PREDICTION OF COMPRESSIVE STRENGTH OF CONCRETE FROM EARLY AGE TEST RESULT

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  1. 1. PREDICTION OF COMPRESSIVE STRENGTH OF CONCRETE FROM EARLY AGE TEST RESULT M. Monjurul Hasan Undergraduate Student (Level-4, Term-2) Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh Dr. Ahsanul Kabir Professor, Dept. of Civil Engineering Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh
  2. 2. Outline Introduction Objective Previous Approaches. Proposed Approach Mathematical Model Performance Conclusion
  3. 3. Introduction Concrete has versatile use in the construction practice. The compressive strength is one of the most important and useful properties of concrete. The design strength of the concrete normally represents its 28th day strength. 28 days is a considerable time to wait for the test results of concrete strength, while it is mandatory to represent the process of quality control.
  4. 4. Introduction (Contd..) For every mix one has to wait a long time for the assurance of its quality. Hence, the need for an easy and suitable means for estimating the strength at an early age of concrete is being felt all the time.
  5. 5. Objective To develop a simple relation which has the potential to predict the compressive strength of the concrete from early days strength. To evaluate nature of concrete strength gain pattern with time for a particular type of mix. To formulate a quick, handy & flexible computational method to asses the nature of concrete strength gain with time.
  6. 6. Previous Approaches Traditional empirical formula Linear Regression model Artificial neural network Genetic algorithm Support vector mechanism M5P Tree model
  7. 7. Proposed Approach (Nonlinear Regression model) Data used for this study was taken from previous study (Garg, 2003).
  8. 8. Proposed Approach ( cont. ) Concrete Data Ranges (without Admixture, ordinary Portland cement)
  9. 9. Proposed Approach ( cont. ) First step : to understand the strength gaining pattern of the concrete with age
  10. 10. Proposed Mathematical Model The Mathematical Model: where, Stn = Strength of the concrete at nth day.(n = 1,2,3,..); Dn = Number of days; p and q are constants for each curve but different for different data sets (curves). Though this equation (Eq. 1) is formed independently, it is similar to the equation (Eq. 2) proposed by ACI committee ( ACI 209-71) for predicting compressive strength at any time. Here a and b are constants, = 28-day strength and t is time and this equation (Eq. 2) can be recast to similar form of Equation 1. dcf 28 ' )(
  11. 11. Mathematical Model ( Cont. ...) To utilize the above equation (Eq. 1), just value of two constants (p and q) are to be determined. It was observed that, , values of p can be expressed as the function of q and (Stn) [which is a polynomial surface equation]. The equation of the correlation is given below: p = a + b.q + c.Stn + d.q.Stn + e.Stn 2 (3) Where, Stn= Strength of the concrete at nth day. (n = 1, 2, 3, ) and a, b, c, d and e are the coefficients.
  12. 12. Mathematical Model ( Cont. ...) As we build up the correlation for 7th day test result of concrete [n=7], the values of the coefficients were derived as, a = 10.23; b = -0.9075; c = 0.3412; d = 0.1721; e = 0.0112 from regression analysis of the available data for concrete with stone chips as course aggregate Putting these values in Equation 3 the following equation was obtained: p = 10.23 - 0.9075q + 0.3412St7 + 0.1721q.St7 + 0.0112St7 2 (4) For 14th day strength results [n=14] the coefficients are, a = -4.527; b = -1.041; c = 1.373; d = 0.1406; e = -0.0125. Putting these values into Equation 3 the following equation was obtained: p = -4.527- 1.041q + 1.373St14 + 0.1406q.St14 - 0.0125St14 2 (5)
  13. 13. Mathematical Model ( Cont. ...) Represented surface .
  14. 14. Mathematical Model ( Cont. ...) Represented surface .
  15. 15. Performance
  16. 16. Performance ( Cont. ...)
  17. 17. Performance ( Cont. ...)
  18. 18. Conclusion This paper represents a simple mathematical model In this study, the concrete strength gain characteristic with age is modeled by a simple mathematical equation (rational polynomial) and a polynomial surface equation The proposed equations have the potential to predict strength data for every age. This will help in making quick decision for accidental poor concreting at site and reduce delay.
  19. 19. Thats it, Thank You