ARTICLE
TITLE

Models for Predicting Hydration Degree and Adiabatic Temperature Rise of Mass Concrete containing Ground Granulated Blast Furnace Slag

SUMMARY

Predicting adiabatic temperature rise is essentially useful for investigating thermal cracking potential especially in early stage of mass concrete.  Existing prediction methods and models have some problems such as constant thermal properties are mostly utilized for predicting temperature rise. This study is aimed to develop time-dependent models for predicting hydration degrees of cement and slag, free water amount, specific heat, and total heat generation of concrete incorporating slag.  These models are then composed to predict the adiabatic temperature rise of mass concrete incorporating slag.  The model is able to predict adiabatic temperature rise in mass concrete with different water to binder ratios, slag replacements, physical properties of slag, and initial temperature conditions.  The validity of the proposed model was evaluated by comparing the model predictions with test results for adiabatic temperature rise of slag concrete.  The model simulations can be used to predict the experimentally measured data from different

 Articles related

Ievgen Fedorchenko,Andrii Oliinyk,Alexander Stepanenko,Tetiana Zaiko,Serhii Korniienko,Anastasiia Kharchenko    

A genetic method has been proposed to forecast the health indicators of population based on neural-network models. The fundamental difference of the proposed genetic method from existing analogs is the use of the diploid set of chromosomes in individuals... see more


Armin Azad, Jamshid Pirayesh, Saeed Farzin, Leila Malekani, Sheida Moradinasab, Ozgur Kisi    

Traditionally, climate conditions has been one of the influential factors in population growth in worldwide. Hence, predicting these conditions can be an important step to improve life conditions in worldwide. In this study, application of genetic algori... see more


?.?. ???????,?.?. ????????,?.?. ???????    

 In this paper the possibility of building prediction models by using artificial neural networks using the most common software products designed to meet the challenges of this type. The analysis of the results. Display disadvantages and advantages ... see more


?.?. ???????,?.?. ????????,?.?. ?????????    

 In this work represents building prediction models by using artificial neural networks, using one of the most common software product designed to solve the problems of this type. The analysis of the results. Display disadvantages and advantages of ... see more


Teodoziia Yatsyshyn,Lesya Shkitsa,Oleksandr Popov,Mykhailo Liakh    

The study tackles the development of new mathematical means for determining distribution in space and time of technogenic load on atmospheric air as a result of non-burning gas well gushing. To date, modeling is the only tool for studying and solving pre... see more