Seismic resilient three-stage enhancement for gas distribution network using computational optimization algorithms

A computer-simulation-based three-stage optimization strategy is proposed for the resilience enhancement of urban gas distribution networks (GDNs). In stage I (pre-earthquake stage), the Fixed Proportion and Direct Comparison Genetic Algorithm (FPDC-GA) is applied to select key pipelines need to be...

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Vydáno v:Soil dynamics and earthquake engineering (1984) Ročník 152; s. 107057
Hlavní autoři: Zong, Chengcai, Ji, Kun, Wen, Ruizhi, Bi, Xirong, Ren, Yefei, Zhang, Xiaorui
Médium: Journal Article
Jazyk:angličtina
Vydáno: Barking Elsevier Ltd 01.01.2022
Elsevier BV
Témata:
Algorithms
Computational optimization algorithms
Computer applications
Earthquake resistance
Earthquakes
Enhancement
Exponential functions
Funding
Gas distribution network
Gas pipelines
Genetic algorithms
Greedy algorithms
Nearest-neighbor
Optimization
Optimization algorithms
Performance function
Pipelines
Pressure
Repair
Resilience
Seismic activity
Seismic resilience
Seismic resilience
Gas distribution network
Enhancement
Performance function
Computational optimization algorithms
ISSN:0267-7261, 1879-341X
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Shrnutí:A computer-simulation-based three-stage optimization strategy is proposed for the resilience enhancement of urban gas distribution networks (GDNs). In stage I (pre-earthquake stage), the Fixed Proportion and Direct Comparison Genetic Algorithm (FPDC-GA) is applied to select key pipelines need to be strenthened or replaced under limited funding in preparation for future potential earthquakes. In stage II (post-earthquake stage), pressure tests must be carried out according to the gas leakage situation reported by users or detected by devices. The Multi-Label K-Nearest-Neighbor (ML-KNN) algorithm is used to predict the corresponding failed pipelines and optimize the pipeline pressure test order. In stage III (repair stage), a strategy based on a greedy algorithm is applied to optimize the pipeline repair sequence. The proposed methods were applied to the GDN of a city in northern China. The following conclusions were drawn from the results: (1) The FPDC-GA enhanced the robustness and resourcefulness of the GDN system to the maximum level within the available funding budget. (2) The pipeline pressure test order calculated using the ML-KNN algorithm was significantly improved compared with a random pressure test order or one based on the empirical failure probability of pipelines. (3) After optimization using a greedy algorithm, the performance recovery curves under different earthquake conditions were shaped as an exponential function, which indicates that the performance of the GDNs recovered in the most efficient manner. The findings of this study could be useful as tools for the seismic resilience enhancement of GDNs in different stages. The proposed optimization algorithms can also be extended to the lifeline of other networks. •Gas supply capacity and social influence measurement of gas distribution networks (GDNs).•Three-stage seismic resilience enhancement using computational optimization algorithms.•Seismic resilience enhancement for real GDN system in northern China.
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ISSN:0267-7261
1879-341X
DOI:10.1016/j.soildyn.2021.107057