ABSTRACT

In low-to-moderate seismicity regions, seismic loss functions (SLFs) are barely established due to limited observational data, making it difficult to derive decision-making on disaster prevention and management. Herein, a Bayesian framework is developed to update the SLFs with limited observational data. The proposed point-based Bayesian method updates local probability density function parameters for damage ratios at each seismic intensity, which helps to avoid an unrealistic underestimation of damage ratios in the low-to-moderate range of seismic intensities. The feasibility of the developed framework in a low-to-moderate seismicity region is verified by the comparison between the updated SLF and post-event data.

摘要

在中低地震活动区，由于观测数据有限，地震损失函数（SLFs）几乎没有建立，这使得防灾管理决策难以推导出来。在此，开发了贝叶斯框架以使用有限的观测数据更新 SLF。所提出的基于点的贝叶斯方法更新了每个地震烈度下损伤率的局部概率密度函数参数，这有助于避免在低到中等地震烈度范围内不切实际地低估损伤率。通过更新的 SLF 和事后数据之间的比较，验证了所开发框架在中低地震活动区的可行性。