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A platform for research: civil engineering, architecture and urbanism
A Stochastic Interpolation-Based Fractal Model for Vulnerability Diagnosis of Water Supply Networks Against Seismic Hazards
Historical seismic events show that water supply networks are increasingly vulnerable to seismic damage, especially in a violent earthquake, which leads to an unprecedented level of risk. Evaluation of vulnerability to seismic hazards can be considered as one of the first steps of risk management and mitigation. This paper presents a stochastic interpolation-based fractal model for assessing the physical vulnerability of urban water supply pipelines. Firstly, based on the formation mechanism of natural disaster risk and the concept of seismic vulnerability, the most representative factors were selected as the vulnerability evaluation indices, and the classification criterion of each index was teased out according to the earthquake damage investigations and researches on the aseismatic behavior of water supply pipelines. Secondly, considering the randomness of vulnerability to earthquake hazards, the test data set was produced by way of stochastic interpolation according to the uniform distribution, on the basis of the classification criterion. The fractal dimensions of all of the indices were calculated based on the test data set. The fractal interpolation diagnosis function for identifying the vulnerability levels of pipelines to earthquake disasters was established. Finally, the application of the proposed model to a real water supply network and its comparative analysis showed that the water supply network was basically in a medium vulnerability level. Through the case study verification, we could find that the model was theoretically and practically feasible. This study helps to gain a better understanding of the extents of potential vulnerability levels of water supply pipelines. It can provide technical support for disaster prevention plans of urban water supply networks.
A Stochastic Interpolation-Based Fractal Model for Vulnerability Diagnosis of Water Supply Networks Against Seismic Hazards
Historical seismic events show that water supply networks are increasingly vulnerable to seismic damage, especially in a violent earthquake, which leads to an unprecedented level of risk. Evaluation of vulnerability to seismic hazards can be considered as one of the first steps of risk management and mitigation. This paper presents a stochastic interpolation-based fractal model for assessing the physical vulnerability of urban water supply pipelines. Firstly, based on the formation mechanism of natural disaster risk and the concept of seismic vulnerability, the most representative factors were selected as the vulnerability evaluation indices, and the classification criterion of each index was teased out according to the earthquake damage investigations and researches on the aseismatic behavior of water supply pipelines. Secondly, considering the randomness of vulnerability to earthquake hazards, the test data set was produced by way of stochastic interpolation according to the uniform distribution, on the basis of the classification criterion. The fractal dimensions of all of the indices were calculated based on the test data set. The fractal interpolation diagnosis function for identifying the vulnerability levels of pipelines to earthquake disasters was established. Finally, the application of the proposed model to a real water supply network and its comparative analysis showed that the water supply network was basically in a medium vulnerability level. Through the case study verification, we could find that the model was theoretically and practically feasible. This study helps to gain a better understanding of the extents of potential vulnerability levels of water supply pipelines. It can provide technical support for disaster prevention plans of urban water supply networks.
A Stochastic Interpolation-Based Fractal Model for Vulnerability Diagnosis of Water Supply Networks Against Seismic Hazards
Chaofeng Liu (author) / Yawei Li (author) / He Yin (author) / Jiaxin Zhang (author) / Wei Wang (author)
2020
Article (Journal)
Electronic Resource
Unknown
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