Instability Risk Factors on Road Pavements of Bridge Ramps
Abstract
1. Introduction
- Flexible;
- Rigid;
- Semi-rigid.
- Asphalt overlaid in ramps cracks;
- Floating r.c. slabs (approach slabs);
- Vegetation in the vicinity of ramps.
2. Defects and Deterioration of Road Pavements
2.1. Functional Defects
- Grip;
- Roughness.
- Polishing of aggregates;
- Bleeding of bitumen (bleedings);
- Disintegration and raveling of aggregates (stripping or erosion by weathering agents).
- Depressions and bulges;
- Rutting over extensive areas;
- Surface irregularities of the driving lane;
- Edge cracking;
- Block cracking;
- Joint cracking.
2.2. Structural Defects
- Longitudinal cracking;
- Branching, transverse, and longitudinal cracking, spiderweb or crocodile skin cracking;
- Settlements;
- Potholes.
2.3. Overview of Defects
- (A)
- The slope of the embankment;
- (B)
- The movement of the r.c. floating slab;
- (C)
- The growth of vegetation in the adjacence of the ramp
3. Analysis Technologies of Defects on Bridge Ramps
3.1. Cracks in Asphalt Overlays on Ramps
3.2. Floating R.C. Approach Slabs
3.3. Vegetation in the Adjacence of Ramps
- Integrated Vegetation Management (IVM): Native species (e.g., switchgrass) reduce invasive biomass by 30% and maintenance costs by USD 4200/acre annually [30].
- LiDAR drones map root systems, enabling targeted herbicide application.
- Corrosion Monitoring: Electrochemical sensors embedded in concrete detect pH drops (<11) and chloride ingress, preventing rebar corrosion [31].
3.4. Integrated Approaches and Future Directions
- GPR and AI Integration: Merging GPR data with AI models can improve the detection of subsurface anomalies;
- UAV-Based Inspections: Utilizing Unmanned Aerial Vehicles (UAVs) equipped with high-resolution cameras enables efficient visual inspections, especially in hard-to-reach areas;
- Edge Computing: Deploying AI models on edge devices allows for real-time damage detection and assessment in the field;
- The LSTM-driven Health Index (HI) predicts RC slab deterioration with >93% accuracy, enabling initiative-taking maintenance [32];
- Vehicle–Bridge Interaction (VBI) systems use vehicle-mounted sensors to monitor bridge frequencies, reducing reliance on fixed infrastructure [31].
4. Conclusions
- -
- Quick and easy use: In most cases, the technicians managing the road network are not highly trained to manage and interpret the data.
- -
- Efficiency in transmission and conservation of data: The wireless data or the automatic measurements must be stored and retained for possible future uses.
- -
- Early warning factors: The data shall be accompanied by synthetic factors, in order to compare the measurements over time and prevent failures or large damages.
- -
- Finally, the experimental monitoring activity should be extended to the underground of the bridge ramps, to better determine the causes of damage and failures, including geotechnical measurements.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Degradation Type | Image | Description | Assessment of Possible Causes |
---|---|---|---|
(S1) Depressions and bulges | Localized deformations of the driving surface, often accompanied by bulges and localized irregularities | Low-quality bituminous mixtures or unbalanced dosages. Surface layer with limited thickness. Insufficient compaction of the binder layers. | |
(S2) Rutting | Deformations, settlements, or failures not attributable to failures over extensive areas. (B3) | The deformation can affect the layers of unbound materials up to the base layer. The cause could be related to (i) bearing capacity defects caused by frost; (ii) plastic soils in the subgrade. | |
(S3) Surface irregularities of the driving lane | The surface layer deforms plastically until failure occurs, resulting in irregularities of the driving surface. | Mix formulation errors. Poor construction. Use of low-quality materials. Unanticipated increase in traffic. | |
(S4) Edge cracking | Cracking and failure near the pavement edge, running parallel to the lane and/or roadway axis. | Load-bearing layers not adequately extended beyond the pavement edge. Lack of lateral containment. | |
(S5) Block cracking | Polygonal cracking with interconnected fracture lines affecting large portions of the road surface. | Excessive stiffness of the layer often associated with poor bonding. Differential thermal shrinkage phenomena of the bound layers. | |
(S6) Joint cracking | The cracking, of a linear type, is localized at the adjacent lane joint. | Lack of compaction and failure to close the joint during construction. Lack of staggering of longitudinal joints between the various layers. | |
(B1) Longitudinal and transversal cracking | The main cracks develop parallel to the longitudinal axis of the lane or roadway. They have a linear pattern with more or less pronounced transverse branches. | Possible presence of cement concrete slabs with different risks of thermal shrinkage. Very stiff mixtures in relation to the characteristics of the bound layers. | |
(B2) Branching, transverse, and longitudinal cracking, spiderweb or crocodile skin cracking | A network of closely interconnected cracks extending over large areas. The cracks tend to progressively open, compromising the waterproofing of the superstructure. | Structural collapse of the superstructure (in case of extensive rutting). Excessive stiffness of the surface layer (in case of absence of deformation of the surface). Fatigue. Freeze/thaw cycles, (in case of degradation of only bituminous layer). | |
(B3) Settlements | Pronounced rutting affecting the pavement over extensive areas. Often preceded or accompanied by branching cracks. | Low strength of the load-bearing layers and/or the subgrade. Improperly sized bituminous aggregate layers or poor workmanship. | |
(B4) Potholes | This type of degradation progressively affects the various layers of the superstructure, where the surface and binder layers are undermined by the combined action of traffic and rainwater. | Typical damage of structures that are improperly designed, built with poor-quality materials, or constructed by directly placing the surface layers on the subgrade. The progressive infiltration of stagnant water causes the upward movement of material, leading to the degradation of the original characteristics of the layers. |
Model | Accuracy | Application |
---|---|---|
CAE | 90% | Multi-vehicle cracks |
HHT | 80% | Microcracks |
Parameter | Allowable Limit |
---|---|
Maximum Deflection | ≤3 mm |
Natural Frequency | 10–24 Hz |
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Rassu, N.; Maltinti, F.; Puppio, M.L.; Coni, M.; Sassu, M. Instability Risk Factors on Road Pavements of Bridge Ramps. Geotechnics 2025, 5, 44. https://doi.org/10.3390/geotechnics5030044
Rassu N, Maltinti F, Puppio ML, Coni M, Sassu M. Instability Risk Factors on Road Pavements of Bridge Ramps. Geotechnics. 2025; 5(3):44. https://doi.org/10.3390/geotechnics5030044
Chicago/Turabian StyleRassu, Nicoletta, Francesca Maltinti, Mario Lucio Puppio, Mauro Coni, and Mauro Sassu. 2025. "Instability Risk Factors on Road Pavements of Bridge Ramps" Geotechnics 5, no. 3: 44. https://doi.org/10.3390/geotechnics5030044
APA StyleRassu, N., Maltinti, F., Puppio, M. L., Coni, M., & Sassu, M. (2025). Instability Risk Factors on Road Pavements of Bridge Ramps. Geotechnics, 5(3), 44. https://doi.org/10.3390/geotechnics5030044