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PSFP in TSN Networks: Insights into Some Practical Limitations
No full textInternational audiencePer-Stream Filtering and Policing (PSFP), standardized in IEEE 802.1Qci, is a mechanism for enhancing fault containment in Time-Sensitive Networking (TSN) domains. This paper examines two limitations of PSFP that challenge the prevailing “zero-fault” perception. First, the Flow Meter inside PSFP measures traffic in Service Data Unit (SDU) bytes—i.e., from the MAC destination address through Frame Check Sequence—while common Ethernet shapers such as the Credit-Based Shaper (CBS) regulate on the full “on-wire” packet length, which includes the SDU plus the 8-byte preamble and 12-byte inter-frame gap. This results in a 20-byte per-frame gap that can increase admissible rates: for minimum-size packets, a talker may exceed its contractual bandwidth by up to 30%, allowing queue build-up. Second, CBS positive-credit recovery phase permits the transmission of bursts, whose size increases with the idleSlope setting. To avoid unintended drops, the Flow Meter’s Committed Burst Size must be set proportionally higher, which can reduce the policing effect and widen the window in which faulty talkers may impact critical streams. Through deterministic analysis with RTaW-Pegase and hardware-in-the-loop experiments on an automotive TSN testbed, we quantify both effects and assess configuration-level mitigations. We then discuss possible standard-evolution options, including SDU-aware byte counting and lower-bound filters for frame sizes, that could address these gaps. The aim of this paper is to guide practitioners toward PSFP configurations that enable effective fault containment and make suggestions for PSFP improvements that could provide even stronger guarantees
Considerations on Software Verification of Multi-Core Processors in Pursuance of Aeronautical Certification
No full textInternational audienceEmbedded systems undergo a rigorous certification process to ensure the airworthiness of aircraft. The process becomes increasingly difficult as the systems become complex. Nowadays, multi-core processors (MCPs) are present in everyday equipment. Naturally, the question of their certification for aeronautical use then arises. Indeed, while they offer many advantages, they come with risks concerning the potential use of shared resources leading to interference between applications, and therefore unsafe behaviour for airworthiness. The AMC 20-193 is one of the most prominent certification standards for the use of MCP in avionic systems and equipment. It provides a set of ten objectives, going from software planning to verification of the MCPs. While these objectives enlighten the applicant on the path to certification, they are not prescriptive on the means to satisfy them. Our work aims at investigating a way to satisfy a particularly challenging objective of the AMC 20-193 dealing with software verification, named MCP Software 1, in a particular context. In this paper, we present our understanding of MCP Software 1 and suggest a strategy for its satisfaction for MCPs in our scope. We also recommend an adapted process to apply the strategy
The Challenges posed by the Aeronautical Certification of Open-Hardware System in Package
No full textInternational audienceSafety-critical airborne embedded processing devices must undergo certification processes according to standards that were written for custom developments and COTS devices usage. However, modern electronic devices are evolving from monolithic chips toward System in Package (SiP) architectures and from proprietary IPs toward Open-source Hardware IPs, paving the way to more tailoring, modularity and potential reuse of components across projects. This shift raises the question of whether the existing certification baseline remains adequate for such modern electronic devices and whether evolutions are required. The article aims to address this question by formalizing both the Open Hardware SiP domain and the certification baseline using ontologies, framing the adequacy between these two formal models as an ontology alignment problem and drawing conclusions from this alignment
Mathematical aspects of registration methods in bounded domains
No full textRegistration methods in bounded domains have received significant attention in the model reduction literature, as a valuable tool for nonlinear approximation. The aim of this work is to provide a concise yet complete overview of relevant results for registration methods in -dimensional domains, from the perspective of parametric model reduction. We present a thorough analysis of two classes of methods, vector flows and compositional maps: we discuss the enforcement of the bijectivity constraint and we comment on the approximation properties of the two methods, for Lipschitz -dimensional domains
Évaluation de la vélocimétrie par images de particules In-Line pour les mesures de turbulence dans les milieux poreux
