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[27660] Artykuł: PREDICTION OF FREEZE-THAW RESISTANCE OF GGBFS CONCRETE BASED ON ANN MODELS.Czasopismo: Architecture, Civil Engineering, Environment – ACEE Tom: 8, Zeszyt: 4, Strony: 61-66ISSN: 1899-0142 Wydawca: SILESIAN UNIV TECHNOLOGY, UL AKADEMICKA 2A, GLIWICE, 44-100, POLAND Opublikowano: Grudzień 2015 Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Publikacja w recenzowanym czasopiśmie wymienionym w wykazie ministra MNiSzW (część B) Punkty MNiSW: 11 Klasyfikacja Web of Science: Article Web of Science Keywords: Air entrainment  ANN Model  Durability  Frost resistance  GGBFS concrete  |
In the paper the neural network modelling approach was used to construct an ANNs model to investigate the influence of mix proportion on freeze-thaw GGBFS concrete internal cracking resistance. The simplest way to prevent the internal cracking due to freeze-thaw cycles is the good air-entrainment with an adequate air void spacing. The first step in developing the network was collecting the data set containing the information about mix proportion parameters, characteristics of physical structure of hardened concrete (absorption, permeability, compressive strength) and freeze-thaw durability test results obtained in laboratory using the method of polish standard PN-B-06250: 1988. The collected data dealt with normal and high strength concretes made with cements: CEMI, CEMII/A, B-S and CEMIII/A, air-entrained or not. The four classes of freeze-thaw durability were used in assessing the concrete resistance to internal cracking.