Example dataset for a CFD thermal simulation of a mounted heat sink. The dataset serves as sample file to develop, test, and verify - interfaces - import functions or - data migration.

The numerical data in this repository consists of the simulation data of multi-crack-seak syntaxial quartz vein formation. The simulations were performed using the software package "Pace3D (v. 2.5.1)".

The simulation data shows intermediate fracturing and growth stages and was converted from Pace3D output data format to VTK data format. The VTK files can be visualized using open source software packages like Paraview. Some data files in the subfolders are also compressed (file format *.gz). For visualization the data has to be decompressed with e.g. gzip or 7zip.

This dataset contains the results of our method Geodesic-BP, presented in https://arxiv.org/abs/2308.08410. The original rabbit torso model can be found in https://zenodo.org/record/6340066, on which we based the setup. The dataset consists of the final results, optimization results over the 400 iterations and a pseudo-bidomain simulation from the final result. All files are provided in variants of the VTK file format (https://vtk.org/) The setup/result files are organized as follows:

result_mesh_init_final.vtu - The biventricular mesh containing both initial and final solution φk result_x0_init.vtp - The initial conditions (xi , ti) used in the first optimization iteration result_x0_final.vtp - The initial conditions (xi, ti) computed using our optimization algorithm ecgs.npz - Numpy-readable (np.load) arrays of ECGs (ecg_init, ecg_final, ecg_target) ecgs.vtp - Target and optimized ECGs converted to a Paraview-readable format ecg_history.npz - Numpy-readable array of the ECGs over the iterations The animation files present allows you to preview the solution in each iteration

phi_history.xdmf - The solution φk in each iterations (surface only) x0_history.xdmf - The initial conditions in each iteration ecg_anim.xdmf - The computed ECGs in each iteration The files can be easily viewed in VTK-compatible viewers, such as Paraview (https://www.paraview.org/). We additionally provide a Paraview state file (preview.pvsm), which when opened in Paraview automatically creates several views that visualize the data in different views. Simply open Paraview, select File -> Load State, locate the preview.pvsm. In the next prompt (Load State Options) select "Search files under specified directory" and locate the folder with the files, then press OK.

The numerical data in this repository consists of the simulation data of epitaxial crystal growth in open fractures with lateral flow. The simulations were performed using the software package named "Pace3D".

The simulation data shows the grain structure, the concentration field and the fluid flow velocity in stream direction (if present) at intermediate stages. It was converted from the Pace3D output data format to VTK data format. The VTK files can be visualized using open source software packages like Paraview. For visualization the data has to be decompressed (e.g. with gzip, 7zip).

This set of results stems from a database computed with a Direct Numerical simulation of the incompressible flow around a rectangular cylinder with chord-to-thickness ratio 5:1 (also known as BARC benchmark). The Reynolds number based on the cylinder thickness and the incoming velocity is set to Re=3000. We provide the two-dimensional mean field as well as the complete set of Reynolds stresses and the terms involved in their single-point budget equations. Further details can be found on an accompanying paper by Chiarini & Quadrio, Flow Turbul. Combust. 107, 875–899 (2021), available at https://doi.org/10.1007/s10494-021-00254-1.

Data are provided in VTK file format, so that they can be visualized with several applications, as for example the open-source package ParaView.

The file mean.vtk contains the mean flow in terms of the velocity components U and V and pressure field P in the x − y plane. The files uu-Budget.vtk, vv-Budget.vtk, ww-Budget.vtk, uv-Budget.vtk, uw-Budget.vtk, vw-Budget.vtk and k-Budget.vtk contain the complete set of terms appearing in the budget equations for the components of the Reynolds stress tensor and for the turbulent kinetic energy.

