Research Article
Time-Dependent Reliability Analysis of RC Deep Beams considering Linear/Nonlinear Creep and Shrinkage Using ANFIS Network and MCS
Table 5
Train data used in ANFIS for the load level of 40% of the beam strength (100 input-output datasets).
| | | | | | | | L (mm) | |
| | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 2.41 | | 0.8 | 0.8 | 30 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 2.12 | | 0.7 | 0.7 | 30 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 2.01 | | 1 | 1 | 40 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 2.32 | | 1 | 1 | 50 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 1.95 | | 1 | 1 | 30 | 0.012 | 0.8 | 7 | 0.6 | 3000 | 2.04 | | 1 | 1 | 30 | 0.012 | 0.7 | 7 | 0.6 | 3000 | 1.96 | | 1 | 1 | 30 | 0.012 | 0.6 | 7 | 0.6 | 3000 | 1.84 | | 1 | 1 | 30 | 0.012 | 0.5 | 7 | 0.6 | 3000 | 1.78 | | 1 | 1 | 30 | 0.012 | 1.2 | 7 | 0.6 | 3000 | 2.52 | | 1 | 1 | 30 | 0.012 | 1.45 | 7 | 0.6 | 3000 | 3.08 | | 1 | 1 | 30 | 0.012 | 1.7 | 7 | 0.6 | 3000 | 4.43 | | 1 | 1 | 30 | 0.012 | 2 | 7 | 0.6 | 3000 | 4.97 | | 1 | 1 | 30 | 0.012 | 2.2 | 7 | 0.6 | 3000 | 5.66 | | 1 | 1 | 30 | 0.012 | 2.4 | 7 | 0.6 | 3000 | 6.13 | | 1 | 1 | 30 | 0.012 | 2.5 | 7 | 0.6 | 3000 | 6.43 | | 1 | 1 | 30 | 0.013 | 1.1 | 7 | 0.6 | 3000 | 2.4 | | 1 | 1 | 45 | 0.015 | 1.1 | 7 | 0.6 | 3000 | 2.38 | | 1 | 1 | 40 | 0.017 | 1.1 | 7 | 0.6 | 3000 | 2.35 | | 1 | 1 | 50 | 0.018 | 1.1 | 7 | 0.6 | 3000 | 2.32 | | 1 | 1 | 40 | 0.02 | 1.1 | 7 | 0.6 | 3000 | 2.3 | | 1.2 | 1.3 | 30 | 0.012 | 1.1 | 7 | 0.6 | 3000 | 3.65 | | 1 | 1 | 30 | 0.012 | 1.1 | 14 | 0.6 | 3000 | 2.34 | | 1 | 1 | 30 | 0.012 | 1.1 | 21 | 0.6 | 3000 | 2.11 | | 1 | 1 | 30 | 0.012 | 1.1 | 28 | 0.6 | 3000 | 2.02 | | 1 | 1 | 30 | 0.012 | 1.1 | 35 | 0.6 | 3000 | 1.96 | | 1 | 1 | 30 | 0.012 | 1.1 | 42 | 0.6 | 3000 | 1.91 | | 1 | 1 | 30 | 0.012 | 1.1 | 49 | 0.6 | 3000 | 1.86 | | 1 | 1 | 30 | 0.012 | 1.1 | 56 | 0.6 | 3000 | 1.84 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.3 | 3000 | 4.98 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.4 | 3000 | 4.11 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.5 | 3000 | 3.34 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.7 | 3000 | 2.03 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.8 | 3000 | 1.87 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.9 | 3000 | 1.76 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 4000 | 3.6 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 5000 | 5.94 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 6000 | 9.12 | | 1 | 1 | 35 | 0.012 | 1.1 | 14 | 0.6 | 7000 | 10.14 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 8000 | 17.77 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.4 | 8000 | 19.37 | | 1 | 1 | 50 | 0.018 | 1.1 | 49 | 0.4 | 8000 | 15.88 | | 1 | 1 | 40 | 0.012 | 1.1 | 7 | 0.6 | 8000 | 18.31 | | 0.5 | 0.5 | 30 | 0.012 | 1.1 | 7 | 