Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests
Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 an...
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| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad
2018-01-01
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| Series: | Journal of Engineering |
| Online Access: | https://www.jcoeng.edu.iq/index.php/main/article/view/489/417 |
| _version_ | 1797707423297830912 |
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| author | Suhair K. Al-Hubboubi Zena K. Abbas |
| author_facet | Suhair K. Al-Hubboubi Zena K. Abbas |
| author_sort | Suhair K. Al-Hubboubi |
| collection | DOAJ |
| description | Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.
The experimental results showed that the accelerated strength were equal to about (0.356), (0.492) and (0.595) of the 28-day compressive strength for warm water, autogenous and British curing methods respectively. A statistical regression analysis using SPSS program is implemented for the experimental results of the 28-day compressive strength ranging from (16 to 55.2)Mpa and accelerated strength for different curing methods. The linear models with high R2 and F-value are adopted for different curing methods while the Power model with constant is the best model for non parametric analysis. |
| first_indexed | 2024-03-12T06:07:09Z |
| format | Article |
| id | doaj.art-db6a9513cd7745a9872e4ced505a4b32 |
| institution | Directory Open Access Journal |
| issn | 1726-4073 2520-3339 |
| language | English |
| last_indexed | 2024-03-12T06:07:09Z |
| publishDate | 2018-01-01 |
| publisher | University of Baghdad |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj.art-db6a9513cd7745a9872e4ced505a4b322023-09-03T03:34:44ZengUniversity of BaghdadJournal of Engineering1726-40732520-33392018-01-01241119Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing TestsSuhair K. Al-HubboubiZena K. AbbasRegression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3. The experimental results showed that the accelerated strength were equal to about (0.356), (0.492) and (0.595) of the 28-day compressive strength for warm water, autogenous and British curing methods respectively. A statistical regression analysis using SPSS program is implemented for the experimental results of the 28-day compressive strength ranging from (16 to 55.2)Mpa and accelerated strength for different curing methods. The linear models with high R2 and F-value are adopted for different curing methods while the Power model with constant is the best model for non parametric analysis.https://www.jcoeng.edu.iq/index.php/main/article/view/489/417 |
| spellingShingle | Suhair K. Al-Hubboubi Zena K. Abbas Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests Journal of Engineering |
| title | Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests |
| title_full | Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests |
| title_fullStr | Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests |
| title_full_unstemmed | Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests |
| title_short | Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests |
| title_sort | regression analysis models to predict the 28 day compressive strength using accelerated curing tests |
| url | https://www.jcoeng.edu.iq/index.php/main/article/view/489/417 |
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