Extract of a computer tomographic imaging dataset of the thorax, showing the upper lumbar and lower thoracic spine, stored as VTK image. The dataset is used to develop the SODALITE virtual clinical trial use-case. It contains a part of the lumbar spine. Starting caudal at L2 which is only partially contained and ending cranial with T9 which also only partially contained. The datasets content is illustrated by the attached png image which shows a volume rendering of the dataset. Format : VTKFile, type="ImageData", version="1.0" Header : ASCII Byte Order : LittleEndian Grid Type : Rectilinear Extend [x,y,z] : 201 , 301 , 161 Spacing [x,y,z] : 0.78125 , 0.78125 , 1.0 Data-Type : Float64 Min Value : 0 Max Value : 2210.5396825

Supplementary data for 18 cases of hepatic tumors, treated with percutaneous irreversible electroporation ablation.- segmentation.nii (NIfTI format):Tissue masks, segmented from pre-interventional CECT.

• liver_interv.vtk (VTK format):Liver surface model, obtained from pre-interventional CT segmentation, registered to computation domain

• tumor_interv.vtk (VTK format):Tumor surface model, obtained from pre-interventional CT segmentation, registered to computation domain

• liver_follow_trans.vtk (VTK format):Liver surface model, obtained from 6-week follow-up MRI, registered to computation domain

• segmented_lesion_trans.vtk (VTK format):Ablation zone surface model, obtained from 6-week follow-up MRI, registered to computation domain

• field400-field900.vtk (VTK format):Computed electric field surfaces obtained by thresholding the volumetric data with 400, 500, 600, 700, 800, 900 V/cm

Newborn mesh

Description:

This dataset contains a labelled mesh of the thorax of a newborm premature human baby with the sectionning of different region of the body. The mesh is composed of 229363 nodes that are grouped into 1356069 tetrahedron elements.

Original data

The original DICOM (Digital Imaging and communications in medicine) images belong to the Cork University Hospital (CUH) data base. The hospital contacted the parents who approved the academic use of the anonymised CT scan of their child, under the ethical approval ECM 4 (gg) 07/03/18 from the Clinical Research Ethics Committee of the Cork Teaching Hospitals. The thoracic CT scan consist of a stack of 367 cross sectional slices, 0.625 mm thick. The area of each image is 512 x 512 pixels with a pixel size of 0.3555 mm. The neonate was born at 36 weeks gestational age with 3.58 kg weight.

Sectioning process

The segmentation of nine main organs (skin, fat, muscle, bone, cartilage, heart, artery, trachea and lung) was done using NIRFASTSlicer2.0. Each DICOM image exhibits the different organs in an especific Housenfield Unit (HU, quantitave scale of radiodensity); dense organs like bone have whitish color, in contrast with less dense organs which appereance is dark. A distinctive colour was assigned to each organ by direct drawing over the CT images one by one. The HU were used to define the boundaries between organs. The organs were considered homogeneous, therefore fine structures present in the human body were ignored.

For our study, we subdivided the lungs into 3 different segments (inner, middle and external). On completion of segmentation, the thoracic CT was subdivided in the 11 regions.

Regions

The mesh has been divided in 11 different regions number from 1 to 11 in the following way:

1 -> lung (external segment)

2 -> bone

3 -> cartilage

4 -> heart

5 -> muscle

6 -> artery

7 -> fat

8 -> skin

9 -> trachea

10 -> lung (middle segment)

11 -> lung (inner segment)

Data format

The mesh data is written in 3 different file format:

mesh.mat: MATLAB .mat format that contains 5 variables:

dimension: Number of dimension in the mesh

nodes: Matrix of size 229363 x 3 containing the (x,y,z) coordinates of each node in the mesh in milimetres (mm)

elements: Matrix of size 1356096 x 4 containing the indices of the nodes corresponding to each element (tetrahedron) of the mesh

region: Vector size 229363 x 1 indicating to which region the nodes belongs.

bndvtx: Vector of size 229363 x 1 indicating whether the node is on the boundary of the mesh.

mesh.vtk: Mesh in the vtk Datafile Version 2.0 format. The only data field in the VTK file corresponds to the region variable in the .mat file.

mesh_csv.zip: Mesh in a .csv format. The zip file contains 4 csv files containing the nodes list, the elements list, the region list and the bndvtx list.

Licence

The mesh is published under the creative common CC-BY licence. You are free to use this data as you wish, but please cite this dataset using its DOI for example.

