A two-dimensional effective stress framework for modelling whole-life soil strength changes due to pore pressure generation and dissipation, Part 2: Applications
Bibliographic record
Abstract
The accurate quantification of the temporal changes in seabed strength allows for more reliable and less conservative geotechnical design. A recently developed effective stress framework, established within a one-dimensional computational domain to quantify changes in soil strength due to pore pressure generation and dissipation, has been extended to a two-dimensional (2D) computational domain to allow for consideration of boundary value problems that are too complex to be simplified to one-dimensional conditions. The work to implement the 2D framework is reported across two companion papers. The first of the two papers utilises large deformation finite element analyses to quantify the spatial distribution of accumulated plastic shear strain. These distributions are encapsulated within a strain influence function that is used within the new 2D framework in this paper to calculate the extent and magnitude of excess pore pressure, and in turn the mobilised soil strength for a number of boundary value problems that represent typical offshore geotechnical processes. The merit of the new 2D framework is explored via retrospective simulations of existing experimental and numerical data. The resulting comparisons demonstrate the potential of the new framework, which is in quantifying the reliability of a range of geotechnical structures under complex loading conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".