A bimodal lognormal model of the distribution of strength of carbon fibres: effects of electrodeposition of titanium di (dioctyl pyrophosphate) ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1986-11

AUTHORS

Shi-Hau Own, R. V. Subramanian, S. C. Saunders

ABSTRACT

The tensile strength distribution of Fortafil-3 carbon fibres of circular cross-section has been investigated at different gauge lengths. The unimodal Weibull, unimodal lognormal and bimodal lognormal models were tested. Estimating the model parameters by the method of maximum likelihood, and testing each model by the Kolmogorov-Smirnov goodness-of-fit statistic at prescribed levels of significance, it is found that the data for untreated unsized fibres fit a bimodal lognormal model best. The proportions of the low and high strength populations,p andq, respectively, did not show any well-defined trend with gauge length and had average values close to 0.5. But the lognormal mean for each population showed an increasing trend with decreasing gauge length. It is inferred thatp andq are, respectively, related to the presence of surface flaws and internal defects, both of which probably have the same structural origin. After electrodeposition of titanium di (dioctyl pyrophosphate) oxyacetate (TDPO), the fibre strength was still best approximated by a bimodal lognormal distribution. But the weighting factorp for the weak population was reduced markedly, with a corresponding increase ofq, indicating the healing of surface flaws during electrodeposition of a protective layer of TDPO. Furthermore, in contrast to the observations with untreated fibres, the lognormal means for both the low and high strength populations of the electrocoated fibres were essentially unchanged with gauge length. Changes were also indicated in the number and severity of surface flaws, caused by concurrent electrochemical processes. More... »

PAGES

3912-3920

References to SciGraph publications

  • 1983-11. Strength-structure relationships in PAN-based carbon fibres in JOURNAL OF MATERIALS SCIENCE
  • Journal

    TITLE

    Journal of Materials Science

    ISSUE

    11

    VOLUME

    21

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/bf02431629

    DOI

    http://dx.doi.org/10.1007/bf02431629

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1044310190


    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": "Washington State University", 
              "id": "https://www.grid.ac/institutes/grid.30064.31", 
              "name": [
                "Department of Materials Science and Engineering, Washington State University, 99164-2720, Pullman, Washington, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Own", 
            "givenName": "Shi-Hau", 
            "id": "sg:person.011751417253.41", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011751417253.41"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Washington State University", 
              "id": "https://www.grid.ac/institutes/grid.30064.31", 
              "name": [
                "Department of Materials Science and Engineering, Washington State University, 99164-2720, Pullman, Washington, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Subramanian", 
            "givenName": "R. V.", 
            "id": "sg:person.011345232663.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011345232663.25"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Washington State University", 
              "id": "https://www.grid.ac/institutes/grid.30064.31", 
              "name": [
                "Department of Materials Science and Engineering, Washington State University, 99164-2720, Pullman, Washington, USA", 
                "Department of Mathematics, Washington State University, 99164-2720, Pullman, Washington, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Saunders", 
            "givenName": "S. C.", 
            "id": "sg:person.011106240430.01", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011106240430.01"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/bf00544159", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001772266", 
              "https://doi.org/10.1007/bf00544159"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00544159", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001772266", 
              "https://doi.org/10.1007/bf00544159"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1351/pac198052071929", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004481428"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/pen.760180708", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005903514"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0015-0568(82)90015-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014909109"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0015-0568(82)90015-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014909109"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0015-0568(79)90032-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016215028"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0015-0568(79)90032-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016215028"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0008-6223(79)90069-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018363788"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0008-6223(79)90069-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018363788"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0010-4361(80)90009-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043792620"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0010-4361(80)90009-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043792620"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rsta.1980.0059", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045220723"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.1720976", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1057788035"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "1986-11", 
        "datePublishedReg": "1986-11-01", 
        "description": "The tensile strength distribution of Fortafil-3 carbon fibres of circular cross-section has been investigated at different gauge lengths. The unimodal Weibull, unimodal lognormal and bimodal lognormal models were tested. Estimating the model parameters by the method of maximum likelihood, and testing each model by the Kolmogorov-Smirnov goodness-of-fit statistic at prescribed levels of significance, it is found that the data for untreated unsized fibres fit a bimodal lognormal model best. The proportions of the low and high strength populations,p andq, respectively, did not show any well-defined trend with gauge length and had average values close to 0.5. But the lognormal mean for each population showed an increasing trend with decreasing gauge length. It is inferred thatp andq are, respectively, related to the presence of surface flaws and internal defects, both of which probably have the same structural origin. After electrodeposition of titanium di (dioctyl pyrophosphate) oxyacetate (TDPO), the fibre strength was still best approximated by a bimodal lognormal distribution. But the weighting factorp for the weak population was reduced markedly, with a corresponding increase ofq, indicating the healing of surface flaws during electrodeposition of a protective layer of TDPO. Furthermore, in contrast to the observations with untreated fibres, the lognormal means for both the low and high strength populations of the electrocoated fibres were essentially unchanged with gauge length. Changes were also indicated in the number and severity of surface flaws, caused by concurrent electrochemical processes.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/bf02431629", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1312116", 
            "issn": [
              "0022-2461", 
              "1573-4811"
            ], 
            "name": "Journal of Materials Science", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "11", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "21"
          }
        ], 
        "name": "A bimodal lognormal model of the distribution of strength of carbon fibres: effects of electrodeposition of titanium di (dioctyl pyrophosphate) oxyacetate", 
        "pagination": "3912-3920", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "d310934f01306e460ab5042744b702a6ea4906021308cb12118e122a941b6639"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/bf02431629"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1044310190"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/bf02431629", 
          "https://app.dimensions.ai/details/publication/pub.1044310190"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:35", 
        "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/v90/0000000370_0000000370/records_46775_00000002.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2FBF02431629"
      }
    ]
     