Digital Object Identifier:

DOI: 10.5281/zenodo.4916863

Authors

Mesh sectionning: Andrea Pacheco Data formating: Baptiste Jayet

Funding

The research leading to these results was funded by Science Foundation Ireland project no. SFI/15/RP/2828

Newborn mesh

Description:

This dataset contains a labelled mesh of the thorax of a newborm premature human baby with the sectionning of different region of the body. The mesh is composed of 229363 nodes that are grouped into 1356069 tetrahedron elements.

Original data

The original DICOM (Digital Imaging and communications in medicine) images belong to the Cork University Hospital (CUH) data base. The hospital contacted the parents who approved the academic use of the anonymised CT scan of their child, under the ethical approval ECM 4 (gg) 07/03/18 from the Clinical Research Ethics Committee of the Cork Teaching Hospitals. The thoracic CT scan consist of a stack of 367 cross sectional slices, 0.625 mm thick. The area of each image is 512 x 512 pixels with a pixel size of 0.3555 mm. The neonate was born at 36 weeks gestational age with 3.58 kg weight.

Sectioning process

The segmentation of nine main organs (skin, fat, muscle, bone, cartilage, heart, artery, trachea and lung) was done using NIRFASTSlicer2.0. Each DICOM image exhibits the different organs in an especific Housenfield Unit (HU, quantitave scale of radiodensity); dense organs like bone have whitish color, in contrast with less dense organs which appereance is dark. A distinctive colour was assigned to each organ by direct drawing over the CT images one by one. The HU were used to define the boundaries between organs. The organs were considered homogeneous, therefore fine structures present in the human body were ignored.

For our study, we subdivided the lungs into 3 different segments (inner, middle and external). On completion of segmentation, the thoracic CT was subdivided in the 11 regions.

Regions

The mesh has been divided in 11 different regions number from 1 to 11 in the following way:

1 -> lung (external segment)

2 -> bone

3 -> cartilage

4 -> heart

5 -> muscle

6 -> artery

7 -> fat

8 -> skin

9 -> trachea

10 -> lung (middle segment)

11 -> lung (inner segment)

Data format

The mesh data is written in 3 different file format:

mesh.mat: MATLAB .mat format that contains 5 variables:

dimension: Number of dimension in the mesh

nodes: Matrix of size 229363 x 3 containing the (x,y,z) coordinates of each node in the mesh in milimetres (mm)

elements: Matrix of size 1356096 x 4 containing the indices of the nodes corresponding to each element (tetrahedron) of the mesh

region: Vector size 229363 x 1 indicating to which region the nodes belongs.

bndvtx: Vector of size 229363 x 1 indicating whether the node is on the boundary of the mesh.

mesh.vtk: Mesh in the vtk Datafile Version 2.0 format. The only data field in the VTK file corresponds to the region variable in the .mat file.

mesh_csv.zip: Mesh in a .csv format. The zip file contains 4 csv files containing the nodes list, the elements list, the region list and the bndvtx list.

Licence

The mesh is published under the creative common CC-BY licence. You are free to use this data as you wish, but please cite this dataset using its DOI for example.

Digital Object Identifier:

DOI: 10.5281/zenodo.4916863

Authors

Mesh sectionning: Andrea Pacheco Data formating: Baptiste Jayet

Funding

The research leading to these results was funded by Science Foundation Ireland project no. SFI/15/RP/2828

ABSTRACT Objective: The aim of this study was to evaluate the volumetric root resorption in maxillary incisors following clear aligner therapy (CAT) with low-intensity pulsed ultrasound (LIPUS), and compare the results to CAT alone. Material and Methods: This retrospective study evaluated pretreatment (T0) and post-treatment (T1) cone-beam computed tomography imaging of 42 adult patients. Twenty-one patients (14 females, 7 males, mean age= 38.1±12.96 years) were treated using CAT with LIPUS device, whereas the other twenty-one matching controls patients (15 females, 6 males, mean age= 35.6±11.7 years) were treated using CAT alone. Images were analyzed and a segmentation protocol was applied on the maxillary incisors. Each segmented tooth volume was exported as a surface mesh in the Visualization Toolkit (VTK) file format. The VTK files for all maxillary incisors were coded and corresponding teeth volumes from T0 and T1 were superimposed. Clipping the crown of each tooth was done, then measurements of root volumes and differences between groups were performed. Changes in root volumes were assessed (p

