Numerical Modeling of Cough Aerosol Transmission in an Upward-moving Escalator With Multi-objective Optimization Using the Genetic Algorithm for Covid-19 and Other Airborne Diseases

Escalators have been recommended instead of elevators during the COVID-19 pandemic since it allows transportation for a large number of people without being enclosed in a small indoor space. Escalators have a tremendous capacity to move large numbers of people and are commonly used in various public facilities such as shopping centers, supermarkets, airports, and subways. This current study focused on investigating the transmission of cough droplets from an infected source person traveling on an Upward Moving Escalator (UME) using the ANSYS FLUENT. The Eulerian-Lagrangian method combined with two-way coupling was used to numerically obtain the aerosol transport, spatial distribution, and deposition information in the UME. The effect of UME operational speed and Relative Humidity (RH) was also investigated through multiphase flow. Finally, multi-objective optimization was performed using a Genetic Algorithm (GA). The investigation revealed that the hand railings were one of the most susceptible contaminated surfaces to the expelled respiratory droplets. The cough droplets expelled from the mouth entered the recirculation zones via the upper portion of the shoulder and wake zone behind the torso. The droplets contaminated the lower portion of the human body at lower operational speed if another passenger stood two steps behind the infected person. Higher operational speeds and lower RH demonstrated higher penetration lengths. The optimization indicated higher operational speed and lower RH to maintain lower concentration with higher penetration length.