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Modélisation et optimisation multidisciplinaire robuste de l'avion dans le système du transport aérien
No full textFor decades, the economic stakes associated with the design, development and operations of aircraft have been strong drivers for pursuing technological and operational efforts to reduce aircraft fuel consumption. Since the Grenelle de l'environnement and the establishment of the Conseil pour la Recherche Aéronautique Civile (CORAC) in 2008, both environmental concerns and ambitions have further exacerbated the expectations of the air transport system (ATS) towards sustainable development. Finally, the widespread awareness, during COP 21 in Paris, of the climate urgency makes it necessary to bring together all the knowledge and know-how to decarbonize air transport. Aircraft optimization is an essential part of its design and oper- ations, and it involves multiple disciplines. Multi- Disciplinary Optimization (MDO) processes and methods have steadily advanced since they were first developed and used in the scientific community and in the industry in the 1980s. They are now increasingly used at every stage of new aircraft design. The objective of their iterative approach to the problem is to converge towards better solutions. It tends to be used in all phases of the process, from automated aero- structural multidisciplinary analyses based on models of different levels of fidelity, to the overall industrial process aimed at meeting the needs of airlines companies. Despite these efforts, the aircraft is in fact hardly ever operated on the conditions that are defined in the design requirements (technical, geometrical, operational, and regulatory) and that are used for optimizing it from the very early stage of its development process. This implies a loss of optimality of the ATS when fulfilling its fundamental mission: to carry passengers, freight, and mail from one place to another through air transportation. Having noticed this, we ask the following question: is it possible to improve the airplane and make it more robust, from an operational point of view, by tying the link, from the conceptual design phase, with the ATS and its other components, through new MDO formulations? To answer this question, we propose the following methodology. First, we position the aircraft in the ATS in order to better understand and better represent how the aircraft contribute to the ATS activity, but also in order to capture how the operations influence the aircraft design. Our second step consists in gathering data to observe real aircraft operations, such as those obtained via flight data recorder, in order to create meaningful models, and an overall aircraft design (OAD) tool to simulate the conceptual design process of an aircraft. During the last step, we focus on three use cases. The first quantifies the loss of operational optimality due to range variability. The second use case tackles the take-off distance requirements and turn them from design constraints to design variables in the MDO formulation. Finally, the last use case considers cruise variabilities, as observed and modelled, in the conceptual design process. The first chapter of this thesis presents a review of the academic and industrial practices with regards to aircraft design and the representation of the ATS, a synthesis of available operational data and conceptual airplane design tools, as well as a state of the art on how the operations are taken into account in the design process and on the mathematical methods and tools used in this thesis. The second chapter addresses the calibration of the MARILib aircraft conceptual tool, and the processing of the operational data used, how we enrich them and which models we build from them. The third and last chapter describes the three use cases. Finally, a conclusion recalls the main contributions of this thesis, discusses its limits, and presents the related perspectives.Les enjeux économiques associés à la conception, au développement et à l'exploitation des avions sont depuis des décennies des moteurs forts pour poursuivre les efforts technologiques et opérationnels visant à réduire la consommation des avions. Depuis un peu plus d'une décennie et suite au Grenelle de l'Environnement et la mise en place du Conseil pour la Recherche Aéronautique Civile (CORAC), les inquiétudes et ambitions environnementales ont encore exacerbé le besoin de s'inscrire dans une perspective de développement durable du transport aérien. Enfin, la large prise de conscience, lors de la COP 21 à Paris, de l'urgence climatique impose comme une nécessité de réunir toutes les connaissances et les savoir-faire pour décarbonner le transport aérien. L'optimisation de l'avion