LEAP-ASIA-2019 Centrifuge Tests at University Gustave Eiffel
Bibliographic record
Abstract
Abstract In the framework of the LEAP-ASIA-2019 exercise, two dynamic centrifuge tests on a gentle slope of saturated Ottawa F-65 sand have been performed at the centrifuge of University Gustave Eiffel. These tests were conducted in parallel with other tests performed in nine other centrifuge centers. In addition to the objectives of the LEAP-UCD-2017 (comparison of the experimental results, e.g., effect of the experimental procedure or of test parameters on the results, and providing of a database for numerical modeling), the new objective was to evaluate, through the tested configuration, the generalized scaling approach described by Iai et al. (Géotechnique 55(5):355–362, 2005). In this framework, all the centrifuge teams have performed two types of tests. Considering the same prototype geometry, the first test was performed following the classical approach used in centrifuge modeling, and the second test was performed considering the generalized scaling law (GSL). Following the test matrix and test specifications of LEAP-ASIA-2019, University Gustave Eiffel has performed two model tests (test A2 renamed UGE-1/50-62 and test A3 renamed UGE-2/25-62). The two tests have been performed on a slope sand with the same relative density (62%) considering a target motion PGAeff = 0.3 g (1 Hz ramped sine at the prototype scale). In this paper, the test setup and the deviations from the specifications such as the experimental setup improvement that have followed the LEAP-UCD-2017 tests are presented in detail. The results obtained from the two tests are then provided at the prototype scale for comparison. The obtained input base motions are first presented followed by the characterization of the soil through CPT profiles. The responses of the saturated sand slopes for both tests are then detailed through the analysis of the pore pressure buildup, the accelerations in the soil, and the displacements measured through surface markers and embedded sensors. Some preliminary results of the global scaling approach are then discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".