Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
Session 11: Covid-19 & indoor environment
Time:
Wednesday, 25/Aug/2021:
2:00pm - 3:30pm

Session Chair: Prof. Jarek Kurnitski, Tallinn University of Technology
Location: Room 2 - Room 011, Building: 116

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Presentations
2:00pm - 2:15pm

The effect of air conditioning outlets on the spread of respiratory disease in Mosque’s environment

Hayder Murad Khan, Saleh Al Saadi

Sultan Qaboos University, Oman

Mosques are places for daily worship for Muslims where they attend prayers 5 times/day. As a prayer compulsory practice, worshippers conduct prayers in group standing side by side in rows touching shoulders and ankles. Furthermore, worshippers in their praying practice touch the floor with their forehead on the ground for 4 to 8 times in a single prayer. Mosques are usually air-cooled by mechanical means with poor ventilation system. The compulsory prayer practices coupled with the poorly ventilation system increase the risk of spreading respiratory diseases like COVID-19. This study utilizes a Computational Fluid Dynamics (CFD) package to evaluate the movement of disease particles around a row of worshipers. The study focuses on the impact of the air outlet parameters such as air velocity, air direction and the air outlet position on the spread of the disease particles as well as the thermal comfort of the worshippers. The results indicated that the parameters have a significant impact on the particles movement and suspension in the air and final settlement on the ground. It is concluded that the design and operation of the air conditioning system in mosques should be carefully considered to achieve an acceptable air quality without compromising the thermal comfort for worshipers in mosques environment.



2:15pm - 2:30pm

A systematic approach to estimating the effectiveness of multi-scale IAQ strategies for reducing the risk of airborne infection of SARS-CoV-2

Jialei Shen1, Meng Kong1, Bing Dong1, Jianshun Zhang1,2

1Syracuse University; 2Nanjing University

The unprecedented coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made more than 62.7 million people infected and 1.46 million people dead globally, and 13.4 million people infected and 267 thousand people dead in the U.S. by the end of November, 2020. Airborne transmission has been recognized as one of the major transmission routes for the infectious disease COVID-19. A systematic approach to estimating the effectiveness of multiscale indoor air quality (IAQ) control strategies for reducing the risk of airborne transmission of SARS-CoV-2 is developed in this study, including the application of infection risk model, the definition of baseline building cases and the analysis of the effectiveness of source control, ventilation and air cleaning strategies across multiple scales of the built environment raging from whole building, to room, to semi-open space, and to the breathing zones. The Wells-Riley model is used to establish the relationship between viral quantum dose exposure and the risk of airborne infection. And the effects of the various IAQ strategies on the dose exposure are evaluated. The probability distributions of each parameter in the Wells-Riley model and their impacts on the predicted risk of infection are analyzed with the Mont-Carlo simulation method. Requirements specified in the ASHRAE Standard 62.1 are used to establish the baseline cases for different type of building types to enable the estimation of risk reduction factors beyond the existing ventilation and IAQ standard. The IAQ strategies including HVAC system outdoor air supply, central air filtration, room air distribution, space partitioning, in-room filtration/disinfection devices, and personal protection equipment (PPE) are evaluated individually and in combination. Several integrated mitigation strategies are recommended and classified based on their relative cost and effort of implementation.



2:30pm - 2:45pm

Numerical Model for Prediction of Indoor COVID-19 Infection Risk Based on Sensor Data

Janis Virbulis, Maija Sjomkane, Maksims Surovovs, Andris Jakovics

University of Latvia, Latvia

In addition to infection with SARS-CoV-2 via direct droplet transmission or contact with contaminated surfaces, infection via aerosol transport is also an important pathway in indoor environments.

The developed numerical model evaluates the risk of a COVID-19 infection in a particular room based on the measurements of temperature, humidity, CO2 and particle concentration, the number of people and instances of speech, coughs and sneezing using a dedicated low-cost sensor system [1]. The model can dynamically output this information back to the measurement system or the building management system.

The model is integral and considers the mean values of simulated variables. However, the concentration of droplets and aerosol particles has an inhomogeneous vertical distribution. Droplets of mucus expelled by a potentially infectious person at a certain height through breathing, speech, coughing, and sneezing are characterized by the total amount of expelled liquid, droplet size distribution and virus particle (virion) concentration. Droplet evaporation rate depends on temperature and the relative humidity. Droplets are redistributed within the room vertically by turbulent diffusion and gravitational force. If the final droplet diameter is < 5 μm, these particles are assumed airborne and can leave the room only through ventilation or sedimentation on surfaces via Brownian diffusion. As a person in the room inhales the droplets and aerosols, the risk of infection increases as the number of absorbed virions grows, e.g. the probability of infection is 50% when 300 virions have been absorbed.

The parameter studies using the model show that infection risk increases for lower temperature, humidity and ventilation intensity. The cough but especially the sneezing events strongly increase the probability of infection in the room, therefore the recognition of these events is very important for the applied measurement system.

[1] Telicko et al., submitted to IBPC2021



2:45pm - 3:00pm

Digital twins of building physics experimental laboratory setups for effective E-learning during pandemic lockdown

Hicham Johra, Ekaterina Aleksandrova Petrova, Lasse Rohde, Michal Zbigniew Pomianowski

Aalborg University, Department of the Built Environment, Denmark

Hands-on experimental workshops in laboratories are a fundamental and effective educational tool to teach technical sciences, building physics and building thermodynamics in particular. However, laboratories are expensive resources that are not always available to students. Moreover, creating specific experimental setups for teaching purposes only can be very time and resource consuming. Besides, restrictions due to the ongoing Covid-19 pandemic make it difficult to gather students in face-to-face laboratory workshops. In that context, digitalizing experimental setups (or parts thereof) provides a very attractive teaching option. Digital twins of experimental laboratory setups can be used in case of facilities lockdown, but also for remote E-learning activities, or when the laboratories are used for higher-priority purposes. Digital twins are not meant to replace real-world physical experiments but should enable flexible teaching at a lower cost. They complement traditional experimental setups and can serve as virtual extensions of these, allowing for larger and more complex study cases for students.

E-learning has recently gained popularity, and many educational institutions have set online live lectures and provide open-access videos of entire courses. However, digitalization of practical exercises for engineering studies faces obvious challenges. The digitalization project presented here aims to establish a series of digital twins of various experimental setups for university teaching on topics such as; building physics, energy in buildings; indoor environment; and HVAC systems. This article presents the development of the first digital twin of this series. The setup is specifically designed for teaching the balancing of a hydronic heating system. The students have to adjust balancing valves to ensure optimum operation in all hydronic radiators of a building with minimum pumping work. The dynamic numerical model and the graphical user interface of this digital twin have been developed with the LabVIEW programming environment.



 
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