Collision of a droplet chain of a 50% water-glycerol solution colliding with a continuous jet of silicon oil M5, which is a combination of immiscible liquids. The collision process leads to the separation of compound droplets, i.e., the droplets are encapsulated by the jet's liquid. The Cartesian simulation grid originally had a size of 2048 x 1024 x 256 cells covering a domain of 0.704 cm x 0.352 cm x 0.088 cm. The dataset consists of 157 output time steps covering a time span of 1.872 ms. Only half of the jet and droplets were simulated with a mirror boundary condition at the z=0 plane. We reduced the size of the here published data by converting all double-precision floating-point values to single-precision and cropping the grid to regions containing fluid. This results in a grid size of 2048 x 768 x 128 cells. Finally, the data is stored in the VTK XML file format utilizing the built-in zlib compression. The dataset is stored as a rectilinear grid and contains the following fields: f3-function[-]: volume fractions of the f3-field ("droplets") vof-function[-]: volume fractions of the f-field ("jet") n_c_3ph[1]: PLIC normals for the f-field in three-phase cells velocity[cm/s]: velocity-field In addition, two spatially downsampled variants of the dataset are attached. The 'ds1' directory is a downsampled variant where every eight cells were averaged to a single cell. The 'ds2' directory is downsampled the same way using the 'ds1' data. This simulation is a variant of the simulation initially presented in [1] using a slightly larger domain and was run on the Hawk supercomputer specifically for our paper. The specific method used in the simulation is presented in [2] and is implemented in FS3D [3]. References: [1] Potyka et al.: Towards DNS of Droplet-Jet Collisions of Immiscible Liquids with FS3D, https://doi.org/10.1007/978-3-031-46870-4_14. [2] Potyka and Schulte: A volume of fluid method for three dimensional direct numerical simulations of immiscible droplet collisions, https://doi.org/10.1016/j.ijmultiphaseflow.2023.104654. [3] Eisenschmidt et al., Direct Numerical Simulations for Multiphase Flows: An Overview of the Multiphase Code FS3D, https://doi.org/10.1016/j.amc.2015.05.095.

The related data files for the manuscript "3D electrostatic hybrid PIC simulation of the plasma mini-wake near a lunar polar crater", which are obtained by the 3D PIC simulations with SPIS code. There are 17 data files and 5 figures in total. 2 of the 17 data files are in .vtk format, which are related to the Figure 1 and can be opened and edited by ParaView software. The left 15 data files are in .dat format, which are related to the Figures 2-5, and can be edited by Tecplot software.

Dataset for: Bedding scale correlation on Mars in western Arabia Terra

A.M. Annex et al.

Data Product Overview

This repository contains all source data for the publication. Below is a description of each general data product type, software that can load the data, and a list of the file names along with the short description of the data product.

HiRISE Digital Elevation Models (DEMs).

HiRISE DEMs produced using the Ames Stereo Pipeline are in geotiff format ending with ‘*X_0_DEM-adj.tif’, the “X” prefix denotes the spatial resolution of the data product in meters. Geotiff files are able to be read by free GIS software like QGIS.

HiRISE map-projected imagery (DRGs).

Map-projected HiRISE images produced using the Ames Stereo Pipeline are in geotiff format ending with ‘*0_Y_DRG-cog.tif’, the “Y” prefix denotes the spatial resolution of the data product in centimeters. Geotiff files are able to be read by free GIS software like QGIS. The DRG files are formatted as COG-geotiffs for enhanced compression and ease of use.

3D Topography files (.ply).

Traingular Mesh versions of the HiRISE/CTX topography data used for 3D figures in “.ply” format. Meshes are greatly geometrically simplified from source files. Topography files can be loaded in a variety of open source tools like ParaView and Meshlab. Textures can be applied using embedded texture coordinates.

3D Geological Model outputs (.vtk)

VTK 3D file format files of model output over the spatial domain of each study site. VTK files can be loaded by ParaView open source software. The “block” files contain the model evaluation over a regular grid over the model extent. The “surfaces” files contain just the bedding surfaces as interpolated from the “block” files using the marching cubes algorithm.

