Statistical Reliability Analysis of Ultrasonic Velocity Method for Predicting Residual Strength of High-Strength Concrete under High-Temperature Conditions
Abstract
:1. Introduction
2. Experimental Plan and Methods
2.1. Experimental Plan
2.2. Materials
2.3. Mix Proportion and Specimen Preparation
2.4. Test Method
3. Results and Discussion
3.1. Mechanical Properties of Concrete
3.1.1. Compressive Strength
3.1.2. Ultrasonic Pulse Velocity
3.2. Statistical Analysis
3.2.1. Statistical Significance Test for 3 Conditions
3.2.2. Statistical Significance Test according to W/C Ratio and Coarse Aggregate
3.2.3. Regression Analysis Results
4. Conclusions
- (1)
- During the early age of 16 h, all specimens exhibited similar compressive strengths. However, from 1 to 91 d of age, GNA28 showed approximately 72.93% higher strength than GNA33, and CAA28 showed approximately 23.79% higher strength than CAA33. After high-temperature exposure, the lightweight aggregate exhibited a higher residual rate than normal concrete, owing to the influence of small thermal expansion deformation.
- (2)
- At approximately 16 h, at an early age, the specimen with a W/C ratio of 0.28 showed a higher UPV than the specimen with a W/C ratio of 0.33; by 91 d of age, GNA showed approximately 8.72% higher UPV owing to the influence of the porous lightweight aggregate mixed with CAA. After high-temperature exposure, CAA showed a residual rate approximately 10.35% higher than that of GNA.
- (3)
- The compressive strength of all specimens showed a very low mean at an early age, with no significant difference between strength at middle age, and that after high-temperature exposure. UPV showed the highest mean at middle age among the three conditions, while also showing a similar average at early age and after high-temperature exposure; therefore, it was inferred as a statistically identical group.
- (4)
- In the ANOVA result of the compressive strength at an early age, the p-value was 0.05 or more, indicating insignificance. However, in middle age, all compressive strengths were significant except for GNA28. The compressive strengths of the specimens after high-temperature exposure exhibited significant differences between the groups, except for GNA33 and CAA33. On the contrary, UPV did not show a significant difference for concrete at an early age or after high-temperature exposure, except for the middle-age condition.
- (5)
- Regression analyses revealed that the exponential function forms were suitable for GNA and CAA at the early stage, and GNA at middle age. On the contrary, the linear functional forms showed optimal suitability for CAA and GNA after high-temperature exposure, and CAA at middle age. However, after high-temperature exposure, the GNA and CAA groups showed very low R-square values, primarily attributed to their dependence on the W/C ratio; as such, it is generally acknowledged that the W/C ratio of lightweight concrete assumes higher importance in model consideration.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type | Researchers | Equations of Model |
