Gas–liquid–solid three-phase flow induced vibration model and experimental verification for mining riser used in deep-sea natural gas hydrate extraction
Bibliographic record
Abstract
The gas–liquid–solid three-phase flow induced vibration model of the deep-sea hydrate mining riser is established using the finite element method and Hamilton's principle. The model considers the dynamic decomposition process of hydrates (during transportation, hydrates continue to decompose, leading to changes in key parameters, such as the content and velocity of each phase in the riser), as well as multiple factors such as large aspect ratio of the structure, vortex induced vibration effect, gas liquid solid three-phase flow induced vibration effect, and ocean platform uplift and subsidence. The vibration model is solved using the combined iterative method of the incrementally applied Newmark-β method and Newton–Raphson method, obtaining the vibration response of the mining riser. Meanwhile, an experimental device for nonlinear vibration of the mining riser under internal and external flow excitation is developed based on the principles of geometric similarity, kinematic similarity, and dynamic similarity. The simulation experiments on three-phase flow-induced vibration of the mining riser are carried out, and the results such as multi-phase flow patterns inside the riser, riser displacement, vibration modes, and frequency response are obtained. Moreover, by comparing the axial and radial solid-phase and gas-phase flow velocities obtained through experiments and theoretical model calculations, the accuracy is higher than 87%, which can verify the correctness of three-phase flow model for gas–liquid–solid in the mining riser. Meanwhile, by comparing the root mean square displacement and dominant frequency of the mining riser obtained through experiments and theoretical model calculations, the accuracy is higher than 89%, which can verify the correctness of the vibration model. The research results provide a theoretically sound guidance for designing and practically sound approach for effectively improving the service life of mining riser.
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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) | 0.000 | 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".