Cascading Propagation Path of Vinyl Chloride Process Risk Based on Complex Network

Xixi Li

doi:10.54097/cxw6gf62

Authors

Xixi Li

DOI:

https://doi.org/10.54097/cxw6gf62

Keywords:

Cascade fluctuation, Complex network, Fluctuation risk propagation path, Vinyl chloride production.

Abstract

In the production of vinyl chloride, small parameter fluctuations may lead to large-scale cascade fluctuations, causing serious economic losses and casualties, in order to ensure the safety and stability of production, it is necessary to study the cascade fluctuation propagation path of vinyl chloride production process. In this paper, a complex network model of vinyl chloride production process is constructed based on complex network theory, and the concept of comprehensive degree considering network direction is introduced to identify important nodes in the network: secondly, the fluctuation overload propagation probability and material hazard degree of the edge are used to define the fluctuation overload propagation intensity of the edge; finally, according to the fluctuation overload propagation intensity, the risk propagation path of cascading fluctuations under different overload modes is obtained by using ant colony algorithm, it provides a basis for the prevention of cascade overload and the selection and protection of key monitoring nodes.

Downloads

Download data is not yet available.

References

Kaimin Zhang, Libiao Bai, Xiaoyan Xie, et al. “Modeling of risk cascading propagation in project portfolio network,” Physica A: Statistical Mechanics and its Applications, vol. 612, no. 15, pp. 128450, 2023.

Shaohua Wang, Yue Yang, LiyueSun, et al. “Controllability robustness against cascading failure for complex logistic network based on dynamic cascading failure model,” IEEE Access, vol. 8, pp. 127450-127461, 2020.

Yunxia Chen, Yi Jin, Xihui Liang, et al. “Propagation path and failure behavior analysis of cracked gears under different initial angles,” Mechanical Systems and Signal Processing, vol. 110, no. 15, pp. 90-109, 2018.

Xiaojuan Wang, Shize Guo, Lei Jin, et al. “Cascading failures mechanism based on betweenness-degree ratio distribution with different connecting preferences,” International Journal of Modern Physics C, vol. 28, no. 04,pp. 1750052, 2017.

Aleta A., Meloni S., Moreno Y. “A Multilayer perspective for the analysis of urban transportation systems,” Sci. Rep., vol. 7, pp. 44359, 2017.

Arda Halu, Antonio Scala, Abdulaziz Khiyami,et al. “Data-driven modeling of solar-powered urban microgrids,” Sci Adv, vol. 2, no. 1, pp. 15, 2016.

Zhuoyang Wang, Guo Chen, Long Liu, et al. “Cascading risk assessment in power-communication interdependent networks,” Physica A: Statistical Mechanics and its Applications, vol. 540, no. 15,pp. 120496, 2020.

Alireza Yazdani, Paul Jeffrey. “Complex network analysis of water distribution systems,” Chaos, vol. 21, no. 1, pp. 016111, 2011.

Xueming Liu, Enrico Maiorino, Arda Halu, et al. “Robustness and lethality in multilayer biological molecular networks,” Nat Commun, vol. 11, no. 1, pp. 6043, 2020.

Zheng Wang, Yiyi Hu, Ran Dong, et al. “Determination of the risk propagation path of cascading faults in chemical material networks based on complex networks,” The Canadian Journal of Chemical Engineering, vol, 99, no. 1, pp. 540-550, 2021.

Haihua Yang, Shi An. “Critical Nodes Identification in Complex Networks,” Symmetry, vol. 12, no. 01, pp. 126-131, 2020.

Jinqiu Hu, Laibin Zhang, Lin Ma, et al. “An integrated safety prognosis model for complex system based on dynamic Bayesian network and ant colony algorithm,” Expert Systems with Applications, vol. 38no. 03, pp. 1431-1446, 2011.

Jianmin Gao, Guo Li, Zhiyong Gao. “Fault propagation analysis for complex system based on small-world network model,” Annual Reliability and Maintainability Symposium, vol. 21, pp. 359-364, 2008.