263 Emission factors and fume generation rates of particles from various welding processes
Bibliographic record
Abstract
Abstract Welding fumes are classified as a class 1 carcinogen, according to IARC. A conical chamber was built to determine emission factors and fume generation rates of particles from various welding processes. The chamber was calibrated according to the American Welding Society (AWS) standard F1.2:2013 and a high-volume air sampling pump was fixed to the top of the chamber to collect the fumes on 293 mm glass fibre filters located between the cone and the pump. Two welding processes were tested: gas metal arc welding (GMAW) and low power density laser beam welding (LLBW). Tests were performed using seven different types of consumables and different base materials. Consumables included ER70S-2, ER70S-6, ER70S-3, ER308L, ER316L, E316LSi, and ER5356 and the base materials included mild steel, stainless steel, and aluminium. Except for aluminium, which could not ne weld with this particular LLBW machine, the same consumables were used for GMAW and LLBW. Three levels of welding voltages in GMAW and power settings in LLBW were used for each type of consumable to see the effect of voltage and power on particle emission factors and fume generation rates. Additionally, differences between particle emission factors and fume generation rates from GMAW and LLBW for each consumable were compared. Emission factors and fume generation rates increased with increasing voltage/power. Although the fume generation rates were lower for LLBW than for GMAW, the emission factors were higher for LLBW.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".