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Scaling, Packetizers and Aggregation in Network Calculus
No full textInternational audienceReal-time systems often consist of numerous subsystems engaged in extensive data exchange. Despite their complexity, a critical challenge lies in effectively incorporating real-time constraints within these systems. To address this challenge, designers typically conduct analyses to establish upper bounds on delays, ensuring they remain within the deadlines of incoming requests. However, adopting a pessimistic approach often results in over-dimensioning the systems. Then, to reduce the pessimism, we want to take into account the fact that a subsystem cannot propagate more requests/data than it can execute. This phenomenon is well-known in network analysis as it reduces the burst of data. As a consequence, this notion is easier to grasp in theories developed to compute delay bounds in networks. That is why we choose, in this paper, to perform the analysis using the network Calculus theory, since it offers the possibility to easily aggregate flows (i.e. sum flows) and then take into account the phenomenon of smoothing the traffic. To handle tasks and networks, our model relies on packetization and workload scaling. In this paper, we improve some results regarding the already existing elements of Network Calculus and the aggregation. Also, we update and complete definitions and results related to workload scaling
Continual Learning in Remote Sensing : Leveraging Foundation Models and Generative Classifiers to Mitigate Forgetting
No full textInternational audienceContinual learning in dynamic environments is a challenge for large-scale machine learning models. This research addresses Domain Incremental Learning (DIL), a setting where the goal is to incrementally increase the input data scope of a model. More specifically, we investigate the possibility of using foundation models (FMs) as a fixed feature extractor combined with a PPCA that can be sequentially and accurately updated. Focusing on the classification of VHR remote sensing (RS) images, we show on the FLAIR#1 dataset that this simple DIL strategy achieves competitive accuracy compared to memory-based baselines across different pre-trained sources. We also compare different types of foundation models and highlight the importance of data diversity over data specialization to improve the quality of FMs
Mesure BOS haute-cadence grand-champ d'un jet double-flux non-isotherme
No full textInternational audienceDes mesures haute-cadence et grand-champ de déviations optiques à travers un jet chaud turbulent à double-flux mélangés ont été obtenues par Background Oriented Schlieren. Ces mesures optiques ouvrent de nouvelles perspectives pour la caractérisation de la dynamique spatio-temporelle des structures cohérentes azimutales de grande échelle, en partie responsables du bruit de jet
Numerical methods and relaxation techniques for diffuse interface models in high-velocity two-phase flow simulations
No full textInternational audienceCompressible multiphase flows are at the heart of a great number of engineering applications in several domains.Some examples include the aerospace industry, since many rocket propulsion systems rely on the injection of a liquid reactant into the combustion chamber and the efficiency of the combustion is directly related to the atomization process. Other applications include the civil nuclear industry safety analysis but also the naval industry for which underwater solid propulsion systems are of great interest. The design and optimization requirements of these systems lead to an increasing need for predictive numerical simulations. Diffuse interface models are widely used for these tasks as they provide a good trade-off between accuracy and robustness.We consider the class of Baer-Nunziato type of models, in which the most general one allows for full disequilibrium between the two-phases. Reduced order models are obtained by assuming some local equilibrium (velocity, pressure, temperature or chemical potential equilibrium). Among this hierarchy of models, the pressure and velocity equilibrium model of Kapila et al is of particular interest. It allows to recover the classical Wood sound velocity for two-phase mixtures while still allowing thermal disequilibrium which is paramount for many applications such as high-temperature jets impinging on liquid surfaces and for proper modelling of phase changes. Several strategies to solve this model rely on a 6-equation model endowed with stiff pressure relaxation terms. For cavitating flows, an accurate computation of the pressure equilibrium is particularly important to compute the mass transfer fluxes.The purpose of the present contribution is to study the assumptions on the thermodynamics of the two phases and its impact on the mathematical structure of the resulting system of PDEs (where potentially several relaxation processes are involved either relying on finite-rate or instantaneous relaxation source terms). We propose an analysis of the pressure relaxation process in terms of thermodynamically admissible paths and propose a robust numerical scheme, which preserves the set of admissible states of the system. The robustness and accuracy of the proposed numerical scheme involving convection and sources is then assessed on several challenging configurations including shock-interface interactions and cavitating flows, such as shock-droplet interaction or Richtmyer–Meshkov instability
Law-Smooth Update Scheme for the Cross-Entropy Optimization Algorithm And Applications
No full textIt is well known that the Cross-Entropy (CE) algorithm, based on Gaussian distributions family, is significantly less efficient than successful methods such as CMAES or even particle-based approaches such as particle swarms. Nevertheless, the Gaussian-based CE approach implements similar ingredients as the CMAES approach, but it is significantly penalized by its law updating step after sample selection. Variants of the CE approach have been proposed, featuring a smoothing of the distribution parameters. We show why these approaches by smoothing law parameters may result in wrong convergence, and propose an approach based on smoothing laws. We implement this CE updating approach and show that it gets close to the performance of CMAES on an applicative example. Our application concerns the robust optimization of band selection for anomaly detection in multispectral remote sensing images. As it is important to take into account the variability in the scenes observed, as well as the diversity of objects likely to be encountered, we have drawn on robustness measures, such as quantile, to quantify the variations in anomaly detection criteria over the 100 hyperspectral images of the benchmark dataset. Finally, we also explore a generalization of this CE update to laws of the exponential family
