Modelling dynamic ice-structure interaction based on high-pressure zones' behaviour at medium-scale
Bibliographic record
Abstract
Although ice-induced vibrations (IIV) resulting from dynamic ice-structure interaction have been reported as infrequent occurrences in nature, the catastrophic consequences of these events makes them a fundamental design consideration for structures in ice-prone regions. Over the last 50 years, these events have affected a wide range of structures, including bottom founded lighthouses, channel markers, jacket and caisson retained structures, and have led to operational shutdowns, human discomfort, and even complete collapse of the structure in some cases. Rigorous experimental investigations and theoretical modeling approaches over the years have provided valuable insight into the physical mechanism of the process; however, a significant amount of uncertainty in identifying the conditions associated with IIV and its severity still exists. The primary source of the uncertainty comes from the complexity of the ice failure process, since it is highly influenced by the interplay of different competing mechanisms, such as fracture, damage and microstructural changes. One of the fundamental components of compressive ice failure is the development of ‘high-pressure zones (hpzs),’ which are responsible for transmitting the majority of the loads in ice-structure interactions. As the properties and dynamic behaviour of hpzs exhibit similar characteristics over a wide range of scales, efforts to link hpz mechanics with the occurrence of dynamic ice-structure interactions is seen as a promising approach. During ice-structure interaction, the ice failure process is highly influenced by different interaction parameters. An uncertainty analysis with self-excited vibration modeling approaches was performed first to identify the critical parameters and how their effects can propagate through the dynamic ice-structure interaction process. Based on the simulations, ice temperature, interaction speed, and interaction area were identified as the key parameters affecting the dynamic ice-structure interaction process. A medium-scale ice crushing dynamics test program was then carried out to study the influence of these parameters on the dynamics of hpzs under controlled conditions with variable structural compliance. In general, more severe dynamics associated with failure behaviour were observed to be more pronounced for colder ice, smaller interaction areas, higher interaction speed, and lower structural compliances. The observed dynamics of a single hpz was then used to develop a simplified ice-structure interaction model. The behaviour of the hpz was estimated using results from previous triaxial tests, which showed a non-linear relationship between hpz stiffness and the nominal strain, with the degree of softening depending on the average strain-rate. Two distinct failure processes were assessed in the context of the periodic sinusoidal response of the structure using the model. First, such responses can result from the vibration within the layer of damaged ice when the formation of the damaged layer and the extrusion process become cyclical in pure crushing. Theoretical calculation from a previous study was adopted to estimate the equilibrium layer thickness that can result in such vibrations, and the model showed reasonably good agreement with the calculations. The other failure process considered was for spall-dominated interactions with occasional crushing events. Such a failure process can result in frequency lock-in of the structure; however, these responses were observed to be highly sensitive to interaction speed and structural parameters. This was identified as the primary reason for the infrequent observation of frequency lock-in in full-scale interactions. Although the simplified modeling framework presented here shows promising results, further experimental investigation and modeling refinement are required for a full-scale implementation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".