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Record W4376139062 · doi:10.1093/annweh/wxac087.183

155 A test Chamber to Quantify Emission Factors for Welding Fumes

2023· article· en· W4376139062 on OpenAlexaff
Emily Quecke, Zaher Hashisho, Bernadette Quémerais

Bibliographic record

VenueAnnals of Work Exposures and Health · 2023
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConsumablesWeldingShielded metal arc weldingMaterials scienceArc weldingElectrodeShielding gasGas tungsten arc weldingGas metal arc weldingMetallurgyNuclear engineeringComposite materialChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract A conical test chamber was built to quantify emission factors for various types of welding processes. The chamber was built according to American Welding Society (AWS) standard F1.2:2013. Fumes were collected on pre-dried and pre-weighted 293 mm glass fiber filters using a high-volume sampling pump running at approximately 30 cfm. Consumables were weighted before and after welding to calculate the amount of fume emitted per weight of consumable. All the welding was performed by a professional welder. The chamber was calibrated prior to any use to adjust the flowrate inside the chamber. The test chamber was used to calculate emission factors for Shielded Metal Arc Welding process using four different electrodes (E6013, E6011, E7018, E7014) and three different currents for each electrode as fume emission increases with current. Each test was done in triplicates to investigate for variation. Emission factors were calculated by diving the amount of fume on the filters by the weight of consumables used (g/kg). In general test were reproducible with coefficient of variations varying from 0.2 to 18.1% with most variation below 15%. Emission factors were highly dependent on the type of electrode with the lowest values found for E6013 and the highest for E6011. Emission factors increased significantly with increasing current. The chamber works properly and can be used to test other processes such as Gas Metal Arc Welding, Metal Core Arc Welding, Flux Core Arc Welding, as well as Gas Tungsten Arc Welding. Emission factors will also be calculated for metals.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.145
GPT teacher head0.385
Teacher spread0.239 · 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 designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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