Geotechnical survey and mechanical parameters in urban soils: modelling soil variability and inferring representative values using the extension of Lyon subway line D as a case study
Bibliographic record
Abstract
Urban soils are generally heterogeneous and thus require, for any project, careful geotechnical evaluation. Considering the difficulty faced by geotechnical engineers in defining a model of the underground (different soil layers and associated physical-mechanical properties), it appears useful to clearly define a strategy for the analysis of the site investigation results. As well as an in-depth knowledge of the site, this strategy should rely on carefully defined general rules of analysis and treatment of collected data. The processes leading to a representative and accurate model of the volume of soil affected by the underground works are identified in this paper based on the analysis of a case study (extension of the Lyon subway line D). Variability is one of the main features of urban soils, therefore one should be able to quantify and compare this variability with other sources of uncertainties and inaccuracies affecting the design process, such as the quality of measurements and numerical modelling errors. New design codes based on the concept of representative material properties (i.e., Eurocode characteristic values) imply the need for a risk-oriented analysis of the reconnaissance results.Key words: urban soil, underground construction, data analysis, representative value, geotechnical survey, variability.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".