No full textInternational audienceIn-line particle image velocimetry (PIV) is implemented and assessed as a measurement technique for acquiring instantaneous velocity fields within porous structures traversed by turbulent flows. Focusing on triply periodic minimal surface samples, whose geometries are analytically defined, this study evaluates the potential of in-line PIV to maximize optical accessibility relative to conventional light-sheet PIV configurations, while maintaining acceptable particle-image quality despite the unavoidable presence of light-scattering solid surfaces. The primary objective is to assess the feasibility and limitations of in-line PIV when applied through a solid porous matrix, and to identify the methodological adaptations required to obtain reliable velocity fields. This methodological groundwork aims to establish in-line PIV as a robust diagnostic tool for future investigations of turbulent flows within porous media.La vélocimétrie par images de particules In-Line (PIV) est mise en œuvre et évaluée en tant que technique de mesure permettant d'acquérir des champs de vitesse instantanés au sein de structures poreuses traversées par des écoulements turbulents. En se concentrant sur des échantillons de surface minimale triplement périodique, dont les géométries sont définies analytiquement, cette étude évalue le potentiel de la PIV In-Line pour maximiser l'accessibilité optique par rapport aux configurations PIV à feuille de lumière conventionnelles, tout en maintenant une qualité d'image particulaire acceptable malgré la présence inévitable de surfaces solides diffusant la lumière. L'objectif principal est d'évaluer la faisabilité et les limites de la PIV In-Line lorsqu'elle est appliquée à travers une matrice poreuse solide, et d'identifier les adaptations méthodologiques nécessaires pour obtenir des champs de vitesse fiables. Ce travail méthodologique vise à établir la PIV In-Line comme un outil de diagnostic robuste pour les futures investigations des écoulements turbulents dans les milieux poreux
Amélioration de la consistance physique dans l'optimisation stochastique pour les problèmes inverses basés sur les adjoints : application aux simulations RANS compressibles dans le cadre de Galerkin discontinu
No full textInternational audienceThis work explores the use of quasi-Newton and stochastic optimization methods for gradientbased inverse problems in physical modeling, focusing on their application within high-order numerical frameworks. Such problems are often characterized by the following challenges: (i) physical constraints often yield a highly non-convex design space with multiple local optima; (ii) solutions must satisfy intrinsic properties, such as boundary and regularity conditions, which are not easily enforced as explicit constraints. Conventional stochastic optimizers, such as N-ADAM, exhibit significant information loss in their update rules, leading to non-physical solutions. To overcome these limitations, we introduce a novel stochastic optimizer, V-N-ADAM-DG, which incorporates adjoint-state information into the update rule to maintain physically meaningful corrections in terms of regularity and boundary conditions. We validate our approach in the context of mean-flow reconstruction for Reynolds-averaged Navier-Stokes (RANS) simulations using a high-order discontinuous Galerkin (DG) discretization method, as proposed by Fanizza et al. (2025). The optimization framework considers both vectorial corrective terms, inferred in the momentum and energy equations, and scalar corrective terms in the Spalart-Allmaras (SA) transport equation. The V-N-ADAM-DG optimizer effectively reconstructs mean flow quantities while ensuring smooth transitions of corrective parameters at boundaries, an improvement over standard stochastic optimizers. Additionally, it facilitates a rapid decay of the optimal degrees of freedom (DOFs), leading to smoother corrections in high-order reconstructions-achieving a balance between the robustness of quasi-Newton methods (such as L-BFGS) and the flexibility of stochastic approaches. Numerical experiments across various flow configurations demonstrate that V-N-ADAM-DG consistently outperforms both L-BFGS and N-ADAM, particularly in complex inverse problems that employ multiple combined cost functions to reconstruct different physical quantities.Ce travail explore l'utilisation de méthodes d'optimisation quasi-Newton et stochastiques pour les problèmes inverses basés sur le gradient dans la modélisation physique, en se concentrant sur leur application au sein de frameworks numériques d'ordre élevé. Ces problèmes sont souvent caractérisés par les défis suivants : (i) les contraintes physiques engendrent généralement un espace de conception fortement non convexe avec plusieurs optima locaux ; (ii) les solutions doivent satisfaire des propriétés intrinsèques, telles que des conditions aux limites et de régularité, qui ne sont pas facilement imposées comme contraintes explicites. Les optimiseurs stochastiques conventionnels, tels que N-ADAM, présentent une perte d'information significative dans leurs règles de mise à jour, conduisant à des solutions non physiques. Pour surmonter ces limites, nous introduisons un nouvel optimiseur stochastique, V-N-ADAM-DG, qui intègre l'information d'état adjoint dans la règle de mise à jour pour maintenir des corrections physiquement significatives en termes de régularité et de conditions aux limites. Nous validons notre approche dans le contexte de la reconstruction du flux moyen pour les simulations de Navier-Stokes moyennées sur Reynolds (RANS) en utilisant une méthode de discrétisation Galerkin discontinue d'ordre élevé, telle que proposée par Fanizza et al. (2025). Le framework d'optimisation prend en compte à la fois des termes correctifs vectoriels, inférés dans les équations de quantité de mouvement et d'énergie, et des termes correctifs scalaires dans l'équation de transport Spalart-Allmaras (SA). L'optimiseur V-N-ADAM-DG reconstruit efficacement les grandeurs du flux moyen tout en assurant des transitions lisses des paramètres correctifs aux limites, une amélioration par rapport aux optimiseurs stochastiques standard. De plus, il facilite une décroissance rapide des degrés de liberté (DL) optimaux, conduisant à des corrections plus lisses dans les reconstructions d'ordre élevé — atteignant un équilibre entre la robustesse des méthodes quasi-Newton (comme L-BFGS) et la flexibilité des approches stochastiques. Des expériences numériques sur diverses configurations d'écoulement démontrent que V-N-ADAM-DG surpasse systématiquement à la fois L-BFGS et N-ADAM, en particulier dans les problèmes inverses complexes qui emploient plusieurs fonctions de coût combinées pour reconstruire différentes grandeurs physiques
