Research Article
Prediction of Compressive Strength Behavior of Ground Bottom Ash Concrete by an Artificial Neural Network
Table 3
Materials compositions for different mixes at 0–50% replacement with GBA.
| WB | Cement (kg/m3) | GBA (kg/m3) | Water (kg/m3) | Sand (kg/m3) | Stone (kg/m3) |
| 0.80 | 244–122 | 0–122 | 195 | 789–793 | 1024–1016 | 0.70 | 279–140 | 0–140 | 195 | 770–764 | 1024–1015 | 0.62 | 315–158 | 0–158 | 195 | 741–733 | 1024–1014 | 0.55 | 355–178 | 0–178 | 195 | 708–700 | 1024–1012 | 0.48 | 406–203 | 0–203 | 195 | 665–656 | 1024–1010 | 0.43 | 454–227 | 0–227 | 195 | 626–617 | 1024–1008 |
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GBA: ground bottom ash.
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