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Priority Switching Scheduler
No full textInternational audienceWe define a novel core network router scheduling architecture called Priority Switching Scheduler (PSS), to carry and isolate time constrained and elastic traffic flows from best-effort traffic. To date, one possible solution has been to implement a core DiffServ network with standard fair queuing and scheduling mechanisms as proposed in the well-known "A Differentiated Services Code Point (DSCP) for Capacity-Admitted Traffic" from RFC5865. This architecture is one of the most selected solutions by internet service provider for access networks (e.g., Customer-Premises Equipment) and deployed within several performace-enhancing proxies (PEP) over satellite communications (SATCOM) architectures. In this study, we argue that the proposed standard implementation does not allow to efficiently quantify the reserved capacity for the AF class. By using a novel credit-based shaper mechanism called Burst Limiting Shaper (BLS) to manage the AF class, we show that PSS can provide the same isolation for the time constrained EF class while better quantifying the part allocated to the AF class. PSS operates both when the output link capacity is fixed (e.g., wire links, terrestrial networks) or might vary due to system impairments or weather condition (e.g., wireless or satellite links). We demonstrate the capability of PSS through an emulated SATCOM scenario with variable capacity, and show the AF output rate is less dependent on the EF traffic, which improves the quantification of the reserved capacity of AF, without impacting EF traffic
A Verified UAV Flight Plan Generator
No full textInternational audienceFPL is a domain specific language used to specify complex drone missions for the Paparazzi open-source autopilot. FPL missions are compiled into C code that is directly embedded into the autopilot code. The FPL to C code generator, currently written in OCaml, is therefore a critical component when addressing the drone safety. This paper presents the formal verification of the FPL compilation process. First, we have developed in Coq a new three-pass code generator, targeting the Clight intermediate language from the CompCert suite. We have then formally defined an operational semantics for FPL. Finally, we have proved a bisimulation relation between FPL semantics and Clight semantics. In the course of the formalization and verification process, we have also unveiled several problems in the original Paparazzi code generator
Slot allocation for a Multiple Airport System: Equity and Efficiency
No full textInternational audienceAirport slot allocation aims to distribute airport slots to the airlines under given procedures and rules. The objectives of slot allocation are to minimize the total displacements of slot requests, and/or to maximize airline's preferences. Research efforts have been devoted to slot allocation in a single airport over decades. Slot allocation for a Multiple-Airport System (MAS) has been less addressed. In a single airport slot allocation, airport capacity is the only resource that airlines compete for; while in an MAS, there are several resources that should be considered: airport capacity, terminal airspace and fixes capacity. This paper proposes an MAS slot allocation model that incorporates airline fairness. The objective of the model is to minimize the total slot displacements of the MAS, subject to airport capacity constraints, fixes capacity constraints, turnaround time constraints, and fairness constraints. An MAS comprehensive fairness indicator is developed. The trade-off between efficiency and fairness in an MAS slot allocation problem is explored. The model is tested using the data from the MAS of Guangdong-Hong Kong-Macao Greater Bay Area. Computational results show that our model can effectively allocate the airport and airspace capacity of the MAS while considering airline fairness
Simultaneous Wind Field Measurements with Doppler Lidar, Quadrotor and Fixed-Wing UAV
No full textInternational audienceThis study compares the wind velocity field measurements obtained from a ground-based Doppler Lidar, a fixed-wing UAV equipped with a multi-hole probe, and a small quad-rotor estimating the wind from its attitude angles. Wind speed is measured up to 170m of altitude above the ground level with the Doppler Lidar. The fixed-wing UAV measured the wind speed while descending slowly from 150m AGL, and the quadrotor climbed up to 100m AGL and descent back to the ground while continuously estimating the wind. A discrete extended Kalman filter is implemented to observe the wind speed from the aircraft's GPS position, and onboard airspeed measurements. Another global optimization method is also compared side by side with Doppler Lidar and EKF estimations. All the data including the post-processing code has been open-sourced as supplementary material
Microramp wake impinging on canonical shock/boundary-layer interaction
