Environmental assessment of earth retaining wall structures
Bibliographic record
Abstract
Life cycle assessment (LCA) is recognised as a powerful technique to determine the environmental impact component of sustainability assessments of structures in civil engineering projects at the time of design. This paper explains the principal parts and stages in an LCA methodology and demonstrates the approach using the examples of two conventional retaining wall types (gravity and cantilever type) and two mechanically stabilised earth (MSE) wall solutions using steel and polymeric soil reinforcement. The analyses include structures built to four different heights. The LCA methodology was able to quantitatively distinguish between the component environmental impacts of different wall solutions and thus provide a practical numerical score-based tool for designers to choose between candidate solutions. The MSE wall solutions resulted in lower environmental impacts than gravity and cantilever wall solutions as measured by global warming potential, cumulative energy demand, six major midpoint environmental indicator categories, three endpoint damage categories and in terms of overall endpoint scores. The target audiences for this paper are geotechnical and structural engineers engaged in the design of earth retaining wall structures but are less familiar with recent developments in LCA and how LCA can be linked to the design of these systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".