On estimating the Weibull modulus for a brittle material View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1979-05

AUTHORS

K. Trustrum, A. De S. Jayatilaka

ABSTRACT

Common methods of estimating the Weibull modulus are surveyed. Computer simulation is used to obtain the statistical properties of different estimators. Most estimators are shown to be biased and their respective adjustment factors, for a range of experimentally feasible sample sizes, are given.

PAGES

1080-1084

References to SciGraph publications

  • 1977-07. Statistical approach to brittle fracture in JOURNAL OF MATERIALS SCIENCE
  • Journal

    TITLE

    Journal of Materials Science

    ISSUE

    5

    VOLUME

    14

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/bf00561290

    DOI

    http://dx.doi.org/10.1007/bf00561290

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1051039265


    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", 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Sussex", 
              "id": "https://www.grid.ac/institutes/grid.12082.39", 
              "name": [
                "School of Mathematical and Physical Sciences, and School of Engineering and Applied Sciences, University of Sussex, Brighton, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Trustrum", 
            "givenName": "K.", 
            "id": "sg:person.013433402163.12", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013433402163.12"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Sussex", 
              "id": "https://www.grid.ac/institutes/grid.12082.39", 
              "name": [
                "School of Mathematical and Physical Sciences, and School of Engineering and Applied Sciences, University of Sussex, Brighton, UK"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jayatilaka", 
            "givenName": "A. De S.", 
            "id": "sg:person.07417035066.67", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417035066.67"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/bf00540858", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004507991", 
              "https://doi.org/10.1007/bf00540858"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00401706.1969.10490706", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058284072"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "1979-05", 
        "datePublishedReg": "1979-05-01", 
        "description": "Common methods of estimating the Weibull modulus are surveyed. Computer simulation is used to obtain the statistical properties of different estimators. Most estimators are shown to be biased and their respective adjustment factors, for a range of experimentally feasible sample sizes, are given.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/bf00561290", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1312116", 
            "issn": [
              "0022-2461", 
              "1573-4811"
            ], 
            "name": "Journal of Materials Science", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "14"
          }
        ], 
        "name": "On estimating the Weibull modulus for a brittle material", 
        "pagination": "1080-1084", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "f32209b7b7dc0cdddbbe48ea6fc5baca7a7850e694132ea417f795e5352a4179"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/bf00561290"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1051039265"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/bf00561290", 
          "https://app.dimensions.ai/details/publication/pub.1051039265"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T14:02", 
        "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/v90/0000000371_0000000371/records_130830_00000004.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007/BF00561290"
      }
    ]
     

    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/bf00561290'

    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/bf00561290'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf00561290'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf00561290'


     

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

    67 TRIPLES      20 PREDICATES      27 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/bf00561290 schema:author Nb822146d228c4cae906182001764760f
    2 schema:citation sg:pub.10.1007/bf00540858
    3 https://doi.org/10.1080/00401706.1969.10490706
    4 schema:datePublished 1979-05
    5 schema:datePublishedReg 1979-05-01
    6 schema:description Common methods of estimating the Weibull modulus are surveyed. Computer simulation is used to obtain the statistical properties of different estimators. Most estimators are shown to be biased and their respective adjustment factors, for a range of experimentally feasible sample sizes, are given.
    7 schema:genre research_article
    8 schema:inLanguage en
    9 schema:isAccessibleForFree false
    10 schema:isPartOf Nf1d39c9ef79c47babd2d0ae435332856
    11 Nf65f87de8fb04f5f8aacd68b836c7464
    12 sg:journal.1312116
    13 schema:name On estimating the Weibull modulus for a brittle material
    14 schema:pagination 1080-1084
    15 schema:productId N3010bee968d3423ebe30e8481a879681
    16 Nc1cb30ec4f184acca84697f88aec8ad7
    17 Ne93c1fc6c64a4e4e8a6317188b86406a
    18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051039265
    19 https://doi.org/10.1007/bf00561290
    20 schema:sdDatePublished 2019-04-11T14:02
    21 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    22 schema:sdPublisher N2a8f638f5f7046208a10a0eda1626b28
    23 schema:url http://link.springer.com/10.1007/BF00561290
    24 sgo:license sg:explorer/license/
    25 sgo:sdDataset articles
    26 rdf:type schema:ScholarlyArticle
    27 N2a8f638f5f7046208a10a0eda1626b28 schema:name Springer Nature - SN SciGraph project
    28 rdf:type schema:Organization
    29 N3010bee968d3423ebe30e8481a879681 schema:name dimensions_id
    30 schema:value pub.1051039265
    31 rdf:type schema:PropertyValue
    32 N7b928bc8b8e3432d895370f6caf92b03 rdf:first sg:person.07417035066.67
    33 rdf:rest rdf:nil
    34 Nb822146d228c4cae906182001764760f rdf:first sg:person.013433402163.12
    35 rdf:rest N7b928bc8b8e3432d895370f6caf92b03
    36 Nc1cb30ec4f184acca84697f88aec8ad7 schema:name doi
    37 schema:value 10.1007/bf00561290
    38 rdf:type schema:PropertyValue
    39 Ne93c1fc6c64a4e4e8a6317188b86406a schema:name readcube_id
    40 schema:value f32209b7b7dc0cdddbbe48ea6fc5baca7a7850e694132ea417f795e5352a4179
    41 rdf:type schema:PropertyValue
    42 Nf1d39c9ef79c47babd2d0ae435332856 schema:issueNumber 5
    43 rdf:type schema:PublicationIssue
    44 Nf65f87de8fb04f5f8aacd68b836c7464 schema:volumeNumber 14
    45 rdf:type schema:PublicationVolume
    46 sg:journal.1312116 schema:issn 0022-2461
    47 1573-4811
    48 schema:name Journal of Materials Science
    49 rdf:type schema:Periodical
    50 sg:person.013433402163.12 schema:affiliation https://www.grid.ac/institutes/grid.12082.39
    51 schema:familyName Trustrum
    52 schema:givenName K.
    53 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013433402163.12
    54 rdf:type schema:Person
    55 sg:person.07417035066.67 schema:affiliation https://www.grid.ac/institutes/grid.12082.39
    56 schema:familyName Jayatilaka
    57 schema:givenName A. De S.
    58 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417035066.67
    59 rdf:type schema:Person
    60 sg:pub.10.1007/bf00540858 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004507991
    61 https://doi.org/10.1007/bf00540858
    62 rdf:type schema:CreativeWork
    63 https://doi.org/10.1080/00401706.1969.10490706 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058284072
    64 rdf:type schema:CreativeWork
    65 https://www.grid.ac/institutes/grid.12082.39 schema:alternateName University of Sussex
    66 schema:name School of Mathematical and Physical Sciences, and School of Engineering and Applied Sciences, University of Sussex, Brighton, UK
    67 rdf:type schema:Organization
     




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


    ...