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Breaking onset and breaking strength of focused wave packets: Linear prediction model and nonlinear numerical simulations
No full textInternational audienceThe possibility of predicting the occurrence of wave breaking and the intensity of the breaking events using linear wave models is investigated. For this purpose, a new linear breaking onset criterion is proposed, based on the definition of a linear-equivalent wave, which has the same energy and impulse as the associated nonlinear wave. The strength of breaking is characterized by the parameter introduced by Derakhtiet al. (2018) and we derive an empirical law to estimate the breaking strength from the linear-equivalent wave model. The predictive ability of this criterion is assessed through comparisons with results of fully nonlinear potential flow simulations, for focused wave packets of various characteristics. For the considered configurations, the proposed approach is able to predict the onset and strength of breaking with good accuracy
Multimodal learning–based reconstruction of high-resolution spatial wind speed fields
No full textInternational audienceWind speed at the sea surface is a key quantity for a variety of scientific applications and human activities. For its importance, many observation techniques exist, ranging from in situ to satellite observations. However, none of such techniques can capture the spatiotemporal variability of the phenomenon at the same time. Reanalysis products, obtained from data assimilation methods, represent the state-of-the-art for sea-surface wind speed monitoring but may be biased by model errors and their spatial resolution is not competitive with satellite products. In this work, we propose a scheme based on both data assimilation and deep learning concepts to process spatiotemporally heterogeneous input sources to reconstruct high-resolution time series of spatial wind speed fields. This method allows to us make the most of the complementary information conveyed by the different sea-surface information typically available in operational settings. We use synthetic wind speed data to emulate satellite images, in situ time series and reanalyzed wind fields. Starting from these pseudo-observations, we run extensive numerical simulations to assess the impact of each input source on the model reconstruction performance. We show that our proposed framework outperforms a deep learning–based inversion scheme and can successfully exploit the spatiotemporal complementary information of the different input sources. We also show that the model can learn the possible bias in reanalysis products and attenuate it in the output reconstructions
Hierarchical System of Digital Twins: A Holistic Architecture for Swarm System Analysis
No full textInternational audienceSwarm systems are being increasingly adopted for their operational capabilities and are now assigned more sensitive missions, often in unpredictable environments. Therefore, it is crucial to evaluate their performance in the face of natural or human-induced uncertainties before deployment and enhance their resilience during missions. To enable a comprehensive analysis of this system, a multi-level analysis must be conducted to capture the dynamics at the component, cluster, and swarm levels. Digital Twin (DT) offers a promising solution to address this challenge. While there are existing approaches that use digital twins to analyze complex systems, they do not take into account the specific requirements introduced by swarm configuration. This paper presents a holistic reference architecture, the Hierarchical System of Digital Twins (HSDT), which lays the groundwork for creating digital twins of swarm systems. To support this framework, we introduce the concepts of functional and aggregation hierarchies and propose a goal-oriented method for instantiating DT with a specific level of sophistication. Additionally, we present a metamodel that integrates elements of the Asset Administration Shell (AAS) data model to ensure interoperability with external standards. A prototype of HSDT was developed, and a case study was presented, focusing on analyzing spatial parameters within a swarm of Unmanned Vehicles (UVs)
Synthetic Aperture Radar Imagery Modelling and Simulation for Investigating the Composite Scattering Between Targets and the Environment
No full textInternational audienceThe high resolution of the Synthetic Aperture Radar (SAR) imagery, in addition to its capability to see through clouds and rain, makes it a crucial remote sensing technique. However, SAR images are very sensitive to radar parameters, the observation geometry and the scene's characteristics. Moreover, for a complex scene of interest with targets located on a rough soil, a composite scattering between the target and the surface occurs and creates distortions on the SAR image. These characteristics can make the SAR images difficult to analyse and process. To better understand the complex EM phenomena and their signature in the SAR image, we propose a methodology to generate raw SAR signals and SAR images for scenes of interest with a target located on a rough surface. With this prospect, the entire radar acquisition chain is considered: the sensor parameters, the atmospheric attenuation, the interactions between the incident EM field and the scene, and the SAR image formation. Simulation results are presented for a rough dielectric soil and a canonical target considered as a Perfect Electric Conductor (PEC). These results highlight the importance of the composite scattering signature between the target and the soil. Its power is 21 dB higher that that of the target for the target-soil configuration considered. Finally, these simulations allow for the retrieval of characteristics present in actual SAR images and show the potential of the presented model in investigating EM phenomena and their signatures in SAR images
