Les erreurs des modèles de prévision numérique du temps (PNT) peuvent être réduites par des méthodes de post-traitement (dites d'adaptation statistique ou AS) construisant une relation statistique entre les observations et les prévisions. L'objectif de cette thèse est de construire des AS de prévisions de vent pour la France sur la grille de plusieurs modèles de PNT, pour les applications opérationnelles de Météo-France en traitant deux problèmes principaux. Construire des AS sur la grille de modèles de PNT, soit plusieurs milliers de points de grille sur la France, demande de développer des méthodes rapides pour un traitement en conditions opérationnelles. Deuxièmement, les modifications fréquentes des modèles de PNT nécessitent de mettre à jour les AS, mais l'apprentissage des AS requiert un modèle de PNT inchangé sur plusieurs années, ce qui n'est pas possible dans la majorité des cas.Une nouvelle analyse du vent moyen à 10 m a été construite sur la grille du modèle local de haute résolution (2,5 km) de Météo-France, AROME. Cette analyse se compose de deux termes: une spline fonction de la prévision la plus récente d'AROME plus une correction par une spline fonction des coordonnées du point considéré. La nouvelle analyse obtient de meilleurs scores que l'analyse existante, et présente des structures spatio-temporelles réalistes. Cette nouvelle analyse, disponible au pas horaire sur 4 ans, sert ensuite d'observation en points de grille pour construire des AS.Des AS de vent sur la France ont été construites pour ARPEGE, le modèle global de Météo-France. Un banc d'essai comparatif désigne les forêts aléatoires comme meilleure méthode. Cette AS requiert un long temps de chargement en mémoire de l'information nécessaire pour effectuer une prévision. Ce temps de chargement est divisé par 10 en entraînant les AS sur des points de grille contigü et en les élaguant au maximum. Cette optimisation ne déteriore pas les performances de prévision. Cette approche d'AS par blocs est en cours de mise en opérationnel.Une étude préalable de l'estimation du « continuous ranked probability score » (CRPS) conduit à des recommandations pour son estimation et généralise des résultats théoriques existants. Ensuite, 6 AS de 4 modèles d'ensemble de PNT de la base TIGGE sont combinées avec les modèles bruts selon plusieurs méthodes statistiques. La meilleure combinaison s'appuie sur la théorie de la prévision avec avis d'experts, qui assure de bonnes performances par rapport à une prévision de référence. Elle ajuste rapidement les poids de la combinaison, un avantage lors du changement de performance des prévisions combinées. Cette étude a soulevé des contradictions entre deux critères de choix de la meilleure méthode de combinaison : la minimisation du CRPS et la platitude des histogrammes de rang selon les tests de Jolliffe-Primo. Il est proposé de choisir un modèle en imposant d'abord la platitude des histogrammes des rangs. / Errors of numerical weather prediction (NWP) models can be reduced thanks to post-processing methods (model output statistics, MOS) that build a statistical relationship between the observations and associated forecasts. The objective of the present thesis is to build MOS for windspeed forecasts over France on the grid of several NWP models, to be applied on operations at Météo-France, while addressing the two main issues. First, building MOS on the grid of some NWP model, with thousands of grid points over France, requires to develop methods fast enough for operational delays. Second, requent updates of NWP models require updating MOS, but training MOS requires an NWP model unchanged for years, which is usually not possible.A new windspeed analysis for the 10 m windspeed has been built over the grid of Météo-France's local area, high resolution (2,5km) NWP model, AROME. The new analysis is the sum of two terms: a spline with AROME most recent forecast as input plus a correction with a spline with the location coordinates as input. The new analysis outperforms the existing analysis, while displaying realistic spatio-temporal patterns. This new analysis, now available at an hourly rate over 4, is used as a gridded observation to build MOS in the remaining of this thesis.MOS for windspeed over France have been built for ARPEGE, Météo-France's global NWP model. A test-bed designs random forests as the most efficient MOS. The loading times is reduced by a factor 10 by training random forests over block of nearby grid points and pruning them as much as possible. This time optimisation goes without reducing the forecast performances. This block MOS approach is currently being made operational.A preliminary study about the estimation of the continuous ranked probability score (CRPS) leads to recommendations to efficiently estimate it and to generalizations of existing theoretical results. Then 4 ensemble NWP models from the TIGGE database are post-processed with 6 methods and combined with the corresponding raw ensembles thanks to several statistical methods. The best combination method is based on the theory of prediction with expert advice, which ensures good forecast performances relatively to some reference forecast. This method quickly adapts its combination weighs, which constitutes an asset in case of performances changes of the combined forecasts. This part of the work highlighted contradictions between two criteria to select the best combination methods: the minimization of the CRPS and the flatness of the rank histogram according to the Jolliffe-Primo tests. It is proposed to choose a model by first imposing the flatness of the rank histogram.

