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An optimal preconditioned FFT-accelerated finite element solver for homogenization

Publications associées (30)

3D printed large amplitude torsional microactuators powered by ultrasound

Mahmut Selman Sakar, Mehdi Ali Gadiri, Junsun Hwang, Amit Yedidia Dolev

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

2024

The diachronic development of Debussy’s musical style: a corpus study with Discrete Fourier Transform

Martin Alois Rohrmeier, Johannes Hentschel, Gabriele Cecchetti, Sabrina Laneve, Ludovica Schaerf

Claude Debussy’s personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretabil ...

2023

Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

Dimitrios Kyritsis, Xiaochen Zheng, Roberto Pérez

Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023

The Claude Debussy Solo Piano Corpus

Martin Alois Rohrmeier, Johannes Hentschel, Gabriele Cecchetti, Sabrina Laneve, Ludovica Schaerf

This dataset originates from the DCML corpus initiative and contains musicological research data. For more information, please refer to its documentation page https://dcmlab.github.io/debussy_piano Please cite this dataset as Laneve, S., Schaerf ...

Zenodo2023

Computation of the attenuation function of the lightning return-stroke current from electromagnetic fields measured in a short-duration time-window, Part I: Theoretical investigation

Farhad Rachidi-Haeri, Marcos Rubinstein

In a recent paper, a procedure to reconstruct the attenuation function of a return-stroke current from the simultaneous measurements of the channel-base current and the radiated electromagnetic fields was presented. One of the assumptions of the whole fram ...

Elsevier2023

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast camera imaging is used to study ion acoustic waves propagating azimuthally in a magnetized plasma column. The high-speed image sequences are analyzed using proper orthogonal decomposition and 2D Fourier transform, allowing to evaluate the assets and d ...

2023

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

Electron spectrometer calibration method

Tobias Kippenberg, Fabrizio Carbone, Alexey Sapozhnik, Yujia Yang, Thomas La Grange, Arslan Sajid Raja

The present invention concerns an energy dispersion calibration method for calibrating an electron spectrometer of an electron spectrometer system including at least one electron emission source, electron optics and the electron spectrometer. The method co ...

2023

Two-particle azimuthal correlations in γp interactions using pPb collisions at √sNN=8.16 TeV

Matthias Finger, Konstantin Androsov, Jan Steggemann, Qian Wang, Yiming Li, Varun Sharma, Xin Chen, Arvind Shah, Rakesh Chawla, Jian Wang

The first measurements of the Fourier coefficients (V-n Delta) of the azimuthal distributions of charged hadrons emitted from photon-proton (gamma p) interactions are presented. The data are extracted from 68.8nb(-1) of ultra-peripheral proton-lead (pPb) c ...

Elsevier2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink, Tianfu Li

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023