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Record W3108499433 · doi:10.11575/prism/38281

Examine the feasibility of electrifying a natural gas pipeline system: a case study on Enbridge’s Westcoast pipeline

2020· article· en· W3108499433 on OpenAlexfundno aff
Shengnan Li

Bibliographic record

VenueOpen MIND · 2020
Typearticle
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsnot available
FundersBC Hydro
KeywordsPipeline (software)Natural gasPetroleum engineeringGas pipelineMarine engineeringComputer scienceEngineeringGeologyEnvironmental scienceMechanical engineeringWaste management

Abstract

fetched live from OpenAlex

Climate change is an evolving global issue that needs all industries to act. This research aims to examine the feasibility of reducing operational-related (Greenhouse Gas) GHG emissions at natural gas transmission pipeline through electrification, using Westcoast pipeline in BC as the case study. The research evaluated the GHG reduction potential at the pipeline’s gas compressor stations under three electrification scenarios. A cost-benefit analysis was performed for each scenario and compared with baseline scenarios. All the data in the research were selected using publicly available data. The analysis suggests that electrification will significantly reduce GHG emissions at the Westcoast pipeline; however, all three scenarios would surpass baseline operational cost due to incremental electricity demand. Future uncertainties, such as changing carbon tax price, natural gas price, electricity price, and gas compressor maintenance cost, might shift the electrification project financial analysis results.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.095
GPT teacher head0.330
Teacher spread0.235 · 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 designOther design
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
Published2020
Admission routes1
Has abstractyes

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