-5710-6
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1002/geot.200800002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016664626
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1002/nag.2714 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090372647
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1002/nag.2760 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093092737
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.autcon.2010.07.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014510471
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.compgeo.2011.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006986012
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.compgeo.2017.07.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090919589
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.crme.2014.02.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005952921
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.engfailanal.2018.02.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101402636
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.ijrmms.2004.03.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043090945
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1016/j.ijrmms.2006.07.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036925294
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1016/j.ijrmms.2007.02.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001707078
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.ijrmms.2010.09.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040554730
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.ijrmms.2014.07.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031033312
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.ijrmms.2014.12.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043350563
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/j.ijrmms.2015.09.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017896763
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/j.jhydrol.2018.06.075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105193640
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.oceaneng.2015.10.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001194939
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/j.scitotenv.2018.01.138 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101113021
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/j.tust.2006.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011987317
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/j.tust.2007.05.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021678057
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/j.tust.2007.07.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034167408
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/j.tust.2008.12.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038036149
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1016/j.tust.2009.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049163866
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1016/j.tust.2012.06.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027004334
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1016/j.tust.2013.06.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023426154
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1016/j.tust.2013.10.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009946154
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1016/j.tust.2015.08.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023623338
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1016/j.tust.2015.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024382846
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1016/j.tust.2017.05.028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085961158
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1016/j.tust.2017.12.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100073603
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1016/j.tust.2018.04.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103668782
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1061/(asce)0733-9410(1993)119:1(69) schema:sameAs https://app.dimensions.ai/details/publication/pub.1057587547
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1061/(asce)0733-947x(1985)111:6(633) schema:sameAs https://app.dimensions.ai/details/publication/pub.1057602507
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1061/(asce)cf.1943-5509.0001058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084867227
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1061/(asce)cf.1943-5509.0001082 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090972021
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1061/(asce)gt.1943-5606.0000433 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057632404
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1061/(asce)gt.1943-5606.0000709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057632679
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1061/(asce)gt.1943-5606.0001166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057633135
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1061/(asce)gt.1943-5606.0001441 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057633410
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1061/(asce)gt.1943-5606.0001611 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057633575
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1098/rsta.1921.0006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033816692
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1139/cgj-2017-0355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092525617
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1139/t11-049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004041961
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1680/geot.14.p.024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068208498
228 rdf:type schema:CreativeWork
229 https://doi.org/10.3390/su10020304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100590070
230 rdf:type schema:CreativeWork
231 https://www.grid.ac/institutes/grid.1027.4 schema:alternateName Swinburne University of Technology
232 schema:name Department of Civil and Construction Engineering, Swinburne University of Technology, 3122, Melbourne, VIC, Australia
233 rdf:type schema:Organization
234 https://www.grid.ac/institutes/grid.16821.3c schema:alternateName Shanghai Jiao Tong University
235 schema:name Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Department of Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China
236 State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China
237 rdf:type schema:Organization
 




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


...