The bond behavior of reinforcing bars is an important determinant of strength an

Question

The bond behavior of reinforcing bars is an important determinant of strength and stability. The article "Experimental Study on the Bond Behavior of Reinforcing Bars Embedded in Concrete Subjected to Lateral Pressure"t reported the results of one experiment in which varying levels of lateral pressure were applied to 21 concrete cube specimens, each with an embedded 16 mm plain steel round bar, and the corresponding bond capacity was determined. Due to differing concrete cube strengths (fcur in MPa), the applied lateral pressure was equivalent to a fixed proportion of the specimen's fcu (0, O.1fcuv . .., 0.6fcu). Also, since bond strength can be heavily influenced by the specimen's fcur bond capacity was expressed as the ratio of bond strength (MPa) to Vfcu Pressure 0 0 0.1 0.10.1 0.2 0.2 0.2 0.3 0.3 0.3 0.4 Ratio 0.123 0.100 0.101 0.172 0.133 0.107 0.217 0.172 0.151 0.263 0.227 0.252 0.310 Pressure 0.4 0.4 0.5 0.5 0.5 0.6 0.6 0.6 Ratio 0.365 0.239 0.365 0.319 0.312 0.394 0.386 0.320 (a) Does a scatterplot of the data support the use of the simple linear regression model? A scatterplot of the data shows a weak, negative, linear relationship between pressure and the bond capacity ratio and supports the use of a simple linear regression model. A scatterplot of the data shows a reasonably strong, negative, linear relationship between pressure and the bond capacity ratio and supports the use of a simple linear regression model A scatterplot of the data shows a reasonably strong, positive, linear relationship between pressure and the bond capacity ratio and supports the use of a simple linear regression model A scatterplot of the data shows a reasonably strong, negative, linear relationship between pressure and the bond capacity ratio and does not support the use of a simple linear regression model A scatterplot of the data shows a weak, positive, linear relationship between pressure and the bond capacity ratio and does not support the use of a simple linear regression model

Explanation / Answer

slope =0.46071

intercept =0.10121

c) point estimate =0.10121+0.46071*0.03=0.1150

point estimate of error =(MSE)1/2 =(0.00110)1/2 =0.0331662

e) total variation =SST =0.199929

% of it that can be explained =SSR/SST =89.5%

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