TY - GEN
T1 - Risk-based life-cycle loss assessment using statistical moments
AU - Zhang, Y.
AU - Li, Y.
N1 - Publisher Copyright:
© 2023 The Author(s).
PY - 2023
Y1 - 2023
N2 - Evaluating the economic loss of civil infrastructure subjected to hazards can be significant for life-cycle risk assessment. In the past, the expected value of loss has been widely investigated during risk assessment and employed as a standard decision-making criterion. However, the inherent uncertainties may be neglected when focusing on the mean value. Hence, other statistical moments, especially the higher-order moments, and the probability density function of the long-term loss should be considered. In this paper, a probabilistic analysis framework is proposed for risk quantification to compute the probability density function of the long-term loss using statistical moments. By using the first-four statistical moments of the long-term loss, the maximum entropy method can construct the probability density function of the long-term loss effectively and accurately. The proposed method can enhance the computation efficiency during risk assessment and benefit the decision-making process.
AB - Evaluating the economic loss of civil infrastructure subjected to hazards can be significant for life-cycle risk assessment. In the past, the expected value of loss has been widely investigated during risk assessment and employed as a standard decision-making criterion. However, the inherent uncertainties may be neglected when focusing on the mean value. Hence, other statistical moments, especially the higher-order moments, and the probability density function of the long-term loss should be considered. In this paper, a probabilistic analysis framework is proposed for risk quantification to compute the probability density function of the long-term loss using statistical moments. By using the first-four statistical moments of the long-term loss, the maximum entropy method can construct the probability density function of the long-term loss effectively and accurately. The proposed method can enhance the computation efficiency during risk assessment and benefit the decision-making process.
UR - http://www.scopus.com/inward/record.url?scp=85186706643&partnerID=8YFLogxK
U2 - 10.1201/9781003323020-240
DO - 10.1201/9781003323020-240
M3 - Conference contribution
AN - SCOPUS:85186706643
SN - 9781003323020
T3 - Life-Cycle of Structures and Infrastructure Systems - Proceedings of the 8th International Symposium on Life-Cycle Civil Engineering, IALCCE 2023
SP - 1961
EP - 1966
BT - Life-Cycle of Structures and Infrastructure Systems - Proceedings of the 8th International Symposium on Life-Cycle Civil Engineering, IALCCE 2023
A2 - Biondini, Fabio
A2 - Frangopol, Dan M.
T2 - 8th International Symposium on Life-Cycle Civil Engineering, IALCCE 2023
Y2 - 2 July 2023 through 6 July 2023
ER -