Dans cette thèse, nous nous intéressons à la représentation et à la prise en compte des incertitudes dans les systèmes de prévision hydrologique probabilistes à moyen-terme. Ces incertitudes proviennent principalement de deux sources : (1) de l’imperfection des prévisions météorologiques (utilisées en intrant de ces systèmes) et (2) de l’imperfection de la représentation du processus hydrologique par le simulateur pluie-débit (SPQ) (au coeur de ces systèmes).La performance d’un système de prévision probabiliste s’évalue par la précision de ses prévisions conditionnellement à sa fiabilité. L’approche statistique que nous suivons procure une garantie de fiabilité à condition que les hypothèses qu’elle implique soient réalistes. Nous cherchons de plus à gagner en précision en incorporant des informations auxiliaires.Nous proposons, pour chacune des sources d’incertitudes, une méthode permettant cette incorporation : (1) un post-traitement des prévisions météorologiques s’appuyant sur la propriété statistique d’échangeabilité et permettant la prise en compte de plusieurs sources de prévisions, ensemblistes ou déterministes ; (2) un post-traitement hydrologique utilisant les variables d’état des SPQ par le biais d’un modèle Probit arbitrant entre deux régimes hydrologiques interprétables et permettant ainsi de représenter une incertitude à variance hétérogène.Ces deux méthodes montrent de bonnes capacités d’adaptation aux cas d’application variés fournis par EDF et Hydro-Québec, partenaires et financeurs du projet. Elles présentent de plus un gain en simplicité et en formalisme par rapport aux méthodes opérationnelles tout en montrant des performances similaires. / In this thesis, we are interested in representing and taking into account uncertainties in medium term probabilistic hydrological prediction systems.These uncertainties mainly come from two sources: (1) from the imperfection of meteorological forecasts (used as inputs to these systems) and (2) from the imperfection of the representation of the hydrological process by the rainfall-runoff simulator (RRS) (at the heart of these systems).The performance of a probabilistic forecasting system is assessed by the sharpness of its predictions conditional on its reliability. The statistical approach we follow provides a guarantee of reliability if the assumptions it implies are complied with. We are also seeking to incorporate auxilary information to get sharper.We propose, for each source of uncertainty, a method enabling this incorporation: (1) a meteorological post-processor based on the statistical property of exchangeability and enabling to take into account several (ensemble or determistic) forecasts; (2) a hydrological post-processor using the RRS state variables through a Probit model arbitrating between two interpretable hydrological regimes and thus representing an uncertainty with heterogeneous variance.These two methods demonstrate adaptability on the various application cases provided by EDF and Hydro-Québec, which are partners and funders of the project. Those methods are moreover simpler and more formal than the operational methods while demonstrating similar performances.

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Compressed images are used very frequently in interactive applications in digital video broadcasting. New methods increasing efficiency of the image transmission in digital video broadcasting networks are proposed. Adaptive spatial filtering methods have been proposed for enhancement of the visual perception of the compressed images. New optimalization method is based on application of the filtering algorithms on more compressed images (data size are reduced). Visual quality enhancement is processed in interactive application. Further, new compression methods JPEG2000 and H.264 for image compression have been analysed. Novel compound image compression method for standard and high spatial television resolution is proposed in the thesis.

Topology optimization has seen rapid developments in its field with algorithms getting better and faster all the time. These new algorithms help reduce the lead time from concept development to a finished product. Simulation and post-processing of geometry are one of the major developmental costs. Post-processing of this geometry also takes up a lot of time and is dependent on the quality of the geometry output from the solver to make the product ready for rapid prototyping or final production. The work done in this thesis deals with the post-processing of the results obtained from topology optimization algorithms which output the result as a 2D image. A suitable methodology is discussed where this image is processed and converted into a CAD geometry all while minimizing deviation in geometry, compliance and volume fraction. Further on, a validation of the designs is performed to measure the extracted geometry's deviation from the post-processed result. The workflow is coded using MATLAB and uses an image-based post-processing approach. The proposed workflow is tested on several numerical examples to assess the performance, limitations and numerical instabilities. The code written for the entire workflow is included as an appendix and can be downloaded from the website:https://github.com/M87K452b/postprocessing-topopt.

This presentation is intended to inform about the enhancements of Creo Simulate and the Roadmap for the future.

Additive Manufacturing, and specifically powder bed fusion processes, have advanced rapidly in recent years. Selective Laser Melting in particular has been adopted in a variety of industries from biomedical to aerospace because of its capability to produce complex components with numerous alloys, including stainless steels, nickel superalloys, and titanium alloys. Post-processing is required to treat or solve metallurgical issues such as porosity, residual stresses, and surface roughness. Because of the geometric complexity of SLM produced parts, the reduction of surface roughness with conventional processing has proven especially challenging. In this Thesis, two processes, abrasive flow machining and ultrasonic shot peening, are evaluated as surface finishing processes for selective laser melted 316L. Results of these experiments indicate that AFM can reliably polish as-built internal passages to 1 µm Ra or better but is unsuitable for passages with rapidly expanding or contracting cross-sections. AFM can also polish relatively small passages, but lattice components may prove too complex for effective processing. USP cannot achieve such low surface roughness, but it is a versatile process with multiple advantages. Exterior surfaces were consistently processed to 1.7 to 2.5 µm Ra. Interior surfaces experienced only partial processing and demonstrated high geometric dependence. USP significantly hardened the surface, but steel media hardened the surface better than ceramic media did. Both AFM and USP are recommended processes for the surface finishing of SLM manufactured parts. Good engineering judgement is necessary to determine when to use these processes and how to design for post-processing.

