Modeling adiabatic temperature rise during concrete hydration with the use of artificial neural networks
Title: Modeling adiabatic temperature rise during concrete hydration with the use of artificial neural networks
Author(s): G. Trtnik, F. Kavcic, G. Turk
Paper category : conference
Book title: International RILEM Symposium on Concrete Modelling - ConMod '08
Editor(s): E. Schlangen and G. De Schutter
Publisher: RILEM Publications SARL
Publication year: 2008
Pages: 79 - 86
Total Pages: 8
Nb references: 8
Abstract: Concrete is one of the most commonly used structural materials and is composed from individual base materials. Every base material has, on its specific way, some influence on the hydration process of cement in concrete. The most commonly used experimental method for the determination of the heat of hydration is the adiabatic method. Adiabatic hydration curves would be the most sutiable starting point for temperature calculations in hardening structures, so the adiabatic curves are judged to be of great practical importance. It is well known, that the kinetics and intensity of the hydration process is affected by many factors, such as external temperature, moisture content, cement composition, fineness of grinding, watercement ratio, type of cement, initial temperature of fresh concrete, presence of admixtures etc.
The idea of modeling adiabatic temperature rise during concrete hydration with the use of artificial neural networks was introduced in order to describe the adiabatic hydration of an arbitrary concrete mixture, depending on factors which influence the hydration process of cement in concrete. The influence of these factors was analized by our own experiments. This model can be easily incorporated in the computer programs for prediction of the thermal fields in young concrete structures, implemented in the finite element and finite difference codes.
Online publication: 2009-06-15
Publication type : full_text
Public price (Euros): 0.00