Future Directions in Reliability-Based Geotechnical Design
Bibliographic record
Abstract
World-wide, geotechnical design codes-of-practice are increasingly targeting acceptable failure probabilities, rather than factors of safety, since the latter do not provide an accurate estimate of safety, despite their name. This trend requires an ever-increasing understanding of the probabilistic behaviour of geotechnical systems. As a result, probabilistic geotechnical models are becoming more complex, yet more realistic. In particular, models which consider the effects of the ground’s spatial variability on failure probability of geotechnical systems are rapidly gaining popularity. This is because it is well known that spatial variability leads to weakest paths which are preferentially followed by geotechnical failure mechanisms. The paper begins by looking at the current state-of-the-art in probabilistic ground models. The effect of spatial variability on geotechnical system failure probability is discussed, followed by how the random finite element method (RFEM) has and can be used to aid in the calibration of geotechnical design codes-of-practice. The paper finally looks at what is needed in the future to further improve cost effective geotechnical design practices while increasing overall geotechnical system reliability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".