Practicalizing Tree-Based Model Acceleration with CAM through Model Pruning and Data Placement Optimization
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Faraday waves and period tripling in a horizontal circular tank
No full textInternational audienceUnderstanding wave kinematics is crucial for analysing the thermodynamic effects of sloshing, which can lead to pressure drops in non-isothermal cryogenic fuel tanks. In the research reported here, Faraday waves in a horizontal circular tank (partially filled with water) under vertical excitation are investigated. The tank geometry is referred to as a horizontal circular tank throughout, with its circular face oriented perpendicular to the horizontal plane. Firstly, this paper addresses the eigenvalue problem through linear potential flow theory, in order to provide theoretical evidence of Faraday waves in horizontal circular tanks, the impact the density ratio has on the eigenvalues is then considered. Secondly, an experimental investigation testing multiple liquid fill levels is conducted. A soft-spring nonlinear response is demonstrated throughout the parameter space. The results showed larger sloshing amplitudes for low fill levels and smaller sloshing amplitudes for high fill levels. Asymmetry between anti-nodes at the container sidewalls and through the tank centreline are evident for low fill levels. Moreover, the sloshing wave amplitude at which breaking waves occur is smaller for high fill level conditions. Finally, period tripling was observed for all fill levels tested, confirming nonlinear mode interactions before the onset to wave breaking
Effect of the Laser Cleaning Process on the Surface State and the Fatigue Strength of a Ferritic Steel
No full textInternational audienceThe laser cleaning process is carried out on a ferritic steel for two configurations: a flat top beam profile on a squared-shaped laser spot and a Gaussian beam profile on a round-shaped laser spot. The two laser configurations induced fluence values of 0.20 and 0.27 J/cm2, respectively. An exhaustive characterization is then carried out, including microstructure, roughness, nanohardness and residual stresses, showing that the laser affected layer reaches a maximum depth of 90 µm. Fatigue tests were performed for each configuration, showing that the endurance limits remain unchanged in the stress range explored. This is attributed to the combination of negative effects (tensile residual stresses up to 354 MPa) and positive effects (grain refinement, increased nanohardness, reduced maximum valley depth
Self-heating measurements at high temperature under high frequency cyclic loading
No full textInternational audienceThe self-heating method, which is based on the measurement of temperature evolution of a specimen during cyclic loading, makes it possible to considerably reduce characterization times. The aim of this paper is to propose a test protocol at very high frequency (20 kHz) and very high temperature (up to 1000 °C), as well as an ad hoc analysis method to determine the dissipative sources field responsible for the measured temperature rise. To this end, a method for solving the 1D heat diffusion equation, based on Fourier transforms, is developed. This method is validated using finite element calculations, then applied to experimental results obtained at 850 °C on AM1, a single-crystal nickel-base superalloy, which exhibits a single regime of dissipation
Two years of passive acoustic monitoring in a French MPA: gaining knowledge on the annual presence of porpoises and delphinids, and testing acoustic equipment
No full textInternational audienceAims: (1) Learn more about year-round small odontocete presence in the Iroise sea (Britanny, France) using passive acoustic monitoring (2) Compare different instruments and recording configurations to better understand their effects on detection results Targeted species: porpoises, delphinids (particularly common and bottlenose dolphins) Calendar: May 2022 - Jan 202
Taiwanese Universities at the Crossroads: Engineering Education for Sustainability Transitions and Industrial Demands
No full textInternational audienceThis paper examines the interplay between sustainability transitions and industrial demands within Taiwanese engineering education. Taiwan, a newly industrialized economy, faces unique challenges in integrating sustainability into its engineering programs while maintaining economic growth. Based on 34 interviews with professors, deans, and university administrators across five prominent Taiwanese universities, this study explores how higher education stakeholders perceive and address these challenges. The findings reveal a strong emphasis on technical proficiency and alignment with industry needs, often at the expense of broader educational goals and sustainability. A significant gap exists between engineering and social sciences, with social sciences often being marginalized despite their critical role in fostering a more holistic educational approach. Despite the socio-economic pressures and the dominant technological focus, some educators are pioneering efforts to incorporate sustainability into the curriculum through course projects and University Social Responsibility (USR) initiatives. The study underscores the need for a paradigm shift towards more holistic and interdisciplinary approaches in engineering education to support sustainability transitions. By highlighting the specific context of Taiwan, this research contributes to a broader understanding of the complexities faced by newly industrialized countries in aligning educational practices with global sustainable development goals