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Record W4293115986 · doi:10.11159/mmm22.132

Diesel Particulate Matter Exposure to an Operator of LHD Loader Working in an Active Ore Heading Area

2022· article· en· W4293115986 on OpenAlexvenueno aff
Sergei Sabanov, Nursultan Magauiya, Aibyn Zenulla, Akmaral Abil, Gulnur Nurshaiykova

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsLoaderParticulatesHeading (navigation)Diesel fuelEnvironmental scienceAutomotive engineeringEngineeringMechanical engineeringAerospace engineeringChemistry

Abstract

fetched live from OpenAlex

Underground mines are particularly hazardous environments where miners are exposed to toxic fumes and gases. To ensure safety, sufficient mine ventilation must be provided. Ventilation requirements should be estimated considering diesel equipment engine power, blasting fumes, gases, aerosols, dust, and the unit airflow needed. Diesel engines are the main sources of toxic gases (CO, CO₂, NOₓ, SO₂, hydrocarbons) and diesel particulate matter (DPM). DPM consists of elemental carbon (EC), organic carbon (OC), and various gases and aerosols produced by incomplete combustion. The relationship between EC and OC fractions in untreated exhaust depends on engine operating conditions, engine type, fuel composition, and other parameters [5]. Total carbon (TC) is calculated as the sum of EC and OC and typically represents about 80% of total DPM [6]. Only 5–10% of all DPM particles are larger than one micrometer in diameter [2]. The concentration of particulate matter smaller than 1 μm (PM₁) is commonly used as an indicator of DPM levels because this size range encompasses nearly all diesel particulate matter [5]. Mine ventilation, diesel emission rates, exhaust flow direction, and the geometry of drifts influence DPM concentrations and dispersion patterns. Mobile diesel equipment operators generally experience the highest exposure to DPM. The main objective of this study is to conduct experimental sampling and analysis of DPM exposure for an operator of a diesel-powered load–haul–dump (LHD) loader working in an active ore heading area. Experimental sampling of particulate matter (PM) concentrations was carried out using a RigzardPM Plus sampling instrument in an underground polymetallic mine. Sampling was conducted over a 12-minute period inside the open cabin of an R1700 LHD loader (engine model Cat® C11 ACERT, 241 kW, Tier 3/Stage IIIA equivalent engine) working at the active ore heading face. The average PM₁ concentration measured by the RigzardPM Plus was 655 μg/m³ at a mine ventilation air velocity of 0.7 m/s. The LHD loader operated over a 30-meter haulage distance with an approximate cycle time of 2 minutes. Based on the TC–PM₁ correlation (DPM) used in the NIOSH 5040 method, the corresponding TC concentration of 185 μg/m³ is very close to the Mine Safety and Health Administration (MSHA, 2008) DPM limit of 160 μg/m³, measured as total carbon. This indicates that auxiliary ventilation requires moderate improvement to ensure sufficient dilution of toxic fumes in the active ore heading area. The measurement results appear reliable and demonstrate the suitability of the RigzardPM Plus instrument for monitoring DPM concentrations, with strong potential for its validation in computational fluid dynamics (CFD) modelling of DPM dispersion underground. The planned CFD simulations will incorporate LHD loader positions and auxiliary ventilation configurations in the active ore heading area. The expected outcome of this work is improved auxiliary ventilation design and enhanced protection of mine workers’ health.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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 designObservational
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".

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Citations0
Published2022
Admission routes1
Has abstractno

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