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Dataset results
11 results for “numerical particle”
Data for the paper "Particle method for the numerical simulation of the path-dependent McKean-Vlasov equation"
<p>This deposit contains the data obtained by the method described in [A. Bernou, Y. Liu, Particle method for the numerical simulation of the path-dependent McKean-Vlasov equation, 2024]. The notebooks used to generate them through a suitable Euler scheme can be find at https://github.com/ArmdBrn/McKean_PathDep, along with files containing the estimated errors. <br>The two models considered are:<br>- a modified Ornstein-Uhlenbeck model with path-dependency;<br>- a model of neural masses with intrinsic potentiation leading to path-dependent dynamics. </p>
Dataset to "Modeling Collision-Coalescence in Particle Microphysics: Numerical Convergence of Mean and Variance of Precipitation in Cloud Simulations Using University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 " by Zmijewski, Dziekan & Pawlowska
<p>The archive contains datasets, run scripts, time series and plotting scripts used when preparing the paper: P. Zmijewski, P. Dziekan and H. Pawlowska "Modeling Collision-Coalescence in Particle Microphysics: Numerical Convergence of Mean and Variance of Precipitation in Cloud Simulations Using University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 " submitted to Geoscientific Model Development in March 2023.</p>
Numerical data for scattering amplitudes of massive scalar particles in d>2
<p>Numerical data for scattering amplitudes of massive scalar particles in d>2 obtained by solving various optimisation problems. The data is stored as lists in Mathematica .m files. Mathematica notebook is provided for loading and plotting the data.</p>
numerical data to accompany "Strong asymmetry in near-fault ground velocity during an oblique strike-slip earthquake revealed by waveform particle motions and dynamic rupture simulations"
<p>This is the numerical data to accompany the paper "Strong asymmetry in near-fault ground velocity during an oblique strike-slip earthquake revealed by waveform particle motions and dynamic rupture simulations". Please refer to the README.txt file for information about the individual datasets and archive files. </p>
Non-spherical particles in optical tweezers: a numerical solution
<p>We present numerical methods for modeling the dynamics of arbitrarily shaped particles trapped within optical tweezers, which improve the predictive power of numerical simulations for practical use. We study the dependence of trapping on the shape and size of particles in a single continuous wave beam setup. We also consider the implications of different particle compositions, beam types and media. The major result of the study is that for different irregular particle shapes, a range of beam powers generally leads to trapping. The trapping power range depends on whether the particle can be characterized as elongated or flattened, and the range is also limited by Brownian forces.</p> <p>This dataset supplements the publication and contains inputs and processing scripts for usage of scadyn (https://www.github.com/jherrane/scadyn) software for solving dynamical response of arbitrarily shaped particles in electromagnetic fields. Also is contained the minimal dataset (per PLos ONE standards) to reproduce the results presented.</p>
Emulator of PR-DNS: Accelerating Dynamical Fields with Neural Operators in Particle-Resolved Direct Numerical Simulation
<p>The codes directory includes the various machine learning models, such as FNO, UNet and ResNet. R128_init1 and R128_init2 are the PR-DNS time step simulations at different initial conditions. R64_init2, R128_init2 and R256_init2 are the PR-DNS time step simulations at different resolutions. </p> <p> </p>
Dataset of Numerical prediction of changes in atmospheric chemical compositions during a solar energetic particle event on Mars
<p>This dataset contains the input parameters and the simulated results used for figures in the paper "Numerical prediction of changes in atmospheric chemical compositions during a solar energetic particle event on Mars" by Y. Nakamura, F. Leblanc, N. Terada, S. Hiruba, I. Murata, H. Nakagawa, S. Sakai, S. Aoki, A. Piccialli, Y. Willame, L. Neary, A. C. Vandaele, K. Murase, and R. Kataoka.</p> <p>Detailed informations about the data files can be found in "README.txt".</p>
Data-Two-dimensional numerical study on particle motion trajectories and deposition in a channel of partial diesel particulate filter
<p>A numerical investigation on the soot laden flow of gas in a PDPF (Partial Diesel Particulate Filter) is presented based on solving the momentum equations for continuous phase in the Euler frame and the motion equations for dispersed phase in the Lagrangian frame. The interaction between the gas and particles is treated as one-way coupling for extremely dilute particle concentration, while the interaction between particles and porous wall is implemented through user-defined-subroutines. To accurately track the motion of nanoscale particles, the drag force, the Brownian excitation, and the partial slip are included in the particle motion equation. Two methods are used to verify the gas flow model and reasonable agreement for both comparisons is observed. The effects of upstream velocity, wall permeability and particle size on the filtration efficiency and deposition distribution of the particles along the wall surface of inlet channel are quantitatively studied. The results show that (1) the wall permeability plays the most primary role in determining the filtration efficiency of PDPF; (2) high upstream velocity improves filtration efficiency and drives the deposition position of particles to the rear of inlet channel; (3) the dependence of the particle deposition distribution on its own size is mainly reflected in the initial deposition position; (4) the filtration efficiency of PDPF is not proportional markedly to the gas flow into inlet channel at a low wall permeability, implying an intense separation of particles from gas streamline at the flow entrance.</p>
Data-Two-dimensional numerical study on particle motion trajectories and deposition in a channel of partial diesel particulate filter
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Particle velocity shear wave motion data for numerical tissue−like viscoelastic materials
<p>This repository contains the particle velocity shear wave motion data generated using the staggered grid finite difference method. These datasets were used to create images in article:</p> <p>Osika, Mariusz, and Piotr Kijanka. "Ultrasound Shear Wave Propagation Modeling in General Tissue–Like Viscoelastic Materials." <em>Ultrasound in Medicine & Biology</em> 50.4 (2024): 627-638.</p> <p>Each dataset contains shear wave motion waveforms, space and time vectors. </p>
Emulator of PR-DNS: Part II, dataset for training the emulator of thermodynamics and cloud droplet fields in Particle-Resolved Direct Numerical Simulation
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.