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Record W1526205632

Design of an Electrical Power and Communications System for an Autonomous Underwater Vehicle

2010· article· en· W1526205632 on OpenAlexaboutno aff
David Shea, Michael G. Snow, Neil Riggs, C. Williams, Ralf Bachmayer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSystems designUnderwaterElectric power systemEngineeringEthernetPower managementSystems architectureArchitectureSystems engineeringEmbedded systemComputer sciencePower (physics)Electrical engineeringComputer network
DOInot available

Abstract

fetched live from OpenAlex

The SQX-500 Autonomous Underwater Vehicle (AUV) is presently under joint development by Marport Canada Inc, the Institute for Ocean Technology of the National Research Council Canada, and Memorial University of Newfoundland. The design of an electrical system for an underwater vehicle provides several challenges unique to the marine environment. In addition, as an autonomous vehicle operating for long durations without human supervision, further design challenges are introduced. This paper will discuss the nature of these various design challenges, and will feature the SQX-500 AUV electrical system design as a case study. Examples of design topics will include the following: - Selection of an AUV energy system, with a focus on Lithium Ion batteries as a power source, and the necessity of “smart” batteries - Communications system architecture, distributed vs. centralized designs, and commonly used standards (Ethernet, RS232, RS485, CANbus, etc.) - RF antenna design challenges for survivability, acoustic and electrical frequency interference issues - Data management in underwater vehicles, local recording of data or transmission of real-time data, bandwidth limitations of communication systems - Power distribution systems, power bus voltage selection, power isolation between sub-systems - Emergency systems architecture including emergency batteries, preservation of critical systems, and emergency power management This paper will also feature a discussion of the advantages and disadvantages of solutions to these design challenges, including lessons learned and recommendations for future underwater vehicle designs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.251
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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