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Evaluating the impact of human movement-induced airflow on particle dispersion: A novel real-time validation using IoT technology

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F24%3APU156043" target="_blank" >RIV/00216305:26210/24:PU156043 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0378778824009411?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0378778824009411?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.enbuild.2024.114825" target="_blank" >10.1016/j.enbuild.2024.114825</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluating the impact of human movement-induced airflow on particle dispersion: A novel real-time validation using IoT technology

  • Original language description

    Human movement significantly influences local airflow and particle dispersion in indoor environments. Therefore, this study integrates the dynamics of human walking into the analysis of airborne infection risks in a positive pressure isolation ward designed for the protection of immunocompromised patients. Real-time data collection was performed using an anemometer and IoT-based PM sensors to measure airflow velocities and particulate matter (PM) concentrations within a full-scale experimental chamber. Computational Fluid Dynamics (CFD) was used for the numerical simulations, and a User-Defined Function (UDF) code simulated the translational movement of a manikin. The results demonstrated strong agreement with the experimental data, thereby validating the airflow turbulence and Lagrangian-based Discrete Phase Model (DPM) in predicting the airflow velocities and particle transport. The study revealed that human walking substantially enhanced particle dispersion distance by 10-fold compared to static conditions, primarily attributed to intensified air mixing induced by the body movement. Furthermore, the CFD analysis underscored that the direction of walking plays a crucial role in airborne transmission. Specifically, walking away from a patient did not elevate infection risk, whereas approaching a patient significantly increased particle deposition in the patient-occupied region. This study highlights the critical need to consider both movement patterns and directional flow in managing airborne infection risks, contributing to the development of more effective infection control strategies in healthcare settings.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20100 - Civil engineering

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ENERGY AND BUILDINGS

  • ISSN

    0378-7788

  • e-ISSN

    1872-6178

  • Volume of the periodical

    neuveden

  • Issue of the periodical within the volume

    323

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    15

  • Pages from-to

    114825-114825

  • UT code for WoS article

    001322389400001

  • EID of the result in the Scopus database

    2-s2.0-85204645476