4,750 research outputs found

    Simulation architecture definition for complex systems design: A tooled methodology

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    International audienceFor the design of complex systems like in the automotive industry, the use of Model Based Systems Engineering (MBSE) is being considered as a promising solution in order to formalize and communicate information. Numerical simulation is also routinely used as a tool to answer potential design questions that arise. However the link between MBSE and simulation still needs further improvement. In this work, a tooled methodology is proposed in order to enhance the link between system architecture and numerical simulation. In a first step, a solicitation package is formalized and implemented in a SysML-based tool to define the simulation needs. In a second step, a tool that allows to define the simulation architecture and to pilot the execution of the simulation is developed. We show that thanks to the proposed process and exchange format between the system and simulation architects, model reuse and agility is improved in a complex systems design

    Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

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    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

    Supporting multidisciplinary vehicle modeling : towards an ontology-based knowledge sharing in collaborative model based systems engineering environment

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    Simulation models are widely used by industries as an aid for decision making to explore and optimize a broad range of complex industrial systems’ architectures. The increased complexity of industrial systems (cars, airplanes, etc.), ecological and economic concerns implies a need for exploring and analysing innovative system architectures efficiently and effectively by using simulation models. However, simulations designers currently suffer from limitations which make simulation models difficult to design and develop in a collaborative, multidisciplinary design environment. The multidisciplinary nature of simulation models requires a specific understanding of each phenomenon to simulate and a thorough description of the system architecture, its components and connections between components. To accomplish these objectives, the Model-Based Systems Engineering (MBSE) and Information Systems’ (IS) methodologies were used to support the simulation designer’s analysing capabilities in terms of methods, processes and design tool solutions. The objective of this thesis is twofold. The first concerns the development of a methodology and tools to build accurate simulation models. The second focuses on the introduction of an innovative approach to design, product and integrate the simulation models in a “plug and play" manner by ensuring the expected model fidelity. However, today, one of the major challenges in full-vehicle simulation model creation is to get domain level simulation models from different domain experts while detecting any potential inconsistency problem before the IVVQ (Integration, Verification, Validation, and Qualification) phase. In the current simulation model development process, most of the defects such as interface mismatch and interoperability problems are discovered late, during the IVVQ phase. This may create multiple wastes, including rework and, may-be the most harmful, incorrect simulation models, which are subsequently used as basis for design decisions. In order to address this problem, this work aims to reduce late inconsistency detection by ensuring early stage collaborations between the different suppliers and OEM. Thus, this work integrates first a Detailed Model Design Phase to the current model development process and, second, the roles have been re-organized and delegated between design actors. Finally an alternative architecture design tool is supported by an ontology-based DSL (Domain Specific Language) called Model Identity Card (MIC). The design tools and mentioned activities perspectives (e.g. decisions, views and viewpoints) are structured by inspiration from Enterprise Architecture Frameworks. To demonstrate the applicability of our proposed solution, engine-after treatment, hybrid parallel propulsion and electric transmission models are tested across automotive and aeronautic industries.Les systèmes industriels (automobile, aérospatial, etc.) sont de plus en plus complexes à cause des contraintes économiques et écologiques. Cette complexité croissante impose des nouvelles contraintes au niveau du développement. La question de la maitrise de la capacité d’analyse de leurs architectures est alors posée. Pour résoudre cette question, les outils de modélisation et de simulation sont devenus une pratique courante dans les milieux industriels afin de comparer les multiples architectures candidates. Ces outils de simulations sont devenus incontournables pour conforter les décisions. Pourtant, la mise en œuvre des modèles physiques est de plus en plus complexe et nécessite une compréhension spécifique de chaque phénomène simulé ainsi qu’une description approfondie de l’architecture du système, de ses composants et des liaisons entre composants. L’objectif de cette thèse est double. Le premier concerne le développement d’une méthodologie et des outils nécessaires pour construire avec précision les modèles de simulation des architectures de systèmes qu’on désire étudier. Le deuxième s’intéresse à l’introduction d’une approche innovante pour la conception, la production et l’intégration des modèles de simulations en mode « plug and play » afin de garantir la conformité des résultats aux attentes, notamment aux niveaux de la qualité et de la maturité. Pour accomplir ces objectifs, des méthodologies et des processus d’ingénierie des systèmes basés sur les modèles (MBSE) ainsi que les systèmes d’information ont été utilisés. Ce travail de thèse propose pour la première fois un processus détaillé et un outil pour la conception des modèles de simulation. Un référentiel commun nommé « Modèle de carte d'identité (MIC) » a été développé pour standardiser et renforcer les interfaces entre les métiers et les fournisseurs sur les plans organisationnels et techniques. MIC garantit l’évolution et la gestion de la cohérence de l’ensemble des règles et les spécifications des connaissances des domaines métiers dont la sémantique est multiple. MIC renforce également la cohérence du modèle et réduit les anomalies qui peuvent interférer pendant la phase dite IVVQ pour Intégration, Vérification, Validation, Qualification. Finalement, afin de structurer les processus de conception des modèles de simulation, le travail s’est inspiré des cadres de l’Architecture d’Entreprise en reflétant les exigences d’intégration et de standardisation du modèle opératoire de l’entreprise. Pour valider les concepts introduits dans le cadre de cette thèse, des études de cas tirés des domaines automobile et aérospatiale ont été réalisées. L'objectif de cette validation est d'observer l'amélioration significative du processus actuel en termes d'efficacité, de réduction de l'ambiguïté et des malentendus dans la modélisation et la simulation du système à concevoir

    Accelerating the pace of protein functional annotation with intel xeon phi coprocessors

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    © 2002-2011 IEEE. Intel Xeon Phi is a new addition to the family of powerful parallel accelerators. The range of its potential applications in computationally driven research is broad; however, at present, the repository of scientific codes is still relatively limited. In this study, we describe the development and benchmarking of a parallel version of {\mmb e}FindSite, a structural bioinformatics algorithm for the prediction of ligand-binding sites in proteins. Implemented for the Intel Xeon Phi platform, the parallelization of the structure alignment portion of {\mmb e}FindSite using pragma-based OpenMP brings about the desired performance improvements, which scale well with the number of computing cores. Compared to a serial version, the parallel code runs 11.8 and 10.1 times faster on the CPU and the coprocessor, respectively; when both resources are utilized simultaneously, the speedup is 17.6. For example, ligand-binding predictions for 501 benchmarking proteins are completed in 2.1 hours on a single Stampede node equipped with the Intel Xeon Phi card compared to 3.1 hours without the accelerator and 36.8 hours required by a serial version. In addition to the satisfactory parallel performance, porting existing scientific codes to the Intel Xeon Phi architecture is relatively straightforward with a short development time due to the support of common parallel programming models by the coprocessor. The parallel version of {\mmb e}FindSite is freely available to the academic community at www.brylinski.org/efindsite
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