    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/bf02431629'

    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/bf02431629'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf02431629'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf02431629'


     

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

    104 TRIPLES      21 PREDICATES      36 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/bf02431629 schema:about anzsrc-for:09
    2 anzsrc-for:0912
    3 schema:author N9b677d7963e4423f947fcb50c4abbe42
    4 schema:citation sg:pub.10.1007/bf00544159
    5 https://doi.org/10.1002/pen.760180708
    6 https://doi.org/10.1016/0008-6223(79)90069-1
    7 https://doi.org/10.1016/0010-4361(80)90009-9
    8 https://doi.org/10.1016/0015-0568(79)90032-0
    9 https://doi.org/10.1016/0015-0568(82)90015-x
    10 https://doi.org/10.1063/1.1720976
    11 https://doi.org/10.1098/rsta.1980.0059
    12 https://doi.org/10.1351/pac198052071929
    13 schema:datePublished 1986-11
    14 schema:datePublishedReg 1986-11-01
    15 schema:description The tensile strength distribution of Fortafil-3 carbon fibres of circular cross-section has been investigated at different gauge lengths. The unimodal Weibull, unimodal lognormal and bimodal lognormal models were tested. Estimating the model parameters by the method of maximum likelihood, and testing each model by the Kolmogorov-Smirnov goodness-of-fit statistic at prescribed levels of significance, it is found that the data for untreated unsized fibres fit a bimodal lognormal model best. The proportions of the low and high strength populations,p andq, respectively, did not show any well-defined trend with gauge length and had average values close to 0.5. But the lognormal mean for each population showed an increasing trend with decreasing gauge length. It is inferred thatp andq are, respectively, related to the presence of surface flaws and internal defects, both of which probably have the same structural origin. After electrodeposition of titanium di (dioctyl pyrophosphate) oxyacetate (TDPO), the fibre strength was still best approximated by a bimodal lognormal distribution. But the weighting factorp for the weak population was reduced markedly, with a corresponding increase ofq, indicating the healing of surface flaws during electrodeposition of a protective layer of TDPO. Furthermore, in contrast to the observations with untreated fibres, the lognormal means for both the low and high strength populations of the electrocoated fibres were essentially unchanged with gauge length. Changes were also indicated in the number and severity of surface flaws, caused by concurrent electrochemical processes.
    16 schema:genre research_article
    17 schema:inLanguage en
    18 schema:isAccessibleForFree false
    19 schema:isPartOf N8f3518fda1e24f929f523a57761af040
    20 Nfe0394a75e764b4982e20fdf46920f16
    21 sg:journal.1312116
    22 schema:name A bimodal lognormal model of the distribution of strength of carbon fibres: effects of electrodeposition of titanium di (dioctyl pyrophosphate) oxyacetate
    23 schema:pagination 3912-3920
    24 schema:productId N5664bf610f4e4ca0afbbb458cef98724
    25 N8df2341cfaa64b3da53334f022e3bcc8
    26 Nce26f89ed5b24fd68f7bbe82c4a844e0
    27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044310190
    28 https://doi.org/10.1007/bf02431629
    29 schema:sdDatePublished 2019-04-11T13:35
    30 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    31 schema:sdPublisher Nfc784bcf39de452c979f45d2f347c398
    32 schema:url http://link.springer.com/10.1007%2FBF02431629
    33 sgo:license sg:explorer/license/
    34 sgo:sdDataset articles
    35 rdf:type schema:ScholarlyArticle
    36 N1e9d4e078b3941698768dd48907ddd8b rdf:first sg:person.011345232663.25
    37 rdf:rest N7b4685e2ea984315834d4a0c0bb9fc2e
    38 N5664bf610f4e4ca0afbbb458cef98724 schema:name readcube_id
