Utilizing Data driven techniques to determine concrete Strength using concrete temperature and time

Abstract

[500] Concrete strength determination is the utmost important property to be considered for rejecting or accepting a batch of concrete. Concrete strength determination is primarily done using destructive and non-destructive methods. The maturity method is a non-destructive technique for estimating the strength of concrete in real time. The maturity method relies on the measured temperature history of the concrete to estimate strength development during the curing period, when moisture is available for cement hydration. Measuring the concrete temperature over time enables you to know how far the concrete is in the hydration process (Concrete Maturity) and thereby also an estimated concrete strength. Underlying principle is that concrete cured with different temperatures but with the same maturity index will have an equal concrete strength. This can ultimately used to ascertain formwork removal time. Maturity method is a technique for estimating concrete strength that assumes that samples of a given concrete mixture attain equal strengths if they attain equal values of the maturity index [ ASTMC1074]. For this method in place, sensors are embedded in concrete and a real time tracking of the core temperature is done with reference to number of days and further this data can be used for calculating the maturity index and thus further the strength of concrete. With the same concept the present proposal proposes two-fold aims: to determine the strength of concrete using sensor temperature and time as major factors and to determine the surface temperature of concrete by using core temperature and time as primary factors and further by using the estimated surface temperature predict the strength of concrete. The said aims will be done using Data driven Techniques as Non-Linear Regression, Artificial Neural Network and Genetic Programming (Variant: Multi Gene Genetic Programming). The equation developed for each Grade of concrete can be readily used in real time.

Specification

Description:Strength determination of concrete is a critical aspect in concrete technology and primarily done using testing of concrete cubes/cylinders etc. in laboratory. However, on site when concrete is poured in the formwork, it becomes important to know the strength of its concrete in view of form work removal. Similarly, strength of concrete at a given time needs to be known for stripping forms and removing formwork safely in cast-in-situ components, apply post-tension in bridge decks/ beams etc, determining the actual temperature differential allowed to prevent cracking in mass concrete, estimating modulus of elasticity at very early ages in deformation concrete members, correct estimate of strength to avoid damages etc. To determine strength of concrete at a given time, maturity concept of concrete is utilised which along with time considers the temperature during early period of hydration that influence the rate of gain of strength of concrete. Thus, if strength of concrete at full maturity is known, then by using Plowman's equations one can determine the percentage strength of identical concrete at any given maturity as a percentage of strength of maturity. By the wide spread knowledge and application of Data driven techniques in concrete technology, the process of strength prediction using the core temperature of concrete cylinder/cylinder, surface temperature of concrete cube/cylinder and time can be done. For this method in place, sensors are embedded in concrete and a real time tracking of the core temperature is done with reference to number of days and further this data can be used for calculating the maturity index and thus further the strength of concrete. With the same concept the present proposal proposes two-fold aims: to determine the strength of concrete using sensor temperature and time as major factors and to determine the surface temperature of concrete by using core temperature and time as primary factors and further by using the estimated surface temperature predict the strength of concrete. The said aims will be done using Data driven Techniques as Non-Linear Regression, Artificial Neural Network and Genetic Programming (Variant: Multi Gene Genetic Programming). The equation developed for each Grade of concrete can be readily used in real time. , Claims:1. Equations derived from Nonlinear regression and Multi Gene Genetic programming and weights and biases for Artificial Neural Network to predict the strength of concrete (of M25 Grade) using core temperature and time as input parameters.
2. Equations derived from Nonlinear regression and Multi Gene Genetic programming and weights and biases for Artificial Neural Network to predict the strength of concrete (of M25 Grade) using surface temperature and time as input parameters.
3. Equations derived from Nonlinear regression and Multi Gene Genetic programming and weights and biases for Artificial Neural Network to predict the strength of concrete using two-fold methodology: 1. Predict surface temperature of concrete cube/cylinder using core temperature and time as input parameters. Further by using the predicted surface temperature the strength (of M25 Grade) of concrete cube/cylinder can be predicted.

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