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基于云理論的油氣管道滑坡危險性綜合評價

Comprehensive evaluation of landslide risks of oil and gas pipelines based on cloud theory

  • 摘要: 管道滑坡危險性評價是長輸油氣管道沿線滑坡災害預防和治理中規劃決策的重要依據.該評價組織由定量和定性兩類指標構成,評價系統具有隨機性和模糊性的特點.針對常用的定性和半定量評價法在處理系統的隨機性和模糊性上存在顧此失彼和人為主觀性強的問題,引入能同時有效反映事物隨機性和模糊性的云理論,運用黃金分割率法構建5級標度的管道滑坡危險性狀態標尺云和指標重要性權重云,提出定量指標的不確定性推理過程和定性指標專家群語言云轉化的浮動云偏好集結算法,構建了油氣管道滑坡危險性的綜合評價模型并進行了工程例證分析.4處待評樣本的綜合評價結果與半定量法結果基本一致,并與實際相符.該模型軟化了指標邊界的硬劃分,簡化了指標數據的預處理;實現了評價的定量與定性融合和集成決策;提高了結果的精確性、合理性和可視化.

     

    Abstract: Landslides are serious geological hazards along long-distance oil and gas pipelines. Especially common are discontinuous-developing single landslides. A single landslide hazard can cause anything from pipeline rupture and fracture to complete failure and shutdown, thus triggering serious secondary disasters. Risk assessments of oil-and-gas-pipeline landslides are an effective method for ascertaining the degree of landslide risk and can provide an important scientific basis for planning and decision-making regarding landslide prevention and control along long-distance oil and gas pipelines. In addition, risk assessments represent an important step in the pipeline-integrity management process. The evaluation system consists of both quantitative and qualitative indexes, which are characterized by randomness and fuzziness. To address the subjectivity and incompleteness of qualitative and semi-quantitative evaluation methods in the processing of randomness and fuzziness, the cloud theory was introduced, which can simultaneously reflect randomness and fuzziness. The golden section method was used to establish a five-level standard cloud metric for pipeline landslide risk and index weighting. In the cloud transformation process, this paper proposes uncertainty reasoning for the quantitative index and a floating cloud preference algorithm for expert group language as a qualitative index, which comprises the assessment model for landslide risk of oil and gas pipelines. The comprehensive evaluation results indicate that the floating cloud preference algorithm for the qualitative index is more suitable for the language of expert group decision-making than the synthetic cloud algorithm commonly used. In addition, the results of the four pipeline-landslide-risk evaluations are basically consistent with the results of the semi-quantitative method, which is consistent with the actual situation. This method softens the hard divisions between the inner boundaries of the index and simplifies the preprocessing of index data. It fuses the qualitative and quantitative evaluation aspects using composite decision-making and improves the accuracy, rationality, and visualization of the results.

     

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