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Record W1993098437 · doi:10.4043/19054-ms

A New Era in CNG Transportation

2007· article· en· W1993098437 on OpenAlexaboutno aff
Len Thompson

Bibliographic record

VenueOffshore Technology Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCompressed natural gasNatural gasLiquefied natural gasPipeline transportFossil fuelFuel gasLiquid gasPipeline (software)Petroleum engineeringBusinessEngineeringEnvironmental scienceWaste managementEnvironmental engineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

Introduction Floating Pipeline Company Incorporated (FPC Inc), a Canadian Corporation based in Halifax, Nova Scotia, is the licensed manufacturer for TransCanada Pipelines' Gas Transportation Modules (GTMs) used for the volume transport of Compressed Natural Gas (CNG). Compressed Natural Gas can be used economically in the niche market for stranded gas. "Stranded gas" is any gas that cannot today be economically brought to market using conventional pipeline or liquefied natural gas (LNG) technology. It is pplicable to areas where companies are not willing to invest heavily in infrastructure, or in areas where physical limitations inhibit bringing the gas ashore. Approximately 50% of the world's discoveries and expected discoveries fall into the "stranded gas" category. Transporting CNG in GTMs to niche markets can offer substantial price advantages over conventional energy sources such as electricity, propane, and diesel fuels, which are the only alternatives today. Studies carried out for the offshore fields alone indicate conservatively that the potential market for this technology could be as large as 50+ projects over the next 20 years, with clients including all the major oil and gas companies, and companies in the transportation and delivery of gas. Moving natural gas from the well to market is normally achieved by pipeline (as gas) or ships (as LNG). Several other methods are being investigated to improve the economics of transport, namely CNG, gas to liquids (GTL), and variations of these. CNG transportation has been shown to be economical in a number of specific niche situations. Moving ‘stranded gas’ as CNG can be shown to be economically attractive, for distances of less than 1,500 miles, where it is either politically restricted, physically impossible, or where the volumes are too small to justify laying a pipeline or building an LNG facility, This niche market is not limited to sea transport. It also presents significant opportunities on land through road trailers. TransCanada CNG Technology Limited (TCCNGTL) has the worldwide licence to a patented technology that enables sufficient quantities of gas to be transported under pressure economically for projects that fit the above niche markets. This technology " composite spiral wrapped, thin walled steel pressure vessels " was approved by ASME in October 2002, which now enables its use in the applications identified. Approval in Principle for the use of GTMs in ships was granted by Lloyds Registry of Shipping in September 2003. FPC Inc. along with its UK engineering partner, WaveSpec (a wholly owned subsidiary of BraemarSeascope, London) provided the engineering services for the submission to Lloyds on behalf of TCPL. More recently, FPC/TCPL/OSG and Rolls Royce have been working with Lloyds Register for the full approval of the ship for a project in East Africa. This is expected to be complete within the 2nd Quarter 2007. FPC recognizes the potential of this technology and:Is marketing and developing contracts for the transport of CNG worldwide utilizing this technology;Has established a manufacturing facility in New Brunswick, Canada to fabricate, under license, the GTMs;Plans to sell GTMs to third party project developers;

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.069
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.004
Scholarly communication0.0050.009
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0690.015

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 head0.008
GPT teacher head0.207
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2007
Admission routes1
Has abstractyes

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