est un élément essentiel de sa conception et son exploitation et implique de multiples disciplines. Les processus et méthodes d'optimisation multidisciplinaires (MDO) n'ont pas cessé de progresser depuis le début de leur utilisation industrielle dans les années 80 et sont désormais de plus en plus utilisés à chaque étape de la conception d'un nouvel avion. Leur approche itérative du problème visant à converger vers la meilleure solution tend à apparaître à tous les niveaux, des analyses multidisciplinaires aéro-structurales automatisées s'appuyant sur des modèles de différents niveaux de fidélité jusqu'au processus industriel global visant à répondre au besoin des compagnies aériennes. Malgré ces efforts, nous constatons que l'avion est en pratique rarement exploité précisément dans les conditions définies dans les exigences de conception (techniques, géométriques, opérationnelles et réglementaires) et utilisées pour son optimisation dès les premières phases de son processus de développement. Cela est une source de perte d'optimalité pour le système du transport aérien (STA) vis-à-vis de sa mission fondamentale : transporter des passagers ou des marchandises d'un point à un autre par la voie des airs. Ces observations nous amènent à poser à la question suivante : est-il possible de rendre l'avion plus robuste d'un point de vue opérationnel en renforçant, dès les phases de design conceptuel, le lien avec le STA, par de nouvelles formulations MDO? Nous proposons la méthodologie suivante. Dans la première étape, nous repositionnons l'avion dans le STA afin de mieux représenter comment il contribue à son activité mais aussi comment le monde opérationnel influence son design. La deuxième étape vise à réunir des données représentant l'exploitation réelle des avions afin d'en tirer des modèles pertinents, et un outil multidisciplinaire de design conceptuel simulant le processus de conception d'un avion. Lors de la dernière étape, nous étudions trois cas d'application. Le premier étudie la perte d'optimalité opérationnelle due aux variabilités dans les distances de vol. Le deuxième aborde les exigences au décollage en les faisant passer d'un statut de contraintes à un statut de variables de design dans la formulation MDO. Enfin le troisième cas d'application prend en compte les variabilités opérationnelles en croisière, observées et modélisées, dans le processus de design conceptuel. Le premier chapitre de cette thèse présente une analyse de l'existant industriel et académique vis-à-vis de la conception avion et de la représentation du STA, une revue des bases de données opérationnelles existantes et des outils de design conceptuel, ainsi que l'état de l'art relatif à la prise en compte des opérations dans la conception avion et aux méthodes utilisées dans le reste de la thèse. Le deuxième chapitre traite de la calibration de l'outil de conception MARILib, des données opérationnelles utilisées et des modèles qu'elles nous permettent de construire. Le troisième et dernier chapitre présente les trois cas d'application étudiés. Enfin, une conclusion revient sur les principales contributions de cette thèse, les limites et les perspectives associées
Using TDCP Measurements in a low-cost PPP-IMU hybridized filter for real-time applications
No full textInternational audienceMuch of the focus in current positioning systems is on high accuracy, oriented by developing powerful and computationallyheavy algorithms; however, this approach is not compatible with systems that require real-time capabilities. Furthermore, mostPrecise Point Positioning (PPP) algorithms use ambiguity estimation techniques in order to leverage the precision of carrier phasemeasurements. We developed a low-cost PPP algorithm fused with an Inertial Measurement Unit that uses Time DifferencedCarrier Phase (TDCP) measurements which remove the need to resolve the ambiguities while still benefiting from the mostaccurate Global Navigation Satellite System (GNSS) observables. To maximize the accuracy and continuity of the positioningsolution, we designed a tightly coupled Extended Kalman Filter that is capable of processing triple frequency code, Doppler,and carrier phase or TDCP measurements. We observed that the filter which uses TDCP measurements performs 52% betterthan the solution with solely the code and Doppler measurements in deep urban conditions and 5% in open-sky conditions whiletaking 66% less computation time (in MATLAB) than the filter with carrier phase measurements. The results demonstratethat TDCP measurements are a solid alternative to carrier phase measurements, especially in deep urban conditions, for anycomputationally limited applications while maintaining a high level of accuracy
La voix des Femmes au sein de l’AFIHM
