Computational Fluid Dynamics (CFD) Modelling of Diesel Particulate Matter in relation to Lung-Deposited Surface Area (LDSA) in Underground Tunnels

Sergei Sabanov, Assylkhan Aitimbetov

2026

Closed access Metadata (CSL-JSON)
DOI 10.11159/mmme26.151
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Diesel-powered equipment remains a major source of respirable particulate exposure in underground mining, where limited dilution and mechanically driven airflow can create highly non-uniform pollutant fields.Conventional diesel particulate matter (DPM) assessment is commonly based on mass concentration or time-weighted sampling, which can miss the location-specific exposure experienced by workers near the face.This study develops a computational fluid dynamics (CFD) framework for mapping health-relevant DPM exposure in an auxiliary-ventilated underground tunnel by converting simulated passive-scalar concentrations into DPM and LDSA.LDSA is used because it better represents the particle surface area deposited in the respiratory tract, which is especially relevant for fine and ultrafine diesel aerosols [1]-[3].