Find research datasets worth reusing

opencc-by-4.0Sep 2021View details →

Supplemental data for characterization of alpha and beta interactions using the HeXe setup [Eur. Phys. J. C 82, 361]

Repository with supplemental data to: Characterization of alpha and beta interactions in liquid xenon. Jörg, F., Cichon, D., Eurin, G. et al. Eur. Phys. J. C 82, 361 (2022) <a href="https://doi.org/10.1140/epjc/s10052-022-10259-3">10.1140/epjc/s10052-022-10259-3</a> A pre-print of the article is available on arXiv: <a href="http://arxiv.org/abs/2109.13735">2109.13735</a> Note: When re-using the data, please make sure to cite the article (and not only the dataset) The files contain the measured data points (as well as their statistical and systematic uncertainties) as shown in the publication. All datasets are stored in the .csv format. <ul> <li>20210924_yields_hexe_kr83m.csv This file contains the normalized light and charge yields as a function of the applied field from the measurement with the 83mKr source. The data is shown in Figure 16 (dots) of the publication. Furthermore the file contains the LY ratio between the two Isomeric transitions of the 83mKr source, shown in Figure 17 of the article.</li> <li>20210924_yields_hexe_rn222.csv This file contains the normalized light and charge yields as a function of the applied field from the measurement with the 222Rn source. The data is shown in Figure 18 (blue-ish points) of the publication</li> <li>20210924_drift_velocity_hexe_rn222.csv This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the  222Rn source. Drift velocity is given in units of mm/µs and the datapoints are shown in Figure 20 (black dots) of the publication </li> <li>20210924_drift_velocity_hexe_kr83m.csv This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the  83mKr source. Drift velocity is given in units of mm/µs and are not displayed in the publications due to visibility reasons.</li> </ul> Minimum working example to plot the drift velocity using the 83mKr data: <pre><code class="language-python"> 1 import numpy as np 2 import matplotlib.pyplot as plt 3 4 # load the data set 5 data = np.loadtxt("20220427_drift_velocity_hexe_kr83m.csv", delimiter=",") 6 7 # Plot the systematic uncertainty on the drift field 8 plt.errorbar(data[:,0], data[:,2], xerr=data[:,1], fmt="o", capsize=2, ecolor="darkgray", 9 alpha=0.7, elinewidth=3, color="black") 10 11 # Plot the actual data points 12 plt.errorbar(data[:,0], data[:,2], yerr=data[:,3], fmt="o", color="black") 13 14 # Label the axis and define the range 15 plt.ylabel("Drift Velocity [mm/µs]") 16 plt.xlabel("Drift Field [kV/cm]") 17 plt.xscale("log") 18 plt.xlim(0.006, 2) 19 plt.ylim(0, 2.4) 20 plt.show() </code></pre>

opencc-by-4.0Apr 2022View details →

Supporting Information for 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces'

Supporting Information of 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces' This dataset contains the Supporting Information of the publication  Rühr PT & Blanke A (2022): 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces'. doi: <a href="https://doi.org/10.1111/2041-210X.13909">10.1111/2041-210X.13909</a>. It includes <ul> <li>validation measurements the forceX setups (1 Ruehr Blanke 2022 validation measurements.zip)</li> <li>all CAD files to build the forceX setup (3D-printed or metal-turned) (2 Ruehr Blanke 2022 forceX CAD files.zip)</li> <li>forceX assembly instructions in HTML format, including schematics of custom electronics (3 Ruehr Blanke 2022 forceX Assembly instructions.html)</li> <li>forceX assembly instructions as video (4 Ruehr Blanke 2022 forceX assembly video 03.mp4)</li> <li>R code that produced all validation-related figures used in the original publication and that functions as a forceR v.1.0.13 example workflow (5 Ruehr Blanke 2022 forceR_workflow_example.R)</li> <li>Python code to take videos of force measurements using the forceX camera module (6 Ruehr Blanke 2022 forceX_RPi_camera_code.py)</li> <li>bundled version of forceR v.1.0.15 (forceR_1.0.15.tar.gz)</li> </ul> The CAD files and assembly instructions are also available on <a href="https://www.thingiverse.com/thing:4961834">Thingiverse</a>. The forceR package is available on <a href="https://cran.r-project.org/web/packages/forceR/index.html">CRAN</a> (stable version) and <a href="https://github.com/Peter-T-Ruehr/forceR">GitHub</a> (development version).

