Critical Review of Polymeric Building Envelope Materials: Degradation, Durability and Service Life Prediction
Bibliographic record
Abstract
This paper provides a critical review of the degradation, durability and service life prediction (SLP) of polymeric building envelope materials (BEMs), namely, claddings, air/vapour barriers, insulations, sealants, gaskets and fenestration. The rate of material deterioration and properties determine the usefulness of a product; therefore, knowledge of the significant degradation mechanisms in play for BEMs is key to the design of proper SLP methods. SLP seeks to estimate the life expectancy of a material/component exposed to in-service conditions. This topic is especially important with respect to the potential impacts of climate change. The surrounding environment of a building dictates the degradation mechanisms in play, and as climate change progresses, material aging conditions become more unpredictable. This can result in unexpected changes and/or damages to BEMs, and shorter than expected SL. The development of more comprehensive SLP methods is economically and environmentally sound, and it will provide more confidence, comfort and safety to all building users. The goal of this paper is to review the existing literature in order to identify the knowledge gaps and provide suggestions to address these gaps in light of the rapidly evolving climate.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".