Quantitative Accident Risk Estimation for Infrastructure Facilities Based on Accident Case Analysis
Author(s): |
Jeongung Lee
Jaewook Jeong |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 24 April 2024, n. 5, v. 14 |
Page(s): | 1283 |
DOI: | 10.3390/buildings14051283 |
Abstract: |
The construction industry records higher accident rates than other industries, and thus, risk estimation is necessary to manage accident rates. Risk levels differ based on facility type and construction project size. In this sense, this study aims to calculate the quantitative accident risk level according to the construction project size per infrastructure facility type. To this end, the following five-step risk estimation was performed: (1) data collection and classification; (2) calculation of fatality rate based on construction cost; (3) calculation of fatal construction probability by construction cost classification; (4) reclassification of construction cost considering fatal construction probability; and (5) calculation of risk level by facility type and construction cost classification. As a result, the fatality rate per facility type was the highest in ‘Dam’ at 0.01024 (person/USD million). Additionally, the risk level according to the construction project size per facility type was the highest for ‘Dam’ (0.00403 person/USD million) for a construction of less than USD 0.77 million. The risk level presented in this study can be utilized as basic data in the design stage for safety management. Our results also indicate the necessity of preparing a separate construction cost classification for safety management. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
1.25 MB
- About this
data sheet - Reference-ID
10787930 - Published on:
20/06/2024 - Last updated on:
20/06/2024