Non-Linear Finite Elements Simulations of Level Ice Forces on Offshore Structures Using a Multi Surface Failure Criterion
Bibliographic record
Abstract
Finite elements simulations of indentation loads caused by an ice sheet on a rigid conical offshore structure were carried out using the ANSYS structural commercial code (www.ansys. com). A square level ice sheet (20.0 m x 20.0 m) pushing a 10 m waterline diameter water cone was considered as the engineering application. The interactions between the structure and the ice sheet were modeled using a nonlinear 3-D contact element formulation. The mechanical behaviour of ice (constitutive model for ice) is elastic, while its failure was modeled using a multi surface failure criterion. The latter includes the effects of the strain (loading) rate, temperature, salinity and porosity on the magnitude of ice strength. During the simulations, failed elements (i.e. elements that satisfy the stress conditions of failure criterion) were taken out from the initial geometry of the ice sheet. Therefore, the process and sequence for breaking ice pieced from the original ice sheet were modeled. This was achieved via developing and ANSYS macro (routine) for element death numerical technique. The validation of the numerical model is presented. The validation was achieved by comparing the computed ice loads from the numerical simulations with full-scale ice load measurements obtained form the Kemi-I test cone (Määttänen et al., 1996). In addition to the validation, the results of sensitivity and parametric analyses are presented and discussed. Conclusions and recommendations are provided.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".