Wave Patterns, Wave Induced Forces and Moments for a Gravity Based Structure Predicted Using CFD
Bibliographic record
Abstract
Gravity Based Structures (GBSs) are commonly used in the offshore oil and gas industry for storage during the production of hydrocarbons. The GBS sits on the sea bed, but it is subjected to forces and moments caused by waves. Obtaining accurate predictions of the magnitude of wave induced forces and bending moments is essential input to the structural design. Other key operational factors are the wave field in the vicinity of the structure and the amount of green water that will come onto the deck of the GBS. Scale model experiments can be used to obtain these predictions but this is an expensive option, especially in the early stages of a design, when many different concepts may be considered. An alternative method is to use Computational Fluid Dynamics (CFD). One CFD approach that is particularly suited to the challenges of predicting the required performance parameters for a GBS is the Volume of Fluid method, which is available in the commercial code Flow-3D. This paper presents the numerical simulation of the wave field around a surface piercing cylinder using the Volume of Fluid approach and compares it to published results. It also presents the simulations of the forces, moments and wave field around a proposed Gravity Based Structure, for which model data was available. The results show that predictions made using the Volume of Fluid method agree well with the observed wave patterns close to the structure in both cases, and that the method also gives good predictions of the observed forces and bending moments acting on the GBS.
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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 | 0.000 | 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) | 0.001 | 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".