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Characterization of onset of dynamic stall for low Mach number flows

低马赫数流动态失速开始的表征

基本信息

批准号：
1935255
负责人：
Anupam Sharma
金额：
$ 37.26万
依托单位：
Iowa State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935255&HistoricalAwards=false
关键词：
Characterization onset dynamic stall low

项目摘要

Dynamic stall is a common occurrence in maneuvering aerodynamic bodies (e.g., insect/bird wings, helicopter/wind turbine blades, aircraft wings) which is characterized by large increases in unsteady aerodynamic loads. Such loads can lead to catastrophic and fatigue failure of aircraft wings and rotor blades in helicopters and wind turbines. The flow physics affecting the onset of dynamic stall remains unclear and is highly dependent on a large parameter space consisting of geometry, type of maneuver, pitch rate, and Reynolds and Mach numbers. The project will utilize a combination of novel data analysis techniques with high fidelity simulations to understand dynamic stall onset. A clear understanding and characterization of stall onset will pave the way for effective strategies to control and mitigate dynamic stall. The project has transformative implications for a broad range of applications including fixed-wing aircraft and rotating machinery. In addition, broader impacts are expected through curricular enhancements and recruiting women and underrepresented minorities.The goal of this project is to understand and characterize the onset of dynamic stall using efficient fluid simulations with data-driven analysis methods and experimental validation. The specific objectives are: (1) identify a universal parameter/marker of stall onset through characterization of stall incipience using a suite of physics-based, data-driven, and machine learning approaches, (2) use novel simulation strategies to effectively explore the large parameter space by employing a novel 4-D, space-time framework to remove transients and significantly reduce computation time and by efficiently exploring the parameter space using an adaptive, asynchronous, Bayesian sampling strategy, and 3) validate the universal parameter using experimental data and additional simulations, and investigate the role of acoustic radiation on stall onset. The proposed work consists of intellectual advances in identifying the underlying physical phenomenon that triggers dynamic stall onset, developing an innovative approach to efficiently remove flow transients, and investigating the effect of acoustics on laminar separation bubble dynamics. The project will leverage outreach and workforce development activities ongoing at Iowa State University.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

动态失速在操纵空气动力学物体中很常见（例如，昆虫/鸟类翅膀、直升机/风力涡轮机叶片、飞行器机翼），其特征在于非定常空气动力学载荷的大幅增加。这样的载荷可导致直升机和风力涡轮机中的飞行器机翼和转子叶片的灾难性和疲劳失效。影响动态失速起始的流动物理学仍然不清楚，并且高度依赖于由几何形状、机动类型、俯仰速率、雷诺数和马赫数组成的大参数空间。该项目将利用新的数据分析技术与高保真模拟相结合，以了解动态失速的发生。对失速起始的清楚理解和表征将为控制和减轻动态失速的有效策略铺平道路。该项目对包括固定翼飞机和旋转机械在内的广泛应用具有变革性影响。此外，通过课程的改进和招募妇女和代表性不足的少数民族，预计将产生更广泛的影响。该项目的目标是利用数据驱动的分析方法和实验验证的有效流体模拟来理解和描述动态失速的发生。具体目标是：（1）通过使用一套基于物理学的、数据驱动的和机器学习方法表征失速起始来识别失速起始的通用参数/标记，（2）通过采用新颖的4-D、空间-时间框架来移除瞬态并显著减少计算时间，并通过使用自适应、异步、贝叶斯抽样策略; 3）使用实验数据和额外的模拟来验证通用参数，并研究声辐射对失速开始的作用。拟议的工作包括知识的进步，确定潜在的物理现象，触发动态失速发作，开发一种创新的方法，以有效地消除流动瞬变，并调查声学层流分离气泡动力学的影响。该项目将利用爱荷华州州立大学正在进行的外展和劳动力发展活动。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models

DOI：
10.1109/mlhpcai4s51975.2020.00013
发表时间：
2020-07
期刊：
2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S)
影响因子：
0
作者：
Sergio Botelho;Ameya Joshi;Biswajit Khara;S. Sarkar;C. Hegde;Santi S. Adavani;B. Ganapathysubramanian
通讯作者：
Sergio Botelho;Ameya Joshi;Biswajit Khara;S. Sarkar;C. Hegde;Santi S. Adavani;B. Ganapathysubramanian

Evaluating Dynamic Stall-Onset Criteria for Mixed and Trailing-Edge Stall

评估混合和后缘失速的动态失速开始标准