Designing a Subsea Neutrino Observatory: The Deployment Challenges of Instrumenting a Cubic Kilometer
Bibliographic record
Abstract
Ocean Networks Canada (ONC) in partnership with the Pacific Ocean Neutrino Experiment (P-ONE) collaboration are developing a subsea neutrino telescope by instrumenting a large volume of water with thousands of photomultiplier tubes (PMTs). For neutrino telescopes to effectively detect neutrinos, a large volume of transparent material, such as water or ice, must be instrumented as the neutrinos can weakly interact with the matter to create Cherenkov radiation, which can be detected by the PMTs. The P-ONE telescope plans to take advantage of the existing subsea cabled observatory, NEPTUNE, operated by Ocean Networks Canada to provide the telescope with power and communications. Pathfinder projects called STRAW-a and STRAW-b were conducted in the Cascadia Basin, the proposed site for the P-ONE telescope. The deployments of these pathfinder moorings shared similarities with deployment requirements for the future P-ONE moorings. Many design decisions for the P-ONE integrated power and communications backbone were inspired by challenges encountered during STRAW and STRAWb. The design of the backbone cable and the novel instrumented hemisphere design will be discussed in the paper. In order to instrument a cubic kilometer of water, many moorings must be deployed, each consisting of many instruments. The P-ONE plan is to deploy 70 moorings strings, each 1km tall with 20 instruments. Installing a dense cluster of long moorings creates several significant challenges. The location of the moorings relative to one another must be very precise, both for the quality of the neutrino detection and to ensure that the moorings do not entangle. Additionally, a remotely operated vehicle (ROV) must be used to connect each mooring to the power and communications infrastructure. Navigating an ROV around such a closely packed cluster of moorings creates a significant risk to the vehicle. To solve many of these challenges, the concept of a ‘bottom up’ mooring deployment was investigated, where the mooring string will be deployed to the seafloor while packed into a frame. The frame will be a compact structure, roughly the size of a 20ft shipping container. The frame can be deployed and repositioned more accurately than a mooring. Additionally, the frame does not pose a significant hazard for the ROV. Once cabled to the surrounding infrastructure and tested subsea, the mooring will be ‘released’ and the entire mooring will unfurl from the frame and rise into a deployed configuration. Once several of these moorings have unfurled, the ROV will no longer be able to enter into the field of moorings. Several different concepts for the mechanism of the frame releasing the mooring were developed with detailed investigation into the advantages and disadvantages of each concept. Eventually, one concept was selected for further design. The development of the proposed deployment frame requires a detailed understanding of the mechanics involved in the cable and instrumentation being acted upon by the buoy upon its release. Scale model testing, full scale testing, and simulations were completed to better understand different aspects of the design. To ensure that the cable would fit correctly into the frame, with it's known tolerances and twist properties, software was written to determine the available spooling configurations that would result in zero net twist during release. These scripts were used in conjunction with computer aided design (CAD) modeling to ensure the cable path during spooling and release would function as desired. The behaviour of the cable as it unfurls is a critical operation that must be carefully planned out as part of the frame development. Several systems will be designed to ensure a successful deployment. The frame will have lift points for handling and deployment from the deck of the ship, however these lift points must be able to clear out of the way of the unfurling string. A shock absorber will be present to allow the buoy to decelerate without creating high snap loads on the cable and junction box. The junction box must be able to articulate between a horizontal position for deployment and a vertical position after unfurling. A mechanism must constrain the buoy to the frame during deployment, but allow for the ROV or an acoustic trigger to release the buoy. All of these systems will fit together in a confined space and not interfere with the cable or instruments and thus the development of the frame requires careful consideration.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".