opencc-by-4.0Jan 2022View details →

A setup for studies of photoelectron circular dichroism from chiral molecules in aqueous solution - data

Data set pertaining to the article  "A setup for studies of photoelectron circular dichroism from chiral molecules in aqueous solution" | Review of Scientific Instruments, aip.org, doi: <a href="https://doi.org/10.1063/5.0072346">10.1063/5.0072346</a> . Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.06, see https://www.nexusformat.org/ https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format: * nexpy (distributed with python) * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium) Files with extension .asc are ascii-files. The following files are provided: fig-fenchone-rsi.asc : numeric form of traces shown in Fig. 7 fig-lfenchone-roi-rsi.asc : numeric form of traces shown in Fig. 8 data relevant for Fig.s 7,8 and Table 1 gas-phase_1R-fenchone.h5 : data set of gas phase photoemission data for (1R,4S)-(−)-fenchone gas-phase_1S-fenchone.h5 : data set of gas phase photoemission data for (1S,4R)-(+)-fenchone liquid-phase_1R-fenchone.h5 : data set of liqiud phase photoemission data for (1R,4S)-(−)-fenchone liquid-phase_1S-fenchone.h5 : data set of liquid phase photoemission data for (1S,4R)-(+)-fenchone data relevant for Fig. 9 gas-liq_1R-fenchone.h5 : data set for photoemission of (1R,4S)-(−)-fenchone (biased and grounded) data relevant for Fig. 10 flatjet_fig10a.h5 flatjet_fig10b.h5 flatjet_fig10c.h5 Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .

opencc-by-sa-4.0Mar 2018View details →

Survey of participant experience in workshop for testing IGP software setup: supplemental dataset for SimAUD 2018

This is a supplemental dataset for a SimAUD 2018 paper. For the context of the dataset, plots, and description text given here, please refer to the paper: <blockquote> Heinrich, M.K., Zahadat, P., Harding, J., et al. Using interactive evolution to design behaviors for non-deterministic self-organized construction. In Proc. of SimAUD (2018). In print. </blockquote> These survey results (see attached file dataset_survey-responses), are regarding the experience of participants in a workshop testing the Integrated Growth Projection software setup, including an implementation of the Vascular Morphogenesis Controller, and the Interactive Evolution software Biomorpher. The full-time one-week workshop was held as part of the normal coursework of the Master's degree program CITAstudio: Computation in Architecture, in the Institute of Architecture and Technology, at [KADK] The Royal Danish Academy, School of Architecture, Copenhagen, Denmark. It was part of the first semester of the 2017-2018 school year. Workshop participants were current Master's students in the CITAstudio program. The workshop teaching was led by Mary Katherine Heinrich and Phil Ayres, with guest teaching by Payam Zahadat and John Harding, overall program teaching supervision by Paul Nicholas, and teaching assistance by Sebastian Gatz. Survey method: The workshop participants gave survey responses anonymously. Survey responses were collected via Google Forms (https://www.google.com/forms/about/). At the start of the survey, participants gave permissions for use and publication, and verified that they participated in the workshop and had not previously taken the survey. The platform discourages duplicate responses by requiring an email sign-in (which is not visible to the surveyor). Although workshop participants gave permission for survey results to be published before taking the survey, the participants were unaware of the specific intended context and purpose of publishing, prior to taking the survey. Authors of the related paper who were workshop participants had no contact with the process of survey preparation, analysis of its results, or writing of related paper sections.  There were 26 workshop participants. Participants were architects or architectural designers.  Participants were asked about 1) their prior experience, 2) their understanding of topics before and after the workshop, 3) the helpfulness of specific software aspects for their understanding and their project work, and 4) their likelihood to use specific software aspects in the future. In addition to looking at the full surveyed group, we compare experience sub-groups. Participants select relevant tasks that they have previously completed, from a provided list. They are placed in the Less Experience sub-group if they select one or no tasks, and in the More Experience sub-group if they select two or more.  Survey results: Close to two-thirds of workshop participants submitted survey responses (16 of 26, or 61.5%), with at least two respondents per group. One respondent indicated workshop absence; their responses were removed. One respondent indicated that they did not understand two questions, so those two responses were removed. All responses were submitted within 18 days of workshop end. Attached file: Plot_1, caption: <blockquote> Plot 1: Participants' scoring of their understanding of the topics "self-organization" and "Interactive Evolution" respectively, comparing scores before and after the workshop. </blockquote> Attached file: Plot_2, caption: <blockquote> Plot 2: (Left) Participants' scoring of their likelihood to use certain aspects of the software setup again, if they were to design a non-deterministic self-organizing behavior, and (right) participants' indications of the helpfulness of those same software aspects. </blockquote> Responses regarding understanding (see attached file, Plot_1) give evidence that the Integrated Growth Projection software setup helped participants of both experience levels improve their understanding of related topics. Those with less prior experience improved their understanding more than others, and understanding of "Interactive Evolution" improved slightly more than understanding of "self-organization."  Responses regarding the usefulness of certain software aspects (see attached file, Plot_2) give evidence that: 1) Interactive Evolution helped participants to understand and design a non-deterministic self-organizing behavior (see Plot_2, a); 2) visualization of the environment and simultaneous viewing of multiple results helped them to understand and design such behaviors (see Plot_2, b and c); and 3) the Integrated Growth Projection's features of environment visualization and simultaneous results inside the artificial selection preview windows of the IE setup helped them to evolve behaviors to solve their chosen tasks (see Plot_2, d and e).  ____________________________________ The research work involved here is part of EU project flora robotica. <a href="http://www.florarobotica.eu/">http://www.florarobotica.eu/</a> Project flora robotica has received funding from the European Union's Horizon 2020 research and innovation program under the FET grant agreement, no. 640959.

