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Lessons learned from Use of Large-Scale Particle Image Velocimetry in Shallow-Low-velocity Flows and Floods

机译:从浅低速流动和洪水中使用大规模粒子图像速度测量的经验教训

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Large-Scale Particle Image Velocimetry (LSPIV) has been developed for more than a decade for a variety of laboratory and filed situations. The technique has been tested against conventional instrument and proved to be within acceptable uncertainty range (about 5%). The most distinctive feature of LSPIV compared with the conventional velocimeters, however, is its non-intrusive characteristics. This feature allows to carry out velocity measurements under extreme flow conditions which presents many difficulties for conventional instruments. During the more than a decade use of LSPIV, the researchers has gathered useful information for further perfecting LSPIV as well as practical lessons with respect to LSPIV use in various measurement environments and situations. This paper summarizes some of these LSPIV implementation aspects. Specifically, lessons learned on the seeding in natural streams and the areas of applications where LSPIV can efficiently complement or exceed the capabilities of the conventional velocity and discharge estimation techniques and instruments are presented.
机译:对于各种实验室和提交的情况,已经开发了大规模的粒子图像Velocimetry(LSPIV)超过十年。该技术已经针对常规仪器进行了测试,并被证明是可接受的不确定性范围(约5%)。然而,与传统速度计相比,LPIV的最独特特征是其非侵入式特性。该特征允许在极端流动条件下进行速度测量,这对传统仪器具有许多困难。在十多年的LSPIV使用期间,研究人员已经收集了有用的信息,以便在各种测量环境和情况下进一步完善LPIV以及实际课程。本文总结了一些LPPIV实现方面。具体而言,在自然流中的播种中学习的经验教训以及LSPIV可以有效地补充或超过传统速度和放电估计技术和仪器的能力的应用领域。

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