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Record W2762575604

Opportunities for Improved Warship Energy Efficiency: A Canadian Patrol Frigate’s Operational Energy Use Patterns

2016· dissertation· en· W2762575604 on OpenAlex
Fraser W. Work

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2016
Typedissertation
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsAeronauticsEngineeringEnergy (signal processing)Operations researchMarine engineeringTransport engineeringStatisticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

This project explores a Canadian warship’s propulsion and electrical energy use patterns to define energy baselines and determine if the ship would be able to save energy without compromising mission capability. The study also aims to define the key factors preventing more efficient energy use, and suitable technical and behavioral options to reduce overall mission fuel consumption. The author postulates that improved energy efficiency can coincidentally improve mission, cost and environmental performance. \n\nThis study defines a Canadian Patrol Frigate’s energy baselines for a single warship between July 2015 and March 2016. HMCS VANCOUVER (VAN) machinery control system and bridge logbook data were combined to define the ship’s daily trends for both propulsion and electrical energy, and determine what opportunities were available to meet speed demands, using more efficient engine configurations. The ship’s new machinery control system also allowed for real-time data capture of the ship’s total electrical power demand, and monitoring of the operating trends of electrical motors that drive the ship’s array of pumps and fans. These data, coupled with equipment amperage load-checks, provided an estimate of various system’s electrical energy use, both at sea and in port. \n\nDuring approximately 70% of all operations, VAN would have had favorable engineering, operational and weather conditions to assume the most efficient engine configuration, without degrading mission effectiveness. The ship used an average of 40.6 m3 of fuel, each of the 71 days at sea, spending the majority of her time at speeds between 10 and 15 knots, and demonstrating a strong tendency to utilize a gas turbine for slower speeds where the propulsion diesel engine (PDE) would have been most efficient. The study shows that if the ship assumed the most efficient, available drive mode, she could have saved 10% of total fuel without compromising mission capability. These results suggest that over a 15-year timeframe, enough fuel could be saved to send the entire fleet to sea for two years. This analysis highlights the criticality of the ship’s PDE, due to its fuel economy when compared to the more powerful, but less efficient gas turbines. The reliability and maintenance shortfalls of the PDE may prevent achievable fuel savings unless the PDE’s performance can be improved for more frequent use, especially at lower speeds. \n\n The analysis also defines the baseline electrical energy use patterns of the VAN, which used an average of 961 kW per hour at sea, and 620 kW per hour in harbor. The ship used a quarter of its total energy to supply costly onboard electrical power, to feed the high energy demands of key systems, including chilled water, fireman, air compressors, and machinery space ventilation. \n \nThis analysis shows that significant energy savings are possible through the implementation of efficient machinery configurations, improved system maintenance, and the isolation of redundant equipment. However in some cases, these savings would require additional investment for more efficient system performance. The information in this study can be used to support additional, detailed energy assessments of individual systems to identify attractive areas for saving energy and costs, with coincidental benefits to capability, and environmental and reputational performance.

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.005
Open science0.0020.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.030
GPT teacher head0.222
Teacher spread0.193 · 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