opencc-by-4.0Dec 2019View details →

Setup of the 2010 Darfield earthquake for SeisSol

Dynamic rupture setup of the 2010 Darfield earthquake built for SeisSol (https://github.com/SeisSol/SeisSol/). SeisSol version This setup is built for SeisSol version 479583792e651bf18bd582f71254722ee023ca07. Fault segments are distinguished by using the fault tagging feature (see https://seissol.readthedocs.io/en/latest/fault-tagging.html). In essence, boundary conditions 3, 7, 8, 9, 10, 11, and 12 are all interpreted as fault and each number marks a fault segment. However, fault tagging is experimental and this behaviour might change in future versions of SeisSol. In case the fault tags need to be adjusted, make sure to edit meshing_options.xml and re-generate the mesh, and edit initial_stress.yaml. Projection EPSG:32759 File list - Darfield.h5     Mesh with 98113814 elements. - fault_cad_model.geo     CAD model of the fault geometry for Gmsh. - initial_stress.yaml   material.yaml   fault.yaml     Material model and fault parameterisation with easi. - meshing_options.xml     Meshing options to generate the mesh with PUMGen (https://github.com/SeisSol/PUMGen/tree/xml). - Qp.nc   Qs.nc   vel_model.nc     3D material model on uniform grid (lambda, mu, rho, Qp, Qs). - roughness0.nc   roughness1.nc   roughness2.nc   roughness3.nc   roughness4.nc   roughness5.nc     Relative pre-stress ratio for the six fault segments. - Darfield.smd     CAD model with topography. Opens with SimModeler from Simmetrix and is passed to     PUMGen for mesh generation. - parameters.par     Settings for invoking SeisSol. - receivers.txt     Position of synthetic seismographs.

opencc-by-4.0Nov 2017View details →

Setup of the TPV16 benchmark for dynamic rupture verification

Verification benchmark for simulations with dynamic rupture and local time stepping with SeisSol, version Shaking Corals. More details can be found in the publication Uphoff et al. "Extreme scale multi-physics simulations of the tsunamigenic 2004 Sumatra megathrust earthquake", 2017 and on the project homepage (http://www.seissol.org/).

opencc-by-4.0Nov 2017View details →

Setup of the 2004 Sumatra-Andaman earthquake for SeisSol, version Shaking Corals

Sample input dataset of the 2004 Sumatra-Andaman earthquake for SeisSol, version Shaking corals. The mesh consists of 3.645.163 elements and is partitioned to run with 20 MPI processes. SeisSol can be obtained from from Github (https://github.com/SeisSol/SeisSol/releases/tag/201703). A description on how to set up SeisSol is available in the artifact description of Uphoff et al. "Extreme scale multi-physics simulations of the tsunamigenic 2004 Sumatra megathrust earthquake", 2017 and in the Github Wiki (https://github.com/SeisSol/SeisSol/wiki).

opencc-by-4.0Jun 2022View details →

Building and characterizing a fluorescence setup to measure very low concentrations of analytes/biomarkers