Low-cost CMOS-based luminescence lifetime imaging with oxygen, temperature and pH sensors
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Towards Multi-Policy Hierarchical Scheduling in Linux for Containerized Space Applications
No full textInternational audienceThis paper examines the challenges of running containerized flight software on Linux for space systems, focusing on how to achieve both predictability and flexibility in scheduling. While containers provide lightweight isolation, they complicate the temporal determinism required by safety-critical spacecraft. Hierarchical scheduling and support for multiple policies are increasingly necessary to accommodate heterogeneous onboard workloads, from hard real-time control loops to best-effort processing.To address these challenges, a methodology is introduced for designing, analyzing, and implementing hierarchical multi-policy scheduling on Linux. The approach is structured around a meta-model capturing the key concepts of hierarchical reservation, a formal analysis based on the Compositional Scheduling Framework (CSF) for sizing container budgets, and a kernel-level execution model built on Linux task groups. Building on these principles, the paper presents the Task Group Bandwidth Server (TGBS), a kernel mechanism that enforces per-container CPU reservations using deadline-server abstractions and full virtual runqueues. Unlike the Hierarchical Constant Bandwidth Server (HCBS), which is limited to real-time (RT) workloads, TGBS applies uniformly to fair-share (FAIR), RT, and deadline-based (DL) scheduling classes.The experimental evaluation assesses functional behavior, real-time latency, and the execution of workloads sized analytically. Functional tests confirm correct enforcement of hierarchical reservations and priority ordering across scheduling classes. Latency measurements show that the overhead introduced by virtual runqueues remains moderate and comparable to HCBS. Finally, schedulability experiments demonstrate that reservations dimensioned with CSF are respected for real-time tasks in a mixed-policy environment, while highlighting the need for extended analytical models to fully capture FAIR scheduling.Overall, the results indicate that hierarchical reservations provide a practical path toward predictable and isolated execution of mixed-policy workloads on Linux. The work establishes a foundation that links analytical reservation sizing with kernel mechanisms and identifies future directions, including multicore support and improved multi-policy schedulability analysis
Wingtip vortex dynamics at low Reynolds numbers under the influence of turbulence
No full textInternational audienceThe influence of turbulence on the aerodynamics of a NACA0012 wing and the behavior of the associated wingtip vortex is investigated at a chord-based Reynolds number of 5000. The study is conducted through water tunnel experiments using a half-wing setup with an aspect ratio of 6 and an angle of attack of 10 degrees. At this low Reynolds number, relevant for aerodynamics at low-speed, the flow over a stationary wing exhibits laminar separation. Longitudinal Particle Image Velocimetry (PIV) measurements show a laminar flow separation over the wing upper surface and its reduction with increased incoming turbulence. Four turbulence conditions are tested: three different passive grids and one baseline (no-grid) configuration, yielding turbulence intensities ranging from 1.4 to 8.2%. Transverse PIV measurements are conducted over three cross-sections up to 24 chord lengths downstream of the wing trailing edge, to characterize the vortex dynamics. At the wingtip, the flow rolls up into a single coherent tip vortex, which exhibits significant unsteadiness in the form of a dominant displacement mode, as Proper Orthogonal Decomposition (POD) shows. In the no-grid case, the vortex exhibits significantly lower-frequency and higher-amplitude motion than in the grid-generated turbulence cases. This indicates that, at low Reynolds numbers, vortex meandering can arise either from unsteady perturbations linked to large-scale flow separation on the wing under low turbulence intensity, or from the direct receptivity of the vortex to freestream turbulence at higher turbulence levels. These results highlight the coexistence and relative importance of two distinct sources of disturbance—wing-separated flow and inflow turbulence—in governing wingtip vortex dynamics
Analysis of Collocation-based Model Order Reduction
No full textWe consider a novel reduced-order modeling strategy, termed collocation Model Order Reduction (cMOR), as an alternative to classical projection-based Model Order Reduction (pMOR). Like pMOR, cMOR follows an offline-online paradigm, with an offline stage devoted to the construction of a reduced basis from solution snapshots. In contrast to pMOR, where the online phase computes the reduced solution by projecting the high-fidelity residual onto the reduced space, cMOR enforces the high-fidelity discretization of the governing equations only at a small set of mesh locations, referred to as collocation points. These points are selected using hyper-reduction techniques. Within this framework, we provide a theoretical analysis of the stability and convergence properties of cMOR and illustrate the method performance through numerical examples