{"title":"Does Scatter Matter? Improved Understanding of UH-60A Wind Tunnel Rotor Measurements Using Data-Driven Clustering and CREATE-AV Helios","authors":"M. Ramasamy, T. Norman, R. Jain","doi":"10.4050/f-0077-2021-16721","DOIUrl":null,"url":null,"abstract":"\n A data-driven clustering algorithm based on proper orthogonal decomposition was applied to assess the scatter found in the UH-60A wind tunnel airloads measurements. Upon verifying the capability of the algorithm, pushrod loads, blade surface pressure, sectional loads, and torsional moments were analyzed. Spatial eigenmodes resulting from the decomposition provided the optimal basis; projection of the individual cycles on to the high singular value modes allowed visualizing the statistical distribution of data over the entire azimuth. While not all cases showed furcation in the data, bimodal distribution was found in the high thrust cases, where statistically normal distribution is generally assumed. Consequent clustering of the measured cycles produced excellent correlation among clusters found in the pushrod loads, blade surface pressure, and torsional moment that suggest a common source for furcation in the data. The cycles assigned to one group repeatedly showed distinguishable variations from the other group in terms of the presence/absence of a dynamic stall vortex, azimuthal occurrence of stall, chordwise location of separation and reattachment etc. When one of the cluster is smaller in size compared to the other, the conventional phase-average obscured all the intricate features even when the loads are substantially higher than the larger cluster. In general, clustering the data set when warranted showed not only higher peak loads but also lower variance for both the clusters across the entire azimuth compared to the conventional simple phase-average results. Computational simulations were conducted using CREATETM-AV Helios towards understanding the underlying flow field. Misjudged earlier as under/over-predictive when compared with the simple phase-average data, Helios results consistently showed significantly improved correlation with the smaller of the two clusters. Combining the clustered results and the flow visualization provided by Helios, aperiodicity in the spatial location and the strength of both the trim tab vortices and tip vortices have also been hypothesized as potential sources of furcation.\n","PeriodicalId":273020,"journal":{"name":"Proceedings of the Vertical Flight Society 77th Annual Forum","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Vertical Flight Society 77th Annual Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4050/f-0077-2021-16721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A data-driven clustering algorithm based on proper orthogonal decomposition was applied to assess the scatter found in the UH-60A wind tunnel airloads measurements. Upon verifying the capability of the algorithm, pushrod loads, blade surface pressure, sectional loads, and torsional moments were analyzed. Spatial eigenmodes resulting from the decomposition provided the optimal basis; projection of the individual cycles on to the high singular value modes allowed visualizing the statistical distribution of data over the entire azimuth. While not all cases showed furcation in the data, bimodal distribution was found in the high thrust cases, where statistically normal distribution is generally assumed. Consequent clustering of the measured cycles produced excellent correlation among clusters found in the pushrod loads, blade surface pressure, and torsional moment that suggest a common source for furcation in the data. The cycles assigned to one group repeatedly showed distinguishable variations from the other group in terms of the presence/absence of a dynamic stall vortex, azimuthal occurrence of stall, chordwise location of separation and reattachment etc. When one of the cluster is smaller in size compared to the other, the conventional phase-average obscured all the intricate features even when the loads are substantially higher than the larger cluster. In general, clustering the data set when warranted showed not only higher peak loads but also lower variance for both the clusters across the entire azimuth compared to the conventional simple phase-average results. Computational simulations were conducted using CREATETM-AV Helios towards understanding the underlying flow field. Misjudged earlier as under/over-predictive when compared with the simple phase-average data, Helios results consistently showed significantly improved correlation with the smaller of the two clusters. Combining the clustered results and the flow visualization provided by Helios, aperiodicity in the spatial location and the strength of both the trim tab vortices and tip vortices have also been hypothesized as potential sources of furcation.