Life Cycle Cost Assessment of an Existing All-Aluminum Bridge: Comparison of Two Deck Options
Bibliographic record
Abstract
Traditionally, initial material cost has been the governing factor for material selection in structural construction. However, the growing maintenance cost of existing infrastructure has demanded a long-term vision in material selection and in this regard, life cycle cost assessment has been proven to be a better assessment tool than the initial cost of construction. Despite its higher initial cost, aluminum offers many positive attributes, such as a high resistance to weight ratio, good recyclability, and excellent corrosion resistance, which can significantly reduce the life cycle cost of a structure over its entire service life. Yet, the limited use of aluminum in bridge construction and the lack of literature on this matter do not provide comprehensive evidence of its superior performance in the long-term. Based on this premise, this study performs a life cycle cost analysis on the first all-aluminum bridge situated in Arvida, Quebec. The analysis has revealed that most maintenance costs are associated with the rehabilitation of the concrete deck. The frequent concrete deck maintenance dismisses the benefits of the low maintenance aluminum structure. In order to investigate further, an alternative analysis has also been performed on the bridge with a hypothetical aluminum deck that replaces the existing concrete deck. The comparison shows that the aluminum deck reduces the maintenance cost significantly. However, further analysis should be performed with an optimized aluminum deck that can also yield a significantly lower life cycle cost compared to the existing bridge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".