用CFD模拟和遗传算法优化管道腐蚀传感器放置在油水双相流中
Shuomang Shi1, Baiyu Jiang2, Simone Ludwig3
1Department of Civil, Construction, and Environmental Engineering, North Dakota State University, Fargo, ND 58105, USA.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
本研究介绍了一种混合计算流体动力学 (CFD) 和遗传算法 (GA) 模型,以优化传感器放置以检测内部管道腐蚀. 该方法通过有效识别高风险区域来提高安全性.
科学领域:
- 工程 工程师 工程师 工程师
- 材料科学 材料科学 材料科学
- 计算科学 计算科学
背景情况:
- 内部腐蚀对管道安全构成重大风险,需要有效的结构健康监测 (SHM).
- 目前的方法通常需要广泛的传感器部署来覆盖易受高腐蚀率影响的区域.
- 优化传感器放置对于具有成本效益和全面的腐蚀检测至关重要.
研究的目的:
- 开发和验证混合建模策略,以优化管道中的传感器放置,用于内部腐蚀监测.
- 集成计算流体动力学 (CFD) 用于流动模拟和遗传算法 (GA) 用于优化.
- 提高管道行业腐蚀检测系统的效率和准确性.
主要方法:
- 这是一种混合方法,结合了CFD来模拟油水双相流和GA来进行全球搜索优化.
- 基于CFD的腐蚀率预测,根据实验数据进行验证.
- 整合传感效率和传感器覆盖成本的适应性标准的GA优化.
主要成果:
- 混合战略在管道配件中检测腐蚀的传感器放置方面表现出高精度.
- 对U形,向上倾斜和向下倾斜管道的案例研究显示,最佳适应性值分别为0.9415,0.9064和0.9183.
- 该模型有效地平衡了传感能力与传感器部署的经济考虑.
结论:
- 混合CFD-GA建模策略为管道腐蚀监测中的实际传感器布局设计提供了一个有希望的工具.
- 这种方法可以显著提高输送和收集管道结构健康监测的安全性和效率.
- 经过验证的方法为工业应用中先进的传感器放置优化提供了基础.
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