The Structural Reliability of the Usumacinta Bridge Using InSAR Time Series of Semi-Static Displacements
Abstract
:1. Introduction
2. Case Study
3. Methodology
3.1. PS InSAR
3.2. Reliability Index
4. Controlled Testing Using CR
5. Field Testing on the Usumacinta Bridge
Structural Reliability of the Usumacinta Bridge
6. Discussion
7. Conclusions
- The displacements of the Usumacinta Bridge achieved a maximum reliability index value (β) of 8.1 and a minimum one of 3.4. The mean value of β was 5.9, and the standard deviation was 1.4. On the other hand, the calculated monthly velocities presented a maximum probability of risk (PR) of 2.61%. The minimum value was 1.5 × 10−5%, the mean 0.4%, and the standard deviation 0.8%. Based on the results, it can be established that the areas of the bridge analyzed did not present damages produced by the heavy vehicles overloading the main structure.
- InSAR is a useful technology to determine the semi-static displacements of bridges and estimate their structural reliability. Therefore, a support decision system can be developed to improve the quality of the road infrastructure with the methodology presented in this manuscript.
- Due to the Sentinel-1 image resolution, a few zones of the bridge were analyzed, which represents a general idea of the actual reliability of the Usumacinta Bridge. An ideal assessment would be a study in detail of the bridge considering the relevant structural elements. This can be accomplished using commercial images and corner reflectors.
- The proposed probabilistic assessment can be improved by using specific limit states for each structure instead of employing a general one. In addition, more PDFs can be integrated into the methodology to obtain the structural risk.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Image Mode | Azimuthal Resolution (m) | Slant Range Resolution (m) | Ground Range Resolution (m) | Ground Range Resolution Area (m2) | Clutter (dB) |
---|---|---|---|---|---|
Interferometric wide swath | 20.0 | 5.0 | 8.7 | 174.3 | −12 |
Number of the Test | Ground Truth (mm) | InSAR Displacements (mm) | Differences (mm) |
---|---|---|---|
1 | 0 | 1 | 1 |
2 | 0 | 1.6 | 1.6 |
3 | 0 | 1 | 1 |
4 | 7.9 | 10 | 2.1 |
5 | 7.9 | 8.4 | 0.5 |
6 | 15.8 | 14.4 | −1.4 |
Number of the Test | Ground Truth (mm) | InSAR Displacements (mm) | Differences (mm) |
---|---|---|---|
1 | 0 | 0.2 | 0.2 |
2 | 0 | 0.2 | 0.2 |
3 | 0 | 1.2 | 1.2 |
4 | 7.9 | 9.1 | 1.2 |
5 | 7.9 | 8.2 | 0.3 |
6 | 15.8 | 14.6 | −1.2 |
Number of the Point | Velocity (mm/year) | Cumulative Displacements (mm) |
---|---|---|
1 | −3.5 ± 1.4 | −7 |
2 | −0.5 ± 0.35 | −1 |
3 | −0.66 ± 0.45 | −1.3 |
4 | −0.8 ± 0.59 | −1.6 |
5 | 0.37 ± 0.59 | 0.8 |
6 | 0.45 ± 0.59 | 0.9 |
7 | −0.2 ± 0.34 | −0.4 |
8 | −0.45 ± 0.57 | −0.9 |
9 | −0.19 ± 0.37 | −0.4 |
10 | 0.51 ± 0.4 | 1 |
11 | 0.37 ± 0.28 | 0.8 |
12 | 1.68 ± 0.8 | 3.4 |
13 | −0.83 ± 0.56 | −1.6 |
14 | 1.22 ± 0.9 | 2.4 |
15 | −0.29 ± 0.39 | −0.6 |
16 | −0.23 ± 0.49 | −0.4 |
Number of the Point | Mean Velocity (mm/month) | Standard Deviation (mm) |
---|---|---|
1 | −0.37 | 2.45 |
2 | 0.71 | 3.23 |
3 | −1.59 | 4.13 |
4 | −0.38 | 3.39 |
5 | 0.1 | 2.29 |
6 | −0.003 | 3.34 |
7 | 0.06 | 2.12 |
8 | 0.14 | 1.44 |
9 | 0.7 | 3.56 |
10 | 0.77 | 5.03 |
11 | 0.57 | 3.53 |
12 | 0.26 | 2.06 |
13 | −0.23 | 1.45 |
14 | −0.25 | 2.47 |
15 | 0.59 | 3.31 |
16 | 0.64 | 2.92 |
Point | Best-Fitted PDF | β |
---|---|---|
1 | Extreme Value | 8.1 |
2 | Extreme Value | 6.6 |
3 | Weibull | 6.1 |
4 | Generalized Extreme Value | 6.7 |
5 | Extreme Value | 7.5 |
6 | Extreme Value | 6.0 |
7 | Weibull | 7.6 |
8 | Stable | 5.2 |
9 | Extreme Value | 4.9 |
10 | Stable | 3.4 |
11 | Extreme Value | 6.5 |
12 | Weibull | 7.2 |
13 | T Location Scale | 5.9 |
14 | Stable | 3.6 |
15 | Extreme Value | 5.9 |
16 | Weibull | 3.7 |
Point | Best-Fitted PDF | PR |
---|---|---|
1 | Logistic | 0.013 |
2 | Logistic | 0.17 |
3 | t student | 1.64 |
4 | Stable | 2.61 |
5 | Logistic | 0.006 |
6 | Fatigue life | 0.012 |
7 | Fisk | 0.036 |
8 | Logistic | 1.5 × 10−5 |
9 | Stable | 1.78 |
10 | Generalized Extreme Value | 8.4 × 10−5 |
11 | Logistic | 0.22 |
12 | Logistic | 0.002 |
13 | Stable | 0.001 |
14 | Logistic | 0.001 |
15 | Generalized Extreme Value | 0.03 |
16 | t student | 0.35 |
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Guzman-Acevedo, G.M.; Quintana-Rodriguez, J.A.; Gaxiola-Camacho, J.R.; Vazquez-Becerra, G.E.; Torres-Moreno, V.; Monjardin-Quevedo, J.G. The Structural Reliability of the Usumacinta Bridge Using InSAR Time Series of Semi-Static Displacements. Infrastructures 2023, 8, 173. https://doi.org/10.3390/infrastructures8120173
Guzman-Acevedo GM, Quintana-Rodriguez JA, Gaxiola-Camacho JR, Vazquez-Becerra GE, Torres-Moreno V, Monjardin-Quevedo JG. The Structural Reliability of the Usumacinta Bridge Using InSAR Time Series of Semi-Static Displacements. Infrastructures. 2023; 8(12):173. https://doi.org/10.3390/infrastructures8120173
Chicago/Turabian StyleGuzman-Acevedo, German Michel, Juan A. Quintana-Rodriguez, Jose Ramon Gaxiola-Camacho, Guadalupe Esteban Vazquez-Becerra, Vanessa Torres-Moreno, and Jesus Guadalupe Monjardin-Quevedo. 2023. "The Structural Reliability of the Usumacinta Bridge Using InSAR Time Series of Semi-Static Displacements" Infrastructures 8, no. 12: 173. https://doi.org/10.3390/infrastructures8120173