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Showing results for: [ Simulation and Modelling ]
A program for generating atomistic models in real space by a combination of empirical potential energy minimization and the fitting of experimentally motivated constraints. Suitable inputs include ex... moreperimental data such as diffraction data (structure factor and radial distribution functions) and computational data (bond angle, bond length, coordination distributions). Output is a model in Cartesian coordinates in xyz format that can be visualized in standard visualization packages. A manual and tutorial are provided.less
MMM Research & Applications - MMM Software - Published 10 Oct 2017
KSN Project 2.2.2 provides key information on the oceanographic and biological forcing associated with nutrient supply that determines the near-shore productivity of the Kimberley region, and links th... moreese with higher trophic levels. Key objectives of the research were - To make new estimates of pelagic primary productivity, identifying the key physical and community processes driving production in the region. - To better describe the phytoplankton and zooplankton communities in coastal waters of the Kimberley, to determine the trophic linkages within these communities and to identify the key factors controlling pelagic secondary productivity. - To integrate these parameters into an extensible biogeochemical modelling framework, allowing predictive linkages between physical and biological processes in the region. This metadata records specifically relates to modelling aspects of the project completed by CSIRO. The data originates from a number of model simulations conducted between 3/1/2010 to 21/12/2010. All field data is held by AIMS.less
WAMSI-Kim 2.2.2 Biogeochemical pr - Biogeochemical modelling - Published 22 Jun 2016
Pollination provided by honey bees is crucial for global agricultural production yet bee populations are declining. To investigate potential stressors to honey bee health, the Swarm Sensing Project is... more developing miniature sensing devices and mounting them on large numbers of bees, in order to provide detailed information on their behaviour. An agent-based computational model has been developed to simulate insect flight behaviours under different environmental conditions. The model is currently generating synthetic data to support the development of analysis and visualisation techniques for the project. Subsequently, it will process field data from the micro-sensors to characterise honey bee flight behaviour and to understand changes in their behaviour once exposed to stressors. This model provides a comprehensive platform for the simulation, representation and analysis of insect flight behaviour. Initial results have been validated using radio-frequency identification tags attached to foraging worker bees.less
MicroSensing Technology & Systems - Modelling swarm sensing data ingestion and analysis and visualisation - Published 08 Aug 2016
3D online images for the paper: Sulfide-silicate textures in magmatic Ni-Cu-PGE sulfide ore deposits. 1. Disseminated and net-textured ores.
by Stephen J. Barnes, James E. Mungall, Margaux Le Vaillant... more, Belinda Godel, C. Michael Lesher, David Holwell, Peter C. Lightfoot, Nadya Krivolutskaya, Bo Wei
OCE Science Leader - Stephen Barnes - Magmatic sulfide ore petrology - Published 30 May 2016
Three sub-samples were collected at different locations of a shale slab from the Junger Basin, north western China, and were referred to as S1 and S4′. The shale is composed primarily of calcite, sodi... moreum feldspar, potash feldspar and dolomite. The mineral can be grouped as the following: calcite, sodium feldspar and potash feldspar (group as feldspar), and dolomite. For CT scan experiments, the samples S1 and S4′ were cut into a small cylinder with the diameters of 0.8 mm and 3 mm, respectively. less
CSS-TCP - Data Constrained Mater - Data-constrained modelling (DCM) - Published 28 Jul 2016
This data set is a collection of multi-energy X-ray CT data and DCM generated 3D compositional microstructural data for an anthracite coal sample which are comprised with void, coal matrix, minerals.
