Predicting Concrete Compressive Strength Using Ultrasonic Pulse Velocity and Rebound Number

This paper shows how, as a general index of concrete strength, the compressive strength of concrete f(c) is important in the performance assessment of existing reinforced concrete (RC) structures. The paper shows how many nondestructive testing methods have been developed to estimate the in-place value of f(c). In particular, the combination of rebound hammer and ultrasonic pulse velocity tests, known as SonReb, is frequently used. With the SonReb measurements, regression models are commonly applied to predict f(c). The available regression models are not sufficiently valid, however, because of the limited range of data used for their calibration. This paper proposes a probabilistic multivariable linear regression model to predict f(c) using SonReb measurements and additional concrete properties. The Bayesian updating rule and the all possible subsets model selection are used to develop the proposed model based on the collected data with a wide range of concrete properties. The proposed model is compared with currently available regression models, concluding that the proposed model gives, on average, a more accurate prediction.

[1]  Clifford M. Hurvich,et al.  Regression and time series model selection in small samples , 1989 .

[2]  G. Trtnik,et al.  Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. , 2009, Ultrasonics.

[3]  T. H. Wee,et al.  DEVELOPMENT OF STATISTICAL QUALITY ASSURANCE CRITERION FOR CONCRETE USING ULTRASONIC PULSE VELOCITY METHOD , 1999 .

[4]  J L Schafer,et al.  Multiple Imputation for Multivariate Missing-Data Problems: A Data Analyst's Perspective. , 1998, Multivariate behavioral research.

[5]  Stefan Hurlebaus,et al.  Adaptive Reliability Analysis of Reinforced Concrete Bridges Using Nondestructive Testing , 2011 .

[6]  Jerzy Hoła,et al.  New technique of nondestructive assessment of concrete strength using artificial intelligence , 2005 .

[7]  Manish A. Kewalramani,et al.  Concrete compressive strength prediction using ultrasonic pulse velocity through artificial neural networks , 2006 .

[8]  Sandor Popovics,et al.  History of a Mathematical Model for Strength Development of Portland Cement Concrete , 1998 .

[9]  Robert Gould,et al.  A Modern Approach to Regression with R , 2010 .

[10]  V. M. Malhotra,et al.  Comparison of Pullout Strength of Concrete with Compressive Strength of Cylinders and Cores, Pulse Velocity, and Rebound Number , 1980 .

[11]  Roderick J. A. Little.  Regression with Missing X's: A Review , 1992 .

[12]  A. Samarin,et al.  Use of Combined Ultrasonic and ReboundHammer Method for Determiningstrength of concrete structural members , 1981 .

[13]  A. Christopoulos,et al.  Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting , 2004 .

[14]  D. Breysse.  NON-DESTRUCTIVE ASSESSMENT OF CONCRETE DAMAGE: INTEREST, DIFFICULTIES AND RESEARCH NEEDS , 2009 .

[15]  H. Chung,et al.  Effects of embedded steel bars upon ultrasonic testing of concrete , 1978 .

[16]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[17]  Hiroshi Mori,et al.  Estimation of Concrete Strength by Combined Nondestructive Testing Method , 1984 .

[18]  Maria Q. Feng,et al.  Neuro-fuzzy application for concrete strength prediction using combined non-destructive tests , 2009 .

[19]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .

[20]  H. Akaike.  A new look at the statistical model identification , 1974 .

[21]  Tsong Yen,et al.  Prediction of Ultrasonic Pulse Velocity (UPV) in Concrete , 2003 .

[22]  R. Dennis Cook,et al.  Graphics for Assessing the Adequacy of Regression Models , 1997 .

[23]  Joseph L Schafer,et al.  Analysis of Incomplete Multivariate Data , 1997 .

[24]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[25]  G. F. Kheder.  A two stage procedure for assessment of in situ concrete strength using combined non-destructive testing , 1999 .

[26]  B. Hobbs,et al.  Non-destructive testing techniques for the forensic engineering investigation of reinforced concrete buildings. , 2007, Forensic science international.

[27]  C. R. Passerino,et al.  Combined non-destructive methods applied to normal-weight and lightweight-concrete , 2004 .

[28]  Sandor Popovics,et al.  Ultrasonic pulse velocity test of concrete properties as specified in various standards , 1996 .

[29]  P. Beno,et al.  The use of combined non-destructive testing methods to determine the compressive strength of concrete , 1984 .

[30]  Moon Sung Lee,et al.  The assessment of the compressive strength and thickness of concrete structures using nondestructive testing and an artificial neural network , 2009 .

[31]  D. Rubin.  Multiple imputation for nonresponse in surveys , 1989 .

[32]  C. T. Tam,et al.  Strength evaluation of recycled-aggregate concrete byin-situ tests , 1988 .