Life Cycle Assessment of an Innovative Hybrid Highway Bridge Made of an Aluminum Deck and Glulam Timber Beams
Bibliographic record
Abstract
Reinforced concrete and steel are the most commonly used materials in bridge applications in Quebec (Canada). The production of these materials has a significant environmental impact and contributes to the scarcity of non-renewable resources due to the numerous maintenance requirements during the life of the structure. Consequently, there are governmental initiatives and efforts in the province of Quebec to promote the use of aluminum and engineered wood in the construction and rehabilitation of roadway bridges. Those two materials are not widely used due to the short-term vision of decision makers and the lack of technical knowledge for structural uses in highway bridge structures. However, they can be competitive materials due to their local production, durability and recyclability. The life cycle assessment method allows for an analysis of the use of complementary materials, considering all the stages of the life cycle of a structure. The comparison of a roadway bridge made of an aluminum deck on glulam timber beams against a bridge made of an aluminum deck on steel girders shows that, due to the local production and low environmental impact of glulam timber, the aluminum-to-timber bridge is economically and environmentally more advantageous than the aluminum-to-steel bridge. Similarly, a comparison of this alternative aluminum/wood solution to the conventional concrete slab-on-steel girder bridge solution shows a decrease in overall cost by 86% and a decrease in environmental impacts by 88% due to the ease of prefabrication and the relatively low number of interventions over its lifetime.
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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".