Robust Deep Reinforcement Learning Control for a Launcher Upper Stage Module with Stability Certificate
No full textInternational audienceThis paper considers the design of an attitude controller of a launcher upper stage module during its exoatmospheric phase, where short boosts are performed to adapt the flight path. Those maneuvers can increase propellants' motion in the tanks, leading to the so-called sloshing phenomenon that may affect the stability of the vehicle.A Deep Reinforcement Learning (DRL) algorithm is proposed to design the controller accounting for non linearities of the launcher and sloshing dynamics as well as presence of time-delay, bias and saturations on the actuation system. Based on Proximal Policy Optimization (PPO) and Almost Lyapunov functions in an actor-critic scheme, it allows to robustly learn a controller along with stability certificates, in presence of model uncertainties. Simulation results are proposed to illustrate the approach
Key Challenges in True Multistatic OTH Radar Concepts based on HF-Radar in iFURTHER
No full textInternational audienceThe system concept of a multistatic network of collaborative high frequency (HF) over-the-horizon (OTH) radar nodes has been proposed and is being tested in the European Union-funded study iFURTHER. These system setups are subject to the electromagnetic situation given in the high frequency range and challenging ionospheric skywave or surface-wave propagation paths in combination with a bistatic beyond-line-ofsight (BLOS) geometry. It is foreseen to combine data from widely distributed HF sensor nodes in a cohesive OTH radar network for the coherent operation below approximately 30 MHz. Inherent technical challenges affect the choice of possible system designs and the performance in terms of target tracking and localization. Being thereby distinct to a classical OTH skywave backscatter principle in (quasi-)monostatic configurations, this idea requires conceptually new and agile system architectures, which include the support by cognitive radar principles and a sensing of the ionosphere to retrieve latest supplementary information on current propagation conditions. The possibilities are enhanced by a combined hybrid skywave and surface-wave propagation with a likely support of complementary sensor data. It may benefit from an exploitation of non-cooperative illumination by transmitters of opportunity. Successful verification of this system-of-systems concept will provide powerful radar and sensing capabilities that can be used in a wide range of upcoming OTH applications
Simulation de la Surface Equivalente Radar (SER) d'objets enfouis en utilisant une méthode hybride volumes finis : Validation expérimentale à travers des mesures de SER d'une sphère PEC
No full textInternational audienceThis paper introduces an innovative hybrid finite volume method designed to assess the Radar Cross Section (RCS) of buried objects exposed to a plane wave. The study includes a comprehensive experimental validation of this method, involving a specific experiment tailored to evaluate its performance. The article outlines the fundamental principles of the numerical scheme and offers a detailed description of the experimental setup. Furthermore, it includes a comparative analysis between simulation results and actual measurements.Cet article présente une méthode hybride innovante volumes finis conçue pour évaluer la Surface Equivalente Radar (SER) d'objets enfouis exposés à une onde plane. L'étude comprend une validation expérimentale de cette méthode, impliquant une expérience spécifique, adaptée pour évaluer sa performance. L'article décrit les principes fondamentaux du schéma numérique et offre une description détaillée de la configuration expérimentale. De plus, il inclut une analyse comparative entre les résultats de simulation et les mesures expérimentales
Simulation d'images RSO avec écran de phase ionosphérique / SAR images simulation with ionospheric phase screen
No full textInternational audienceLow-frequencies SAR images (especially at P or L band) can be impacted by ionosphere layer irregularities. Ionospheric stripes on SAR images are a well-known phenomena due to high electronic density anisotropy in ionosphere at low latitude. Some authors have already presented methods for the simulation of disturbed images, based on propagation modeling using the Parabolic Wave Equation method. This work presents a method for ionospheric phase screen generation based on the Rytov’s theory of weak scattering which allows deriving analytic formulations of log-amplitude and phase spatial spectra of the received signal. These spectra are used to create a 2D phase screen modeling the propagation of an electromagnetic wave crossing the ionosphere and propagating from the satellite to the ground. The SAR signal is modulated with the phase screen which allows to consider ionosphere impact and create a disturbed SAR image.Les images RSO basse fréquence (en particulier dans la bande P ou L) peuvent être affectées par des irrégularités de la couche ionosphérique. Les stries observées sur les images SAR sont un phénomène bien connu du à la forte anisotropie de densité électronique dans l’ionosphère aux basses latitudes. Certains auteurs ont déjà présenté des méthodes de simulation d’images perturbées, basées sur la modélisation de la propagation à l’aide de la méthode des équations d’ondes paraboliques. Ce travail présente une méthode de génération d’écran de phase ionosphérique basée sur la théorie de faible pertubation de Rytov qui permet de déterminer des formulations analytiques des spectres de log-amplitude et phase du signal reçu. Ces spectres sont utilisés pour créer un écran de phase 2D modélisant la propagation d’une onde électromagnétique traversant l’ionosphère et se propageant du satellite au sol. Le signal SAR est modulé avec l’écran de phase qui permet de considérer l’impact de l’ionosphère et de créer une image SAR perturbée