No full textInternational audienceOn the first anniversary of changing the name of AFIHM from "Association Francophone de l’Interaction HOMME-Machine" (French-Speaking Association for MAN-Machine Interaction) to "Association Francophone de l’Interaction HUMAIN-Machine" (French-Speaking Association for HUMAN-Machine Interaction), we conducted a series of interviews about the role of women within AFIHM. We interviewed 11 women and non-binary people from different French-speaking research laboratories and universities in France and around the world, at different stages of their careers (from doctoral students to Honorary Professors and Research Directors), and coming from different backgrounds. We asked these women about their experiences as well as the difficulties and opportunities they have encountered during their careers. We also asked them to propose actions that could encourage women in the field of HCI. We hope that this work presented at AltIHM will contribute to making the voices of women in our field heard and encourage young women to become interested in and embark on careers in HCI research.À l’occasion du premier anniversaire de changement de nom de l’AFIHM de "Association Francophone de l’Interaction HOMME-Machine" en "Association Francophone de l’Interaction HUMAIN-Machine", nous avons mené une série d’entretiens sur la place des femmes au sein de l’AFIHM. Nous avons interviewé 11 femmes et personnes non binaires provenant de différents laboratoires de recherche et universités francophones en France et dans le monde, à différents stades de leurs carrières (de doctorantes à Professeures honoraires et Directrices de Recherche), venant de formations différentes et ayant des origines différentes. Nous avons questionné ces femmes sur leurs vécus ainsi que les difficultés et opportunités qu’elles ont rencontrées durant leur carrière. Nous leur avons aussi demandé de proposer des actions qui puissent encourager les femmes dans le domaine de l’IHM. Nous espérons que ce travail présenté à AltIHM contribuera à faire entendre la voix des femmes de notre domaine et à encourager les jeunes femmes à s’intéresser à et se lancer dans des carrières de recherche en IH
Rotorcraft Low Noise Trajectory Design: a focus on RACER
No full textInternational audienceAviation is heading towards more sustainability. In this context, this paper proposes a methodology to design low noise trajectories for rotary-wing aircraft. A dedicated algorithmic scheme is presented, embedding Airbus Helicopters internal noise footprint computation chain. This software is able to accurately model rotorcraft noise emission, and perform realistic impact assessment on population. The proposed optimization method has been tested on several real-world instances, predicting notable noise reductions by flying such optimized low noise procedures. Furthermore, additional acoustic gains can be obtained thanks to a supplementary degree of freedom brought by a new innovative rotorcraft configuration
From Dual Connections to Almost Contact Structures
No full textInternational audienceA dualistic structure on a smooth Riemaniann manifold M is a triple ( M, g, ∇) with g aRiemaniann metric and ∇ an affine connection generally assumed to be torsionless. From g and ∇,dual connection ∇∗ can be defined. In this work, we give conditions on the basis of this notion for amanifold to admit an almost contact structure and some related structures: almost contact metric,contact, contact metric, cosymplectic, and co-Kähler in the three-dimensional case
Rethinking LEO Constellations Routing with the Unsplittable Multi-Commodity Flows Problem
No full textInternational audienceThis study investigates the performance of an innovative routing protocol inspired by the Unsplittable Multi-Commodity Flow (UMCF) problem. LEO routing schemes are often based on Shortest Path (SP) algorithms, the Floyd-Warshall algorithm is usually chosen to compute these network paths within the constellation and their end-toend latency. Instead of considering latency as a criterion, we seek to optimize the overall amount of IP traffic crossing the constellation. This criterion can be optimized by considering the Unsplittable Multi Commodity Flow problem associated with the system. To solve this problem, we use a heuristic algorithm based on randomized rounding that was shown to return solutions of good quality of the Unsplittable Multi Commodity Flow problem in the optimization literature. Using network simulation over Telesat constellation, we show this proposal significantly reduces the overall congestion level compared to the standard SP routing schemes
Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation
