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Record W7066562858

HySeas III: The World's First Sea-Going Hydrogen-Powered Ferry – A Look at its Technical Aspects, Market Perspectives and Environmental Impacts

2019· article· en· W7066562858 on OpenAlexfundno aff

Bibliographic record

Venueelib (German Aerospace Center) · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsnot available
FundersDeutsches Zentrum für Luft- und RaumfahrtUniversity of St AndrewsEuropean CommissionBallard Power Systems
KeywordsGreenhouse gasFuel cellsRelation (database)Order (exchange)Global warmingProduction (economics)Life-cycle assessmentHydrogen economy
DOInot available

Abstract

fetched live from OpenAlex

The greenhouse gas emissions from international shipping were estimated to be 2.1% of the global emissions by 2012. In order to decrease them in the future, new measures are being taken but also new alternative power systems employing batteries, hydrogen and fuel cells and the production of alternative fuels are now under development. Currently, several projects are aiming at the implementation of hydrogen and fuel cells in Ro-on/roll-off and passenger (RoPax) ferries. In relation to this, a comparison of hydrogen and fuel cell systems against other technologies such as batteries in terms of costs, system mass and volume is presented in this paper. In addition, an overview of the market potential of RoPax ferries in Europe is given, showing that fuel cells have potential, particularly if their power is scaled up. Finally, we present the first results of the life cycle assessment carried out within the project of HySeas III, which shows that the global warming potential generated by the ship in a 30 year life would decrease by 89% compared to a ship operating with a diesel-electric system.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0270.001

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 head0.004
GPT teacher head0.205
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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