As the fidelity of computer generated imagery has increased, the need to digitally create convincing natural phenomena like fluids has become fundamental to the entertainment production industry. Because fluids are complex, the underlying physics must be computationally simulated. However, because a strictly physics-based approach is both computationally expensive and difficult to control, it does not lend itself well to the way artists and directors like to work. Directors require control to achieve their specific artistic vision. Furthermore, artistic workflows rely on quick iteration and the ability to apply changes late in the production process. In this dissertation we present novel techniques in adaptive simulation and fluid post-processing to improve artistic workflows for fluid simulation. Our methods reduce fluid simulation iteration time and provide a new way for artists to intelligently resize a wide range of volumetric data including fluid simulations. To reduce iteration time, we present a more cache-friendly linear octree structure for adaptive fluid simulation that reduces the overhead of previous octree-based methods. To increase the viability of reusable effects libraries, and to give artists intuitive control over simulations late in the production process we present a ``fluid carving" technique. Fluid carving uses seam carving methods to allow intelligent resizing on a variety of fluid phenomena without the need for costly re-simulation. We present methods that improve upon traditional seam carving approaches to address issues with scalability, non-rectangular boundaries, and that generalize to a variety of different visual effects data like particles, polygonal meshes, liquids, smoke, and fire. We achieve these improvements by guiding seams along user-defined lattices that can enclose regions of interest defined as OpenVDB grids with a wide range of shapes. These techniques significantly improve artist workflows for fluid simulation and allow visual entertainment to be produced in a more intuitive, cost-effective manner.

This presentation is intended to inform about the enhancements to Creo Simulate 4.0 and the Roadmap for the future (5.0 +)

Följande studie syftar till att kartlägga planeringsprocessen och identifiera brister med den, samt ge förbättringsåtgärder för omrullningen på ett fallföretag. Genom utvecklingen av en generell konceptuell modell för att förbättra planeringsprocesser av omrullning. Under alla år har efterbehandlingsprocessen varit nedprioriterad på fallföretaget, och därmed också planeringsprocessen av den. Vid produktion av papper sker, som i många industrier, ett oväntat utfall av produkter som fått defekter under tillverkningen. Produkterna som har defekter kan oftast räddas och säljas genom att efterbehandlas, och en av dessa efterbehandlingar kallas omrullning. Att undersöka och förstå processer inom företag är avgörande för att göra förbättringar.   Studien presenterar förbättringsförslag som baserats på de brister som identifierades med planeringsprocessen. Förslagen innefattar bland annat att skapa ett effektivare IT-system, etablera tydliga kommunikationsvägar och öka engagemanget från ledningen. Dessa insatser kan öka effektiviteten, minska slöseri och bättre tillgodose kundernas behov, vilket ökar konkurrenskraften och lönsamheten inom pappersindustrin. Företaget kan implementera detta förbättringsarbete genom att tillsammans analysera och bryta ner målbilden till mindre små mål som går att uppnå på kort sikt. Baserat på insamlade data presenterar studien en konceptuell modell för att analysera och förbättra planeringsprocessen för omrullning. Förslag på vidare studier har getts, där det kan undersökas samma process på flera företag för att se om samma problematik finns där. Det är också vidare forskning att på fler företag använda den framtagna modellen för att analysera och förbättra planeringsprocesser för efterbehandling för att öka generaliserbarheten. / The following study aims to map the planning process and identify deficiencies within it, as well as provide improvement measures for the rewinding process in a case company. By developing a general conceptual model to enhance rerolling planning processes. Over the years, post-processing operations have been overseen, including the planning process associated with them. In paper production, like in many industries, defective products are generated during manufacturing. These defective products can often be salvaged and sold through post-processing, with one such process being rewinding. Examining and understanding processes within companies is crucial for making improvements. This study aims to map the planning process of rewinding and develop a conceptual model to enhance post-processing planning.   The study presents improvement suggestions based on the deficiencies identified in the planning process. The suggestions include creating a more efficient IT system, establishing clear communication channels, and increasing management involvement. These efforts can enhance efficiency, reduce waste, better meet customer needs, thereby increasing competitiveness and profitability within the paper industry. The company can implement these improvement efforts by collectively analyzing and breaking down the target vision into smaller short-term goals that can be achieved. Based on the collected data, the study presents a conceptual model for analyzing and improving the rerolling planning process. Suggestions for further studies have been provided, where the same process can be examined in multiple companies to determine if similar issues exist. Additionally, further research can be conducted in more companies using the developed model to analyze and improve post-processing planning processes, aiming to increase generalizability.