A simplified tempo-spatial model to predict airborne pathogen release risk in enclosed spaces: An Eulerian-Lagrangian CFD approach

Mirzaei, Parham A.; Moshfeghi, Mohammad; Motamedi, Hamid; Sheikhnejad, Yahya; Bordbar, Hadi

doi:10.1016/j.buildenv.2021.108428

Cited by 17 publications

(7 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although physics-based models such as the CFD simulations used in the control are typically too time consuming for real-time applications, numerous studies demonstrated that machine-learning-based models can be used as a surrogate to obtain the desired predictions. [36][37][38] Since the purpose of the case study was to serve as an illustrative example of how real-time resilience can be enabled and assessed in relation to health safety against airborne infection, the development of such surrogate models was outside the scope of the present study. Additionally, the occupancy detector in the control was assumed to be incapable of identifying and tracking individual diners over time as this would require facial recognition or wearable technologies that are not typically implemented in a food court setting.…”

Section: Ventilation Scenarios For Assessment Of Real-time Resiliencementioning

confidence: 99%

Digital-twin-controlled ventilation for real-time resilience against transmission of airborne infectious disease in an indoor food court

Tan,

Law,

Kumar Maan

et al. 2023

Building Services Engineering Research and Technology

View full text Add to dashboard Cite

During a disruption, actionable insights generated from real-time data of the disrupted system can be used to dynamically recalibrate mitigation and recovery responses but there is currently a paucity of investigation on such assessment and management of resilience in real time. In this study, we propose the concept of real-time resilience to encapsulate the capacity of a disrupted system to continuously recalibrate its responses and minimize its damage. Quantitative metrics to assess the real-time resilience are also established. Subsequently, a digital-twin-based control for mechanical ventilation systems was developed as a tool to enable real-time resilience against airborne infection in indoor spaces. For demonstration, numerical simulations were performed with the adoption of the new tool in an indoor food court. Results showed that the gross resilience of the diners was enhanced in terms of improvements to the metrics of disruption duration (26%–61%), loss of resilience (2%–39%), and average rate of recovery (26%–74%). At the same time, the tempo-spatial variations suggested that increasing the ventilation rate increased the dilution and dispersion of infectious aerosols simultaneously, which can have opposing effects on individual resilience depending on the diner’s location. The trade-off between real-time resilience and energy use was discussed based on the results. Practical applications: This study proposed a new tool based on the concept of real-time resilience to control ventilation to mitigate the indoor transmission of airborne infectious disease. The tool utilized numerical simulations to assess the tempo-spatial variation of infection risks and determine the adaptive changes needed for risk mitigation based on the predictive assessment. The evaluation of the tool using the proposed metrics of real-time resilience was demonstrated and the results showed that adoption of the tool can lead to improvements in disruption duration, loss of resilience, and average rate of recovery for diners in a food court.

show abstract

Section: Ventilation Scenarios For Assessment Of Real-time Resiliencementioning

confidence: 99%

Digital-twin-controlled ventilation for real-time resilience against transmission of airborne infectious disease in an indoor food court

Tan,

Law,

Kumar Maan

et al. 2023

Building Services Engineering Research and Technology

View full text Add to dashboard Cite

show abstract

“…Their results also showed that the Lagrangian model is better in predicting transient dispersion of the particles. In addition, for the CFD simulation of pathogens and volatile droplets generated by respiratory events, one should consider that numerical simulation of evaporation of smaller particles (sub-moicron particles) demand smaller time-step values which add to computational costs ( Mirzaei et al, 2022 ). This is contrary to the Eulerian framework, which does not include simulation of particles and hence is faster and cheaper, however, provides fewer details.…”

Section: Cfd Modeling Of Airborne Pathogen Dropletsmentioning

confidence: 99%

Airborne and aerosol pathogen transmission modeling of respiratory events in buildings: An overview of computational fluid dynamics

