Decision-Making Approach to Support the Selection of Remotely Operated Inspection Methods of FPSO Tanks
Bibliographic record
Abstract
Abstract The inspection of structural members within the cargo or ballast tanks of Floating Production Storage and Offloading (FPSO) platforms is usually carried out in accordance with the requirements of classification society rules. Traditionally, these inspections are conducted by operators who need to access the interior of the tank to inspect points considered critical for the development of degradation processes. Based on the level of degradation, the ship’s owners can evaluate the structural strength and determine the need for maintenance. However, in addition to being time-consuming, inspections carried out by human operators can pose a risk to human life. With the aim of reducing human exposure to risk, remotely operated inspection methods are being considered for their potential application in structural inspections. In this context, this paper presents an approach to support the selection of remotely operated inspection methods for FPSO cargo and ballast tanks. A literature review identified the main remotely operated resources used to assess the structural elements and their different analysis techniques. Then, a multiple criteria decision-making (MCDM) was applied to select the most suitable remotely operated tank inspection method considering criteria that were aligned with the operational context of the organization and performance evaluation of the alternatives supported by expert elicitation.
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 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 | 0.001 |
| 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".