Numerical Simulation of the Straight-Swirling Integrated Jet and Its Application in Natural Gas Hydrate Drilling
Bibliographic record
Abstract
Summary Natural gas hydrate (NGH) is a potential clean energy source and is buried abundantly in seafloor sediments. Waterjet is a key technology involved in both the marine NGH solid fluidization exploitation method and the integrated radial jet drilling and completion method. To improve the efficiency of breaking and extracting NGH through a waterjet, a straight-swirling integrated jet (SSIJ) nozzle is designed based on the convergent-divergent geometry and impeller in this study. With a computational fluid dynamics method, the 3D model of SSIJ is constructed, and the characteristics of velocity field, pressure field, cavitation cloud distribution, and turbulence kinetic energy are analyzed, the results of which are compared with conical jet (CJ), convergent-divergent jet (CDJ), and swirling jet (SJ). Laboratory experiments of gas hydrate-bearing sediments (GHBS) erosion by the four kinds of jets mentioned above are conducted to evaluate the jet erosion performance based on the in-house experimental apparatus for NGH generation and cavitating jet erosion. Results indicate that the SSIJ can significantly enhance the breaking volume and efficiency of waterjet erosion on GHBS compared with the other three methods. The most important driving force for improved efficiency is the 3D velocity, which can induce axial impact stress, radial tensile stress, and circumferential shear stress on the impinged GHBS. Additionally, the insertion of an impeller with the center hole greatly improves the cavitation erosion performance of SSIJ. This paper illustrates the erosion performance of four kinds of waterjets in breaking GHBS and provides preliminary insights into the potential field applications in NGH exploitation.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".