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Electrifying Maritime Shipping: Evaluating the CO<sub>2</sub> Reduction and Viability of Future Battery-Powered Container Ships Calling at the Port of Los Angeles

2024· article· en· W4405537408 on OpenAlexaff
Jules Wilson, Rupp Carriveau, William Hurley, Reza Babaei, David S.‐K. Ting

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPort (circuit theory)Container (type theory)Battery (electricity)Reduction (mathematics)Environmental scienceMarine engineeringAeronauticsOn boardEngineeringAutomotive engineeringElectrical engineeringAerospace engineeringPower (physics)Mechanical engineering

Abstract

fetched live from OpenAlex

Abstract Maritime shipping plays a pivotal role in global logistics, influencing efficiency, emissions, and adaptability. This academic study envisions future electrified shipping fleets and evaluates the potential for CO 2 reduction and the cost delta between grid electricity and marine fossil fuels using three types of container ships (5000-7999 TEU, 8000-11999 TEU, and 12000-14499 TEU). The scenario evaluated envisions an electrical charging infrastructure at the Port of Los Angeles, supported fully by wind and solar energy sources, to recharge future battery-powered ships. It is recognized that electric-powered ocean-going long-transit ships are not practical, but this study provides baseline groundwork to justify and support future development of hybrid or partially electric ships to help meet the International Maritime Organization’s (IMO) target of a 50% reduction in CO 2 emissions from the world’s shipping by 2050. Additionally, a real case study analysis of all container ships at POLA was conducted using container vessel activity to further evaluate the practical implications and benefits of this transition. This analysis underscores the significant electrical infrastructure investments required and highlights the potential economic challenges as well as the environmental benefits of integrating electric power into maritime operations.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.267
Teacher spread0.244 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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