Sheikhnejad

Aghamolaei

Fallahpour

et al. 2022

Sustainable Cities and Society

View full text Add to dashboard Cite

Pathogen droplets released from respiratory events are the primary means of dispersion and transmission of the recent pandemic of COVID-19. Computational fluid dynamics (CFD) has been widely employed as a fast, reliable, and inexpensive technique to support decision-making and envisage mitigatory protocols. Nonetheless, the airborne pathogen droplet CFD modeling encounters its limitations in the oversimplification of involved physics and the intensive computational demand. Moreover, uncertainties in the collected clinical data required to simulate airborne and aerosol transport such as droplets’ initial velocities, tempo-spatial profiles, release angle, and size distributions are broadly reported in the literature. Furthermore, there is a noticeable inconsistency around these collected data amongst many reported studies. Hence, this study aims to review the capabilities and limitations associated with CFD modeling. Setting the CFD models needs experimental data of respiratory flows such as velocity, particle size, and number distribution. Hence, we will also briefly review the experimental techniques used to measure the characteristics of airborne pathogen droplet transmissions together with their limitations and reported uncertainties. Moreover, the relevant clinical data related to pathogen transmission needed for postprocessing of CFD data and translating them to safety measures will also be reviewed. Eventually, we scrutinize the uncertainty and inconsistency of the existing clinical data available for airborne pathogen CFD analysis to pave a pathway toward future studies ensuing these identified gaps and limitations.

show abstract

“…and Hossain and Faisal, for example, studied the exhalation and dispersion of a single person and investigated the distance that aerosol particles are transported. [ 1 , 2 ] Their studies show that aerosol clouds do not travel further than 1 m when talking or coughing and ≈0.2 m when breathing. [ 2 ] Other simulations show that aerosol clouds can reach up to ≈2.7 m. [ 1 ] Here, the velocity range reported is very broad.…”

Section: Introductionmentioning

confidence: 99%

“…[ 1 , 2 ] Their studies show that aerosol clouds do not travel further than 1 m when talking or coughing and ≈0.2 m when breathing. [ 2 ] Other simulations show that aerosol clouds can reach up to ≈2.7 m. [ 1 ] Here, the velocity range reported is very broad. In both studies, the focus is on the exhalation process and the area directly behind the inlet (mouth) is resolved.…”

Section: Introductionmentioning

confidence: 99%

Fates of Emitted Particles Depending on Mask Wearing Using an Approach Validated Across Spatial Scales

2023

View full text Add to dashboard Cite

The spread of emitted potentially virus-laden aerosol particles is known to be highly dependent on whether a mask is worn by an infected person and on the emission scenario, i.e., whether the person is coughing, speaking, or breathing. The aim of this work is to investigate in detail the fates of particles emitted by a person wearing a perfectly fitting, a naturally fitted mask with leakage, and no mask depending on the emission scenario. Therefore, a two-scale numerical workflow is proposed where parameters are carried through from a micro-scale where the fibers of the mask filter medium and the aerosol particles are resolved to a macro-scale and validated by comparison to experimental measurements of fractional filtration efficiency and pressure drop of the filter medium as well as pressure drop of the mask. It turns out that masks reduce the number of both emitted and inhaled particles significantly even with leakage. While without a mask, the person opposite of an infected person is generally at the highest risk of being infected, a mask worn by an infected person speaking or coughing will deflect the flow leading to the fact that the person behind the infected person might inhale the largest number of aerosol particles.

show abstract

A simplified tempo-spatial model to predict airborne pathogen release risk in enclosed spaces: An Eulerian-Lagrangian CFD approach

Cited by 17 publications

References 48 publications

Digital-twin-controlled ventilation for real-time resilience against transmission of airborne infectious disease in an indoor food court

Digital-twin-controlled ventilation for real-time resilience against transmission of airborne infectious disease in an indoor food court

Airborne and aerosol pathogen transmission modeling of respiratory events in buildings: An overview of computational fluid dynamics

Fates of Emitted Particles Depending on Mask Wearing Using an Approach Validated Across Spatial Scales

Contact Info

Product

Resources

About