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Record W1483647569 · doi:10.2172/963356

Five Kilowatt Fuel Cell Demonstration for Remote Power Applications

2008· report· en· W1483647569 on OpenAlexaboutno aff
Dennis Witmer, Tom Johnson, Jack Schmid

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsnot available
Fundersnot available
KeywordsElectric powerElectricityElectricity generationAutomotive engineeringEngineeringSolid oxide fuel cellElectrical engineeringEnvironmental sciencePower (physics)Anode

Abstract

fetched live from OpenAlex

While most areas of the US are serviced by inexpensive, dependable grid connected electrical power, many areas of Alaska are not. In these areas, electrical power is provided with Diesel Electric Generators (DEGs), at much higher cost than in grid connected areas. The reasons for the high cost of power are many, including the high relative cost of diesel fuel delivered to the villages, the high operational effort required to maintain DEGs, and the reverse benefits of scale for small utilities. Recent progress in fuel cell technologies have lead to the hope that the DEGs could be replaced with a more efficient, reliable, environmentally friendly source of power in the form of fuel cells. To this end, the University of Alaska Fairbanks has been engaged in testing early fuel cell systems since 1998. Early tests were conducted on PEM fuel cells, but since 2001, the focus has been on Solid Oxide Fuel Cells. In this work, a 5 kW fuel cell was delivered to UAF from Fuel Cell Technologies of Kingston, Ontario. The cell stack is of a tubular design, and was built by Siemens Westinghouse Fuel Cell division. This stack achieved a run of more than 1 year while delivering grid quality electricity from natural gas with virtually no degradation and at an electrical efficiency of nearly 40%. The project was ended after two control system failures resulted in system damage. While this demonstration was successful, considerable additional product development is required before this technology is able to provide electrical energy in remote Alaska. The major issue is cost, and the largest component of system cost currently is the fuel cell stack cost, although the cost of the balance of plant is not insignificant. While several manufactures are working on schemes for significant cost reduction, these systems do not as yet provide the same level of performance and reliability as the larger scale Siemens systems, or levels that would justify commercial deployment.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.031
GPT teacher head0.317
Teacher spread0.286 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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