No full textInternational audienceWe analyze the influence of microramp vortex generators (mVGs) on a canonical oblique shock wave/turbulent boundary-layer interaction (SBLI) in terms of mean flow field and unsteady dynamics. The flow configuration of our wall-resolved large-eddy simulations (LES) reproduces the experiment of Bo et al. [“Experimental investigation of the micro-ramp based shock wave and turbulent boundary-layer interaction control,” Phys. Fluids 24, 055110 (2012)]: a rake of microramps is inserted upstream of the SBLI, protruding by 0.476δ in a turbulent boundary layer (TBL) at free-stream Mach number M = 2.7 and corresponding to a Reynolds number based on the displacement thickness of Reθ=3600. The long integration time of 1672 Lsep/U∞ allows an accurate characterization of the low-frequency dynamics of the SBLI under the influence of the microramps. With respect to the reference SBLI without control devices, the mean flow field shows a new spatial organization of the recirculation bubble due to the mVGs' wake. The alternating high and low-speed zones in the near-wall region of the incoming TBL, induced by the counter-rotating streamwise vortices generated by the mVGs, trigger spanwise corrugations of the separation and reattachment lines and locally alter the reverse flow region. Tornado-like vortices are found in the vicinity of these zones, yielding a new fluid collection mechanism of the reverse flow region. These vortices redirect the fluid coming from regions outside of the wake in the incoming TBL to three key spanwise exit locations located in between the mVGs and at their centerline. Interestingly, power spectral densities of wall-pressure probes show a damping of the low-frequency dynamics of the reflected shock foot for spanwise stations aligned with the mVGs' wake, whereas this activity appears to be reinforced in the planes located in between the mVGs. However, we found no evidence of unsteady forcing linked to the high-frequency shedding of the coherent structures developing in the wake of the microramps. Dynamic mode decomposition highlights a significant change in the low-frequency dynamics, mostly affecting the mass budget of the recirculation bubble. The breathing of the recirculation zone that occurs at StL=0.1 for the SBLI without control devices (with StL=fLsep/U∞) appears to shift toward a lower frequency of StL=0.05. Remembering that the reflected shock foot motion is related to frequencies in the range StL=[0.03−0.05], the SBLI with upstream mVGs seems to highlight a synchronization of this motion with the breathing of the separation bubble
Formulation of the measurement problem and application to antenna measurement correction
No full textInternational audienceAfter designing and prototyping phases, the antenna measurement process is run in order to assess and optimize the antenna performances. However the measurement can be tainted with errors coming from the measurement room. It is then crucial to erase or mitigate those errors. A new formulation of the measurement problem is introduced in this article: the measurement can be described as an angular convolution between the field radiated by the antenna and the field corresponding to the radiation of the probe in the measurement environment
Towards AI-automated TEM
No full textInternational audienceTransmission electron microscopes, like other scientific instruments, are becoming more and more complex. Take, for example, the I2TEM in Toulouse, a dedicated TEM for electron holography and in-situ studies (HF-3300 C from Hitachi) which has a cold-field emission gun, 9 lenses, 4 apertures, 4 biprisms, 18 pivot points to align and almost as many elements in the corrector. Operation involves over one hundred configurable parameters but with approximately 10^300 possible configurations, one wonders if the instrument is used to its highest capability.To address this complexity, we first developed full computer control of the microscope. Hitachi supplied the access to every single element (even aperture positions, deflector currents and alignment) and details of the communication protocol. This allowed us to develop dynamic automation of the microscope to stabilize the specimen and hologram alignment through traditional control and feedback loops in real-time. But to go further, we wondered if the computer could take complete control of the microscope according to the user’s needs using artificial intelligence (AI).Machine Learning, such as Convolutional Neural Networks (CNN), are gradually replacing older forms of automation in other sectors. We created an API to automatically change the microscope parameters whilst acquiring images. This enabled us to create training datasets for matching the configuration to the images produced by the microscope. Because most configurations would not create an image on the screen, we first aligned the TEM and then randomly shifted the parameters around their respective values. This allowed us to predict image characteristics based on the microscope configuration, as well as configurations that satisfied specific image characteristics. In parallel, we have developed a realistic simulation of the I2TEM to produce a dataset of virtual experiments.Users are primarily interested in what one can call meta-parameters, such as beam size, beam position, focus and magnification, rather