Geological Model geologic maps (geologic_map.tif).

Geologic maps from geological models are standard geotiffs readable by conventional GIS software. The maximum value for each geologic map is the “no-data” value for the map. Geologic maps are calculated at a lower resolution than the topography data for storage efficiency.

Beds Geopackage File (.gpkg).

Geopackage vector data file containing all mapped layers and associated metadata including dip corrected bed thickness as well as WKB encoded 3D linestrings representing the sampled topography data to which the bedding orientations were fit. Geopackage files can be read using GIS software like QGIS and ArcGIS as well as the OGR/GDAL suite. A full description of each column in the file is provided below.

Column	Type	Description
uuid	String	unique identifier
stratum_order	Real	0-indexed bed order
section	Real	section number
layer_id	Real	bed number/index
layer_id_bk	Real	unused backup bed number/index
source_raster	String	dem file path used
raster	String	dem file name
gsd	Real	ground sampling distant for dem
wkn	String	well known name for dem
rtype	String	raster type
minx	Real	minimum x position of trace in dem crs
miny	Real	minimum y position of trace in dem crs
maxx	Real	maximum x position of trace in dem crs
maxy	Real	maximum y position of trace in dem crs
method	String	internal interpolation method
sl	Real	slope in degrees
az	Real	azimuth in degrees
error	Real	maximum error ellipse angle
stdr	Real	standard deviation of the residuals
semr	Real	standard error of the residuals
X	Real	mean x position in CRS
Y	Real	mean y position in CRS
Z	Real	mean z position in CRS
b1	Real	plane coefficient 1
b2	Real	plane coefficient 2
b3	Real	plane coefficient 3
b1_se	Real	standard error plane coefficient 1
b2_se	Real	standard error plane coefficient 2
b3_se	Real	standard error plane coefficient 3
b1_ci_low	Real	plane coefficient 1 95% confidence interval low
b1_ci_high	Real	plane coefficient 1 95% confidence interval high
b2_ci_low	Real	plane coefficient 2 95% confidence interval low
b2_ci_high	Real	plane coefficient 2 95% confidence interval high
b3_ci_low	Real	plane coefficient 3 95% confidence interval low
b3_ci_high	Real	plane coefficient 3 95% confidence interval high
pca_ev_1	Real	pca explained variance ratio pc 1
pca_ev_2	Real	pca explained variance ratio pc 2
pca_ev_3	Real	pca explained variance ratio pc 3
condition_number	Real	condition number for regression
n	Integer64	number of data points used in regression
rls	Integer(Boolean)	unused flag
demeaned_regressions	Integer(Boolean)	centering indicator
meansl	Real	mean section slope
meanaz	Real	mean section azimuth
angular_error	Real	angular error for section
mB_1	Real	mean plane coefficient 1 for section
mB_2	Real	mean plane coefficient 2 for section
mB_3	Real	mean plane coefficient 3 for section
R	Real	mean plane normal orientation vector magnitude
num_valid	Integer64	number of valid planes in section
meanc	Real	mean stratigraphic position
medianc	Real	median stratigraphic position
stdc	Real	standard deviation of stratigraphic index
stec	Real	standard error of stratigraphic index
was_monotonic_increasing_layer_id	Integer(Boolean)	monotonic layer_id after projection to stratigraphic index
was_monotonic_increasing_meanc	Integer(Boolean)	monotonic meanc after projection to stratigraphic index
was_monotonic_increasing_z	Integer(Boolean)	monotonic z increasing after projection to stratigraphic index
meanc_l3sigma_std	Real	lower 3-sigma meanc standard deviation
meanc_u3sigma_std	Real	upper 3-sigma meanc standard deviation
meanc_l2sigma_sem	Real	lower 3-sigma meanc standard error
meanc_u2sigma_sem	Real	upper 3-sigma meanc standard error
thickness	Real	difference in meanc
thickness_fromz	Real	difference in Z value
dip_cor	Real	dip correction
dc_thick	Real	thickness after dip correction
dc_thick_fromz	Real	z thickness after dip correction
dc_thick_dev	Integer(Boolean)	dc_thick <= total mean dc_thick
dc_thick_fromz_dev	Integer(Boolean)	dc_thick <= total mean dc_thick_fromz
thickness_fromz_dev	Integer(Boolean)	dc_thick <= total mean thickness_fromz
dc_thick_dev_bg	Integer(Boolean)	dc_thick <= section mean dc_thick
dc_thick_fromz_dev_bg	Integer(Boolean)	dc_thick <= section mean

