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Integration of Small Hydropower Plants into Microgrids: Overview, Control, and Modeling Challenges
No full textInternational audienceHydroelectric power is a dispatchable energy source and plays a crucial role in maintaining stability in islanded microgrids through grid-forming control. This paper presents a comprehensive overview of the modeling and control strategies for small hydropower plants (SHPs), their integration into microgrids, and their interactions with other distributed energy resources (DERs), such as solar power. The study focuses on examining key challenges related to stability, modeling, and control of SHPs to promote hybrid power integration within a microgrid. To address these challenges, recommendations for improving the performance of microgrid-based small hydropower plants are proposed, including advanced control techniques and the implementation of Hardware-in-the-Loop (HIL) simulations to enhance the accuracy of modeling, testing, and validation
Experimental and Detonation-Shock Dynamics analyses of cellular detonations in diverging channels: the effects of the cross-sectional shape
No full textInternational audienceThis experimental study examines the transients of cellular detonations during weak diffraction from straight to diverging channels. First, we analyze the effects of the cross-sectional shapes (square or round) on the 3D transients of the detonation cells using parietal and head-on soot recordings. The diverging channels have the same initial cross-sections (shape and area) as the straight channels, with their area increasing linearly at an equal moderate expansion rate. The cell mean widths first increase from starting values dependent on the channel shape and then decrease to stabilize at the same higher value independent of the channel shape. Then, we use a relationship between velocity, acceleration, and total curvature of the average detonation front which qualitatively explains the experimental trends, particularly the non-monotonic variation in the mean cell widths. This sensitivity makes the experimental data reliable for high-resolution numerical simulations that can handle three-dimensionality and detailed chemical kinetic mechanisms
Tree-Based Diagnosis Enhanced with Meta-Knowledge and Discovery of Analytical Redundancy Relations
No full textInternational audienc
Frequency Model Investigation for ESD failure prediction
No full textInternational audienceDynamic model of ESD protection devices presents many advantages to simulate the response of these components when they are submitted to very high-level transient pulses such as EMP (electro-magnetic pulses) residual. Dynamic models extracted from frequency measurements will be used to demonstrate how such measurement can provide a complete dynamic model (including fast response and thermal effect of ESD device protection). Doing so, a topology composed of a capacitor in parallel to a snapback protection will be studied in order to decide whether or not it is interesting to used dynamic model obtained from frequency measurement over usual quasi-static model to predict a component failure
Performance Isolation in Multi Tenant Cloud Data Centers
No full textInternational audienceEnsuring network performance isolation in multitenant cloud data centers is critical for maintaining Service Level Agreement (SLA) compliance while supporting diverse and dynamic workloads. Traditional approaches predominantly emphasize flow-level fairness, which, although effective in certain scenarios, often fails to address the broader needs of tenant-based fairness essential for SLA-driven environments. My research introduces a novel framework leveraging control theory and AI-enhanced decision-making to achieve adaptive and intelligent network resource management. By shifting the focus to tenantbased fairness, the proposed solution ensures that resources are allocated equitably among tenants while meeting SLA requirements under fluctuating conditions. Preliminary investigations demonstrate the potential of this approach to enhance reliability, scalability, and efficiency, addressing the limitations of fairnesscentric methods focused solely on flows. This work lays the groundwork for intelligent, automated resource management in cloud data centers, advancing the capabilities of multi-tenant infrastructure to meet future demands
Directional light scattering in Mie-resonant Si particles with ultra-thin plasmonic shells
No full textInternational audienceMetamaterial research has sought to create nanostructures with strong directional optical scattering to control light propagation at the nanoscale. Core-shell architectures comprised of both resonant cores and resonant shells have been suggested as candidate particles in which the spectral overlap of the electric and magnetic dipoles can be controlled to create strong directional scattering. In this study, we present Au-decorated Si core-shell (Si@Au) particles. These were synthesized by first creating Si particles through the thermal disproportionation of hydrogen silsesquioxane (HSQ), which were then decorated with ∼ 4 nm diameter Au nanoparticles. We characterized the resonant behavior of the core-shell particles using electron energy-loss spectroscopy mapping and optical single-particle scatter spectroscopy. These observations were supported by T-matrix simulations and Mie theory calculations of the scattering spectra, which show that compared to Si, Si@Au particles demonstrate a dampened magnetic dipole resonance for smaller Si core diameters (100 -130 nm) and an enhanced magnetic dipole resonance for larger Si core sizes (150 -200 nm). However, we show that to significantly improve forward scattering intensity, continuous plasmonic shells of ~12 nm thickness are needed
Mostow Rigidity and the Gravitational Monopoles.
No full textWe give a new proof of the following theorem using the Gravitational Monopole equations Theorem 0.1. Let be a smooth compact quotient of complex-hyperbolic 2-space Let be its standard complex-hyperbolic metric. Then every Einstein metric on is of the form , where ϕ : M → M is a diffeomorphism and η > 0 is a constant. and in due course of proving the above theorem we proved the following inequalities (0.1) and a generalised Bogomolov-Miyaoka-Yau inequality (0.2) χ ≥ 3σ.$
Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
No full textInternational audienceWe develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition
Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction
No full textInternational audienceThis study evaluates a surrogate modeling approach that provides rapid ensemble predictions of air pollutant dispersion in urban environments for varying meteorological forcing, while estimating irreducible and modeling uncertainties. The POD–GPR approach combining Proper Orthogonal Decomposition (POD) and Gaussian Process Regression (GPR) is applied to emulate the response surface of a Large-Eddy Simulation (LES) model of the Mock Urban Setting Test (MUST) field-scale experiment. We design and validate new methods for (i) selecting the POD-latent space dimension to avoid overfitting noisy structures due to atmospheric internal variability, and (ii) estimating the uncertainty in POD–GPR predictions. To train and validate the POD–GPR surrogate in an offline phase, we build a large dataset of 200 LES 3-D time-averaged concentration fields, which are subject to substantial spatial variability from near-source to background concentration and have a very large dimension of several million grid cells. The results show that POD–GPR reaches the best achievable accuracy levels, except for the highest concentration near the source, while predicting full fields at a computational cost five orders of magnitude lower than an LES. The results also show that the proposed mode selection criterion avoids perturbing the surrogate response surface, and that the uncertainty estimate explains a large part of the surrogate error and is spatially consistent with the observed internal variability. Finally, POD–GPR can be robustly trained with much smaller datasets, paving the way for application to realistic urban configurations
On Dual of LMIs for Absolute Stability Analysis of Nonlinear Feedback Systems with Static O'Shea-Zames-Falb Multipliers
No full text8 pages, 5 figures, submitted to European Control Conference 2025International audienceThis study investigates the absolute stability criteria based on the framework of integral quadratic constraint (IQC) for feedback systems with slope-restricted nonlinearities. In existing works, well-known absolute stability certificates expressed in the IQC-based linear matrix inequalities (LMIs) were derived, in which the input-to-output characteristics of the slope-restricted nonlinearities were captured through static O'Shea-Zames-Falb multipliers. However, since these certificates are only sufficient conditions, they provide no clue about the absolute stability in the case where the LMIs are infeasible. In this paper, by taking advantage of the duality theory of LMIs, we derive a condition for systems to be not absolutely stable when the above-mentioned LMIs are infeasible. In particular, we can identify a destabilizing nonlinearity within the assumed class of slope-restricted nonlinearities as well as a non-zero equilibrium point of the resulting closed-loop system, by which the system is proved to be not absolutely stable. We demonstrate the soundness of our results by numerical examples