No full textConvolutional Neural Network (CNN) have been widely used in image classification. Over the years, they have also benefited from various enhancements and they are now considered as state of the art techniques for image like data. However, when they are used for regression to estimate some function value from images, fewer recommendations are available. In this study, a novel CNN regression model is proposed. It combines convolutional neural layers to extract high level features representations from images with a soft labelling technique. More specifically, as the deep regression task is challenging, the idea is to account for some uncertainty in the targets that are seen as distributions around their mean. The estimations are carried out by the model in the form of distributions. Building from earlier work, a specific histogram loss function based on the Kullback-Leibler (KL) divergence is applied during training. The model takes advantage of the CNN feature representation and is able to carry out estimation from multi-channel input images. To assess and illustrate the technique, the model is applied to Global Navigation Satellite System (GNSS) multi-path estimation where multi-path signal parameters have to be estimated from correlator output images from the I and Q channels. The multi-path signal delay, magnitude, Doppler shift frequency and phase parameters are estimated from synthetically generated datasets of satellite signals. Experiments are conducted under various receiving conditions and various input images resolutions to test the estimation performances quality and robustness. The results show that the proposed soft labelling CNN technique using distributional loss outperforms classical CNN regression under all conditions. Furthermore, the extra learning performance achieved by the model allows the reduction of input image resolution from 80x80 down to 40x40 or sometimes 20x20
Multi-DMEs for alternative position, navigation and timing (A-PNT)
No full textInternational audienceDistance measuring equipment (DME/DME) as the main reversionary method provides alternative positioning, navigation and timing (A-PNT) services for use during a Global Navigation Satellite System (GNSS) outage. Considering the geometry limitation of DME/DME, multi-DMEs with better geometry can be used to increase the accuracy and integrity performance of positioning. This paper discusses the opportunities and challenges related to use of multi-DMEs as an alternate source of positioning, navigation and timing. To support the performance for A-PNT, the basic idea is considering the existing installed equipment. In this paper, barometer altimeter and TACAN are used to help improve the performance of A-PNT provided by multi-DMEs both in accuracy and integrity. Based on the database of EUROCONTROL, the test results demonstrate that 79⋅7% of a reference area roughly matching with the continental European locations achieve RNP 1 using multi-DMEs when the DME measurement accuracy is 0⋅2 NM (95%). When the DME measurement accuracy is 0⋅1 NM (95%), 87⋅9% of the reference area can achieve RNP 1 using multi-DMEs. The usage of barometer/TACAN measurements aided multi-DMEs improves the performance of the accuracy and integrity monitoring
An MINLP and a continuous optimization formulations for aircraft conflict avoidance via heading and speed deviations
No full textHow Attention Deep Learning Can Improve Copa Congestion Control Performance
No full textInternational audienceMost modern congestion control algorithms, that aim to optimize delay and throughput, exploit more metrics than the sole packet loss congestion information. These additional metrics are mostly based on the round trip time evolution and allow congestion controls to reach better performance, in particular on wireless and cellular links as demonstrated by Copa, BBR, or REMY. Basically, these metrics allow congestion control to estimate the queuing level of the path and its evolution, to assess the presence of congestion. Actually, a good estimation of this level obviously prevents congestion losses, but also allows assessing a ratio of error link losses among the whole observed losses. The consistency and accuracy of these metrics are key to good congestion control performance, and this explains, for instance, the good performance of Copa currently in production at Facebook. However, these metrics remain challenging and the quest of an accurate and practical estimation seems complex. This paper investigates how a novel deep learning algorithm, known as Attention, can help in assessing queuing evolution and status on an end-to-end path. Among others, we focus on the evolution of the total time spent by packets in the buffers, which is the key metric of Copa. The results unequivocally demonstrate a better accuracy of this metric used by Copa