{"title":"拉格朗日室内颗粒物迁移模拟的质量控制:粒子数、通风策略和采样量的影响","authors":"Ye Seul Eom, Donghyun Rim","doi":"10.1016/j.jaerosci.2024.106346","DOIUrl":null,"url":null,"abstract":"<div><p>Airborne particle transport in indoor environments plays an important role in occupant exposure to aerosols and public health problems. Several studies have examined indoor airflow and particle transport using computational fluid dynamics models. For the Lagrangian particle tracking model, the minimum particle concentration necessary for accurate prediction may vary with the airflow regime and sampling volume. Nonetheless, only a few studies have systematically quantified suitable particle numbers and sampling volumes, according to indoor airflow and ventilation conditions. This study addresses this gap by exploring quality control strategies for a Lagrangian particle tracking model to reliably predict indoor particle transport. Based on transient simulations, we analyzed the spatiotemporal distributions of indoor particle trajectories while varying the number of particles, sampling volume, and ventilation strategy. The results indicate that in general a sampling volume of 5 L can predict the normalized mean concentrations better than a 1 L sampling volume, particularly when dealing with a smaller number of particles. Furthermore, the required particle number concentrations vary significantly depending on the chosen ventilation strategy. For instance, under the conditions of a 5 L sampling volume and an air exchange rate of 2.7 h<sup>−1</sup>, the minimum particle number concentrations for achieving reliable modeling predictions were observed to be 0.0075 cm<sup>−3</sup> for displacement ventilation and 0.015 cm<sup>−3</sup> for mixing ventilation. These results highlight the crucial role of the number of simulated particle trajectories in Lagrangian particle tracking models in determining prediction quality. The study findings suggest that quality control measures should acknowledge the significant variability in required particle numbers, which can often differ by an order of magnitude, contingent upon the specific combination of ventilation strategy and sampling volume.</p></div>","PeriodicalId":14880,"journal":{"name":"Journal of Aerosol Science","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quality control of Lagrangian indoor particle transport simulation: Effects of particle numbers, ventilation strategy, and sampling volume\",\"authors\":\"Ye Seul Eom, Donghyun Rim\",\"doi\":\"10.1016/j.jaerosci.2024.106346\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Airborne particle transport in indoor environments plays an important role in occupant exposure to aerosols and public health problems. Several studies have examined indoor airflow and particle transport using computational fluid dynamics models. For the Lagrangian particle tracking model, the minimum particle concentration necessary for accurate prediction may vary with the airflow regime and sampling volume. Nonetheless, only a few studies have systematically quantified suitable particle numbers and sampling volumes, according to indoor airflow and ventilation conditions. This study addresses this gap by exploring quality control strategies for a Lagrangian particle tracking model to reliably predict indoor particle transport. Based on transient simulations, we analyzed the spatiotemporal distributions of indoor particle trajectories while varying the number of particles, sampling volume, and ventilation strategy. The results indicate that in general a sampling volume of 5 L can predict the normalized mean concentrations better than a 1 L sampling volume, particularly when dealing with a smaller number of particles. Furthermore, the required particle number concentrations vary significantly depending on the chosen ventilation strategy. For instance, under the conditions of a 5 L sampling volume and an air exchange rate of 2.7 h<sup>−1</sup>, the minimum particle number concentrations for achieving reliable modeling predictions were observed to be 0.0075 cm<sup>−3</sup> for displacement ventilation and 0.015 cm<sup>−3</sup> for mixing ventilation. These results highlight the crucial role of the number of simulated particle trajectories in Lagrangian particle tracking models in determining prediction quality. The study findings suggest that quality control measures should acknowledge the significant variability in required particle numbers, which can often differ by an order of magnitude, contingent upon the specific combination of ventilation strategy and sampling volume.</p></div>\",\"PeriodicalId\":14880,\"journal\":{\"name\":\"Journal of Aerosol Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Aerosol Science\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0021850224000132\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Aerosol Science","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021850224000132","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Quality control of Lagrangian indoor particle transport simulation: Effects of particle numbers, ventilation strategy, and sampling volume
Airborne particle transport in indoor environments plays an important role in occupant exposure to aerosols and public health problems. Several studies have examined indoor airflow and particle transport using computational fluid dynamics models. For the Lagrangian particle tracking model, the minimum particle concentration necessary for accurate prediction may vary with the airflow regime and sampling volume. Nonetheless, only a few studies have systematically quantified suitable particle numbers and sampling volumes, according to indoor airflow and ventilation conditions. This study addresses this gap by exploring quality control strategies for a Lagrangian particle tracking model to reliably predict indoor particle transport. Based on transient simulations, we analyzed the spatiotemporal distributions of indoor particle trajectories while varying the number of particles, sampling volume, and ventilation strategy. The results indicate that in general a sampling volume of 5 L can predict the normalized mean concentrations better than a 1 L sampling volume, particularly when dealing with a smaller number of particles. Furthermore, the required particle number concentrations vary significantly depending on the chosen ventilation strategy. For instance, under the conditions of a 5 L sampling volume and an air exchange rate of 2.7 h−1, the minimum particle number concentrations for achieving reliable modeling predictions were observed to be 0.0075 cm−3 for displacement ventilation and 0.015 cm−3 for mixing ventilation. These results highlight the crucial role of the number of simulated particle trajectories in Lagrangian particle tracking models in determining prediction quality. The study findings suggest that quality control measures should acknowledge the significant variability in required particle numbers, which can often differ by an order of magnitude, contingent upon the specific combination of ventilation strategy and sampling volume.
期刊介绍:
Founded in 1970, the Journal of Aerosol Science considers itself the prime vehicle for the publication of original work as well as reviews related to fundamental and applied aerosol research, as well as aerosol instrumentation. Its content is directed at scientists working in engineering disciplines, as well as physics, chemistry, and environmental sciences.
The editors welcome submissions of papers describing recent experimental, numerical, and theoretical research related to the following topics:
1. Fundamental Aerosol Science.
2. Applied Aerosol Science.
3. Instrumentation & Measurement Methods.