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Aerobars Position Effect: What is the Interaction Between Aerodynamic Drag and Power Production?
No full textInternational audienceExtensive research has been dedicated to optimizing the cyclist's position on the bike to enhance aerodynamic performance. This study aims to further investigate the aerobars position modification impact on cycling speed. Drawing from previous work (Fintelman et al. 2015), a connection is established between position adjustments and hip angle, a critical determinant of power output. Based on a 3D scan of an elite athlete on his Time Trial (TT) bike, a digital twin with upper body mobility is created. Utilizing inverse kinematics with aerobars as a root, adjustments to the aerobars position translate into alterations in the cyclist's upper body posture. These changes influence both aerodynamic drag -quantified by Computational Fluid Dynamics method (CFD)- and hip angle, directly affecting the athlete's capacity for power generation. The interplay between aerodynamic efficiency and power output is analyzed, with varying parameters such as speed and slope angle considered to ascertain the optimal aerobar position for individual athletes in a specific cycling context. Results show impactful variations in cycling speed as a function of the aerobars position, the latter having a strong influence on aerodynamic drag and theoretical power production
Mechanical characterization of regenerating Hydra tissue spheres
No full textInternational audienceHydra vulgaris, long known for its remarkable regenerative capabilities, is also a long-standing source of inspiration for models of spontaneous patterning. Recently it became clear that early patterning during Hydra regeneration is an integrated mechanochemical process whereby morphogen dynamics is influenced by tissue mechanics. One roadblock to understanding Hydra self-organization is our lack of knowledge about the mechanical properties of these organisms. In this study, we combined microfluidic developments to perform parallelized microaspiration rheological experiments and numerical simulations to characterize these mechanical properties. We found three different behaviors depending on the applied stresses: an elastic response, a viscoelastic response, and tissue rupture. Using models of deformable shells, we quantify their Young’s modulus, shear viscosity, and the critical stresses required to switch between behaviors. Based on these experimental results, we propose a description of the tissue mechanics during normal regeneration. Our results provide a first step toward the development of original mechanochemical models of patterning grounded in quantitative experimental dat
Exploring Control Co-Design's Versatility in System Optimisation: A Case Study of DC Motors
No full textInternational audienceThis study explores the integration of Control Co-Design (CCD) with Linear Quadratic Regulator (LQR) optimisation to enhance DC motor performance. Focusing on early designstages, it demonstrates how CCD and LQR can cooperatively improve system parameters, addressing both step and triangular disturbances. Results show significant enhancements, including up to 44.3% overshoot reduction and 62.2% energy consumption decrease, alongside a notable reduction in maximum actuator voltage by 51.1%. These findings underscore the technical advantages of incorporating CCD and LQR optimisation from the outset of system design, offering a comprehensive framework for achieving superior system performance, adaptability, and efficiency. The results contribute valuable technical insights into the application of CCD in system optimisation
Real‐Time and High‐Resolution Monitoring of Neuronal Electrical Activity and pH Variations Based on the Co‐Integration of Nanoelectrodes and Chem‐FinFETs
No full textInternational audienceDeveloping new approaches amenable to the measurement of neuronal physiology in real-time is a very active field of investigation, as it will offer improved methods to assess the impact of diverse insults on neuronal homeostasis. Here, the development of an in vitro bio platform is reported which can record the electrical activity of cultured primary rat cortical neurons with extreme sensitivity, while simultaneously tracking the localized changes in the pH of the culture medium. This bio platform features passive vertical nanoprobes with ultra-high signal resolution (several mV amplitude ranges) and Chem-FinFETs (pH sensitivity of sub-0.1 pH units), covering an area as little as a neuronal soma. These multi-sensing units are arranged in an array to probe both chemically and electrically an equivalent surface of ≈ 0.5 mm2. A homemade setup is also developed which allows recording of multiplexed data in real-time (10 ps range) from the active chem-sensors and passive electrodes and which is used to operate the platform. Finally, a proof-of-concept is presented for a neuro-relevant application, by investigating the effect on neuronal activity of Amyloid beta oligomers, the main toxic peptide in Alzheimer's Disease, which reveals that exposure to amyloid beta oligomers modify the amplitude, but not the frequency, of neuronal firing, without any detectable changes in pH values along this process
Robust Cooperative Load Frequency Control for Enhancing Wind Energy Integration in Multi-Area Power Systems
