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Application of Machine Learning for Prediction of Mechanical Properties of Mortars and Concretes

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F24%3APU154811" target="_blank" >RIV/00216305:26110/24:PU154811 - isvavai.cz</a>

  • Result on the web

    <a href="https://dspace.vut.cz/server/api/core/bitstreams/309c6a7b-3f57-49a0-9112-e09d7699f002/content" target="_blank" >https://dspace.vut.cz/server/api/core/bitstreams/309c6a7b-3f57-49a0-9112-e09d7699f002/content</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of Machine Learning for Prediction of Mechanical Properties of Mortars and Concretes

  • Original language description

    This paper deals with the application of machine learning (ML) in the field of concrete technology. Two databases of test mortars and concretes were created from selected academic theses, which include mechanical properties in relation to their composition. These databases were used to develop two ML models that predict the mechanical properties of mortars and concretes depending on their composition. The mortar test database contains a total of 242 mechanical property records and the concrete test database contains 111 records. The materials in the database are CEM I, CEM II and CEM III cements combined with additives such as ground granulated blast furnace slag, high temperature fly ash and micro-ground limestone.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • OECD FORD branch

    20501 - Materials engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů