La recherche expérimentale en aérodynamique à l’ONERA – L’exemple du buffet transsonique

International audienceThe paper reviews research conducted at ONERA over the last thirty years on the transonic buffet. We first present the transonic buffet phenomenon and we explain its importance for aeronautical applications. Then, a distinction is made between the 2D buffet produced by an airfoil and the 3D buffet that characterizes swept wings of finite span. The 2D buffet amounts to a pure oscillation of the shock phase-locked with the detachment and reattachment of the boundary layer downstream, whereas the 3D buffet takes the form of a pocket of broadband perturbations located in a limitedportion of the wing. We recall that these mechanisms were first studied in the 1980s through a series of tests conducted in the transonic wind tunnel ONERA T2 at Toulouse and in the large transonic wind tunnel ONERA S2Ma at Modane. Since this pioneering work, progress in the measurement techniques has led to the constitution of a comprehensive database of the 2D buffet that we describe. This database, obtained in the wind tunnel ONERA S3Ch at Meudon, has been extensively used to validate various CFD tools, with the latter being used in turn to investigate the buffet physics. We illustrate this collaboration between simulation and physics by recalling that a linear stability analysis of accurate Reynolds-Averaged-Navier-Stokes (RANS) solutions made it possible to prove that the buffet on a 2D airfoil stems from a global instability mechanism.We also review more recent tests done in the case of a laminar airfoil, which reveal very distinct behaviors of the buffet flow. This illustrates how sensitive the buffet is to the nature of the boundary layer. The last section of the paper gives a short overview of advanced simulations for these different test cases. In the conclusion, we list research perspectives, which include some more general topics such as data assimilation.L'article passe en revue les recherches menées à l'ONERA au cours des trente dernières années sur le buffet transsonique. Nous présentons d'abord le phénomène du buffet transsonique et nous expliquons son importance pour les applications aéronautiques. On distingue ensuite le buffet 2D produit par une aile bidimensionnelle et le buffet 3D qui caractérise les ailes en flèches d’envergure finie. Le buffet 2D se présente sous la forme d’une oscillation d’ensemble de tout l’écoulement couplant un déplacement de l’onde de choc et le décollement de la couche limite en aval de ce choc. Le buffet 3D prend quant à lui la forme d'une poche de perturbations localisées dans une portion limitée de l'aile. Nous rappelons que ces mécanismes ont d'abord été étudiés à l’ONERA dans les années 80 à travers une série de tests réalisés dans la soufflerie transsonique T2 à Toulouse et dans la grande soufflerie transsonique S2 de Modane. Ces travaux pionniers ont ensuite été approfondis dans la soufflerie S3Ch de Meudon de manière à élaborer une base de données complète du buffet 2D sur une aile 2D en régime turbulent, que nous décrivons. Cette base de données a été utilisée de façon extensive, à l’ONERA et dans d’autres institutions pour valider différents outils de simulation, ces derniers étant alors utilisés à leur tour pour étudier la physique du buffet. Nous illustrons cette collaboration entre la simulation et la physique en rappelant qu'une analyse de stabilité linéaire de solutions précises des équations de Navier-Stokes moyennées au sens de Reynolds (RANS) a permis de prouver que le buffet 2D provient d'un mécanisme d'instabilité globale. Nous passons également en revue des essais plus récents réalisés dans la soufflerie S3Ch sur le cas d'une aile 2D laminaire qui révèlent des comportements très distincts par rapport au cas turbulent. Cela illustre la sensibilité du buffet à la nature de la couche limite. Le dernier paragraphe du document donne un bref aperçu des simulations avancées de ces différents cas tests. Dans la conclusion, nous énumérons les perspectives de recherche sur le sujet, qui incluent aussi des thématiques méthodologiques plus générales telles que l'assimilation de données

The Photochemical Reflectance Index from Directional Cornfield Reflectances: Observations and Simulations

The two-layer Markov chain Analytical Canopy Reflectance Model (ACRM) was linked with in situ hyperspectral leaf optical properties to simulate the Photochemical Reflectance Index (PRI) for a corn crop canopy at three different growth stages. This is an extended study after a successful demonstration of PRI simulations for a cornfield previously conducted at an early vegetative growth stage. Consistent with previous in situ studies, sunlit leaves exhibited lower PRI values than shaded leaves. Since sunlit (shaded) foliage dominates the canopy in the reflectance hotspot (coldspot), the canopy PRI derived from field hyperspectral observations displayed sensitivity to both view zenith angle and relative azimuth angle at all growth stages. Consequently, sunlit and shaded canopy sectors were most differentiated when viewed along the azimuth matching the solar principal plane. These directional PRI responses associated with sunlit/shaded foliage were successfully reproduced by the ACRM. As before, the simulated PRI values from the current study were closer to in situ values when both sunlit and shaded leaves were utilized as model input data in a two-layer mode, instead of a one-layer mode with sunlit leaves only. Model performance as judged by correlation between in situ and simulated values was strongest for the mature corn crop (r = 0.87, RMSE = 0.0048), followed by the early vegetative stage (r = 0.78; RMSE = 0.0051) and the early senescent stage (r = 0.65; RMSE = 0.0104). Since the benefit of including shaded leaves in the scheme varied across different growth stages, a further analysis was conducted to investigate how variable fractions of sunlit/shaded leaves affect the canopy PRI values expected for a cornfield, with implications for 20 remote sensing monitoring options. Simulations of the sunlit to shaded canopy ratio near 50/50 +/- 10 (e.g., 60/40) matching field observations at all growth stages were examined. Our results suggest in the importance of the sunlit/shaded fraction and canopy structure in understanding and interpreting PRI