No full textInternational audienceThe wind energy, as a kind of renewable energy resources, has the potential to replace traditional fossil fuels. However, its intermittent power output can incur frequency instability due to the instantaneous unbalance between power generation and load demand. To smooth the penetration of wind energy, this paper presents a robust cooperative load frequency control (LFC) strategy for multi-area power systems, which is a hierarchical control approach. For the low-level wind turbine control, this paper adopts model predictive control (MPC) method to achieve the rated wind power tracking. In the meantime, an improved event-triggered scheme (ETS) considering multiple historic released signals is employed to relieve the computational burden of MPC. For the high-level cooperative LFC, this paper incorporates the robust performance index in the control synthesis to suppress the impact of intermittent wind power on frequency stability. In addition, to address the underlying shift of the steady-state operating point caused by the intermittent wind power supply, this paper improves the commonly used small-signal LFC model by adding an uncertain matrix, which reasonably explains the possible change of system parameters and extends the applicability of the traditional LFC model. Simulations are done on a four-area power system, and the results verify the efficacy of the presented event-triggered scheme and the robust cooperative LFC approach. Note to Practitioners —To promote the penetration of wind energy into power systems, this work explores a robust cooperative LFC approach under multi-agent structure to ensure the stability of the system, aiming at extending the applicability of existing approaches. The proposed approach is hierarchical. At the rated wind power tracking level, the MPC is employed to handle constraints associated with actuating devices, such as heterogeneous convertors. Simultaneously, an improved ETS considering multiple historic triggered signals is integrated in the MPC to reduce the computational burden. At the power system level, the robust performance index is incorporated in the control design to smooth the impacts of intermittent wind power on frequency stability. Additionally, the study accounts for the potential shift of the steady-state operating point and improves the traditional small-signal LFC model by adding an uncertain matrix, which can better explain the variation of system parameters and is more applicable in practical power system engineering. Simulation results demonstrate that the proposed robust cooperative LFC approach can effectively maintain the system frequency within the admissible range under the high penetration of wind energy, whereas the traditional PI controller falls short in this regard
Stochastic Differential Equations for modeling first order optimization methods
No full textInternational audienceIn this article, a family of SDEs are derived as a tool to understand the behavior of numerical optimization methods under random evaluations of the gradient. Our objective is to transpose the introduction of continuous version through ODEs to understand the asymptotic behavior of discrete optimization scheme to the stochastic setting. We consider a continuous version of the stochastic gradient scheme and of a stochastic inertial system. This article first studies the quality of the approximation of the discrete scheme by a SDE when the step size tends to 0. Then, it presents new asymptotic bounds on the values F (X(t)) − F * where X(t) is a solution of the SDE and F * = min F , when F is convex and under integrability conditions on the noise. Results are provided under two sets of hypotheses : first considering C 2 and convex functions and then adding some geometrical properties of F. All these results give an insight on the behavior of these inertial and perturbed algorithms in the setting of stochastic algorithms
Redundant Decompositions in PO HTN Domains: Goto Considered Harmful
No full textInternational audienceHTN planning is a widely used approach for solving planning problems by breaking them down into smaller sub-problems.This approach is often motivated by the ability to add constraints between tasks, which can guide the search towards a solution and improve performance by reducing the search space. In this paper, we identify a common pattern in PO HTN planning that can lead to a pathological explosion of the search space, resulting in a significant decrease in computational performance. However, this is not a fatal issue. Alternative HTN models can be used to reduce the search space. We propose two models that maintain the expressiveness of the original problem while reducing the number of possible decompositions. Our results demonstrate improved computational performance on IPC benchmarks
Assessing the energetical cost of 5G softwarization
No full textInternational audience5G is a new key technology for future communication networks. It aims at providing a broad range of new services and capabilities for users as well as facilitating its management for network operators (NetOps). Whereas networks still have monolithic architectures, 5G design takes advantage of softwarization and virtualization of its functionalities, for this purpose. However, 5G is also raising a lot of critics, especially related to its energy consumption. This paper then deals with assessing the energetic cost of the future softwarized 5G facilities. To this aim, an experimental platform has been set-up taking advantage of the software 5G OpenAirInterface (OAI) implementation. This paper shows the complexity of designing energy consumption measurement tools. It then exhibits the level of energy consumption of the main 5G components, pointing out the ones that need to be optimized