Fracture Analysis of a Steel Plate Loaded by Ice
Bibliographic record
Abstract
There are several theories used to describe the fracture process including Linear Elastic Fracture Mechanics (LEFM), Elastic-Plastic Fracture Mechanics (EPFM), and Cohesive Zone Models (CZM), which allow for development of predictive capabilities. The main disadvantage of LEFM and EPFM techniques is that only structures with an initial crack can be modeled. Other drawbacks of these techniques are geometry dependence and validity limits. In contrast, CZM can simulate fractures in any structures, with or without a crack. CZM is not confined to a class of materials, but can be used for arbitrary materials. In this paper, the CZM is used to numerically simulate crack initiation and growth in a steel plate. Within the CZM, material separation (i.e. damage of the structure) is described by interface elements, which open irreversibly and lose their stiffness at failure, causing the continuum elements to be disconnected.
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 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 | 0.000 | 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 | 0.000 |
| 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".