İlker Bekir TOPÇU, Cenk KARAKURT, Mustafa SARIDEMİR

Farklı Puzolanlarla Üretilmiş Çimentoların Dayanım Gelişiminin Yapay Sinir Ağlarıyla Tahmini

Bu çalışma, çimento üretiminde kullanılan mineral katkılarda en uygun kullanım oranının belirlenmesi için yapılmıştır. Laboratuvarda farklı kaynaklardan sağlanan doğal zeolit, tras, volkanik tüf, uçucu kül ve yüksek fırın cürufu katkıları, çimento üretiminde klinker yerine %10, 20, 30, 35, 40 ve 45 oranlarında kullanılmıştır. Çimentolar üzerinde yapılan 2, 7, 28 ve 180 günlük basınç dayanımı deneyleriyle dayanım gelişimi belirlenmiştir. Daha sonra deneysel çalışmadan elde edilen veriler kullanılarak yapay sinir ağı (YSA) yönteminde model geliştirilmiştir.

Anahtar Kelimeler:

Katkılı çimento, Puzolanlar, Basınç dayanımı, Yapay sinir ağları

Predicting The Strength Development Of Different Pozzolan Cements By Artificial Neural Networks

This study is based on the determination of optimum usage of mineral additives as supplementary cementing material for blended cement production. For this purpose, blended cements were produced under laboratory conditions with natural zeolite, trass, volcanic tuff, fly ash and ground granulated blast furnace slag at 10, 20, 30, 40 and 45% clinker replacement ratios. Strength development of the cements was determined with compressive strength tests performed at 2, 7, 28 and 180 days. Experimental results were also obtained by building models according to artificial neural network (ANN) system.

Keywords:

Blended cement, Pozzolans, Compressive strength, Artificial neural network,

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