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864 results for “numerative”
Data from: Voice efficiency for different voice qualities combining experimentally derived sound signals and numerical modeling of the vocal tract
<p>This dataset contains Stereo-Lithographic (STL) surface models of a human vocal tract, derived Finite-Element-Models, numerical results, and scripts for analyzing these results and (re-)running the computation.</p> <p> </p> <p><strong>In the main folder, this dataset contains:</strong></p> <p>1) Python files (*fig*.py) for the creation of figures and tables (*tab*.py)</p> <p>2) Python files (*.py) for analyzing Finite-Element (FE) calculations (x_resonances.py, x_libs.py, x_fem2excel.py)</p> <p>3) Python-files (*.py) for analyzing stl-data (x_analyzeSTL.py)</p> <p>4) Python files (*.py) for deriving Infinite-Impulse-Response (IIR) filter and their impulse responses (x_IIR.py)</p> <p>5) Excel files (*.xlsx) containing Volume-velocity-transfer-functions (Vlg.xlsx), Pressure-transfer-functions at the lips (Hlg.xlsx), and the glottis (Hgg.xlsx) based on FE, the sound spectra of audio signals (sound_spectra.xlsx), the polynomials describing the IIR (IIR_polynomial.xlsx) and their impulse responses (IIR_impulse_responses.xlsx), and glottal waveforms (glottal_waveform.xlsx) and spectra (glottal_spectra.xlsx)</p> <p>6) Several figures (*.pdf)</p> <p> </p> <p><strong>In folder „x_fenics/x_Subject-1“ (and sub-folders), this data set contains:</strong></p> <p>1) Surface models of the human vocal tract for different voice qualities (glottis.stl, wall.stl, lips.stl)</p> <p>2) Sub-volumes of the vocal tract cavities (*ET.stl, *HPl.stl, *HPu.stl, *OPf.stl, *OPr.stl, *SP.stl, *.VV.stl)</p> <p>3) Derived gmsh volume meshes (*.msh) (www.gmsh.info)</p> <p>3) Derived volume models applicable to FE-Solvers (*.h5, *.xdmf)</p> <p>4) Results of the FE-calculation (*pvtf*.txt, *vvtf*.txt, *pglottis*.txt)</p> <p>5) Formant frequencies computed by inverse filtering (*.for)</p> <p> </p> <p><strong>In folder „x_fenics/x_misc“ the data set contains:</strong></p> <p>1) Python-files (*.py) for (re-)running the calculations using the FE-Method</p>
Relevant data for numerical simulation of Xiangjiao post-fire debris flow
<p>This is a data set used for numerical simulation analysis of post-fire debris flow in Xiangjiao catchment, Sichuan Province, including the original rainfall data on the day of the debris flow event, the interpolated rainfall data, and some relevant experimental data. If you have any questions in the process of using these data, you can contact the email: 622200090027@mails.cqjtu.edu.cn.</p>
Numerical data for scattering amplitudes of photon in d=4.
<p>Numerical data for scattering amplitudes of photons in d=4 obtained by solving various optimisation problems. The data is stored in .txt files. Mathematica notebook is provided for loading and plotting the data.</p>
Supporting data for "The time scale of shallow convective self-aggregation in large-eddy simulations is sensitive to numerics"
<p>Numerical settings, routines and post-processed data used to generate the figures presented in "The time scale of shallow convective self-aggregation in large-eddy simulations is sensitive to numerics", manuscript submitted to Journal of Advances in Modeling Earth Systems. This version is an update after accounting for comments of three reviewers to the submitted manuscript.</p>
Switching between Numerical Black-box Optimization Algorithms with Warm-starting Policies - Reproduction artifacts
<p># Reproducibility instructions</p> <p>This document details the steps to reproduce the results presented in the paper 'Chaining of Numerical Black-box Algorithms: Investigating the Impact of Warm-Starting and the Switching Point'</p> <p>## Algorithm code<br> The code for the individual algorithms and the switching routines is included in the 'dynas.zip' folder. </p> <p>## Data collection<br> To collect the performance data for the static algorithms, the file 'data_collection.py' can be used. This file runs all 5 static algorithm on the function suite used in the paper, using the 'ioh' package. To run it, please modify the 'ioh_dir' variable to a place where the data should be stored. <br> The resulting data is made available under the 'static.zip' file.</p> <p>## Processing code<br> The code which processes the performance data into the list of usecases is part of the 'Processing_R' notebook. <br> This results in a set of rds-files with the data in IOHanalyzer's internal format, and in a csv file ('Split_performances_relative.csv') with the selected usecases. </p> <p>This csv file can then be read in using the 'visualization' notebook, which can generate Figure 1 from the paper. This notebook can then be used to count the specific usecases, which is the data shown in Table 1. The csv-file containing the selected usecases ('usecases.csv') is also generated here.</p> <p>The 'usecases' csv file can be used in the 'Data_collection_switch' notebook to run the dynamic configurations. This results in the 'Dynamic.zip' data, which can again be read using IOHanalyzer in the 'Processing_R' notebook. This then generates several csv-files, for both the static and dynamic case, containing the per-run hitting times ('RT_samples.zip'). These are then used in the 'Visualization' notebook to generate figure 3 and 4, as well as table 2. </p> <p>## Countour plots<br> The code for generating Figure 5 is included in the end of the 'Visualization' notebook.</p> <p>## Performance comparison plot<br> Figure 6 has been generated using IOHanalyzer web-interface (iohanalyzer.liacs.nl), by uploading the files in 'cma_bfgs.zip'. </p> <p>## Switch point impact plot<br> Figure 7 has been generated using the 'split_experiment' notebook</p>
Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling; Model input and output files
<p>These are the model input and output associated with the manuscript "Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling" in consideration for publication in the Journal of Volcanology and Geothermal Research.</p>
Mechanical behavior of C45 steel at high temperatures and high strain rates—experimental data set and numerical approach
<p>In this publication we provide experimental data of dynamic compression tests of four microstructural variants of the C45 steel alloy performed at high temperatures and high strain rates. The presented data evidences the presence of Dynamic Strain Aging (DSA) in the material. Moreover, we provided the MATLAB codes of a calibration approach to estimate the material parameters of a plasticity model that accounts for DSA.</p> <p>The file "Mechanical behavior of C45" contains:</p> <p>1) Folder EXP_DATA contains experimental data of dynamic compression tests of the C45 steel variants in .mat format. The data is organized in cell arrays, and every cell in the arrays contains the data of one experiment. The data of each experiment is arranged as four columns arrays, as: column 1: Plastic strain, column 2: Flow stress, column 3: absolute temperature, column 4: strain rate</p> <p>2) Matlab code named CALIBRATION.m which executes a calibration approach of a modified Johnson-Cook that accounts for DSA. The form of the model is the following:</p> <p><span class="math-tex">\(\sigma(\varepsilon ,T,\dot{\varepsilon}) = (A+B\varepsilon^n)\left(1+Cln\left(\frac{\dot{\varepsilon}}{\dot{\varepsilon}^{ref}}\right)\right)\left( 1-\left(\frac{T-T^{ref}}{T^{melt}-T^{ref}}\right)^m\right) +\sigma^{dsa}(\varepsilon ,T,\dot{\varepsilon}) \)</span></p> <p>with,</p> <p><span class="math-tex">\(σ^{dsa} (ε,T,\dotε )=\frac{B_1}{ν} \left(\frac{ε^β}{ ε ̇T} exp(-\frac{Q_m}{KT}) \right)^{\frac{2}{3}}\)</span>, <span class="math-tex">\(\frac{B_1}{\nu} = \frac{\psi \dot{\varepsilon}}{exp(\eta \frac{T}{\dot{\varepsilon}^\alpha})} \)</span></p> <p> </p> <p>The code CALIBRATION contains a data presentation section that can be used to generate plots to compare calibrated models with the experimental data. Further instructions are commented in the code CALIBRATION.m.</p>
An experimental and numerical study of turbulent oscillatory flow over an irregular rough wall
<p>Phase-averaged experimental data, phase- and spatial-averaged numerical data, and digitized roughness as described in: Dunbar, D., van der A, D.A., Scandura, T., O'Donoghue, T. (2023). An experimental and numerical study of turbulent oscillatory flow over an irregular rough wall. Journal of Fluid Mechanics, 955, A33, doi:10.1017/jfm.2022.1090.</p> <p>If interested in the time-series data and/or the spatially varying numerical data please contact the corresponding author of the paper. </p>
Numerical Investigation of Interface Passivation Strategies for Sb2Se3/CdS Solar Cells
<p>Sb<sub>2</sub>Se<sub>3</sub> is an emerging earth-abundant material praised for its promising optoelectronic properties, although the presence of interfacial defects at the vicinity of the p–n junction limit its performance as photovoltaic absorber. Using a device modeling approach and a realistic set of material parameters, it unravels pathways mitigating the impact of interfacial defects with a baseline Sb<sub>2</sub>Se<sub>3</sub>/CdS. Two straightforward strategies are devised and tested against the baseline. First, a thin front surface sulfurization of the Sb<sub>2</sub>Se<sub>3</sub> absorber allowing a local lowering of the valence band and creating a “front surface field,” resulting in an increased carrier selectivity and limiting the density of holes available for interface recombination, leading to a significant efficiency improvement for optimized conditions. Second, the use of an ultrathin insulating Al<sub>2</sub>O<sub>3</sub> layer between the absorber and the buffer layer is considered, helping in preventing detrimental chemical interdiffusion at the junction. This strategy provides a direct interface passivation, though the interlayer thickness needs a fine tuning to balance the benefits of reduced interface recombination and a detrimental Al<sub>2</sub>O<sub>3</sub> low-conductivity layer. In each case, an analysis covering a broad range of parameters is presented, and conclusions are made in the frame of past numerical and experimental results.</p>
