TY  - JOUR
TI  - Compressive Strength Prediction of Ferrochrome Slag Based Geopolymer Concretes Produced Under Different Curing Conditions by Using Prediction Methods
AB  - In this study, compressive strength (CS) values of ferrochrome slag (FS) based geopolymerconcretes in different curing conditions were investigated. Ground FS was activated with themixture of sodium hydroxide and sodium silicate. The silica modulus (Ms) of the geopolymerconcrete samples were selected as 1.25, 1.50 and 1.75. Also, samples were prepared by substituting0%, 10% and 20% silica fume (SF) replacement the FS. Thus, 9 groups geopolymer concretesamples were produced. The CS values of the samples were determined on different curing times(24, 48, 72 and 96 hours) and curing temperatures (23, 40, 60, 80 and 100 °C). At the same time,multilayer perceptron neural network (MLPNN), extreme learning machine neural network(ELMNN) and M5 model tree were modeled for the CS prediction of the samples, the predict andexperimental results were compared. According to the experiment results, it was determined thatthe CS values generally increased as the curing time increased, but with the addition of SF, the CSvalues generally decreased. The highest CS was obtained in the sample containing 100% FS that hadsilica modulus of 1.25 and cured at 100 °C for 24-48-72 or 96 hours. The R2 values of MLPNN,ELMNN and M5 model tree in testing phase were 0.956, 0.935 and 0.922, respectively. MLPNN, themodel that gave the best predict result, had root mean square error (RMSE) of 0.723 and normalizedroot mean square error (NMRSE) of 26.485 in testing.
AU  - Karakoç, Mehmet Burhan
AU  - Özcan, Ahmet
AU  - KALKAN, YAŞAR
DO  - 10.21205/deufmd.2021236916
PY  - 2021
JO  - Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi
VL  - 23
IS  - 69
SN  - 1302-9304
SP  - 881
EP  - 891
DB  - TRDizin
UR  - http://search/yayin/detay/443740
ER  -