CSS-TCP - Data Constrained Mater - Data-constrained modelling (DCM) - Published 27 Jul 2016
The maps in this data base identify most profitable land use in 2050. The information plotted on the maps is classified by current and potential land use, for seven scenarios assuming new land markets... more and recent trend agricultural productivity. Each scenario assumes a different level of carbon payment for single-species plantings, expressed as a share of the maximum payment in the very strong abatement scenario. Differences in payment rate arise from the level of global abatement incentives, interacting with biodiversity settings. The analysis assumes that no land shifts from native vegetation (including forest, woodland, shrubland and grassland) to agricultural use. The H3 map is for balanced land market settings. The CSIRO Data Access portal provides individual PowerPoint slides for each scenario, individual .tif files for each scenario map. Access to the Australian National Outlook Report and Technical Report can be found at http://www.csiro.au/nationaloutlook/.less
Integration Science and Modelling (ISAM) - Modelling - Published 14 Mar 2016
This data set is a sub-set of “Carbonate rock X-ray CT and DCM microstructure data” at http://dx.doi.org/10.4225/08/5476787E08766, for new users of the DCM software (http://research.csiro.au/dcm and h... morettps://data.csiro.au/dap/landingpage?pid=csiro:9448) as a tutorial training data. less
CSS-TCP - Data Constrained Mater - Data-constrained modelling (DCM) - Published 26 Jul 2016
Using the Land-Use Trade-Offs (LUTO) model, this data collection was produced via a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia... more’s intensive-use agricultural land to 2050, under intersecting global change and domestic policies, and considering key uncertainties. We assessed land use competition between multiple land uses and assessed sustainability of economic returns and multiple ecosystem services at high spatial (1.1 km grid cell) and temporal (annual) resolution.
Results available are for 648 scenarios covering combinations of four global outlooks, three general circulation climate models, three domestic land-use policies, three productivity growth rates, three land-use change adoption hurdle rates, and two capacity constraint settings.
Outputs included for each scenario are:
- annual land-use layers
- summary data table
- graphical dashboard summary
- animation of potential land-use change, drivers, and impacts
This analysis was conducted in conjunction with CSIRO’s Australian National Outlook initiative to assess future potential land-use change and the impacts for the sustainability of ecosystem services. A full description of the methods and synthesis of the results can be found in the papers listed in the Related Information below and freely available via email from the author.
The data is provided to support a national conversation on the future for Australian land systems, public decision-making and policy design, and further scientific research.
SIP 59 LUTO land use modelling science p - Modelling - Published 07 Jun 2016
This is an application of the Spark framework configured for command-line use on a server.
Design, validate and employ custom fire propagation models, using Spark’s computational fire-front propagati... moreon solver. Incorporate any number of modules specifically designed for wildfire spread, including readers and writers for geospatial data and a wide range of visualisations and tools to analyse the resulting data.less
Natural Hazards and Infrastruture - Spark Batch Demo - Published 03 Mar 2017
This is an application of the Spark framework configured for interactive use through a graphical user interface on a personal computer.
Design, validate and employ custom fire propagation models, usi... moreng Spark’s computational fire-front propagation solver. Incorporate any number of modules specifically designed for wildfire spread, including readers and writers for geospatial data and a wide range of visualisations and tools to analyse the resulting data.less
Natural Hazards and Infrastruture - Spark GUI demo - Published 03 Mar 2017
This data set uses a sub-set of “CIPS sandstone microstructure” at http://dx.doi.org/10.4225/08/5476787A1A50F, for new users of the DCM software (https://data.csiro.au/dap/landingpage?pid=csiro:9448) ... moreas a tutorial training data set. less
The Hungry Microbiome is an exciting biomedical animation that takes the audience on a journey through the digestive tract to reveal the world of the human gut microbiome. The video explores how inter... moreactions between a human and their gut microbiota plays a key role in colorectal cancer risk. The dataset comprises a 4 minute mp4 video and a thumbnail.
TCP03 VIZBI Visualising Biological Data - Visualisations - Published 15 Dec 2014
The DCM software is a Microsoft Windows™-based application for 3D microstructure characterization, modelling and visualization. It include the following functionalities:
• Generate digital 3D represen... moretation of material compositional phases in a sample using the data-constrained modelling methodology and X-ray CT data, even for the cases that there are partial volumes of multiple phases in the same image voxel;
• Visual presentation of 3D volumetric data. The visualization is compatible with various display devices, including stereo 3D monitors;
• Exporting 3D data in various formats, including the web-friendly Web3D format for interactive 3D online view, animation, serial sectional slices, etc.;
• Functionality of the software can be extended by adding plug-in modules to perform virtually unlimited 3D modelling. A set of C++ programming API is included for user convenience.
The DcmLite can be downloaded for evaluation. Please feel free to contact us if you would be interested in acquiring a DCM software user licence, R&D collaboration, commercial exploitation, or knowing more about DCM. The DCM website is at http://research.csiro.au/dcm.
Non-destructive quality evaluation of additive-manufactured components - Data-constrained modelling - Published 12 Nov 2017