Numerical data from: Gasotransmitter modulation of hypoglossal motoneuron activity
<p>Using the rhythmic brainstem slice preparation, which contains the preBötzinger complex (preBötC) and the hypoglossal nucleus, we tested the hypothesis that central HO-2 dysregulation weakens hypoglossal motoneuron output. Disrupting HO-2 activity increased transmission failure as determined by the intermittent inability of the preBötC rhythm to trigger output from the hypoglossal nucleus. Failed transmission was associated with a reduced input-output relationship between the preBötC and the motor nucleus. These network phenomena were related to smaller inspiratory drive currents and reduced intrinsic excitability among hypoglossal neurons. In addition to HO-2, hypoglossal neurons also expressed the CO-regulated H2S producing enzyme cystathionine ϒ-lyase (CSE). H2S abundance was higher in hypoglossal neurons of HO-2 null mice than wild-type controls. Disrupting CSE function normalized transmission in HO-2 null mice and an H2S donor mimicked the effects of HO-2 dysregulation. These findings demonstrate a hitherto uncharacterized modulation of hypoglossal activity through the interaction of HO‑2 and CSE-derived H2S, and supports the perspective that centrally derived HO-2 activity plays an important role regulating upper airway control. This archived dataset contains the numerical data used to generate the figures in the preprint titled: Gasotransmitter Modulation of Hypoglossal Motoneuron Activity by Brigitte Browe, Ying-Jie Peng, Jayasri Nanduri, Nanduri R. Prabhakar, and Alfredo J. Garcia III. This report can be found at <a href="https://www.biorxiv.org/content/10.1101/2022.03.23.485481">https://www.biorxiv.org/content/10.1101/2022.03.23.485481</a>. </p>
Data for "Convective Organization and Dry Tropical Cyclones in Direct Numerical Simulations of Idealized Fluid Setups"
<p>Supporting data and analysis scripts for work contained in the manuscript Velez-Pardo, Martin & Cronin, Timothy W. (2023) Convective Organization and Dry Tropical Cyclones in Direct Numerical Simulations of Idealized Fluid Setups. README and scripts for running simulations and for data post-processing are found in README_and_scripts.zip. Data obtained using supercomputer Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory (CISL), sponsored by the National Science Foundation.</p>
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data
<p>This repository contains the code and data for reproducibility of the paper 'Computing Star Discrepancies with Numerical Black-Box<br> Optimization Algorithms'. </p> <p>The following files are included:</p> <p>- TA.zip and DEM.zip: The code used for the TA and DEM algorithms respectively.</p> <p>- experiment_runner: Python file which was used to run the black-box optimization algorithms on the discrepancy problems from IOHexperimenter (requires package 'ioh', version 0.3.6 or higher). This generates data in IOH-format, which is included in 'raw_data.zip'</p> <p>- process_stardicr.R: R script which uses IOHanalyzer to extract the performance from the raw data into csv files for visualization. The resulting csvs are included in 'csv_with_pos' for the final results including the corresponding coordinates and 'csv_perf.zip', which contains the convergence information.</p> <p>- Found_Values: The discrepancy values found by TA and DEM, separated by sampler.</p> <p>- A csv file of the relative performance of each of the optimizers compared to the values found by TA is included in 'final_precision_table.csv'</p> <p>- Plot_StarDiscr: the python notebook used to generate all figures, except figure 3 which was created using the IOHanalyzer GUI (iohanalyzer.liacs.nl). The full dataset is available on the website under the source 'star_discrepancy'</p> <p>- Figures: some additional figures which were not included in the paper because of space constraints + higher quality versions of some of the landscape plots.</p>
Evaluations on numerical simulations of ozone dry deposition over the Yangtze River Delta
<p>Regional simulation of ozone dry deposition is an important tool for understanding ozone pollution threats and quantifying the ozone impact on terrestrial ecosystems. In this study, we evaluate ozone dry deposition in the Yangtze River Delta (YRD) region using two different dry deposition schemes. The WRF-Chem model, Wesely dry deposition scheme, and revised Surfatm dry deposition scheme were used to simulate the ozone dry deposition process in the YRD region, and results are compared with the observation over a winter wheat field. The results show that the simulated ozone concentrations (<em>c</em><sub>O3</sub>) of the two dry deposition schemes were good and lower than the measurements. The simulated ozone dry deposition velocity (<em>V</em><sub>d</sub>) in the Surfatm dry deposition scheme was more close to the measurements. The mean value of <em>c</em><sub>O3 </sub>and <em>V</em><sub>d</sub> in the YRD region ranged from 30 to 50 nL·L<sup>−1</sup> and from 0.2 to 0.5 cm·s<sup>−1 </sup>in the daytime, respectively. To improve the simulation results of the ozone dry deposition process, the simulation errors due to different land use types, the meteorological factors on dry deposition resistance functions, and the influence of chemical reactions must all be considered.</p>
