To develop the method for concrete setting evaluation, different types of concrete specimens were tested using Smartec Standard SOFO sensors, Concrete Setting SOFO Sensors and for a purpose developed slim sensor. The specimens were mostly cylindrically and rectangularly shaped with various border conditions in terms of strain, temperature insulation and humidity insulation. To keep the cost limited specially designed re-usable moulds were developed.
Aim of monitoring:
The overall objective of this project was to develop a methodology for predicting mechanical properties and for separating important phenomena in hardening materials, such as commercial concrete and mortar, to be ultimately applied in real-time and in situ.
|INSTALLATION PERIOD||TYPE OF SENSORS||NUMBER OF SENSORS|
|2002 – 2005||SOFO||80|
Results confirm the hypothesis that relative hardening curves obtained using early age measurement of standard and setting SOFO sensors are related to properties of concrete such as activation energy, rate of reaction and equivalent age. The work performed in this project demonstrates that compressive strength evolution can be predicted and that a decomposition of the total deformation into the effects of physical phenomena is possible in real-time and in situ. More specifically, during this work the following results have been achieved: • Compressive strength evolution has been successfully predicted for seven very different types of concretes after only three days of measurements • Strength-maturity curves obtained can be reused for the same mix to determine, by instance, save removal times for shores and moulds, cable release in prestressed units (see Figures 1 and 3) • A prototype of testing equipment has been developed. It allows for to reuse of sensors, reducing laboratory expenses • Autogenous deformation, thermal expansion coefficient and drying deformation have been calculated for six types of concrete mixes and one type of mortar • A new, low axial stiffness sensor has been developed • Software for the treatment and interpretation of data has been implemented