Bibliographic record
Abstract
Abstract During subsea mining operations, minerals are extracted from the seabed, typically at about 2000m depth, and pumped with water through a riser pipe to a surface processing vessel. TechnipFMC, through its subsidiary Technip France, is the lead of a consortium comprising COMEX and DCNS which has been awarded a contract by BPIFrance to develop a pilot subsea mining system. The scope includes the development of a flexible riser. This flexible riser comprises an inner wear protection layer to resist the wear from the slurry, covered by a structure to withstand mechanical loads applied to the flexible during its lifetime. In order to select the most appropriate anti-abrasion material, a large scale bench test has been built to reproduce realistic flow in a piping system and compare wear on different materials; rubber, polyethylene and stainless steels. Complete analysis of the wear patterns has been conducted with the expertise of a laboratory. A statistical comparison between materials is presented. The response to wear, depending on material, geometry and position, is better known. One of the materials shows much better wear resistance than the others and is selected for further development. The next step is the development and qualification of the manufacturing process for the wear protection layer. This process has to be as much as possible compatible with current flexible pipe manufacturing plant. Parameters such as thickness, diameter or length of the layer should be adaptable according to needs. The compatibility with the pipe mechanical structure has to be tested as well. To meet these requirements, existing manufacturing processes are limited. At the time of writing this paper, different manufacturing methods to incorporate this wear protection layer within a continuous industrial flexible production are currently under investigation. Several prototypes will be realized for each manufacturing step. Prototyping is under test and will be presented in a forthcoming presentation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".