Guidelines to Improve the Quality of Element-Level Bridge Inspection Data (2019) / Chapter Skim
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Pages 4-38
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4 3 FINDINGS AND APPLICATIONS This portion of the report describes the research and findings from the project. This includes a survey of bridge engineers conducted to determine the current state of the practice for element-level inspection.
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5 measurable quality. Only three respondents indicated that they were using subjective criteria, of these, two respondents indicated that they had procedures for "calibrating" inspectors; these generally consisted of quality assurance (QA)
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6 could be characterized as monthly, quarterly, or biannually. These results are significant in showing that most agencies are providing feedback and information to their inspectors through face-to-face meetings.
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7 Previous research has indicated that the time required or allowed to complete an inspection has an impact on the quality of results. It is interesting to note that, similar to previous studies, the anticipated time required to complete a routine element-level inspection of the example bridge varied significantly.
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8 a NBI component condition rating below a 6, were required. About 16% of responses indicated that inspection teams determine the appropriate photographs.
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9 subject of the image was difficult to determine. In some cases, the images were not clear, or the resolution of the image was too low for use in the new visual guide.
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10 appear larger on the page and to simplify the use of the guide. A visual guide with an excessive number of pages is more difficult to use in the field then a guide with a smaller number of pages.
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11 Table 1. Listing of defect elements included in the visual guide.
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12 3.2.1.1 Spatial Estimation Diagrams The guideline also includes diagrams intended to assist in making accurate quantity estimates in the field. Figure 6 shows an example of a spatial estimating diagram for use on bridge elements recorded in units of sq ft.
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13 approach uses a statistical model that describes the anticipated variation in the inspection result for a given NDE technology. This variation is then compared with a decision threshold such as a critical crack length.
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14 Figure 7. Examples of probability density functions for normally distributed inspection results.
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15 For example, assume that a bridge deck with less than 10% damage in CS 3 will have a preservation activity, a deck with 10-20% damage will have a maintenance activity, and a deck with greater than 20% damage will have a repair activity. In this case, the decision interval is 10%, and the mean of the interval is 15%.
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16 on the probability of transition from one state to another. The Markov model was used historically in the Pontis bridge management system, and provides some operational capabilities of the new AASHTOWare Bridge Management (AASHTO BrM)
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17 were completed to provide some range of rational values for an inspection accuracy requirement, and to illustrate the trends in these data. The results of the analysis were evaluated to consider the effect of different tolerances on longer-term modeling.
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18 2.5%. If the inspection were accurate, such that the inspection indicates the true value of 5% in CS 3, then the threshold value of 10% would be exceeded after 14 years.
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19 Table 3. Quality ratio for different threshold values and accuracy levels.
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20 (photographs) developed through the research were inserted with the appropriate materials and defect elements.
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21 1 Where is the actual value and is the average of the estimate provided by inspectors. In this way the difference between the estimated value (in %)
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22 3.3.1.1 S-BRITE Testing This portion of the summary provides data from the inspection tasks completed at the S-BRITE Center. The objectives of the field exercises at the S-BRITE Center were to evaluate the fundamental capabilities of inspectors for estimating quantities of damage and to evaluate if the use of the visual guide improved the quality of inspection results.
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23 with increasing areas of damage. These data did not indicate that there was an improvement in accuracy, or a reduction in variability, associated with the use of the visual guide.
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24 In S-BRITE Task 4 and 5, damage estimates were made using unit of length (ft)
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25 inspectors assigned any damage to CS 2 when units of ft were used. In contrast, 6/6 inspectors assigned CS 2 when areas of sq ft were used.
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26 Significant results from these tests included that there was a high degree of variation in the assessment of corrosion damage for element 107-Open Steel Girder/Beam. Figure 16 shows the raw inspection data from TGA and TGB.
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27 Table 6. Results for Element 12-RC Deck for bridges I1 and I2 with two outliers removed from TGB.
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28 3.3.2.1 Routine Inspection of Twin Prestressed Girder Bridges Figure 17 shows photographs of inspectors conducting an assessment of bridges M1 and M2. The prestressed girders were in generally good condition, and there was agreement between TGA and TGB regarding the amount of damage when mean values were considered.
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29 Table 8. Inspection result for element 205 - Reinforced Concrete Column for bridge M1 and M2 inspected using units of (ea)
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30 In a separate task, inspectors were asked to assess the columns using units of length (ft) instead of the traditional units of ea.
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31 Element 310-Elastomeric Bearing, had some reported damage in CS 3, and the inspection result is shown in Table 10. For bridge M1, the data indicated that there was good agreement regarding the total quantities of bearings with damage in either CS 2 or CS 3.
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32 For bridge M4 assessed by inspectors, there was again consistency shown in the average values (mean) between the groups; TGA assessed 8.8% and TGB assessed 10% examining the results for damage (CS 2 + CS 3)
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33 The inspection results were also analyzed considering the raw data provided by the ten inspectors that participated in the study, as shown in Figure 20. These data illustrate the significant variation in the amount of deck assigned to CS 3.
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34 a meaningful measure. These data do not include ancillary elements such as joint seals, bearings, or bridge railings.
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35 To further illustrate the test results, Figure 21 includes two graphs showing the measured σ values from the field exercises for CS 3 (Figure 21A) and for CS 2 + CS 3 (Figure 21B)
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36 One of the objectives of the field trial was to compare the use of the visual guide with the traditional inspection approach. The data was studied to determine if there was a measurable improvement in the accuracy of spatial estimates as a result of using the visual guide.
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37 assignment of defects and CSs in the study, a visual guide appears to be needed to improve the quality of element-level data. Part of the study evaluated the differences between making estimates based on a percentage as compared with tallying individual areas, and making estimates in area (sq ft)
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38 The field exercises did not show that there was a decrease in inspection variability when using the visual guide as compared with not using the visual guide. The variation in the data from the field exercises did not allow for recognizable trends regarding the assignment of the appropriate CSs.
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