Multimodal electromechanical model of piezoelectric transformers by Hamilton's principle

This work deals with a general energetic approach to establish an accurate electromechanical model of a piezoelectric transformer (PT). Hamilton’s principle is used to obtain the equations of motion for free vibrations. The modal characteristics (mass, stiffness, primary and secondary electromechanical conversion factors) are also deduced. Then, to illustrate this general electromechanical method, the variational principle is applied to both homogeneous and nonhomogeneous Rosen-type PT models. A comparison of modal parameters, mechanical displacements, and electrical potentials are presented for both models. Finally, the validity of the electrodynamical model of nonhomogeneous Rosen-type PT is confirmed by a numerical comparison based on a finite elements method and an experimental identification

First Approach for the Modelling of the Electric Field Surrounding a Piezoelectric Transformer in View of Plasma Generation

This paper is about an open multi-physics modelling problem resulting from recent investigations into plasma generation by piezoelectric transformers. In this first approach, the electric field distribution surrounding the transformer is studied according to a weak coupling formulation. Electric potential distribution views obtained numerically are compared to real views of plasma generation observed experimentally

Identification Methodology of Electrical Equivalent Circuit of the Piezoelectric Transformers by FEM

Methodology using Ansys analyses for the identification of Electrical Equivalent Circuit of piezoelectric transformer. The demonstration is done with typical multilayered Rosen transformer but the method is relevant for any kind of transformer structures

Modeling of a Ring Rosen-Type Piezoelectric Transformer by Hamilton’s Principle

This paper deals with the analytical modeling of a ring Rosen-type piezoelectric transformer. The developed model is based on a Hamiltonian approach, enabling to obtain main parameters and performance evaluation for the first radial vibratory modes. Methodology is detailed, and final results, both the input admittance and the electric potential distribution on the surface of the secondary part, are compared with numerical and experimental ones for discussion and validation

Convective dissolution of CO2_2 in 2D and 3D porous media: the impact of hydrodynamic dispersion

Convective dissolution is the process by which CO$_2$ injected in deep geological formations dissolves into the aqueous phase, which allows storing it perennially by gravity. The process results from buoyancy-coupled Darcy flow and solute transport. Proper theoretical modeling of the process should consider in the transport equation a diffusive term accounting for hydrodynamics (or, mechanical) dispersion, with an effective diffusion coefficient that is proportional to the local interstitial velocity. A few two-dimensional (2D) numerical studies, and three-dimensional (3D) experimental investigations, have investigated the impact of hydrodynamic dispersion on convection dynamics, with contradictory conclusions. Here, we investigate systematically the impact of the dispersion strength $S$ (relative to molecular diffusion), and of the anisotropy $\alpha$ of its tensor, on convective dissolution in 2D and 3D geometries. We use a new numerical model and analyze the solute fingers' number density (FND), penetration depth and maximum velocity; the onset time of convection; the dissolution flux in the quasi-constant flux regime; the mean concentration of the dissolved CO2; and the scalar dissipation rate. The efficiency of convective dissolution over long times is observed to be mostly controlled by the onset time of convection. For most natural porous media ($\alpha = 0.1$), the onset time is found to increase as a function of $S$, in agreement with previous experimental findings and in stark contrast to previous numerical findings. However, if $\alpha$ is sufficiently large this behavior is reversed. Furthermore, results in 3D are fully consistent with the 2D results on all accounts, except that in 3D the onset time is slightly smaller, the dissolution flux in the quasi-constant flux regime is slightly larger, and the dependence of the FND on the dispersion parameters is impacted by $Ra$.Comment: 30 pages, 18 figure

Learning Energy-Efficient Hardware Configurations for Massive MIMO Beamforming

Hybrid beamforming (HBF) and antenna selection are promising techniques for improving the energy efficiency~(EE) of massive multiple-input multiple-output~(mMIMO) systems. However, the transmitter architecture may contain several parameters that need to be optimized, such as the power allocated to the antennas and the connections between the antennas and the radio frequency chains. Therefore, finding the optimal transmitter architecture requires solving a non-convex mixed integer problem in a large search space. In this paper, we consider the problem of maximizing the EE of fully digital precoder~(FDP) and hybrid beamforming~(HBF) transmitters. First, we propose an energy model for different beamforming structures. Then, based on the proposed energy model, we develop an unsupervised deep learning method to maximize the EE by designing the transmitter configuration for FDP and HBF. The proposed deep neural networks can provide different trade-offs between spectral efficiency and energy consumption while adapting to different numbers of active users. Finally, to ensure that the proposed method can be implemented in practice, we investigate the ability of the model to be trained exclusively using imperfect channel state information~(CSI), both for the input to the deep learning model and for the calculation of the loss function. Simulation results show that the proposed solutions can outperform conventional methods in terms of EE while being trained with imperfect CSI. Furthermore, we show that the proposed solutions are less complex and more robust to noise than conventional methods.Comment: This preprint comprises 15 pages and features 15 figures. Copyright may be transferred without notic

