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Phononic compliant surfaces for the suppression of travelling-wave flutter instabilities in boundary-layer flows
No full textInternational audienceCompliant walls made from homogeneous viscoelastic materials may attenuate the amplification of Tollmien–Schlichting waves (TSWs) in a two-dimensional boundary-layer flow, but they also amplify travelling-wave flutter (TWF) instabilities at the interface between the fluid and the solid, which may lead to a premature laminar-to-turbulent transition. To mitigate the detrimental amplification of TWF, we propose to design compliant surfaces using phononic structures that aim at avoiding the propagation of elastic waves in the solid in the frequency range corresponding to the TWF. Thus, stiff inserts are periodically incorporated into the viscoelastic wall in order to create a band gap in the frequency spectrum of the purely solid modes. Fluid–structural resolvent analysis shows that a significant reduction in the amplification peak related to TWF is achieved while only marginal deterioration in the control of TSWs is observed. This observation suggests that the control of TSWs is still achieved by the overall compliance of the wall, while the periodic inserts inhibit the amplification of TWF. Bloch analysis is employed to discuss the propagation of elastic waves in the phononic surface to deduce design principles, accounting for the interaction with the flow
Absolute positioning from remote sensing images based on road network
No full textAs sealed roads are one of the most standard man-made infrastructure worldwide, segmenting them seems scalable using simple convolutional neural network. This invites to consider the possibility to use road intersection patterns to retrieve absolute positioning from remote sensing image like stellar patterns allow to retrieve absolute orientation from space image
Intégration d'un modèle de propulsion hybride électrique dans un modèle d'aéronef complet, incluant aérodynamique et structure, en vue de sa conception multidisciplinaire
No full textInternational audienceCet article se focalise sur la conception multidisciplinaire d’un avion régional hybride série. L’étude fait suite au projet européen HASTECS coordonné par le LAPLACE, qui visait à concevoir la chaîne de propulsion hybride électrique. Le travail réalisé a été repris et enrichi dans notre étude en incluant le couplage aux caractéristiques aérodynamiques et de structure de l’avion, sur la base de modèles système avion complémentaires développés par l’ONERA. La nouvelle formulation proposée pour la conception multidisciplinaire de l’avion par optimisation conduit à une meilleure prise en compte des différents couplages et permet d’intégrer de nouveaux degrés de liberté exploitables dans une optimisation «système» multidisciplinaire dite «MDO» (forme de la mission de vol, conception de l’aile, topologie de l’avion, etc.
Control variates for variance-reduced extreme value index estimators
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Towards MTG-IRS retrieval of CO using IASI from the interferogram domain
No full textInternational audienceOnboard of MetOp satellite series, Infrared Atmospheric Sounding Interferometer (IASI) is a Fourier Transform spectrometer based on the Michelson interferometer. IASI acquires interferograms from which high-resolution atmospheric emission spectra are provided, enabling the derivation of temperature and humidity profiles (among other parameters) with exceptional spectral resolution. In this study, we will use the IASI archive to evaluate a retrieval approach in the interferogram domain, which we anticipate will be well-suited for near-real-time (NRT) analysis of extensive spectral datasets expected from next-generation tropospheric sounders like MTG-IRS. The Partially Scanned Interferograms (PSI) method, applied to the retrieval of trace gases from IASI, has only rarely been studied. However, existing studies suggest its potential for specific gases, including CO, CO₂, CH₄, and N₂O, which could enable highly accurate trace gas column density retrievals at the resolution of a single IASI footprint
Extending Consensus-based Task Allocation Algorithms with Bid Intercession to Foster Mixed-Initiative
No full textInternational audienceWe propose a new approach for controlling task allocation in teams of robots with different capabilities. This approach allows human operators, who have a better understanding of the situation, to influence or even dictate how tasks are distributed, whilst allowing autonomous decisions. Our method works within existing consensus-based allocation algorithms by introducing intercession in the bidding process. Intercession allows agents to bid on behalf of others. This allows for a flexible range of control, from completely decentralized to fully human-controlled, without refactoring the consensus-based allocation scheme, which has been proven to be efficient. We build upon an existing algorithm, Consensus-based Bundle Auction (CBBA), while maintaining its solution quality and ability to reach agreement (convergence). We test our new method, I-CBBA, in simulated multi-robot task allocation (MRTA) scenarios using the ROS framework
Suivi de particules pour la PTV-3D à hautes densités à l'aide d'une méthode de consensus
No full textInternational audienceA robust pairing algorithm with outlier removal is introduced in the context of two-pulse 3D Particle Tracking Velocimetry at high seeding densities, with high concentrations of ghost particles. Integrating the Vector Field Consensus approach from Ma et al. ( 2014), the algorithm, its underlying hypotheses and its relevant input parameters are investigated in the context of turbulent flow measurements. 2D synthetic tests are first carried out to quantify the algorithm's performance and derive simple guidelines for optimal parameter tuning strategies based on experimental quantities. It is found that 2D vector fields with up to 90% outliers can be handled by our algorithm. 