The data consists of seven HIGRAD/FIRETEC simulations, each with multiple time series (each 70 to 100 times steps) of 3D scalar fields on a curvilinear grid from coupled Higrad/Firetec simulations. These .vts (VTK structured grid data format, can be opened using Paraview) files were generated to study a phenomena known as vorticity-driven lateral spread in mountain and canyon topographies. There are six mountain and one canyon scenario. Simulations names are first tagged with the topographical structure - either mountain or valley. Mountain simulations are then tagged with either head curve or back curve to indicate whether the fire starts as a headfire or a backing fire and that the simulation is a part of a suite of simulations exploring the influence of the radius of curvature along the ridgeline. Finally, a numerical value is associated with each simulation - 40, 80 or 320. This value determines the radius of curvature or roundness of the peak of the mountain. A higher value indicates a more rounded ridgeline, resulting in a gentle hill top as opposed to a sharp pointy ridge. For questions, please contact Divya Banesh, dbanesh@lanl.gov.

This dataset contains two- and quasi-three-dimensional hydrodynamic model outputs from the Flow and Sediment Transport with Morphologic Evolution of CHannels (FaSTMECH) hydrodynamic model in the open-source binary Visualization Toolkit (VTK) format (https://vtk.org/). The simulations were run at flows in the range of 185-635 cms at increments of 30 cms. This set of flow conditions pertains to the base lateral eddy viscosity scenario referred to as LEVx1 in Call et al., 2023. Files can be opened using the open-source software program Paraview: (https://www.paraview.org/).

The data consists of seven HIGRAD/FIRETEC simulations, each with multiple time series (each 70 to 100 times steps) of 3D scalar fields on a curvilinear grid from coupled Higrad/Firetec simulations. These .vts (VTK structured grid data format, can be opened using Paraview) files were generated to study a phenomena known as vorticity-driven lateral spread in mountain and canyon topographies. There are six mountain and one canyon scenario. Simulations names are first tagged with the topographical structure - either mountain or valley. Mountain simulations are then tagged with either head curve or back curve to indicate whether the fire starts as a headfire or a backing fire and that the simulation is a part of a suite of simulations exploring the influence of the radius of curvature along the ridgeline. Finally, a numerical value is associated with each simulation - 40, 80 or 320. This value determines the radius of curvature or roundness of the peak of the mountain. A higher value indicates a more rounded ridgeline, resulting in a gentle hill top as opposed to a sharp pointy ridge. For questions, please contact Divya Banesh, dbanesh@lanl.gov.

This contains the original simulation data used by the paper 'Where is Region 1 field-aligned current generated?', which will appear in Journal of Geophysical Research - Space Physics. The data were obtained by the global MHD simulation (REPPU) with Level 6.

The VTK file (Visualization Tookkit format) contains the physical variables in the magnetosphere at t = 244. 8 min as

• plasma pressure (P in nPa),
• velocity vector (V in km/s),
• current density vector (J in nA/m2),
• magnetic field vector (B in nT).

The VTK file can be opened by Visualization Toolkit, and 3-D visualization software packages "VisIT", and "ParaView".

The ASCII files named packet-position-P.txt and packet-position-Q.txt include lists of the position of the packet traced backward in time from the positions P and Q, respectively.

The results contained in this repository are computed from a database produced with Direct Numerical Simulation of the turbulent incompressible flow in a plane channel with a small concave-convex-concave bump on the bottom wall. The database is documented by Banchetti, Luchini & Quadrio, J. Fluid Mech. 896, A10 (2020). The Reynolds number based on the bulk velocity and on the channel half-height is Re=3173. We provide the two-dimensional mean field as well as all the non-null components of the second-order structure function tensor, and the terms involved in their budget equations, i.e. the Anisotropic Generalised Kolmogorov Equations (AGKE). Further details can be found on the accompanying paper (same title, same authors), currently submitted to the Journal of Fluid Mechanics.