Data and Software for "Numerical diffusion and Turbulent mixing in convective self-aggregation"
<p>This folder contain the python scripts and the data necessary for reproducing figures and results reported in the paper " Numerical diffusion and turbulent mixing in convective self-aggregation" (in preparation for submission for the Journal of Advances in Modeling Earth System)</p>
LiftWEC deliverable 3.6 - Part II: Dataset from numerical simulations of full-scale LiftWEC device using a high-fidelity RANS model
<p>This dataset contains the numerical simulation results for a full-scale LiftWEC device in regular and irregular wave conditions. The regular wave cases occur at static pitch and fixed rotational velocity. The parameters used for these cases are described in the corresponding *CaseParameters.csv file. These simulations were used to derive a first estimate of the maximum conversion efficiency of the rotor from wave power to shaft power. A detailed description of the employed numerical model and the case setup can be found in LiftWEC deliverable 3.6 Hydrodynamic Validation of Final Design, which was also uploaded to the LiftWEC community on zenodo. In accordance with the coordinate system definition used in the validation case, a relative phase angle of 270° degree corresponds to foil1 at 3 o'clock position while the wave crest passes over the rotor axis position. Rotation is clockwise, Rotor rotates in the direction of orbital wave particle velocities.</p> <p>The control reference case describes the first test case of a cyclorotor in irregular waves under active control of angular velocity and foil pitch. This case is also documented in deliverable D3.6. The case files can be used to recreate wave conditions and motion signal. The load-file can be used to validate the obtained tangential and radial forces on foil 1 as well as the total power output over time. More information on the control model can be found in the corresponding project deliverables D5.X.</p> <p>All loads given as values per unit span length (e.g. for forces [N/m]).</p>
Data from: Prediction of three years of annual rain attenuation statistics at Ka-band in French Guiana using the Numerical Weather Prediction model WRF
<p><span>This study highlights the interest in using an Atmospheric Numerical Simulator (ANS) relying on a high-resolution weather forecast model coupled with an ElectroMagnetic Module (EMM) to compute Ka-band rain attenuation statistics in an equatorial region. An optimization of the parametrisation of the Weather Research and Forecasting meteorological model (WRF) is carried out using measurements collected from a propagation experiment carried out by CNES and ONERA near Kourou in French Guiana. Both simulated and experimental annual Complementary Cumulative Distribution Functions (CCDF) of rain attenuation are presented in this dataset.</span></p> <p>More specifically, this dataset includes the statistical distribution from both the WRF-EMM model and from the propagation experiment for the years 2017, 2018, 2020 and the whole three-year period.</p>
Theoretical and numerical comparison of quantum- and classical embedding models for optical spectra
<p>This repository contains the files for the computational study on "Theoretical and numerical comparison of quantum- and classical embedding models for optical spectra".<br> The repository is organized into different folders as described below:</p> <p>====================================================================================================<br> 1_pna<br> This folder contains the configuration structures for p-nitroaniline extracted from the Molecular Dynamics (MD) simulations in *.xyz format that were used for any further calculations.<br> ====================================================================================================<br> 2_pftaa<br> This folder contains the configuration structures for pentameric formyl thiophene acetic acid extracted from the Molecular Dynamics (MD) simulations in *.xyz format that were used for any further calculations.<br> ====================================================================================================</p> <p><br> We acknowledge funding by the German Research Foundation (DFG) through the Emmy Noether Young Group Leader Programme (CK, project KO 5423/1-1), The Villum Foundation, Young Investigator Program (EDH, grant no. 29412), the Swedish Research Council (EDH, grant no. 2019-04205), and Independent Research Fund Denmark (EDH, grant no. 0252-00002B and grant no. 2064-00002B) for support.<br> </p>
Dataset and supporting materials of "Numerical simulation of orographic gravity waves observed over Syowa Station. Part 1: Wave propagation and breaking in the troposphere and lower stratosphere" by Kohma et al.