Comparison of synthetic jet actuators based on sharp-edged and round-edged nozzles

Axisymmetric synthetic jet actuators based on a loudspeaker and on two types of flanged nozzles were tested and compared experimentally. The first type of the nozzle was a sharp-edged circular hole. The second one had a special design with fillets at inner and outer nozzle exit and with a small step in the middle of the nozzle. The function of the step was to prevent the flow reattachment during the extrusion stroke. The actuators with the two types of nozzles were operated at resonance and were compared first qualitatively using a simple phase locked flow visualization. Then the hot-wire anemometer was used to measure velocity distributions along nozzle axis and velocity profiles at the nozzle exit. Comparison of the nozzles was based on evaluation of the characteristic velocity and integral quantities (volumetric, momentum, and kinetic energy fluxes). It was found out that these quantities, which were evaluated at the nozzle exit, differ substantially for both nozzles. On the other hand the velocity flow field in farther distances from the nozzle exit area did not exhibit such prominent differences

Structure from motion photogrammetry in forestry : a review

AbstractPurpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers.Recent FindingsOur examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.SummaryWe highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys

Remote sensing of vegetation structure using computer vision

High-spatial resolution measurements of vegetation structure are needed for improving understanding of ecosystem carbon, water and nutrient dynamics, the response of ecosystems to a changing climate, and for biodiversity mapping and conservation, among many research areas. Our ability to make such measurements has been greatly enhanced by continuing developments in remote sensing technology—allowing researchers the ability to measure numerous forest traits at varying spatial and temporal scales and over large spatial extents with minimal to no field work, which is costly for large spatial areas or logistically difficult in some locations. Despite these advances, there remain several research challenges related to the methods by which three-dimensional (3D) and spectral datasets are joined (remote sensing fusion) and the availability and portability of systems for frequent data collections at small scale sampling locations. Recent advances in the areas of computer vision structure from motion (SFM) and consumer unmanned aerial systems (UAS) offer the potential to address these challenges by enabling repeatable measurements of vegetation structural and spectral traits at the scale of individual trees. However, the potential advances offered by computer vision remote sensing also present unique challenges and questions that need to be addressed before this approach can be used to improve understanding of forest ecosystems. For computer vision remote sensing to be a valuable tool for studying forests, bounding information about the characteristics of the data produced by the system will help researchers understand and interpret results in the context of the forest being studied and of other remote sensing techniques. This research advances understanding of how forest canopy and tree 3D structure and color are accurately measured by a relatively low-cost and portable computer vision personal remote sensing system: 'Ecosynth'. Recommendations are made for optimal conditions under which forest structure measurements should be obtained with UAS-SFM remote sensing. Ultimately remote sensing of vegetation by computer vision offers the potential to provide an 'ecologist's eye view', capturing not only canopy 3D and spectral properties, but also seeing the trees in the forest and the leaves on the trees

Large-eddy simulation study of synthetic jet frequency and amplitude effects on a rounded step separated flow

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Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure

Ecological remote sensing is being transformed by three-dimensional (3D), multispectral measurements of forest canopies by unmanned aerial vehicles (UAV) and computer vision structure from motion (SFM) algorithms. Yet applications of this technology have out-paced understanding of the relationship between collection method and data quality. Here, UAV-SFM remote sensing was used to produce 3D multispectral point clouds of Temperate Deciduous forests at different levels of UAV altitude, image overlap, weather, and image processing. Error in canopy height estimates was explained by the alignment of the canopy height model to the digital terrain model (R2 = 0.81) due to differences in lighting and image overlap. Accounting for this, no significant differences were observed in height error at different levels of lighting, altitude, and side overlap. Overall, accurate estimates of canopy height compared to field measurements (R2 = 0.86, RMSE = 3.6 m) and LIDAR (R2 = 0.99, RMSE = 3.0 m) were obtained under optimal conditions of clear lighting and high image overlap (>80%). Variation in point cloud quality appeared related to the behavior of SFM ‘image features’. Future research should consider the role of image features as the fundamental unit of SFM remote sensing, akin to the pixel of optical imaging and the laser pulse of LIDAR

Remote Sensing of Vegetation Structure Using Computer Vision

High spatial resolution measurements of vegetation structure in three-dimensions (3D) are essential for accurate estimation of vegetation biomass, carbon accounting, forestry, fire hazard evaluation and other land management and scientific applications. Light Detection and Ranging (LiDAR) is the current standard for these measurements but requires bulky instruments mounted on commercial aircraft. Here we demonstrate that high spatial resolution 3D measurements of vegetation structure and spectral characteristics can be produced by applying open-source computer vision algorithms to ordinary digital photographs acquired using inexpensive hobbyist aerial platforms. Digital photographs were acquired using a kite aerial platform across two 2.25 ha test sites in Baltimore, MD, USA. An open-source computer vision algorithm generated 3D point cloud datasets with RGB spectral attributes from the photographs and these were geocorrected to a horizontal precision of <1.5 m (root mean square error; RMSE) using ground control points (GCPs) obtained from local orthophotographs and public domain digital terrain models (DTM). Point cloud vertical precisions ranged from 0.6 to 4.3 m RMSE depending on the precision of GCP elevations used for geocorrection. Tree canopy height models (CHMs) generated from both computer vision and LiDAR point clouds across sites adequately predicted field-measured tree heights, though LiDAR showed greater precision (R2 > 0.82) than computer vision (R2 > 0.64), primarily because of difficulties observing terrain under closed canopy forest. Results confirm that computer vision can support ultra-low-cost, user-deployed high spatial resolution 3D remote sensing of vegetation structure