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Creating new capabilities of existing experimental techniques (UVP, PIV) by using CFD and AI

使用 CFD 和 AI 创造现有实验技术（UVP、PIV）的新功能

基本信息

批准号：
20J10276
负责人：
ティワリニトゥ
金额：
$ 1.34万
依托单位：
Tohoku University
依托单位国家：
日本
项目类别：
Grant-in-Aid for JSPS Fellows
财政年份：
2020
资助国家：
日本
起止时间：
2020-04-24 至 2022-03-31
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20J10276/
关键词：
Pressure estimation Shear-thinning fluid Pressure sensitive paint Sensor selection method Flow over cylinder UVP PIV Data driven method Pressure measurement Non- Newtonian fluid Data driven stochastic estimation sensor selection

项目摘要

The overall goal of my project was to improve the experimental tools using data driven methods which I achieved successfully. The project had two parts: first part was to develop technology for pressure field measurement in fluid flows which was not possible by traditional techniques. This part of the project specifically focused on pressure field estimation in opaque Newtonian and non-Newtonian fluids based on UVP (Ultrasonic velocity profiler) and PIV (Particle image velocimetry) measurements. Three novel techniques were developed for milk and shear-thinning fluid flows behind the circular cylinder. Some of the research outcomes have been published as two articles in international journals in “Experiments in Fluids” and “Flow Measurements and Instrumentation” by reputed publishers Springer and Elsevier. The second part of the project was dedicated to the improvement of the temporal resolution of available high-speed cameras for time-resolved measurements and simultaneous measurement of pressure and temperature on same surface by sensitive paints. Data-driven techniques such as proper orthogonal decomposition and sensor selection method have been utilized for time-resolved measurement in supersonic jet flows. A novel technique has been developed based on sensor selection method for simultaneous measurement of pressure and temperature fields on airfoil. The result of my postdoc work will be published very soon in international Journals. The project also resulted in four international conference presentations.

我的项目的总体目标是使用数据驱动方法改进实验工具，我成功地实现了这一点。该项目分为两部分：第一部分是开发传统技术不可能实现的流体流动压力场测量技术。该项目的这一部分特别关注基于UVP(超声速度剖面仪)和PIV(粒子图像测速仪)测量的不透明牛顿和非牛顿流体中的压力场估计。开发了三种用于牛奶和剪切稀释液在圆柱体后流动的新技术。其中一些研究成果已由著名出版商Springer和Elsevier以两篇论文的形式发表在国际期刊上的《流体实验》和《流量测量和仪器》上。该项目的第二部分致力于提高现有高速相机的时间分辨率，用于时间分辨率测量和通过敏感涂料同时测量同一表面上的压力和温度。数据驱动技术，如适当的正交分解和传感器选择方法，已被用于超音速喷流的时间分辨测量。发展了一种基于传感器选择方法的翼型压力场和温度场同时测量的新技术。我的博士后工作成果很快就会发表在《国际期刊》上。该项目还促成了四次国际会议的介绍。