| 基于仿真数据驱动的激光钻进气体喷嘴结构优化 |
| 投稿时间：2023-12-01 修订日期：2024-02-05 点此下载全文 |
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| 基金项目:高功率光纤激光钻进长距离定向穿越导向孔成孔机理研究、煤层气水平孔激光智能定向钻进工艺及煤岩破碎理化作用机理研究 |
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| 中文摘要:激光钻进采用气体作为循环介质进行清孔，合理的气体流动特性是高效清孔的保障，气体喷嘴是影响气体流动特性的直接因素，其结构设计不合理会严重影响激光钻进的效率。针对激光钻进实验平台中的气体喷嘴，构建喷嘴基本型态，对影响气体清孔效率的喷嘴结构尺寸进行分析，制定仿真方案，通过Fluent模拟气体流场，对清孔效果进行分析，采用神经网络分析喷嘴结构及仿真结果，训练神经网络模型，得出最佳清孔效率时的喷嘴结构参数并进行验证，为喷嘴结构设计提供参考。 |
| 中文关键词:激光钻进 流体仿真 神经网络 气体喷嘴 清孔 |
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| Optimization of gas nozzle structure in laser drilling based on simulation data |
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| Abstract:Laser drilling uses gas as circulating medium to clean holes, and reasonable gas flow characteristics are the guarantee of efficient hole cleaning. Gas nozzle is the direct factor affecting gas flow characteristics, and its unreasonable structural design seriously affects the efficiency of laser drilling. Aiming at the gas nozzle in the laser drilling experimental platform, the basic type of the nozzle is constructed, and the nozzle structure size that affects the gas hole cleaning efficiency is analyzed, and the simulation scheme is formulated. The gas flow field is simulated by Fluent, and the hole cleaning effect is analyzed. The nozzle structure and simulation results are analyzed by using neural network, and the neural network model is trained, and the nozzle structure parameters at the best hole cleaning efficiency are obtained and verified, which provides reference for the nozzle structure design. |
| keywords:laser drilling fluid simulation neural network gas nozzle bore cleaning |
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