Matthews, Brian;
Hall, Jim;
Batty, Michael;
Blainey, Simon;
Cassidy, Nigel;
Choudhary, Ruchi;
Coca, Daniel;
... Varga, Liz; + view all
(2023)
DAFNI: a computational platform to support infrastructure systems research.
Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction
, 176
(3)
pp. 108-116.
10.1680/jsmic.22.00007.
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Abstract
Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a ‘multi-systems’ approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users’ models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project.
| Type: | Article |
|---|---|
| Title: | DAFNI: a computational platform to support infrastructure systems research |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1680/jsmic.22.00007 |
| Publisher version: | https://doi.org/10.1680/jsmic.22.00007 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | data, digital twin, information technology, infrastructure planning, numerical modelling |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10170897 |
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