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Record W2083837449 · doi:10.1115/1.3007900

Design and Validation of a Water Transfer Factor Measurement Apparatus for Proton Exchange Membrane Fuel Cells

2009· article· en· W2083837449 on OpenAlexaff
Pierre Sauriol, David S. Nobes, Xiaotao Bi, Jürgen Stumper, Dustin Jones, Darwin Kiel

Bibliographic record

VenueJournal of Fuel Cell Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsCoanda Research and Development Corporation (Canada)Ballard Power Systems (Canada)University of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsProton exchange membrane fuel cellMass transferProcess engineeringSensitivity (control systems)Water flowWater transferChemistryMechanical engineeringEnvironmental scienceEngineeringEnvironmental engineeringMembraneElectronic engineeringChromatography

Abstract

fetched live from OpenAlex

Abstract The investigation of water management within proton exchange membrane fuel cells (PEMFCs) has led to the definition of a water transfer factor to describe the net transfer of water across the membrane. In most fuel cells, the total amount of water transferred across the membrane is a small fraction of the total water passing through the fuel cell, and therefore experimental measurements of the water transfer factor have been very difficult to achieve in practice. This paper presents a four-step systematic approach to design and validate a measurement concept that will enable the measurement of the water transfer factor with the desired accuracy. These steps are: (1) several key equations are obtained from mass balance; (2) potential measurands are screened by sensitivity analysis; (3) the performance of interesting measurement concepts is simulated by a Monte Carlo approach to account for the variability of the instrument performance and other operational considerations; and (4) validation tests are achieved in a simulated fuel cell configuration to determine measurement accuracy of the selected measurement concept. Four key equations were derived from mass balance considerations allowing for the determination of the water transfer factor. The sensitivity analysis showed that measurement concepts that relied on the differential mass flow rate and the differential water content would yield the best accuracy. However, these measurement concepts were found to involve a great risk associated with the development or adaptation of key measurement instruments. A more conventional measurement concept, which utilizes precision liquid injection by syringe pumps and water content measurement by infrared absorption, was therefore selected. The measurement concept was further improved by implementing a reference injection, which, based on the virtual experiments using Monte Carlo calculations, allowed for an order of magnitude improvement in the accuracy. From the validation tests it was determined that combining anode and cathode side measurements, the measurement concept has an accuracy better than ±0.01 on the water transfer factor.

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)0.011
metaresearch head score (Gemma)0.009
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: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0040.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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
GenreMethods

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

Citations10
Published2009
Admission routes1
Has abstractyes

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