Risk assessment of washout by slope flow along long-distance-pipeline based on quantitative index cloud reasoning-integrated weighting

• Main Authors: Zhang Manyin, Sun Zhizhong, Xie Rong, Ka Maocuo, Wang Shengxin
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: E3S Web of Conferences
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/24/e3sconf_caes2021_03059.pdf

The washout by slope flow along long-distance oil & gas pipelines is a common geological hazard that occurs when pipelines pass through the alluvial-proluvial fan section of mountain piedmont. Accurate and effective evaluation of the risk of single washout by slope flow is an important basis for disaster prevention and control decisions. According to the characteristics of the lack of basic research data in the development area of washout by slope flow, the complexity of the risk assessment structure and the strong randomness and ambiguity of the multi-index system, on the basis of rapid acquisition of initial data of indicators through field survey, simple experiment and sampling analysis, a quantitative index cloud reasoning risk evaluation model for slope flow washout of pipeline was established by introducing single-condition and single-rule cloud reasoning with summation integration weighting algorithm, and carry out instance verification. The evaluation results of 11 samples showed medium and relatively high risks, and the overall distribution trend is relatively concentrated. Compared with the results obtained by the entropy weight-extension method and the standard recommendation method, the proposed method is more in line with the small-scale disaster background analysis and the reality of the study area, and it’s also more beneficial to ensure the safe operation of pipelines. In this method, the obtainment of the source data is reliable, objective, and the preprocessing is simplified, the index weighting and classification are more reasonable, and the evaluation process takes into consideration of both the randomness and ambiguity of the system, which improves the accuracy and effectiveness of the evaluation results. It also provides a new way of thinking to other related research.