0.6 | 8000 | 12.66 | | 1 | 1 | 30 | 0.012 | 1.1 | 21 | 0.6 | 8000 | 17.39 | | 1 | 1 | 30 | 0.012 | 1.1 | 14 | 0.6 | 8000 | 16.98 | | 1 | 1 | 30 | 0.012 | 1.1 | 3 | 0.6 | 8000 | 22.14 | | 1 | 1 | 30 | 0.02 | 1.1 | 7 | 0.6 | 3000 | 2.38 | | 1 | 1 | 30 | 0.025 | 1.1 | 7 | 0.6 | 3000 | 2.35 | | 1 | 1 | 30 | 0.005 | 1.1 | 7 | 0.6 | 3000 | 2.43 | | 1 | 1 | 30 | 0.006 | 1.1 | 7 | 0.6 | 3000 | 2.43 | | 1 | 1 | 30 | 0.009 | 1.1 | 7 | 0.6 | 3000 | 2.42 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 12.58 | | 1 | 1 | 30 | 0.012 | 1.1 | 7 | 0.4 | 7000 | 14.17 | | 1 | 1 | 50 | 0.018 | 1.1 | 49 | 0.4 | 7000 | 12.78 | | 1 | 1 | 40 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 12.31 | | 0.5 | 0.5 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 10.27 | | 1 | 1 | 30 | 0.012 | 1.1 | 21 | 0.6 | 7000 | 11.19 | | 1 | 1 | 30 | 0.012 | 1.1 | 14 | 0.6 | 7000 | 12.18 | | 1 | 1 | 30 | 0.012 | 1.1 | 3 | 0.6 | 7000 | 13.44 | | 1.2 | 1.35 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 15.02 | | 0.4 | 0.4 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 8.21 | | 0.8 | 0.4 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 9.48 | | 0.9 | 0.9 | 30 | 0.018 | 1.1 | 7 | 0.6 | 7000 | 11.11 | | 1.1 | 1.1 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 13.49 | | 1.4 | 1.2 | 30 | 0.012 | 1.1 | 7 | 0.6 | 7000 | 15.01 | | 1 | 1 | 30 | 0.01 | 1.1 | 7 | 0.6 | 5000 | 5.98 | | 1 | 1 | 30 | 0.018 | 1.1 | 7 | 0.6 | 5000 | 5.91 | | 1 | 1 | 30 | 0.02 | 1.1 | 7 | 0.6 | 5000 | 5.85 | | 1 | 1 | 30 | 0.03 | 1.1 | 7 | 0.6 | 5000 | 5.63 | | 1 | 1 | 30 | 0.002 | 1.1 | 7 | 0.6 | 5000 | 6.11 | | 1 | 1 | 30 | 0.003 | 1.1 | 7 | 0.6 | 5000 | 6.08 | | 1 | 1 | 30 | 0.005 | 1.1 | 7 | 0.6 | 5000 | 6.05 | | 1 | 1 | 30 | 0.006 | 1.1 | 7 | 0.6 | 5000 | 6.05 | | 1 | 1 | 30 | 0.007 | 1.1 | 7 | 0.6 | 5000 | 6.03 | | 1 | 1 | 30 | 0.012 | 5 | 7 | 0.6 | 6000 | 68.24 | | 1 | 1 | 30 | 0.012 | 4.8 | 7 | 0.6 | 6000 | 51.05 | | 1 | 1 | 30 | 0.012 | 4.3 | 7 | 0.6 | 6000 | 46.37 | | 1 | 1 | 30 | 0.012 | 4 | 7 | 0.6 | 6000 | 39.98 | | 1 | 1 | 30 | 0.012 | 3.5 | 7 | 0.6 | 6000 | 28.51 | | 1 | 1 | 30 | 0.012 | 3.2 | 7 | 0.6 | 6000 | 25.18 | | 1 | 1 | 30 | 0.012 | 3 | 7 | 0.6 | 6000 | 18.24 | | 1 | 1 | 30 | 0.012 | 2.7 | 7 | 0.6 | 6000 | 14.15 | | 1 | 1 | 30 | 0.012 | 2.5 | 7 | 0.6 | 6000 | 12.34 | | 1 | 1 | 30 | 0.012 | 5.3 | 7 | 0.6 | 6000 | 72.34 | | 1 | 1 | 30 | 0.012 | 5.8 | 7 | 0.6 | 6000 | 80.47 | | 1 | 1 | 30 | 0.012 | 4.5 | 7 | 0.6 | 6000 | 48.92 | | 1 | 1 | 30 | 0.012 | 1.1 | 21 | 0.6 | 5000 | 5.56 | | 1 | 1 | 30 | 0.012 | 1.1 | 28 | 0.6 | 5000 | 5.13 | | 1 | 1 | 30 | 0.012 | 1.1 | 35 | 0.6 | 5000 | 4.97 | | 1 | 1 | 30 | 0.012 | 1.1 | 42 | 0.6 | 5000 | 4.74 | | 1 | 1 | 30 | 0.012 | 1.1 | 49 | 0.6 | 5000 | 4.38 | | 1 | 1 | 30 | 0.012 | 1.1 | 56 | 0.6 | 5000 | 4.11 | | 1 | 1 | 30 | 0.012 | 1.1 | 3 | 0.6 | 5000 | 6.18 |
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