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基于物理过程的山地原油泄漏模拟方法

Crude Oil Leakage Simulation Method Based on Physical Processes

  • 摘要: 山地输油管道泄漏事故发生后, 模拟计算污染扩散范围对应急抢险方案的制定具有重要意义. 针对现有的山区原油泄漏模拟方法无法呈现符合物理过程的泄漏油品扩散效果以及模拟速度过慢的问题, 提出基于物理过程的山地原油泄漏模拟方法. 首先基于空间语义约束构建一种融合 Fay 流体扩散算法和光滑粒子流体动力学(SPH)的计算模型 Fay-SPH; 然后设计一个基于 Fay 约束的连续卷积网络 FayNet 来加速模拟, 通过轻量级注意力模块和三重注意力模块增强网络提取粒子特征信息能力; 最后融合位置损失和速度损失来保证模拟结果细节的一致性. 在自行采集的油气管线所处山区数据上, 基于不同地貌和不同地形进行实验的结果表明, 所提方法实现了原油泄漏的高效模拟.

     

    Abstract: After the mountain oil pipeline leakage accident occurs, the simulation of the pollution spread range is of great significance in the designation of emergency rescue plans. Aiming at the existing crude oil leakage simulation methods cannot reflect the crude oil diffusion effect with the physical process and the speed of simulation is too slow, a leakage simulation method combined with the oil surface diffusion Fay model is investigated. Firstly, we propose a calculation model Fay-SPH combined with the smoothed particle hydrodynamics (SPH) method and the Fay fluid diffusion equation based on spatial interaction semantic constraints. Secondly, in order to make the simulation results quickly presented, a Fay-constrained continuous convolutional network FayNet is designed to speed up the simulation, and a lightweight attention module FGAB and a triple attention module FTAB are proposed to enhance the network's ability to extract particle feature information. Finally, the position loss and velocity loss are fused to ensure the consistency of the simulation results in detail. Based on different landform types and different topography, the results of simulation experiment on the mountain area data of the oil pipelines collected by us show that our methods can implement the efficient simulation of crude oil leakage.

     

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