PSI - Issue 44

Andrea Nettis et al. / Procedia Structural Integrity 44 (2023) 1996–2003 Andrea Nettis et al. / Structural Integrity Procedia 00 (2022) 000 – 000

2001

6

associated with almost complete coverage of PSs (POP included in the range 0.80-1.00). A percentage of footprints equal to 14% exhibits POP values included in the range 0.60-0.80. The percentage of bridges characterised by a POP higher than 0.80 is equal to 84% for motorways, while it decreases to 65% for primary roads. This is likely related to the larger road width of motorways with respect to roads of minor importance which leads to a higher number of detected coherent scatterers. Examples of bridges characterised by different PS coverage are reported in Fig. 2. 3.4. Discussion on deformation scenarios The deformation scenarios identified for the bridges in the investigated case-study networks are illustrated in this section. Fig. 3 reports the GDV and DDV values. Only the bridges characterised by a POP parameter higher than 0.40 are considered in this discussion. According to Peduto et al. (2018), stable bridges (not affected by any significant deformation) are associated with a deformation velocity lower than 2 mm/year. With reference to the GDV (Fig. 3a), several bridges are associated with a value between 2 mm/year and 4 mm/year. It is worth mentioning that most of the bridges showing GDV or DDV higher than 2 mm/year are located in areas affected by subsidence as described by (Orellana et al., 2020). These areas are characterized by alluvial deposits of the Tevere and Aniene rivers, respectively and are indicated with A1 and A2 in Fig. 3a. MTInSAR results for these areas are shown in Fig. 1b and c. The results of the interferometry analysis on selected test bridges are shown in Fig. 4. The location of these test bridges is indicated in Fig. 3b. The PSs are shown as point-type markers whose colour depends on the corresponding LOS-projected velocity. The bridges T1-1 and T1-2 exhibit a similar deformation scenario characterised by a GDV of approximately -3.0 mm/year and a maximum cluster deformation of -5.5 mm/year (DDV is 2.5 mm/year) observed in the spans overlapping the main branch of the A91. Note that, in this study, both PS associated with ascending and descending SAR images are used in the calculation of GDV and DDV. This is deemed to be correct since both PS datasets show displacement moving away from the satellite (denoting mainly displacements are in the vertical direction). If PSs report displacements having opposite trends, these datasets should be treated separately and further elaborations to compose the two datasets (Talledo et al., 2022) are required. Fig. 4b shows three bridges on the Tevere river. These test bridges are affected by differential displacements, resulting in a DDV value ranging between 4.00 and 8.50 mm/year. The displacement time series is related to a PS placed near an expansion joint of the T4-3 bridge. It clearly shows the effect of seasonal temperature variations. Further advances in the adopted methodology can be aimed at using the detection of variations in seasonal temperature-induced deformations to identify anomalous structural behaviours. Fig. 4c refers to the test bridges on the A24 placed within the alluvial deposit of the Aniene river. In this case, the bridges in T3 group are associated with DDV included within 2 and 4 mm/year since instability in the transition deck-abutment zone is observed. Since the PS characterized by relevant displacement velocity are located in the transition deck-abutment zone, a refined definition of the bridge footprint may be useful to avoid erroneous evaluations.

Fig. 3. Global displacement velocity (GDV) (a) and differential displacement velocity (DDV) (b) for the bridges in the case-study network.