Yüksek-Düşük Kireçli Uçucu Kül İçeren Betonların Basınç Dayanımının YSA Ve BM Kullanarak Tahmini

Yıl 2008, Cilt: 21 Sayı: 1, 39 - 56, 30.06.2008

İlker Bekir Topçu , Mustafa Sarıdemir

Öz

Bu calısmada, yuksek ve dusuk kirecli ucucu kuller iceren betonların 7, 28 ve 90 gunluk basınc dayanımını tahmin etmek icin yapay sinir ağları ve bulanık mantıkta modeller olusturulmustur. Bu modelleri olusturmak amacıyla 52 farklı karısımda 180 numune literaturden elde edilmistir. Yapay sinir ağları ve bulanık mantık modellerinde kullanılan veriler; gun, Portland cimento, su, kum, kırmatas-I, kırmatas-II, yuksek oranda su azaltıcı katkı yer değisim oranı, ucucu kul yer değişim oranı ve CaO icerecek bir formatta 9 girdi parametreli; cıktı parametresi betonun basınc dayanımı olarak duzenlenmistir. Modellerdeki eğitim ve test sonucları, yapay sinir ağları ve bulanık mantık sistemlerinin, ucucu kul iceren betonların 7, 28 ve 90 gunluk basınc dayanımını tahmin etmek icin guclu potansiyele sahip olduğunu gostermistir.

Anahtar Kelimeler

Dayanım, uçucu kül, yapay sinir ağları, bulanık mantık.

Prediction Of Compressive Strength Of Concrete Containing High-Low Fly Ash Using ANN And FL

Öz

In this study, artificial neural networks and fuzzy logic models for

predicting the 7, 28 and 90-day compressive strength of concretes containing highlime

and low-lime fly ashes have been developed. For purpose of constructing these

models, 52 different mixes with 180 specimens were gathered from the literature.

The data used in the artificial neural networks and fuzzy logic models are arranged

in a format of nine input parameters that cover the day, Portland cement, water,

sand, crushed stone-I, crushed stone-II, high range water reducing agent

replacement ratio, fly ash replacement ratio and CaO, and an output parameter

which is compressive strength of concrete. In the models of the training and testing

results have shown that artificial neural networks and fuzzy logic systems have

strong potential for predicting 7, 28 and 90-day compressive strength of concretes

containing fly ash.

Anahtar Kelimeler

Strength, fly ash, artificial neural networks, fuzzy logic

Kaynakça

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