1 Ocak 2020 Dergi makalesi Açık Erişim

Sezer, Alper; Sezer, Gozde Inan; Mardani-Aghabaglou, Ali; Altun, Selim

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/7817</identifier>
  <creators>
    <creator>
      <creatorName>Sezer, Alper</creatorName>
      <givenName>Alper</givenName>
      <familyName>Sezer</familyName>
      <affiliation>Ege Univ, Engn Fac, Dept Civil Engn, Izmir, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Sezer, Gozde Inan</creatorName>
      <givenName>Gozde Inan</givenName>
      <familyName>Sezer</familyName>
      <affiliation>Ege Univ, Engn Fac, Dept Civil Engn, Izmir, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Mardani-Aghabaglou, Ali</creatorName>
      <givenName>Ali</givenName>
      <familyName>Mardani-Aghabaglou</familyName>
      <affiliation>Bursa Uludag Univ, Engn Fac, Dept Civil Engn, Bursa, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Altun, Selim</creatorName>
      <givenName>Selim</givenName>
      <familyName>Altun</familyName>
      <affiliation>Ege Univ, Engn Fac, Dept Civil Engn, Izmir, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Prediction Of Mechanical And Penetrability Properties Of Cement-Stabilized Clay Exposed To Sulfate Attack By Use Of Soft Computing Methods</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/7817</alternateIdentifier>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1007/s00521-020-04972-x</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Similar to its effects on any type of cementitious composite, it is a well-known fact that sulfate attack has also a negative influence on engineering behavior of cement-stabilized soils. However, the level of degradation in engineering properties of the cement-stabilized soils still needs more scientific attention. In the light of this, a database including a total of 260 unconfined compression and chloride ion penetration tests on cement-stabilized kaolin specimens exposed to sulfate attack was constituted. The data include information about cement type (sulfate resistant-SR; normal portland (N) and pozzolanic-P), and its content (0, 5, 10 and 15%), sulfate type (sodium or magnesium sulfate) as well as its concentration (0.3, 0.5, 1%) and curing period (1, 7, 28 and 90 days). Using this database, linear and nonlinear regression analysis (RA), backpropagation neural networks and adaptive neuro-fuzzy inference techniques were employed to question whether these methods are capable of predicting unconfined compressive strength and chloride ion penetration of cement-stabilized clay exposed to sulfate attack. The results revealed that these methods have a great potential in modeling the strength and penetrability properties of cement-stabilized clays exposed to sulfate attack. While the performance of regression method is at an acceptable level, results show that adaptive neuro-fuzzy inference systems and backpropagation neural networks are superior in modeling.</description>
  </descriptions>
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