Mapping Voids, Debonding, Delaminations, Moisture, and Other Defects Behind or Within Tunnel Linings (2013) / Chapter Skim
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Pages 66-90
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66 a p p e N D I x J Introduction A significant component of SHRP 2 is research and development of innovative, high-speed, nondestructive testing and evaluation technologies that promise to accelerate design evaluations and construction inspection for highway renewal projects. One of these research and development projects has focused on nondestructive testing (NDT)
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67 Air-coupled GPR data collection settings were the same as used normally in pavement thickness and quality control surveys. Collected data consisted of 100 scans per meter, 16 bits, and 512 samples per scan.
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68 can measure small changes in surface temperatures, even at the range of 0.05°C. The camera measures infrared radiation with a wavelength of 8 µm to 12 µm.
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69 present examples of FLIR thermal camera mounting systems used on the survey van. The mounting system presented in Figure J.5 was judged to be better because an analysis of the data indicated that it reduced the thermal reflection of the van, which was causing noise in the data.
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70 changes in the position of a tunnel lining after an earthquake. For these high-accuracy x, y, z tasks, Category A laser scanner systems are needed.
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71 Figure J.11. Hakamäentie Tunnel structure.
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72 All the data collection was done in tube A along the rightside wall leading south. Because of traffic in the tunnel, all measurements were done in a closed lane using an automatic lane control system.
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73 was removed. A rolling beam supported by the pavement surface was added.
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74 measurement speeds was tested in the Vuosaari Tunnel. Thermal videos were made at van speeds of 20 km/h, 40 km/h, and 60 km/h.
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75 Thermal video collection can also be done without a vehicle; all the required devices can be installed on a cart. Part of the thermal video collection in the United States was done in tunnel air ducts, which were not accessible by vehicle.
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76 to interpret. Figure J.18 presents examples of how different processing operations affected the GPR data collected from the Hakamäentie Tunnel.
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77 Figure J.19. Processed air-coupled GPR data with two-layer interpretation (top)
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78 Figure J.21. Thermal color-scale map (temperature scale in degrees Celsius)
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79 section, which gives information on the shape and dimensions of the tunnel (Figure J.23)
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80 from the top down toward the tunnel roof, proved successful, and those data provided valuable information about cracks and water leakage in the tunnel roof (Figure J.26)
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81 are encountered. The Road Doctor software's automatic surface level detection cannot handle such large changes, which were as much as 1.5 m.
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82 Repeatability, Antenna-to-Wall Distance Effect, and Data Collection Speed Tests To test for repeatability, two measurements were taken along the same line, using the same antenna-to-wall distance. The results are shown in Figure J.29.
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83 by 1 m -- was found to be too small at distances of 1.0 m and 1.5 m (Figure J.32)
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84 Figure J.31. Surface dielectric values in antenna-to-wall distance tests (top)
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85 Figure J.33. Surface dielectric values in speed tests (top)
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86 snow. Wall temperature variation, regardless the time of the year, was less than 1°C.
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87 shows points/areas where salty water was leaching through the shotcrete. Figure J.40 presents a comparison of Category A and Category B laser scanner data in the Vuosaari Tunnel roof surveys.
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88 Figure J.40. Comparison of Category B (top)
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89 Figure J.42. Category B laser scanner reflection amplitude data from the Hakamäentie Tunnel roof.
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90 2. More research is needed before surface dielectric information can be reliably used to find moisture anomalies in the lining structure.
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