PhD Oral Exam - Ali Asghar Sedighi, Civil Engineering

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Advancing Airborne Infection Risk Assessment in Indoor Environments: A CFD-Based Framework Integrating Exposure Modeling, Quanta Distribution, and Ventilation Control Abstract: Airborne infection transmission and the dispersion of pathogen-laden aerosols in buildings are complex phenomena affected by several uncertain parameters, including the number of infectious individuals, their locations, and their pathogen emission rates. In buildings with multiple zones and floors, variations in these parameters can create distinct aerosol dispersion patterns and strongly influence interzonal pathogen transport. However, in real buildings, especially during the design and operation of HVAC systems, these parameters are generally unknown. A key limitation of existing infection-risk assessment approaches, including CFD-based studies, is that the number and position of infectious sources usually need to be predefined as fixed boundary conditions. This thesis addresses this limitation by improving the CFD-based infection risk assessment approach to account for uncertainty in the number and location of infectious sources. The proposed framework enables infection transmission risk to be estimated without requiring fixed infectious-source boundary conditions in advance. It also clarifies the distinction between individual infection risk, which is related to the exposure of a specific person at a specific location, and population infection risk, which is related to the probability of infection occurrence within a group of occupants. In addition, this thesis incorporates uncertainty in pathogen emission by proposing a distribution-based representation of the quanta generation rate, while revisiting the concept of a quantum as the smallest unit associated with airborne infection transmission. Finally, based on the proposed risk-estimation framework, this thesis develops a strategy for controlling airborne infection transmission risk in indoor environments.