Transverse Connectivity and Durability Evaluation of Hollow Slab Bridges Using Surface Damage and Neural Networks: Field Test Investigation
Abstract
:1. Introduction
2. Field Test
2.1. Background Bridges
2.2. Visual Inspection
2.3. Load Test
2.4. Cutting Test of Girders
3. Test Results and Analysis
3.1. Surface Damage
3.2. Transverse Connectivity
3.3. Durability
4. Evaluation of Hollow Slab Girders Based on Surface Damage and Neural Networks
4.1. Evaluation Using Neural Network
4.2. Method Verification
5. Conclusions
- Visual inspection showed that there were two types of the typical defects in the hollow slab bridges, i.e., the transverse cracks on the bottom plates of the girders and the longitudinal cracks in the hinge joints. The transverse cracking mainly occurred in the mid-span of the bridges, while the distribution of the longitudinal cracks on the joints was quite uniform along the longitudinal location.
- The static load test showed that the distribution of the deflection of each girder was non-uniform due to the weakening of the transverse connectivity, and the girder deflection increased with the increase of the joint damage. A damage index was proposed based on the theoretical and measured deflections, and the joint damage can be quantitatively assessed when the index value is larger than 0. The durability of the hollow slab girders was evaluated after cutting off the concrete girders. Results showed that the girders in the background bridges were within a moderate deterioration condition after 25 years’ service life.
- An evaluation method of hollow slab girders based on the surface damage and neural networks was proposed and verified by the field test data. The maximum crack width at different locations of the bridge was used in the input layer of the neural network, and the hinge joint damage or the durability was considered as the output results. The prediction error of the method in the test set was within 15.0% for the hinge joint damage and within 40% for the durability result of the girder, indicating the feasibility of the evaluation method.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | Span Arrangement | Girder Number | No. | Span Arrangement | Girder Number |
---|---|---|---|---|---|
1 | 2 × 16 m | 6 | 8 | 3 × 20 m | 10 |
2 | 2 × 16 m | 4 | 9 | 2 × 16 m | 8 |
3 | 2 × 16 m | 4 | 10 | 1 × 16 m | 13 |
4 | 4 × 16 m | 8 | 11 | 1 × 16 m | 8 |
5 | 3 × 13 m | 8 | 12 | 10 × 22 m | 12 |
6 | 3 × 16 m | 8 | 13 | 2 × 16 m | 8 |
7 | 2 × 13 m | 8 |
Grade | Description |
---|---|
A | Intact or good condition |
B | Mild deterioration |
C | Moderate deterioration |
D | Severe deterioration |
E | In danger |
Parameter | Criteria Description | Grade | Value |
---|---|---|---|
Crack width (mm) | ≤0.05 | 1 | D1 |
0.05 to 0.1 | 2 | ||
0.1 to 0.15 | 3 | ||
>0.15 | 4 | ||
Crack length (m) | ≤0.1 | 1 | D2 |
0.1 to 0.2 | 2 | ||
0.2 to 0.3 | 3 | ||
0.3 to 0.4 | 4 | ||
0.4 to 0.5 | 5 | ||
0.5 to 0.6 | 6 | ||
>0.6 | 7 | ||
Crack location | Auxiliary components | 0 | D3 |
Secondary components | 1 | ||
Main components | 2 | ||
Crack growth rate | None | −1 | D4 |
Small | 0 | ||
Large | +1 | ||
Da = (D1 + D2 + D3 + D4)/14 | 0 to 0.2 | A | |
0.2 to 0.4 | B | ||
0.4 to 0.6 | C | ||
0.6 to 0.8 | D | ||
0.8 to 1.0 | E |