3D synthetic tests are then implemented to test the tracking strategy robustness to increasing image densities and ghost particle concentrations. We show that our algorithm can be used for particle pairing in particle clouds with up to 50% of ghost particles. Results submitted on the two-pulse dataset of the First LPT challenge, using the associated data portal with automatic evaluation, also showcase the overall excellent performances of the method. Finally, the method is used successfully on experimental data from our Giant Von Kármán setup (characterized by up to 65% of ghost particles), as evidenced by comparisons of its output with respect to results provided by the Shake-The-Box algorithm, and with results provided by a pairing approach using a 3D cross-correlation predictor.Un algorithme robuste d’appariement avec élimination des valeurs aberrantes est présenté dans le cadre de la vélocimétrie par suivi de particules 3D à deux impulsions, appliquée à des densités d'ensemencement élevées, où la concentration en particules fantômes est importante. En intégrant l’approche "Vector Field Consensus" proposée par Ma et al. (2014), l’algorithme, ses hypothèses sous-jacentes et ses paramètres d’entrée pertinents sont étudiés dans le contexte de mesures en écoulement turbulent. Des tests synthétiques 2D sont d’abord réalisés afin de quantifier les performances de l’algorithme et d’établir des recommandations simples pour une stratégie optimale de réglage des paramètres à partir de grandeurs expérimentales. Il a été constaté que des champs de vecteurs 2D comportant jusqu’à 90 % de valeurs aberrantes peuvent être traités par notre algorithme. Des tests synthétiques 3D sont ensuite mis en œuvre pour évaluer la robustesse de la stratégie de suivi face à l’augmentation des densités d’images et des concentrations de particules fantômes. Nous montrons que notre algorithme peut être utilisé pour l’appariement de particules dans des nuages comprenant jusqu’à 50 % de particules fantômes. Les résultats soumis sur le jeu de données à deux impulsions du First LPT Challenge, via le portail de données associé avec évaluation automatique, illustrent également les excellentes performances globales de la méthode. Enfin, la méthode a été appliquée avec succès à des données expérimentales issues de notre installation expérimentale Giant Von Kármán (caractérisée par jusqu’à 65 % de particules fantômes), comme en témoignent les comparaisons de ses résultats avec ceux fournis par l’algorithme Shake-The-Box, ainsi qu’avec ceux obtenus par une approche d’appariement utilisant un prédicteur basé sur la corrélation croisée 3D
A Reference Hydride Ratio Method for the Resolution of Al/Fe Peak Overlapping in Atom Probe Tomography Experiments
No full textInternational audiencePrecise Fe concentration measurements are essential to understand the kinetics of precipitation and evolution of mechanical properties in Al-Fe alloys. Moreover, with the increasing proportion of recycled metals, it is mandatory to rely on techniques capable of tracking impurities in Al-alloys to elucidate their effects on microstructure and properties. Atom Probe Tomography (APT) is a powerful material analysis tool capable of precise composition measurements. As it relies on time-of-flight mass spectrometry, the quality of the composition measurements is highly dependent on the proper peak identification and solving peak overlapping. The complexity of peak decomposition multiplies if molecular ions such as hydrides or oxides are present in the mass spectrum. Al-Fe is one of these systems, where three out of four peaks of Fe isotopes are overlapping with Al, AlH, and AlH2 mass intervals. To solve this complex peak overlapping case, an approach has been developed here. It is based on acquiring the Al-hydride formation ratio from APT analyses of standard materials, where no overlap with Fe peaks is observed. This simple method aims to improve the precision of Fe concentration measurements in Al-Fe system
Modelling of relative velocity, velocity fluctuations and their interactions for two-fluid models by Stationary Action Principle
No full textThe objective of this contribution is the derivation of a two-fluid model including a relative velocity between the two phases and velocity fluctuations, describing pseudo-turbulent effects, as internal variables based on Stationary Action Principle. The variational derivation, used to obtain the model, relies on the variation of a single trajectory related to the mass-weighted average velocity under the barotropic assumption. The model is hyperbolic, satisfies a second principle of thermodynamics, and admits either linearly degenerate or genuinely nonlinear characteristic fields. Moreover, the variational approach yields a fully closed model and its non-conservative products are uniquely defined for weak solutions in 1D, i.e. jump conditions can be derived. In the laminar case, when velocity fluctuations are negligible, we recover previously derived multi-fluid models which have been analyzed in several contributions. As such, the present framework allows for an original extension of the existing models to include velocity fluctuations of each phase for pseudo-turbulent flows, their coupling with the relative velocity between phases, as well as dissipative effects compatible with the thermodynamics of irreversible processes. Eventually, we provide a discussion of the limitations of the proposed model, especially regarding the extension to the open problem of non-barotropic flows
Multi-Fidelity Constrained Bayesian Optimization with Application to Aircraft Wing Design
No full textInternational audienceAircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization (MDO) problems. In this context, there has been growing interest in multi-fidelity models for Bayesian Optimization to improve the MDO process by balancing computational cost and accuracy through the combination of high-and low-fidelity simulation models, enabling efficient exploration of the design process at a minimal computational effort. In the existing literature, fidelity selection focuses only on the objective function to decide how to integrate multiple fidelity levels, balancing precision and computational cost using variance reduction criteria. In this work, we propose novel multi-fidelity selection strategies. Specifically, we demonstrate how incorporating information from both the objective and the constraints can further reduce computational costs without compromising the optimality of the solution. We validate the proposed multi-fidelity optimization strategy by applying it to three analytical test cases, showcasing its effectiveness. The proposed method is used to solve efficiently a challenging aircraft wing design problem. The proposed setting uses a linear Vortex Lattice Method (VLM) as a low-fidelity model and a Reynolds-averaged Navier-Stokes coupled VLM as a high-fidelity model. We show that employing our proposed multi-fidelity approach can reduce the required computational budget for convergence by up to 65% when compared to a mono-fidelity approach