than the microscope configuration itself. Control of the microscope should therefore be in these terms. We use a variational auto-encoder for this, which allows us to encode a picture into only a few parameters, including limitations to ensure that they are intelligible by humans. Then, the user can manipulate the encoded image and we can train a fully connected model to predict a configuration in which the output image has a similar encoding.The aim is to integrate the whole solution into an application relying on reinforcement learning to allow the microscopist to first set the desired image parameters, then let the model iteratively try to find the best configuration to obtain those meta-parameters on the encoded output of the microscope. We will present results for some test cases of practical use
Trajectory Optimization for Fully Actuated Hexacopters : Enhancing Maneuverability and Applications
No full textInternational audienceTrajectory optimization is a challenging task in the robotics community. Several factors need to be taken into account when generating a feasible optimized trajectory. The optimization process heavily relies on the dynamic model of the system. Currently, there are various drone designs available, categorized based on their actuation status. In this study, we apply a trajectory optimization technique to a fully actuated hexacopter (FA-Hex), which is a new application to the best of our knowledge. This type of vehicle has been successfully integrated into several practical applications. Unlike the under-actuated hexacopter (UA-Hex), the FA-Hex can perform maneuvers with minimal banking angles, significantly enhancing the drone's maneuverability. Our research focuses specifically on trajectory optimization for the FA-Hex and demonstrates the adaptability of our method to different scenarios. We discuss two specific applications: a drone filming without a gimbal joint and a drone with a cable-suspended pendulum. We compare the simulation results with the UA-Hex model to highlight the differences in maneuverability between the two systems. The trajectory optimization is performed offline using CasADi in the MATLAB framework
Bio-Inspired 3D Flocking Algorithm with Minimal Information Transfer for Drones Swarms
No full textInternational audienceThis article introduces a bio-inspired 3D flocking algorithm for a drone swarm, built upon a previously established 2D model, which has proven to be effective in promoting stability, alignment, and distance variation between agents within large groups of agents. The study highlights how the incorporation of a vertical interaction between agents and the acquisition by each agent of a minimal amount of information about their most influential neighbor impacts the collective behavior of the swarm. Additionally, we present a comprehensive investigation of the impacts of the intensity of alignment and attraction interactions on the collective motion patterns that emerge at the group level. These results, mostly conducted in a validated simulator, have significant implications for designing efficient UAV swarm systems and using collective patterns, or phases, in operational contexts such as corridor tracking, surveillance, and exploration. Further research will explore the effectiveness and efficiency of this UAV swarm flocking algorithm, as well as its ability to ensure safe transitions between collective phases in different operational contexts
Optimizing air-rail travel connections: A data-driven delay management strategy for seamless passenger journeys
No full textInternational audienceIn the world of modern travel, where multimodal trips are becoming increasingly common, flight or train delays can jeopardise passengers' journeys by threatening connections. To address this issue, we present a delay management strategy on a multimodal network that involves seamless collaboration between air and rail transportation stakeholders. The objective is to minimise the total delay experienced by passengers at their final destination by rescheduling flights and trains at a tactical level. The decision whether to hold a train or a flight for connecting passengers depends on the available re-accommodation options. We propose an integer linear programming formulation of the problem at the network level, considering real-world constraints such as train station and airport capacities, minimum aircraft turnaround time, and flight slot adherence. To demonstrate the potential of this approach, we dive into a data-driven case study covering 496 airports, including three major hubs and 72 train stations across Europe. We simulate an incident on the French rail network that causes significant delays at Paris-CDG station. The results show that delaying 5% of departing flights at Paris-CDG airport by 13 minutes on average could reduce the number of stranded passengers at the airport by 71%. Such a decrease translates into a 40% reduction in the total delay experienced by passengers at their destination. This work highlights the potential benefits of air-rail integration, and the importance of information sharing between stakeholders to improve passenger journey reliability