Parameter | Grade | ||||
---|---|---|---|---|---|
A | B | C | D | E | |
Db | ≥0.95 | 0.90 to 0.95 | 0.80 to 0.90 | 0.70 to 0.80 | <0.70 |
Dc | ≥0.98 | 0.95 to 0.98 | 0.90 to 0.95 | 0.80 to 0.90 | <0.80 |
Dd | ≥0.95 | 0.85 to 0.95 | 0.70 to 0.85 | 0.55 to 0.70 | <0.55 |
De | ≥0.80 | 0.60 to 0.80 | 0.40 to 0.60 | 0.20 to 0.40 | <0.20 |
Component | Defect | Number | Total | Proportion (%) |
---|---|---|---|---|
Single girder | Transverse crack on the bottom plates | 313 | 368 | 85.1 |
Rebar corrosion | 27 | 7.3 | ||
Concrete spalling | 18 | 4.9 | ||
Longitudinal crack on the bottom plates | 10 | 2.7 | ||
Hinge joint | Longitudinal crack | 256 | 314 | 81.5 |
Rebar corrosion | 30 | 9.6 | ||
Transverse crack | 21 | 6.7 | ||
Seepage | 7 | 2.2 | ||
Total | 682 | 682 |
Transverse Cracks on the Bottom Plates | Longitudinal Cracks on the Hinge Joints | |||
---|---|---|---|---|
Longitudinal Location | Number | Proportion (%) | Number | Proportion (%) |
0–1/8 span | 17 | 5.4 | 31 | 12.1 |
1/8 span–3/8 span | 61 | 19.5 | 26 | 10.2 |
3/8 span–5/8 span | 220 | 70.3 | 47 | 18.4 |
5/8 span–7/8 span | 10 | 3.2 | 36 | 14.1 |
7/8 span–1 span | 5 | 1.6 | 21 | 8.2 |
Through crack | 0 | 0.0 | 95 | 37.1 |
Total | 313 | 256 | 100 |
Transverse Cracks on the Bottom Plates | Longitudinal Cracks on the Hinge Joints | ||||
---|---|---|---|---|---|
Length/cm | Number | Proportion (%) | Length/cm | Number | Proportion (%) |
0–9 | 35 | 11.2 | 0–10 | 47 | 18.4 |
10–19 | 117 | 37.4 | 10–50 | 30 | 11.7 |
20–29 | 77 | 24.6 | 50–100 | 17 | 6.6 |
30–39 | 48 | 15.3 | 100–150 | 21 | 8.2 |
40–49 | 32 | 10.2 | Through | 95 | 37.1 |
>50 | 4 | 1.3 | 150–1000 | 46 | 18.0 |
Total | 313 | 100 | Total | 256 | 100 |
Width/mm | Number | Proportion (%) | Width/mm | Number | Proportion (%) |
0–0.1 | 22 | 7.0 | 0–2 | 96 | 37.5 |
0.1–0.2 | 159 | 50.8 | 2–4 | 86 | 33.6 |
0.2–0.3 | 76 | 24.3 | 4–6 | 34 | 13.3 |
0.3–0.4 | 20 | 6.4 | 6–8 | 14 | 5.5 |
0.4–0.5 | 17 | 5.4 | 8–10 | 12 | 4.7 |
>0.5 | 19 | 6.1 | >10 | 14 | 5.5 |
Total | 313 | 100 | Total | 256 | 100 |
Indicator | Girder Segment | ||||
---|---|---|---|---|---|
S2-G4-1 | S2-G4-2 | S2-G4-3 | S2-G4-4 | S2-G4-5 | |
Transverse crack | A | C | B | D | C |
Longitudinal crack | A | A | A | A | A |
Concrete strength | D | B | C | C | A |
Corrosion degree of rebars | A | A | B | B | B |
Reinforcement protective layer thickness | B | C | C | D | C |
Grout condition | A | A | A | A | A |
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Jiang, C.; Xiong, W.; Wang, Z.; Cai, C.; Yang, J. Transverse Connectivity and Durability Evaluation of Hollow Slab Bridges Using Surface Damage and Neural Networks: Field Test Investigation. Appl. Sci. 2023, 13, 4851. https://doi.org/10.3390/app13084851
Jiang C, Xiong W, Wang Z, Cai C, Yang J. Transverse Connectivity and Durability Evaluation of Hollow Slab Bridges Using Surface Damage and Neural Networks: Field Test Investigation. Applied Sciences. 2023; 13(8):4851. https://doi.org/10.3390/app13084851
Chicago/Turabian StyleJiang, Chao, Wen Xiong, Zichen Wang, Chunsheng Cai, and Juan Yang. 2023. "Transverse Connectivity and Durability Evaluation of Hollow Slab Bridges Using Surface Damage and Neural Networks: Field Test Investigation" Applied Sciences 13, no. 8: 4851. https://doi.org/10.3390/app13084851