Durability and sustainability of infrastructure — a state-of-the-art report
Bibliographic record
Abstract
This paper discusses the basic concepts involved in infrastructure, durability, and sustainability. At present, infrastructure facilities are designed and constructed on the basis of direct costs only, without explicit consideration of maintenance and depreciation over its service life as in other industries. Proper design, operation, and management of infrastructure must deal with every facet of its service life, ranging from conception, feasibility studies, design, construction, operation, maintenance, repair and rehabilitation, and finally decommissioning and disposal of the system after it has outlived its useful life. Every step of these considerations must be guided by overall socioeconomic and environmental concerns; in summary, they must be guided by the principles of sustainable development, which embrace the issue of embodied energy in the materials, construction, and both initial and recurring maintenance. The degradation of the performance of Canada's infrastructure over the past few decades is reviewed, along with the consequences of proper or deferred maintenance and their impact on Canada's infrastructure deficit. The roles of the civil engineering profession, including education and training, and those of the public and private sectors are discussed briefly.Key words: depreciation, design, deterioration assessment, durability, durability audits, infrastructure surveys, maintenance, life-cycle performance and costs, repair and rehabilitation, sustainability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".