    39 schema:value d310934f01306e460ab5042744b702a6ea4906021308cb12118e122a941b6639
    40 rdf:type schema:PropertyValue
    41 N7b4685e2ea984315834d4a0c0bb9fc2e rdf:first sg:person.011106240430.01
    42 rdf:rest rdf:nil
    43 N8df2341cfaa64b3da53334f022e3bcc8 schema:name dimensions_id
    44 schema:value pub.1044310190
    45 rdf:type schema:PropertyValue
    46 N8f3518fda1e24f929f523a57761af040 schema:volumeNumber 21
    47 rdf:type schema:PublicationVolume
    48 N9b677d7963e4423f947fcb50c4abbe42 rdf:first sg:person.011751417253.41
    49 rdf:rest N1e9d4e078b3941698768dd48907ddd8b
    50 Nce26f89ed5b24fd68f7bbe82c4a844e0 schema:name doi
    51 schema:value 10.1007/bf02431629
    52 rdf:type schema:PropertyValue
    53 Nfc784bcf39de452c979f45d2f347c398 schema:name Springer Nature - SN SciGraph project
    54 rdf:type schema:Organization
    55 Nfe0394a75e764b4982e20fdf46920f16 schema:issueNumber 11
    56 rdf:type schema:PublicationIssue
    57 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
    58 schema:name Engineering
    59 rdf:type schema:DefinedTerm
    60 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
    61 schema:name Materials Engineering
    62 rdf:type schema:DefinedTerm
    63 sg:journal.1312116 schema:issn 0022-2461
    64 1573-4811
    65 schema:name Journal of Materials Science
    66 rdf:type schema:Periodical
    67 sg:person.011106240430.01 schema:affiliation https://www.grid.ac/institutes/grid.30064.31
    68 schema:familyName Saunders
    69 schema:givenName S. C.
    70 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011106240430.01
    71 rdf:type schema:Person
    72 sg:person.011345232663.25 schema:affiliation https://www.grid.ac/institutes/grid.30064.31
    73 schema:familyName Subramanian
    74 schema:givenName R. V.
    75 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011345232663.25
    76 rdf:type schema:Person
    77 sg:person.011751417253.41 schema:affiliation https://www.grid.ac/institutes/grid.30064.31
    78 schema:familyName Own
    79 schema:givenName Shi-Hau
    80 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011751417253.41
    81 rdf:type schema:Person
    82 sg:pub.10.1007/bf00544159 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001772266
    83 https://doi.org/10.1007/bf00544159
    84 rdf:type schema:CreativeWork
    85 https://doi.org/10.1002/pen.760180708 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005903514
    86 rdf:type schema:CreativeWork
    87 https://doi.org/10.1016/0008-6223(79)90069-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018363788
    88 rdf:type schema:CreativeWork
    89 https://doi.org/10.1016/0010-4361(80)90009-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043792620
    90 rdf:type schema:CreativeWork
    91 https://doi.org/10.1016/0015-0568(79)90032-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016215028
    92 rdf:type schema:CreativeWork
    93 https://doi.org/10.1016/0015-0568(82)90015-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1014909109
    94 rdf:type schema:CreativeWork
    95 https://doi.org/10.1063/1.1720976 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057788035
    96 rdf:type schema:CreativeWork
    97 https://doi.org/10.1098/rsta.1980.0059 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045220723
    98 rdf:type schema:CreativeWork
    99 https://doi.org/10.1351/pac198052071929 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004481428
    100 rdf:type schema:CreativeWork
    101 https://www.grid.ac/institutes/grid.30064.31 schema:alternateName Washington State University
    102 schema:name Department of Materials Science and Engineering, Washington State University, 99164-2720, Pullman, Washington, USA
    103 Department of Mathematics, Washington State University, 99164-2720, Pullman, Washington, USA
    104 rdf:type schema:Organization
     




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


    ...