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Mathematical methods of step-by-step and combined shifts are proposed for experimental data processing to reconstruct the measuring system impulse response distorted by shift-invariant blur. Proposed methods base on direct non-blind…

Signal Processing · Electrical Eng. & Systems 2019-01-24 Andrey V. Novikov-Borodin

Inverting an evolving diffusive scalar field to reconstruct the underlying velocity field is an underdetermined problem. Here we show, however, that for two-dimensional incompressible flows, this inverse problem can still be uniquely solved…

Fluid Dynamics · Physics 2019-06-26 Arjun Sharma , Irina I. Rypina , Ruth Musgrave , George Haller

Inversion techniques are widely used to reconstruct subsurface physical properties (e.g., velocity, conductivity) from surface-based geophysical measurements (e.g., seismic, electric/magnetic (EM) data). The problems are governed by partial…

Machine Learning · Computer Science 2022-06-17 Yinan Feng , Yinpeng Chen , Shihang Feng , Peng Jin , Zicheng Liu , Youzuo Lin

Turbulent flows above a solid surface are characterised by a hydrodynamic roughness that represents, for the far velocity field, the typical length scale at which momentum mixing occurs close to the surface. Here, we are theoretically…

Fluid Dynamics · Physics 2023-11-07 Pan Jia , Bruno Andreotti , Philippe Claudin

A non-hydrostatic depth-averaged model for dry granular flows is proposed, taking into account vertical acceleration. A variable friction coefficient based on the $\mu(I)$ rheology is considered. The model is obtained from an asymptotic…

Metadynamics is an established sampling method aimed at reconstructing the free-energy surface relative to a set of appropriately chosen collective variables. In standard metadynamics the free-energy surface is filled by the addition of…

Statistical Mechanics · Physics 2012-07-11 Davide Branduardi , Giovanni Bussi , Michele Parrinello

Multilevel Stein variational gradient descent is a method for particle-based variational inference that leverages hierarchies of surrogate target distributions with varying costs and fidelity to computationally speed up inference. The…

Numerical Analysis · Mathematics 2023-05-02 Terrence Alsup , Tucker Hartland , Benjamin Peherstorfer , Noemi Petra

We present here numerical modelling of granular flows with the $\mu(I)$ rheology in confined channels. The contribution is twofold: (i) a model to approximate the Navier-Stokes equations with the $\mu(I)$ rheology through an asymptotic…

Soft Condensed Matter · Physics 2018-01-17 E. D. Fernández-Nieto , J. Garres-Díaz , A. Mangeney , G. Narbona-Reina

Classical descriptions of flapping propulsion near a free surface emphasize the energetic penalties of wave generation, treating the interface primarily as an energy sink. Here, we show that the same deformable boundary can also act as a…

Fluid Dynamics · Physics 2025-12-16 Qimin Feng , Tianjun Han , Qiang Zhong

Existing works that predict bedform-induced hyporheic exchange flux (HEF) typically either assume a simplified streambed shape and corresponding sinusoidal head distribution or rely on costly computational fluid dynamics simulations.…

Fluid Dynamics · Physics 2024-11-14 Yoni Teitelbaum , Shai Arnon , Aaron Packman , Scott K. Hansen

A model-data inversion is applied to a very large observational dataset collected in the Southern Ocean north of the Ross Sea during late autumn to early winter, producing estimates of the frequency-dependent rate of dissipation by sea ice.…

Atmospheric and Oceanic Physics · Physics 2020-06-16 W. Erick Rogers , Michael H. Meylan , Alison L. Kohout

The paper is devoted to the numerical solution of elastoplastic constitutive initial value problems. An improved form of the implicit return-mapping scheme for nonsmooth yield surfaces is proposed that systematically builds on a…

Computational Engineering, Finance, and Science · Computer Science 2018-01-08 Stanislav Sysala , Martin Cermak , Tomas Koudelka , Jaroslav Kruis , Jan Zeman , Radim Blaheta

A weighted residual collocation methodology for simulating two-dimensional shear-driven and natural convection flows has been presented. Using a dyadic mesh refinement, the methodology generates a basis and a multiresolution scheme to…

Fluid Dynamics · Physics 2020-07-23 Jahrul Alam , Raymond Walsh , Alamgir Hossain , Andrew Rose

Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion…

Geophysics · Physics 2022-01-05 Zitong Zhou , Delphine Roubinet , Daniel M. Tartakovsky

We propose a data-driven algorithm for reconstructing the irregular, chaotic flow dynamics around two side-by-side square cylinders from sparse, time-resolved, velocity measurements in the wake. We use Proper Orthogonal Decomposition (POD)…

Fluid Dynamics · Physics 2022-09-08 Flavio Savarino , George Papadakis

The reconstruction of water wave elevation from bottom pressure measurements is an important issue for coastal applications, but corresponds to a difficult mathematical problem. In this paper we present the derivation of a method which…

Fluid Dynamics · Physics 2017-11-22 Philippe Bonneton , David Lannes

On the proper timescale, amorphous solids can flow. Solid flow can be observed macroscopically in glaciers or lead pipes, but it can also be artificially enhanced by creating defects. Ion Beam Sputtering (IBS) is a technique in which ions…

Materials Science · Physics 2012-03-07 Mario Castro , Rodolfo Cuerno

Estimating subsurface dielectric properties is essential for applications ranging from environmental surveys of soils to nondestructive evaluation of concrete in infrastructure. Conventional wave inversion methods typically assume few…

Signal Processing · Electrical Eng. & Systems 2025-10-30 Ishfaq Aziz , Mohamad Alipour

We propose methods that use specular, multibounce lidar returns to detect and map specular surfaces that might be invisible to conventional lidar systems that rely on direct, single-scatter returns. We derive expressions that relate the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-22 Connor Henley , Siddharth Somasundaram , Joseph Hollmann , Ramesh Raskar

Seismic data frequently exhibits missing traces, substantially affecting subsequent seismic processing and interpretation. Deep learning-based approaches have demonstrated significant advancements in reconstructing irregularly missing…

Geophysics · Physics 2025-01-16 Paul Goyes-Peñafiel , Ulugbek Kamilov , Henry Arguello
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