Effectiveness of Addition of SCMs in Concrete against Ingress of Chloride Presented by Sichoon Park April 25, 2013 EAS 4480/CEE 4480 Environmental Data.

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Presentation transcript:

Effectiveness of Addition of SCMs in Concrete against Ingress of Chloride Presented by Sichoon Park April 25, 2013 EAS 4480/CEE 4480 Environmental Data Analysis Instructor: Professor Yuhang Wang

Background  Chloride-Induced Corrosion  Chlorides from the marine environment are able to ingress into concrete, and it affects steel reinforced rebar corrosion.  Concrete mix design is one of the solution of this problem.  Addition of SCMs

Background Diffusion Test  Bulk Diffusion Test  Chloride Permeability Test  Etc. Profile grinding is performed on the sample to measure diffusivity after exposed to chloride. SCMs: Supplementary Cementitious Materials  Slag, fly ash, silica fume, metakaolin, etc.

Non-Destructive Testing  Non-Destructive Testing (NDT): NDT is a wide group of analysis techniques used in science and industry to evaluate the properties of a material, component or system without causing damage. (April 2013)  To preserve original state of concrete material, high- frequency ultrasound test is applied to characterize material properties of concrete as one of the NDT method.

Objective To analyze the effect of addition of SCMs into concrete, material parameters (diffusivity and dissipation) from three different mix designs in concrete is investigated by using ultrasound waves. Statistical tests such as Chi-squared test, F-test, and t-test are applied to verify if material parameters from each sample are statistically different.

Sample Preparation Mix IDCement fraction in binder (%) ASTM C 150 Cement Type Slag (%) Metakaolin (%) Type II100II00 S35-MK560II355 S50-MK545II505 The number of data for diffusivity and dissipation in each mix design is 30. o A specimen (5 x 5 x 18 in.) is prepared for each mix design and the composition of each mix design is shown below.

Experimental Procedure The diffusion coefficient, D(f) [m 2 /s] : the diffusion rate of the ultrasonic field The dissipation coefficient, σ(f) [1/s] : the rate of loss of energy

Hypothesis 1 Verify if the material parameters of each mix design are normally distributed. Before hypothesis testing, what the distribution looks like to be tested.

 Null hypothesis: Verify if the material parameters of a sample in each mix design are normally distributed. Normality test (for Diffusivity )  Chi-squared test Ideal_chi2= Chi2_typeII= Chi2_S35MK5= Chi2_S50MK5=

Normality test (for Dissipation )  Chi-squared test Ideal_chi2= Chi2_typeII= Chi2_S35MK5= Chi2_S50MK5=  Null hypothesis that material parameters of each mix design are normally distributed cannot reject.

Normality test (2)  Jarque-Bera test Null hypothesis: The data in each mix design comes from a normal distribution with unknown mean and variance. Matlab syntax: [h,p] = jbtest (X,0.05) Results: all distributions come from a normal distribution. (h = 0)  Lilliefors test Null hypothesis: The data in each mix design comes from a distribution in the normal family. Matlab syntax: [h,p] = lillietest (X,0.05) Results: all distributions come from a distribution in the normal family. (h = 0) Jarque-Bera tests often use the chi-square distribution to estimate critical values for large samples, deferring to the Lilliefors test for small samples

Verify if the material parameters of each mix design are not significantly different. Hypothesis 2 F-test: Null Hypothesis: Material parameters of each mix design have equal variances Student t-test Null Hypothesis: Means of material parameters of each mix design are not significantly different

F test (for Diffusivity) F_actual= F_table= (Ftable > Factual) Not reject  Type II vs S35MK5  Type II and S50MK5  S35MK5 and S50MK5 F_actual= F_table= (Ftable > Factual) Not reject F_actual= F_table= (Ftable > Factual) Not reject

F test (for Dissipation)  Type II vs S35MK5  Type II and S50MK5  S35MK5 and S50MK5 F_actual= F_table= (Ftable < Factual) reject F_actual= F_table= (Ftable < Factual) reject F_actual= F_table= (Ftable > Factual) Not reject

Student-T test (for Diffusivity) T_cal= T_crit= h = 1 Sigt t= (h==1, thus hypothesis is rejected)  Type II vs S35MK5  Type II and S50MK5  S35MK5 and S50MK5 T_cal= T_crit= h = 1 Sigt t= (h==1, thus hypothesis is rejected) T_cal= T_crit= h = 0 Sigt t= (h==0, thus hypothesis is not rejected)

Student-T test (for Dissipation)  Type II vs S35MK5  Type II and S50MK5  S35MK5 and S50MK5 T_cal= T_crit= h = 1 Sigt t=4.9212e-020 (h==1, thus hypothesis is rejected) T_cal= T_crit= h = 1 Sigt t= e-021 (h==1, thus hypothesis is rejected) T_cal= T_crit= h = 0 Sigt t= (h==0, thus hypothesis is not rejected)

Results Summary Type II vs. S35MK5Type II vs. S50MK5S35MK5 vs. S50MK5 Diffusivity FNot reject trejectRejectNot reject Dissipation Freject Not reject trejectRejectNot reject  Null hypothesis that the material parameters of Type II and S35MK5 are not statistically different can reject.  Null hypothesis that the material parameters of Type II and S50MK5 are not statistically different can reject.  Null hypothesis that the material parameters of S35MK5 and S50MK5 are not statistically different cannot reject.

 According to statistical test results, it is shown that there appears to be a statistical difference for mean and variance of material parameters in between S35MK5/S50MK5 and Type II samples.  The difference between S35MK5/S50MK5 and Type II may relate to addition of SCMs. The addition of SCMs into concrete influenced on the formation of microstructure in concrete.  Diffusivity of ultrasonic energy in S35MK5/S50MK5 is shown to be higher than the one in Type II, which means the microstructure of S35MK5/S50MK5 is much denser than that of Type II. In conclusion, the addition of SCMs can help to prevent the ingress of Chloride into concrete. Conclusion

References [1] Chi-Won In, “Defect Characterization in Heterogeneous Civil Materials Using Ultrasound”, A dissertation in Georgia Institute of Technology, May [2] R. Brett Holland, “Durability of Precast Prestressed Concrete Piles In Marine Environments”, A dissertation in Georgia Institute of Technology, August 2012 [3] Deroo, F., Kim, J.-Y., Qu, J., Sabra, K. and Jacobs, L.J. (2010) Detection of damage in concrete using diffuse ultrasound. The Journal of the Acoustical Society of America 127, 3315.

THANK YOU Q&A