Application of Data-Driven Building Information Modeling in the Visual Simulation of Disease Transmission and Route with Pipeline System

Chen Yu Pan, Hsieh Chih Hsu, Ko Wei Huang, Ya Hua Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Currently, preventing epidemics is an extremely critical global topic. Using present data to quickly conduct virus simulations is a difficult but interesting problem, especially when real situations are difficult to experimentally demonstrate. In the past, most studies have used package software for disease transmission simulation, but this approach is limited by availability and software cost. Therefore, we propose a visual simulation of disease transmission using building information modeling data and a 3D model using Unity. The results show that the proposed method can effectively predict the probability and route of disease transmission; it also verifies that the vertical pipeline on the floor plane is conducive to the spread of the virus (90%), and disease transmission on the plane gradually expands outward from the starting room and has a higher probability of spreading (80%) from the opposite room. In addition, a vertical pipeline was simulated using a toilet exhaust air ventilation pipeline, from which it can be observed that the adjacent floors have a higher diffusion probability (70%). It has also been confirmed that distance is the primary factor affecting disease transmission. This framework may provide designers and managers further protection against the spread of future epidemics.

Original languageEnglish
Article number7068735
JournalIndoor Air
Volume2023
DOIs
Publication statusPublished - 2023

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Building and Construction
  • Public Health, Environmental and Occupational Health

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