This training report is the result of my internship in the B-Phot Brussels Photonics team of the VUB that took place between February 3 and April 3, 2020. The project of this internship nds its context in the European SensApp project which regroups several European research institutes and universities, including the VUB. The goal of this project is to develop a method to diagnose the Alzheimer's disease in a faster and non-invasive manner, simply through a blood test, which is currently not possible because the concentration of biomarkers of the Alzheimer's disease in the blood is too low. During this internship, I was lead to build, align and calibrate a uorescence detection setup. Using this setup, I made mea- surements of the uorescence intensity of low concentrations of dye solutions. From those measurements, I performed calculations of the signal to noise ratio in order to determine the limit of detection of the setup. Finally, I studied the kinetics of photobleaching in order to get to a better understanding of its impact on the measurements.

opencc-by-4.0Jul 2023View details →

Input and output data (images + boulder labels, model setup, model weights and more) for the manuscript "Automatic characterization of boulders on planetary surfaces from high-resolution satellite images"

File 1: raw_data_BOULDERING.zip Size: 8.8 GB Summary: It contains all of the rasters (planetary images) and labeled boulders (raw data): <ul> <li> a boulder-mapping file, which is the manually digitized outline of boulders. </li> <li> a ROM file (stands for Region of Mapping), which depicts the image patches on which the boulder mapping has been conducted. </li> <li> a global-tiles file, which shows all of the image patches within a raster. </li> </ul> There are multiple locations/images per planetary body. Structure: <pre>. └── raw_data/ ├── earth/ │ └── image_name/ │   ├── shp/ │   │ ├── <image_name>-ROM.shp │   │ ├── <image_name>-boulder-mapping.shp │   │ └── <image_name>-global-tiles.shp │   └── raster/ │     └── <image_name>.tif ├── mars/ │ └── image_name/ │   ├── shp/ │   │ ├── <image_name>-ROM.shp │   │ ├── <image_name>-boulder-mapping.shp │   │ └── <image_name>-global-tiles.shp │   └── raster/ │     └── <image_name>.tif └── moon/   └── image_name/     ├── shp/     │ ├── <image_name>-ROM.shp     │ ├── <image_name>-boulder-mapping.shp     │ └── <image_name>-global-tiles.shp     └── raster/       └── <image_name>.tif</pre>   File 2: best_model.zip Size: 624.7 MB Summary: This zip file contains all of the inputs and outputs required/obtained from the training of the BoulderNet Mask R-CNN model (model setup, augmentation pipeline, model weights, log during training, logged metrics): <ul> <li> augmentation_pipeline.json (required as inputs for the training of the algorithm to apply augmentations). See <a href="https://github.com/astroNils">https://github.com/astroNils</a> and the MLtools repository for more information. </li> </ul> <ul> <li> Base-RCNN-FPN.yaml (base model setup file). </li> <li> config.yaml (complete model setup file, merge of the base and Mars-Moon-Earth setup file). </li> <li> Mars-MoonEarth-v050...yaml (model setup file). </li> <li> log.txt (log during training of the algorithm). </li> <li> model_0055999.pth (model weights at second last saving step) </li> <li> model_0063999.pth (model weights at last saving step) </li> </ul> We advice the use of model weights model_0055999.pth (to avoid slight overfitting). File 3: Apr2023-Mars-Moon-Earth-mask-5px.zip (pre-processed input images) Size: 252.8 MB Summary: This zip files contains the input data (images and boulder outlines) for the train, validation and test datasets. See <a href="https://github.com/astroNils">https://github.com/astroNils</a> and the MLtools repository for more information in how-to-use the different files. <ul> <li> The json folder contains json files that can be given as input (as a custom dataset) to the Detectron2 platform. The only differences between the two files is how the bounding boxes around masks have been generated. We advised to use "Apr2023-Mars-Moon-Earth-mask-5px.json". </li> <li> The pkl folder and pickle file includes some informations about the 950 image patches in our boulder dataset. </li> <li> The pre-processing folder contains all of the training, validation and test image patches and corresponding shapefiles. </li> <li> The shapefile folder is actually empty (it should not be there!). </li> </ul> Structure: <pre>. └── preprocessed_inputs/   ├── json   ├── pkl   ├── preprocessing/   │   ├── train/   │   │   ├── images   │   │   └── labels   │   ├── validation/   │   │   ├── images   │   │   └── labels   │   └── test/   │       ├── images   │       └── labels   └── shp</pre>

opencc-by-4.0Apr 2020View details →

Global Storm Tide Modeling on Unstructured Meshes with ADCIRC v55 - Simulation Results and Model Setup

