DAFNI: A computational platform to support infrastructure systems research

被引:0
|
作者
Matthews B. [1 ]
Hall J. [2 ]
Batty M. [3 ]
Blainey S. [4 ]
Cassidy N. [5 ]
Choudhary R. [6 ]
Coca D. [7 ]
Hallett S. [8 ]
Harou J.J. [9 ]
James P. [10 ]
Lomax N. [11 ]
Oliver P. [1 ]
Sivakumar A. [12 ]
Tryfonas T. [13 ]
Varga L. [14 ]
机构
[1] Scientific Computing Department, Science and Technology Facilities Council, Didcot
[2] School of Geography and the Environment, University of Oxford, Oxford
[3] Centre for Advanced Spatial Analysis, University College London, London
[4] Transportation Research Group, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton
[5] Department of Civil Engineering, University of Birmingham, Birmingham
[6] Department of Engineering, University of Cambridge, Cambridge
[7] Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield
[8] Centre for Environmental and Agricultural Informatics, Cranfield University, Cranfield
[9] Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester
[10] School of Engineering, Newcastle University, Newcastle
[11] School of Geography, University of Leeds, Leeds
[12] Department of Civil and Environmental Engineering, Imperial College London, London
[13] Department of Civil Engineering, University of Bristol, Bristol
[14] Department of Civil, Environmental and Geomatic Engineering, University College London, London
关键词
data; digital twin; information technology; infrastructure planning; numerical modelling;
D O I
10.1680/jsmic.22.00007
中图分类号
学科分类号
摘要
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. © 2023 Emerald Publishing Limited: All rights reserved.
引用
收藏
页码:108 / 116
页数:8
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