---|---|---|
Early age | R. L. Al-Mufti | |
I. Lawson | ||
T. Lee | ||
Middle age | R. K. Majhi | |
P. Shafigh | ||
G. Sua-iam | ||
S. Kou | ||
High temperature | N. V. S. Kumar | |
A. K. Saha | ||
M. Z. Islam | ||
U. Dolinar |
Item | Details |
---|---|
Types of concrete | GNA (Granite aggregate) CAA (Coal-ash aggregate) |
Water–cement ratio | 0.33, 0.28 |
Elapsed time at early age | 6, 12, 16, 20, 24 h |
Curing age | 1, 7, 28, 91 d |
Heating temperature | 20, 200, 300, 500, 700 °C |
Mechanical properties | Compressive strength UPV (Ultrasonic pulse velocity) |
Statistical analysis | Levene’s test, ANOVA (or Welch’s ANOVA), Post hoc test, Regression analysis, Error test |
Item | Details |
---|---|
Cement | ASTM Type-I ordinary Portland cement Density: 3150 kg/m3, fineness: 320 m2/kg |
Coarse aggregate | Granite aggregate Density: 2680 kg/m3, fineness modulus: 7.03, absorption: 0.68%, Sizemax: 20 mm |
Coal-ash aggregate Density: 1470 kg/m3, fineness modulus: 6.39, absorption: 8.68%, Sizemax: 20 mm | |
Fine aggregate | River sand Density: 2540 kg/m3, fineness modulus: 2.54, absorption: 1.60% |
Super plasticizer (SP) | Polycarboxylic-based super plasticizer |
Materials | Chemical Compositions (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|
CaO | SiO2 | Al2O3 | Fe2O3 | MgO | SO3 | K2O | Others | L.O.I | |
OPC (1) | 60.30 | 19.80 | 4.90 | 3.30 | 3.80 | 2.90 | 1.10 | 0.90 | 3.00 |
Mix ID | Ratio | Unit Weight (kg/m3) | |||||
---|---|---|---|---|---|---|---|
W/C (1) | S/a (2) | Water | Cement | River Sand | Granite Aggregate | Coal-Ash Aggregate | |
GNA33 | 0.33 | 0.43 | 165 | 500 | 711 | 762 | - |
GNA28 | 0.28 | 500 | 711 | - | 533 | ||
CAA33 | 0.33 | 600 | 676 | 896 | - | ||
CAA28 | 0.28 | 600 | 676 | - | 507 |
ID | Mean Difference | p-Value | ID | Grouping Letters Table | |||
---|---|---|---|---|---|---|---|
Comp. | UPV | Comp. | UPV | Comp. | UPV | ||
GNA33_E & GNA33_M | 20.35 | 1211.68 | 0.001 | 0.006 | GNA33_E | A | A |
GNA33_E & GNA33_H | 23.06 | 212.23 | <0.001 | 1.000 | GNA33_M | A | B |
GNA33_M & GNA33_H | 2.70 | 999.45 | 1.000 | 0.023 | GNA33_H | B | B |
GNA28_E & GNA28_M | 44.39 | 1417.18 | <0.001 | 0.003 | GNA28_E | A | A |
GNA28_E & GNA28_H | 56.08 | 420.77 | <0.001 | 0.84 | GNA28_M | A | B |
GNA28_M & GNA28_H | 11.69 | 996.42 | 0.46 | 0.04 | GNA28_H | B | B |
CAA33_E & CAA33_M | 19.45 | 821.64 | <0.001 | 0.007 | CAA33_E | A | A |
CAA33_E & CAA33_H | 24.45 | 148.64 | <0.001 | 0.818 | CAA33_M | A | B |
CAA33_M & CAA33_H | 5.00 | 672.99 | 0.67 | 0.026 | CAA33_H | B | B |
CAA28_E & CAA28_M | 31.63 | 970.12 | <0.001 | 0.003 | CAA28_E | A | A |
CAA28_E & CAA28_H | 36.73 | 295.30 | <0.001 | 0.785 | CAA28_M | A | B |
CAA28_M & CAA28_H | 5.10 | 674.82 | 0.539 | 0.041 | CAA28_H | B | B |
ID | Mean Difference | p-Value | ID | Grouping Letters Table | |||
---|---|---|---|---|---|---|---|
Comp. | UPV | Comp. | UPV | Comp. | UPV | ||
GNA33_E & GNA28_E | 10.17 | 252.05 | 0.221 | 1.000 | GNA33_E | A | A |
GNA33_E & CAA33_E | 0.04 | 97.86 | 1.000 | 1.000 | GNA28_E | A | A |