Simulation results and model setup for the paper entitled "Global Storm Tide Modeling with ADCIRC v55: Unstructured Mesh Design and Performance". Simulations conducted using <a href="http://adcirc.org/">ADCIRC</a> (pre-release Version 55) on unstructured triangular meshes of the global Earth's ocean.  Contains: <ol> <li>Global Tide Harmonics: Simulated harmonic constituents of global astronomical tide on various mesh designs (*.53.nc).</li> <li>Local Storm Tide: ADCIRC model setup and simulation results from storm tides forced by Hurricane Katrina and Super Typhoon Haiyan on meshes with different local refinements (1.5 km, 500 m, 150 m) in the storm landfall region. <ul> <li>ADCIRC model input files (*.13, *.14, *.15, *.22, *.221, *.222, fort.rotm)</li> <li>Global maximum storm tide elevations (*_maxele.63.nc)</li> <li>Global 3-hourly storm tide elevation time series (*.63.nc)</li> <li>Storm tide elevation and velocity time series (20-min intervals) at selected stations (*.61.nc, *.62.nc)</li> </ul> </li> <li>Zipped archive of the ADCIRC code (adcirc-cg-GLOBAL.zip) used to produce the results archived here.</li> </ol> See the README files for further details.

opencc-by-4.0Apr 2016View details →

Binaural room impulse responses of a 5.0 surround setup for different listening positions

Binaural Room Impulse Responses - KEMAR, room Calypso, TU Berlin, 5.0 Surround setup   This dataset contains binaural room impulse responses (BRIRs) measured at nine different listening positions for a 5.0 surround setup in the listening room Calypso in the Telefunken building of Technische Universität Berlin, Berlin, Germany. The room has a volume of 83 m³ and a reverberation time RT60 of 0.17 s at a frequency of 1 kHz. "doc.zip" contains additional information for the measurement, "*.sofa" are the actual BRIRs, one file for every listening position, where the position is indicated by the X*-Y*-values. In order to work with those files you need a SOFA API for your programming language. For example, the one for Matlab can be found here: https://github.com/sofacoustics/API_MO/releases/latest If you want to create a single SOFA file containing all listening positions, you can execute the "combine_positions.m" script in Matlab after installing and starting the SOFA API. The BRIRs were with a head-orientation varying in the range of +-90° with 1° resolution. Room shape and size, listener and sound source positions are shown in "setup_calypso_surround_genelec8030A.pdf". Directory "./photos" contains photographs of the measurement setup. Copyright 2016 Hagen Wierstorf Licensed under Creative Commons (CC-BY-4.0)

opencc-by-4.0Apr 2016View details →

Binaural room impulse responses of a 5.0 surround setup for different listening positions

This dataset contains binaural room impulse responses (BRIRs) measured at nine different listening positions for a 5.0 surround setup in the listening room Calypso in the Telefunken building of Technische Universität Berlin, Berlin, Germany. The room has a volume of 83 m³ and a reverberation time RT60 of 0.17 s at a frequency of 1 kHz. The measurment was done with Genelec 8030A loudspeakers and repeated for the central listening positon with the larger Genelec 8250A loudspeakers. "doc.zip" contains additional information for the measurement, "*.sofa" are the actual BRIRs, one file for every listening position, where the position is indicated by the X*-Y*-values. The file `KEMAR_Calypso_Surround.sofa` contains all listening positions in one file. In order to work with those files you need a SOFA API for your programming language. For example, the one for Matlab can be found here: https://github.com/sofacoustics/API_MO/releases/latest The BRIRs were with a head-orientation varying in the range of +-90° with 1° resolution. Room shape and size, listener and sound source positions are shown in `setup_calypso_surround_genelec8030A.pdf` and `setup_calypso_surround_genelec8250A.pdf`. Directory "./photos" contains photographs of the measurement setup. Copyright 2016 Hagen Wierstorf Licensed under Creative Commons (CC-BY-4.0)

opencc-by-4.0Oct 2016View details →

Binaural room impulse responses: Same listener-source-setup at different positions in the room

To study the perception of room acoustics in dependency of the position in the room, measurements with KEMAR head-and-torso-simulator were conducted. The dummy head was placed at 5 different positions in a small conference room (10.3mx5.8mx3.1m, RT=0.65s). The source, a loudspeaker Genelec 1030A, was always positioned in the same relation to the listening position. BRIRs were measured with an azimuth-resolution of 5° from 0°-360°. This data allows a psychoacoustical comparison of the room acoustical properties at different positions in the room.