<p>Dataset and supporting materials of "Numerical simulation of orographic gravity waves observed over Syowa Station. Part 1: Wave propagation and breaking in the troposphere and lower stratosphere" by Kohma, M., K. Sato, D. C. Fritts, & T. S. Lund.</p>
Supplementary Material: Numerical Simulations of Seismoacoustic Nuisance Patterns from an Induced M 1.8 Earthquake in the Helsinki, Southern Finland, Metropolitan Area
<p>Seismic waves can couple with the atmosphere and generate sound waves. The influence of faulting mechanisms on earthquake sound patterns provides opportunities for earthquake source characterization. Sound radiated from earthquakes can be perceived as disturbing, even at low ground-shaking levels, which can negatively impact the social acceptance of geoengineering applications. Motivated by consistent reports of felt and heard disturbances associated with the weeks-long stimulation of a 6-km-deep geothermal system in 2018 below the Otaniemi district of Espoo, Helsinki, we conduct fully coupled 3D numerical simulations of wave propagation in the solid Earth and the atmosphere. We assess the sensitivity of the ground shaking and audible noise distributions to the source geometry of the induced earthquakes based on the properties of the largest local magnitude ML 1.8 event. Utilizing recent computational advances and the open-source software SeisSol, we model seismoacoustic frequencies up to 25 Hz, thereby reaching the lower limit of the audible sound frequency range. We present synthetic distributions of shaking and audible sounds at the 50–100 m scale across a 12 km × 12 km area and discuss implications for better under- standing seismic nuisances in metropolitan regions. In five 3D coupled elastic–acoustic scenario simulations that include data on topography and subsurface structure, we analyze the ground velocity and pressure levels of earthquake-generated seismic and acoustic waves. We show that S waves generate the strongest sound disturbance with sound pressure levels ≤ 0.04 Pa. We use statistical analysis to compare our noise distributions with commonly used empirical relationships. We find that our 3D synthetic amplitudes are generally smaller than the empirical predictions and that the interaction of the source mechanism-specific radiation pattern and topography can lead to significant nonlinear effects. Our study highlights the complexity and information content of spatially variable audible effects associated with small induced earthquakes on local scales.</p>
Synergy between deep learning and numerical modeling in estimating NOx emissions at a fine spatiotemporal resolution
<p>This study focused on the remarkable applicability of deep learning (DL) together with numerical modeling in estimating NO<sub>x</sub> emissions at a fine spatiotemporal resolution in the summer of 2017 over the contiguous United States (CONUS). We leveraged the partial convolutional neural network (PCNN) and the deep neural network (DNN) to impute gaps in the OMI tropospheric NO<sub>2</sub> column and estimate the daily complete surface NO<sub>2</sub> map at a spatial resolution of 10 km × 10 km, showing high capability with a strong correspondence (R: 0.92, IOA: 0.96, MAE: 1.43). We then used the Community Multi-scale Air Quality (CMAQ) model at 12 km grid spacing to conduct an inversion of NO<sub>x</sub> emissions that allowed us to promote a comprehensive understanding of the chemical evolution. Compared to the prior emissions, the inversion suggested 3.21 ± 3.34 times higher NO<sub>x</sub> emissions over CONUS, significantly mitigating the underestimation of surface NO<sub>2</sub> concentrations with the prior emissions. The results displayed the primary benefits of incorporating DL-estimated daily complete surface NO<sub>2</sub> map, which in turn greatly reduced bias (-1.53 ppb to 0.26 ppb) and enhanced daily variability with higher correspondence (0.84 to 0.92) and lower error (0.48 ppb to 0.10 ppb) over the CONUS. </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.