GNA28_E & CAA33_E | 10.13 | 349.88 | 0.226 | 1.000 | CAA33_E | A | A |
GNA33_E & CAA28_E | 4.22 | 234.92 | 1.000 | 1.000 | CAA28_E | A | A |
GNA28_E & CAA28_E | 5.95 | 17.12 | 1.000 | 1.000 | - | ||
CAA33_E & CAA28_E | 4.19 | 332.76 | 1.000 | 1.000 | - | ||
GNA33_M & GNA28_M | 34.20 | 457.55 | <0.001 | 0.011 | GNA33_M | B | B |
GNA33_M & CAA33_M | 0.87 | 487.88 | 1.000 | 0.006 | GNA28_M | A | A |
GNA28_M & CAA33_M | 35.07 | 945.42 | <0.001 | <0.001 | CAA33_M | B | C |
GNA33_M & CAA28_M | 15.50 | 6.64 | 0.119 | 1.000 | CAA28_M | B | B |
GNA28_M & CAA28_M | 18.70 | 464.18 | 0.034 | 0.009 | - | ||
CAA33_M & CAA28_M | 16.37 | 481.24 | 0.086 | 0.007 | - | ||
GNA33_H & GNA28_H | 43.19 | 460.58 | <0.001 | 1.000 | GNA33_H | C | A |
GNA33_H & CAA33_H | 1.43 | 161.42 | 1.000 | 1.000 | GNA28_H | A | A |
GNA28_H & CAA33_H | 41.76 | 622.00 | <0.001 | 0.736 | CAA33_H | C | A |
GNA33_H & CAA28_H | 17.89 | 318.00 | 0.017 | 1.000 | CAA28_H | B | A |
GNA28_H & CAA28_H | 25.30 | 142.58 | <0.001 | 1.000 | - | ||
CAA33_H & CAA28_H | 16.46 | 479.42 | 0.034 | 1.000 | - |
ID | Model | p-Value | Pearson’s r | R-Square | RMSE |
---|---|---|---|---|---|
GNA_E | Linear | <0.0010 | 0.82 | 0.67 | 7.89 |
Exponential | <0.0001 | - | 0.89 | 4.52 | |
GNA_M | Linear | <0.0001 | 0.92 | 0.85 | 9.49 |
Exponential | <0.0001 | - | 0.91 | 7.36 | |
GNA_H | Linear | 0.0001 | 0.70 | 0.49 | 20.09 |
Exponential | 1.0000 | - | −3.99 | 63.13 | |
CAA_E | Linear | <0.0001 | 0.84 | 0.71 | 5.16 |
Exponential | <0.0001 | - | 0.93 | 2.50 | |
CAA_M | Linear | <0.0001 | 0.96 | 0.93 | 4.03 |
Exponential | <0.0001 | - | 0.90 | 4.85 | |
CAA_H | Linear | <0.0001 | 0.88 | 0.77 | 6.26 |
Exponential | 1.0000 | - | −11.51 | 45.86 |
ID | Types of Models | Equation | Regression Coefficient (R2) | |
---|---|---|---|---|
Early age | GNA | Exponential function | 0.89 | |
CAA | 0.93 | |||
Middle age | GNA | 0.91 | ||
CAA | Linear function | 0.93 | ||
High temperature | GNA | 0.49 | ||
CAA | 0.77 |
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Kim, W.; Jeong, K.; Lee, T. Statistical Reliability Analysis of Ultrasonic Velocity Method for Predicting Residual Strength of High-Strength Concrete under High-Temperature Conditions. Materials 2024, 17, 1406. https://doi.org/10.3390/ma17061406
Kim W, Jeong K, Lee T. Statistical Reliability Analysis of Ultrasonic Velocity Method for Predicting Residual Strength of High-Strength Concrete under High-Temperature Conditions. Materials. 2024; 17(6):1406. https://doi.org/10.3390/ma17061406
Chicago/Turabian StyleKim, Wonchang, Keesin Jeong, and Taegyu Lee. 2024. "Statistical Reliability Analysis of Ultrasonic Velocity Method for Predicting Residual Strength of High-Strength Concrete under High-Temperature Conditions" Materials 17, no. 6: 1406. https://doi.org/10.3390/ma17061406
APA StyleKim, W., Jeong, K., & Lee, T. (2024). Statistical Reliability Analysis of Ultrasonic Velocity Method for Predicting Residual Strength of High-Strength Concrete under High-Temperature Conditions. Materials, 17(6), 1406. https://doi.org/10.3390/ma17061406