基于场景缩减法的供水管网抗震可靠性评估∗
Seismic Reliability Assessment of Water Supply Pipeline Networks Based on Scenario Reduction Method
- 防灾减灾工程学报 2023年43卷第2期 页码：286-293
- 作者机构：
昆明理工大学建筑工程学院,云南,昆明,650000
- 作者简介：
- 基金信息：国家自然科学基金项目(52260011)、云南省重点研发计划项目(202203AC100004)、云南省重点研发计划项目(202003AC100001)资助
DOI：
中图分类号： TU443-
纸质出版：2023
- 稿件说明：
移动端阅览
贾睿. 基于场景缩减法的供水管网抗震可靠性评估∗[J]. 防灾减灾工程学报, 2023,43(2):286-293.
贾睿,杜坤,宋志刚.基于场景缩减法的供水管网抗震可靠性评估∗[J].防灾减灾工程学报,2023,43(2):286-293
摘要
供水管网抗震可靠性是在可能地的震烈度下管网的服务水平，目前大多数采用蒙特卡洛模拟产生数量庞大的震损样本进行估计，此方法给大型复杂管网抗震可靠性的评估带来极大工作量和超高时间成本。为了克服这些问题，提出了多爆管压降计算模型，并引入场景缩减方法以提高计算效率。首先，利用多爆管压降模型计算震损场景下节点水压。其次，利用系统聚类中类平均法对震损节点水压进行场景合并和分类。然后利用 k‐medoids 聚类对每一类选取中心点作为典型场景。最后，通过典型场景确定节点和系统可靠性指数。将某实际管网应用所提算法计算并与传统蒙特卡洛模拟结果进行对比。结果表明，基于线性估计多爆管压降模型是合理的，基于场景缩减法的可靠性评估是可行的，提高典型场景数量可降低评估误差。因此，该算法可在保证结果准确的同时提高计算效率。
Abstract
The seismic reliability of a water supply network is the service level of the network underpossible seismic intensities， which is mostly estimated using Monte Carlo simulations to generate alarge number of seismic damage samples， and this method will bring great workload and ultra-hightime cost for seismic reliability assessment of large and complex networks. In order to overcome theseproblems， not only a multi-burst pipe pressure drop calculation model is proposed， but also a scenarioreduction method is introduced to improve the calculation efficiency. Firstly， the multi-burst pipe pressure drop model is used to calculate the nodal water pressure under the seismic damage scenario. Secondly， the scenario merging and classification of nodal water pressure in seismic damage is performedusing the cluster averaging method in system clustering. Then， k-medoids clustering is used to selectthe center point of each cluster as a typical scenario. Finally， the node reliability index and system reliability index are determined by the typical scenarios. The proposed algorithm is applied to a practical pipe network and compared with the results of traditional Monte Carlo simulation. The results showthat the multi-burst pipe pressure drop model based on linear estimation is reasonable； the reliability assessment based on the scenario reduction method is feasible； and increasing the number of typical scenarios can reduce the assessment error. Therefore， the proposed algorithm can ensure the accuracyof the results while improving the computational efficiency.
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