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In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such…

We present a new version of a dynamical spectral model for Large Eddy Simulation based on the Eddy Damped Quasi Normal Markovian approximation \cite{sao,chollet_lesieur}. Three distinct modifications are implemented and tested. On the one…

Fluid Dynamics · Physics 2009-11-13 Julien Baerenzung , Helene Politano , Yannick Ponty , Annick Pouquet

Estimation of the initial state of turbulent channel flow from limited data is investigated using an adjoint-variational approach. The data are generated from a reference direct numerical simulation (DNS) which is sub-sampled at different…

Fluid Dynamics · Physics 2021-07-01 Mengze Wang , Tamer A. Zaki

We present a scalable low dimensional manifold model for the reconstruction of noisy and incomplete hyperspectral images. The model is based on the observation that the spatial-spectral blocks of a hyperspectral image typically lie close to…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Wei Zhu , Zuoqiang Shi , Stanley Osher

The VAMOS++ magnetic spectrometer is characterized by a large angular and momentum acceptance and highly non-linear ion optics properties requiring the use of software ion trajectory reconstruction methods to measure the ion magnetic…

Instrumentation and Detectors · Physics 2025-04-01 M. Rejmund , A. Lemasson

Currently, the engineering of miniature spectrometers mainly faces three problems: the mismatch between the number of filters at the front end of the detector and the spectral reconstruction accuracy; the lack of a stable spectral…

Data Analysis, Statistics and Probability · Physics 2022-09-19 Jiakun Zhang , Liu Zhang , Ying Song , Yan Zheng

Accounting for the Reynolds number is critical in numerical simulations of turbulence, particularly for subsonic flow. For Smoothed Particle Hydrodynamics (SPH) with constant artificial viscosity coefficient alpha, it is shown that the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Daniel J. Price

We present a construction of isotropic boundary adapted wavelets, which are orthogonal and yield a multi-resolution analysis. We analyze direct numerical simulation data of turbulent channel flow computed at a friction Reynolds number of…

We study the three-dimensional turbulent Kolmogorov flow, i.e. the Navier-Stokes equations forced by a low-single-wave-number sinusoidal force in a periodic domain, by means of direct numerical simulations. This classical model system is a…

Fluid Dynamics · Physics 2021-12-22 Wenwei Wu , Francois G. Schmitt , Enrico Calzavarini , Lipo Wang

In the study of weakly turbulent wave systems possessing incomplete self-similarity it is possible to use dimensional arguments to derive the scaling exponents of the Kolmogorov-Zakharov spectra, provided the order of the resonant wave…

Fluid Dynamics · Physics 2009-11-10 Colm Connaughton , Sergey Nazarenko , Alan C. Newell

We study an inverse problem for the time-dependent Maxwell system in an inhomogeneous and anisotropic medium. The objective is to recover the initial electric field $\mathbf{E}_0$ in a bounded domain $\Omega \subset \mathbb{R}^3$, using…

Numerical Analysis · Mathematics 2025-06-27 Thuy T. Le , Cong B. Van , Trong D. Dang , Loc H. Nguyen

Simulating turbulent fluid flows is a computationally prohibitive task, as it requires the resolution of fine-scale structures and the capture of complex nonlinear interactions across multiple scales. This is particularly the case in direct…

Fluid Dynamics · Physics 2026-04-22 Ismaël Zighed , Nicolas Thome , Patrick Gallinari , Taraneh Sayadi

We consider the problem of reconstructing 2D images from randomly under-sampled confocal microscopy samples. The well known and widely celebrated total variation regularization, which is the L1 norm of derivatives, turns out to be…

Image and Video Processing · Electrical Eng. & Systems 2019-09-04 Bibin Francis , Manoj Mathew , Muthuvel Arigovindan

The way in which kinetic energy is distributed over the multiplicity of inertial (intermediate) scales is a fundamental feature of turbulence. According to Kolmogorov's 1941 theory, on the basis of a dimensional analysis, the form of the…

Fluid Dynamics · Physics 2011-10-21 Stefania Scarsoglio , Francesca De Santi , Daniela Tordella

We present an efficient, elastic 3D LiDAR reconstruction framework which can reconstruct up to maximum LiDAR ranges (60 m) at multiple frames per second, thus enabling robot exploration in large-scale environments. Our approach only…

In this work, we explore dimensionality reduction techniques for univariate and multivariate time series data. We especially conduct a comparison between wavelet decomposition and convolutional variational autoencoders for dimension…

Machine Learning · Computer Science 2022-04-26 William Todo , Beatrice Laurent , Jean-Michel Loubes , Merwann Selmani

We introduce a Three-Dimensional Convolutional Variational Autoencoder (3D-CVAE) for automated anomaly detection in Electron Energy Loss Spectroscopy Spectrum Imaging (EELS-SI) data. Our approach leverages the full three-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Seyfal Sultanov , James P Buban , Robert F Klie

According to Richardson's cascade description of turbulence, large vortices break up to form smaller ones, thereby transferring kinetic energy towards smaller scales. Energy dissipation occurs at the smallest scales due to viscosity. We…

Chaotic Dynamics · Physics 2018-04-12 Tamás Kalmár-Nagy , Bendegúz Dezső Bak

Phase-contrast magnetic resonance imaging (MRI) provides time-resolved quantification of blood flow dynamics that can aid clinical diagnosis. Long in vivo scan times due to repeated three-dimensional (3D) volume sampling over cardiac phases…

Image and Video Processing · Electrical Eng. & Systems 2020-04-22 Valery Vishnevskiy , Jonas Walheim , Sebastian Kozerke

We consider the inverse problem of the reconstruction of the spatially distributed dielectric constant $\varepsilon_{r}\left(\mathbf{x}\right), \ \mathbf{x}\in \mathbb{R}^{3}$, which is an unknown coefficient in the Maxwell's equations,…

Numerical Analysis · Mathematics 2015-06-19 Larisa Beilina , Nguyen Trung Thành , Michael V. Klibanov , John Bondestam Malmberg
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