RSSI-Based Hybrid Beamforming Design with Deep Learning

Hybrid beamforming is a promising technology for 5G millimetre-wave communications. However, its implementation is challenging in practical multiple-input multiple-output (MIMO) systems because non-convex optimization problems have to be solved, introducing additional latency and energy consumption. In addition, the channel-state information (CSI) must be either estimated from pilot signals or fed back through dedicated channels, introducing a large signaling overhead. In this paper, a hybrid precoder is designed based only on received signal strength indicator (RSSI) feedback from each user. A deep learning method is proposed to perform the associated optimization with reasonable complexity. Results demonstrate that the obtained sum-rates are very close to the ones obtained with full-CSI optimal but complex solutions. Finally, the proposed solution allows to greatly increase the spectral efficiency of the system when compared to existing techniques, as minimal CSI feedback is required.Comment: Published in IEEE-ICC202

High-Cycle Fatigue Behaviour of Pure Tantalum under Multiaxial and Variable Amplitude Loadings

Due to its specific mechanical properties, tantalum is often used in strength-demandingmilitary applications. High-cycle fatigue (HCF) behaviour of pure tantalum, however, has been rarely reported and the mechanisms at stake to account for deformation under cyclic loadings are still badly understood. This paper aims at better understanding the fatigue behaviour of tantalum and at clarifying the mechanisms of damage formation encountered under such loadings. HCF experiments performed at room temperature on commercially-pure tantalum are presented. Mean stress effects were investigated in the aim of clarifying the interaction between fatigue and creep. Fracture mechanisms were observed to vary from intergranular to transgranular depending on applied stress amplitude and mean stress. Damage mechanisms were investigated under tension and torsion. Results are analyzed in the light of existing fatigue criteria, the limitations of which are discussed. Finally, complex sequential loadings, representative of in-service loadings, were applied to tantalum smooth specimens. The contribution of each loading sequence to the overall damage was quantified and analyzed in terms of linear or non-linear cumulative damage ruleInternational audienceDue to its specific mechanical properties, tantalum is often used in strength-demandingmilitary applications. High-cycle fatigue (HCF) behaviour of pure tantalum, however, has been rarely reported and the mechanisms at stake to account for deformation under cyclic loadings are still badly understood. This paper aims at better understanding the fatigue behaviour of tantalum and at clarifying the mechanisms of damage formation encountered under such loadings. HCF experiments performed at room temperature on commercially-pure tantalum are presented. Mean stress effects were investigated in the aim of clarifying the interaction between fatigue and creep. Fracture mechanisms were observed to vary from intergranular to transgranular depending on applied stress amplitude and mean stress. Damage mechanisms were investigated under tension and torsion. Results are analyzed in the light of existing fatigue criteria, the limitations of which are discussed. Finally, complex sequential loadings, representative of in-service loadings, were applied to tantalum smooth specimens. The contribution of each loading sequence to the overall damage was quantified and analyzed in terms of linear or non-linear cumulative damage rul

Reversible Trapping of Colloids in Microgrooved Channels via Diffusiophoresis under Steady-State Solute Gradients

The controlled transport of colloids in dead-end structures is a key capability that can enable a wide range of applications, such as bio-chemical analysis, drug delivery and underground oil recovery. This letter presents a new trapping mechanism that allows the fast (i.e., within a few minutes) and reversible accumulation of sub-micron particles within dead-end micro-grooves by means of parallel streams with different salinity level. For the first time, particle focusing in dead-end structures is achieved under steady-state gradients. Confocal microscopy analysis and numerical investigations show that the particles are trapped at a flow recirculation region within the grooves due to a combination of diffusiophoresis transport and hydrodynamic effects. Counterintuitively, the particle velocity at the focusing point is not vanishing and, hence, the particles are continuously transported in and out of the focusing point. The accumulation process is also reversible and one can cyclically trap and release the colloids by controlling the salt concentration of the streams via a flow switching valve.Comment: Manuscript under review. 6 pages, 5 figures + Supplementary Informatio