Latest Update of Tests and Improvements to Coast Guard Viscous Oil Pumping System (VOPS)1
Bibliographic record
Abstract
ABSTRACT Over the past nine years, the U.S. Coast Guard has incorporated the Prevention Through People (PTP) philosophy as a “human factors” approach to learn how maritime operations can be regulated safer and be more efficient by evaluating training, management policies, operational procedures, and establishing partnerships with the maritime industry. One of the key elements of applying a PTP approach is identifying and incorporating lessons learned from major marine casualties and pollution incidents. Since 1997, the U.S. Coast Guard National Strike Force (NSF) has responded to three major oil spills involving foreign freight vessels grounding, which included the removal of highly viscous oil using various lightering equipment and systems. An informal workgroup consisting of the U.S. Coast Guard, U.S. Navy Supervisor of Salvage (NAVSUPSALV), and various representatives from oil pollution clean-up companies met at the following facilities: the Chevron Asphalt Facility in Edmonds, WA (September 1999), the Oil and Hazardous Materials Simulated Environmental Test Tank (OHMSETT) testing facility in Leonardo, New Jersey (November 1999 and March 2000), the Alaska Clean Seas (ACS) warehouse annex in Prudhoe Bay, AK (October 2000), and Cenac Towing Company facility in Houma, LA (May 2002). The group shared ideas and techniques, and tested different pumps and hose lengths with viscous oil. It was during the early tests that the first quantitative results showed just how efficient lubricated transport of heavy oil product could be, and broadened the knowledge of such methods to the entire industry. Although this technology had existed for many years in the oil production and handling industry, its use had never been investigated in a laboratory setting with regard to salvage response lightering systems. The lubrication of heavy oil product was first applied in the tests in the form of Annular Water Injection (AWI) by means of an, Annular Water Injection Flange (AWIF). This idea had been developed many years ago by the oil industry to improve oil output production, but was first applied to salvage response using the flange concept by the Frank Mohn Company of Norway. In concept, the flange applies water to the viscous product discharge of a pump by means of its unique geometry. The initial tests resulted in developing the use of AWI on the discharge side of the pump. This technique was further refined and applied to existing U.S. Coast Guard lightering systems in the form of the Viscous Oil Pumping System (VOPS) package, which has been issued to each of the three USCG Strike Teams of the National Strike Force (NSF). Latest improvements include using AWI on the suction side of the pump with hot water or steam. For this suction application, a different device used to deliver water lubrication was also tested concurrently with the discharge AWIF. Other significant improvements, which achieved one of the goals set in 2000, was to seek global partnership with other companies or agencies from other countries. In 2002, the Canadian Coast Guard formally joined the U.S. VOPS workgroup to form the Joint Viscous Oil Pumping System (JVOPS) Workgroup.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".