opencc-by-4.0Oct 2016View details →

Binaural room impulse responses: Same listener-source-setup at different positions in the room

opencc-by-4.0Jan 2017View details →

Tutorial Photonics Explorer Module 3 part 2: lenses, imaging rules, optical setups and telescopes

Photonics Austria (PhAu) has conducted Teacher Training Programmes about Phoronics - the Photonics Explorer- in order to promote the potential of photonics to enliven physics lessons. This video is concerned with the topic polarisation and optical activity.

opencc-by-4.0Jan 2017View details →

Tutorial Photonics Explorer Module 3 part 1: lenses, imaging rules, optical setups and telescopes

Photonics Austria (PhAu) has conducted Teacher Training Programmes about Photonics - the Photonics Explorer- in order to promote the potential of photonics to enliven physics lessons. This video tutorial contains several experiments designed to illustrate imaging equation and the laws of lenses.

opencc-by-4.0Nov 2021View details →

Synthetic dataset for the flow-shop problem with sequence-dependent setup times (FSsdsu_DS_01)

Synthetic dataset containing setup and processing times for a flow-shop problem of 1.000 parts and 200 machines. The setup times are specified for each machine taking into account the previous part produced on the machine.

opencc-by-4.0Dec 2021View details →

Tsunami Simulation: TsunAWI Testcase "Coquimbo 2015", Setups and Example Results

This dataset contains three setups with example results for TsunAWI simulations for the Chilean coast with a focus on the Coquimbo region. They are used in the LEXIS project, WP6 "Earthquake and Tsunami Pilot". coquimbo_150m.tgz - coarse setup with down to 150m resolution in Coquimbo and other areas of interest along the Chilean coast coquimbo_20m.tgz - fine setup with down to 20m resolution in Coquimbo, also high resolution along other areas of interest along the Chilean coast coquimbo_20m_new.tgz - setup tuned for the LEXIS workflow aiming at a real time estimate of the inundation on the City of Coquimbo, thus a focus with 20m resolution only in Coquimbo region.   Each dataset includes a README explaining the included files. The following description is taken as pars pro toto from coquimbo_20m_new.tgz. Computational Mesh <ul> <li>mesh/Coquimbo_20m/nod2D.out  Location of mesh vertices in geographical coordinates, vertices on the open boundary are flagged with "1" Resolution in Coquimbo area: 20m</li> <li>mesh/Coquimbo_20m/nodhn.out Water depth at the respective vertices. Negative values denote elevation on land.  In the ocean: ‘The GEBCO_08 Grid, version 20090202 (http://www.gebco.net)’  On land: SRTM, Shuttle radar topography mission, 1 arcsec resolution, https://www2.jpl.nasa.gov/srtm/ Bilinear interpolation to the mesh vertices.</li> <li>mesh/Coquimbo_20m/elem2D.out Mesh geometry: List of the vertices forming the triangular elements.</li> </ul> Input Parameters <ul> <li>namelist.tsunami Parameters read by TsunAWI at run time, e.g., <ul> <li>path to the mesh and the output</li> <li>the time step dt and the time frame of the simulation T_end</li> <li>physical parameters like Manning friction, viscosity</li> <li>toggle the output </li> </ul> </li> <li>Additional command line parameters The results below are for an idealized source (Cosine bell at the location of the 2015 Coquimbo event, started with  ompTsuna.x -xy -71.674 -31.573 -mw 8.3 -id coquimbo_20m</li> </ul> Result <ul> <li>coquimbo_20m_new.nc  Example output in netcdf format, raw data on the triangular mesh, see ncdump -h coquimbo_20m.nc    </li> <li>coquimbo_20m_new_inundation.nc The same raw data but restricted to the inundated area, for faster postprocessing.</li> </ul> The TsunAWI version used is  https://gitlab.awi.de/tsunawi/tsunawi/-/tags/LEXIS with one minor bugfix: Add      use mpi_parallel to line 881 of tsunawi/src/parameters.F90     Compiled with tsunawi/src/Makefile.in_karolina and run on karolina.it4i.cz in MPI-parallel mode with 128 tasks.   This work was supported by the LEXIS project funded by the EU’s Horizon 2020 research and innovation programme (2014-2020) under grant agreement No 825532.