Development of Deterioration Models for Bridge Decks Using System Reliability Analysis
Bibliographic record
Abstract
Generally, in the existing Bridge Management Systems(BMS) deterioration is modeled based on the visual inspections where the corresponding condition states are assigned to individual elements. In this case, the limited attention is given to the correlation between bridge elements from structural perspective. In this process, the impact of the history of deterioration on the reliability of a structure is disregarded which may lead to inappropriate conclusions. The Improved estimate of service life of a bridge deck may help decision makers enhance the intervention planning and optimize the bridge life cycle costs. A reliability-based deterioration model can potentially be an appropriate replacement for the existing procedures. \nThe objective of this thesis is to evaluate the system reliability of conventional bridges designed based on the existing codes. According to the methodology developed in this thesis, the predicted element-level structural conditions for different time intervals are applied in the non-linear Finite Element model of a bridge superstructure and the system reliability indices are estimated for different time intervals. The resulting degradation curve could be calibrated and updated based on the outcomes of the visual inspections. Also, the reliability of innovative bridges that use non-conventional materials or structural forms such as Steel-Free Deck System has been evaluated by applying the newly developed method. The available deterioration models for conventional superstructuresare not applicable for the innovative bridge systems. Since there is no established deterioration model available for these innovative structures, it is difficult to predict the reliability of such bridges at different time intervals. The method developedhere adopts the reliability theory and establishes deterioration models for conventional and innovative bridges based on their failure mechanisms. \nThis method has been applied in simply-supported traditional reinforced-concrete bridge superstructures designed according to the Canadian Highway Bridge Design Code (CHBDC-S6), and in an innovative structure with a Steel-Free Deck System, namely the Crowchild Bridge, in Calgary, Canada, as case studies. As an example to show the application of such developed deterioration curve, the developed model has been adopted in an old superstructure in Montreal. The results obtained from the newly developed model and bridge engineering groups’ estimations are found to be in accordance. Based on the reliability estimates, the conventional bridges designed based on the new code are found to be in a good condition during the initial stages of their service life,but their condition degrades faster once corrosion in steel reinforcements is initiated and spalling of concrete becomes evident. In case of the Steel-Free Deck, there is a low probability of failure at the end of the 75 years of its service life. It is found that the element-level assessment of a concrete deck is a conservative approach, since the interaction between the structural elements results in considerably higher reliability index and lower probability of failure. This thesis demonstrates how the proposed system reliability-based evaluation method can be adopted in determining the structural condition of a bridge which represents an important step forward in Bridge Management Systems. The system reliability deterioration model can be easily integrated to the existing Bridge Management Systems (BMS) by replacing the existing condition index by the reliability index or adding it to the assessing process as an additional parameter.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".