Bibliographic record
Abstract
The shear modulus and damping of cemented clay are investigated using ultrasound transducers, bender elements, and a resonant column device. The model SimSoil-CC, based on the Pestana and Salvati (published in 2006) model SimSoil, is proposed to represent the maximum shear modulus and stress–strain behavior (under cyclic loading conditions) at small strains for the cemented clay. The model can also be used for uncemented clay when the cementation parameter is set to zero. Model parameters are determined for three types of clay (kaolinite, bentonite, and the equal mix of kaolinite and bentonite) and two types of cementation agents (type III Portland cement and gypsum). The model SimSoil-CC is validated using the laboratory test data of this study and data from other studies in literature. The SimSoil-CC model can be very useful for performing earthquake site response analysis for naturally cemented clay sites or sites that have been improved by cementation. In addition, a relationship between the cementation parameter acc(CC)2 (acc, cement material constant; CC, dry cement content) and the unconfined compression strength is proposed. The relationship simplified modeling for naturally cemented clay soil or cemented clay whose cement contents and cementation type are otherwise difficult to determine. This research advances the understanding of cemented clay by providing a database of test results and creation of a model that can be used to predict the response of cemented clay soils to dynamic loads.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".