ArticleSafety and health at work2024
Comparative Study of Exposure Assessment of Dust in Building Materials Enterprises Using ART and Monte Carlo.
Article in Safety and health at work, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial Neural Network-based Prediction Model to Minimize Dust Emission in the Machining Process.Safety and health at work · 2024Article
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4 authors.
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Abstract
Background: Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods: First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results: The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m Conclusion: ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m
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