The data are provided in VTK format, so that they can be visualised with several applications, as for example the open-source package ParaView.

The file mean.vtk contains the mean flow in terms of velocity components and pressure field.

The files dudu-Budget.vtk, dvdv-Budget.vtk, dwdw-Budget.vtk, dudv-Budget.vtk and dqdq-Budget.vtk contain the complete set of terms appearing in the budget equations for the non-null components of the second-order structure function tensor, and for its trace, i.e. the AGKE.

Abstract

The dataset was derived by the Bioregional Assessment Programme without the use of source datasets. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Finite element mesh for the groundwater model of the BA Hunter subregion. A regional-scale numerical groundwater model was built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) modelling platform to evaluate the hydrological changes due to additional coal resource development on groundwater resources in the Hunter subregion. MOOSE uses the finite-element technique and the size in plan view was chosen to be 500 m in the vicinity of the mines, and up to 15 km elsewhere. Triangular elements are used. The finer mesh clearly identifies the areas of mining within the Hunter subregion. There is a higher density of elements along the river network. The mesh was created using python VTK libraries (see www.vtk.org) and converted to shapefile format for map display purposes. Also included in the dataset are shapefiles for the Mt Arthur, Tasman and Whybrow mines.

Purpose

Finite element groundwater modelling

Dataset History

A regional-scale numerical groundwater model was built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) modelling platform to evaluate the hydrological changes due to additional coal resource development on groundwater resources in the Hunter subregion. MOOSE uses the finite-element technique and the size in plan view was chosen to be 500 m in the vicinity of the mines, and up to 15 km elsewhere. Triangular elements are used. The finer mesh clearly identifies the areas of mining within the Hunter subregion. Also visible is a higher density of elements along the river network.The mesh was created using python VTK libraries (see www.vtk.org) and converted to shapefile format for map display purposes. Also included in the dataset are shapefiles for the Mt Arthur Tasman and Whybrow mines.

Dataset Citation

Bioregional Assessment Programme (2015) HUN Groundwater modelling mesh v01. Bioregional Assessment Derived Dataset. Viewed 18 June 2018, http://data.bioregionalassessments.gov.au/dataset/1ef3629b-a27b-472b-83cc-bde89bdb08fb.

Dataset Ancestors

• Derived From HUN Groundwater footprint polygons v01

• Derived From HUN GW Model boundary and production bores v01

• Derived From Australian Coal Basins

• Derived From Hunter Groundwater Model extent

• Derived From SYD ALL Raw Stream Gauge Data BoM v01

• Derived From HUN GW modelling total mine footprint v01

• Derived From River Styles Spatial Layer for New South Wales

• Derived From HUN GW model output points v01

• Derived From Hunter Surface Water data v2 20140724

• Derived From HUN GW Model v01

• Derived From Selected streamflow gauges within and near the Hunter subregion

• Derived From SYD ALL Unified Stream Gauge Data v01

• Derived From HUN GW Model Mines raw data v01

• Derived From HUN DEM derived catchment boundaries v01

• Derived From Hunter Surface Water data extracted 20140718

• Derived From GEODATA 9 second DEM and D8: Digital Elevation Model Version 3 and Flow Direction Grid 2008

• Derived From SSB Hydstra gauges v01

• Derived From HUN GW Model code v01

• Derived From HUN GW model output points spatial v01

• Derived From HUN AWRA-L Stream Network v01

The local mesh is available in the file _LocalMeshModel.vtk using the ascii vtk format (see https://vtk.org/wp-content/uploads/2015/04/file-formats.pdf). The mesh is a finite elemen tetrahedron based grid and it is reported following the UNSTRUCTURED_GRID format:* Points coordinates, one point per line; * Cell Types (cell type is 10 for tetrahedrons according to the documentation)* Cell number and size (that is to say the total number of vertices) followed by the list of the ids of the points for each vertex on a cell by cell basis.