DAFNI (the Data & Analytics Facility for National Infrastructure) held the inaugural DAFNI Networkshop on 21st May 2024 at the Rutherford Appleton Laboratory. The day-long event provided the opportunity for DAFNI users to meet each other in-person, make new connections, hear from the DAFNI team about new platform developments, and to learn more about projects taking place using the DAFNI platform and within the Centre of Excellence.
Lively discussions and presentations covered use of the DAFNI platform for modelling, visualisation and data storage in areas from energy to roads, rail, airports, and buried infrastructure, facing infrastructure challenges from climate change, extreme climate events, aging infrastructure and plans for new infrastructure. Attendee feedback on the Networkshop event was so positive that we plan to run it on an annual basis.
Presentations included:
Fast changing flood conditions and the impact on roads – under scrutiny in the IMPACT (IMproving flood disruPted road networks with a dynAmic people-Centric digital Twins) project led by Dr Qiuchen Lu, Associate Professor at the Bartlett School of Sustainable Construction, UCL and Tao Cheng, Professor of Geoinformatics at the Department of Civil, Environmental and Geomatic Engineering, UCL and presented at the event by Qiuchen.
Focusing on the impacts of drought on water supplies in a national water supply model, presented by Dr Anna Murgatroyd, Lecturer in Hydrology, School of Engineering, at Newcastle University and led by her in collaboration with University of Oxford in the Pywr-WREW (Water Resource Model for England and Wales) project led by her.
Adaptation models for safe underground infrastructure, and graded risks for failure of pipes in soil – being studied in the STORMS project (Strategies and Tools for Resilience of Buried Infrastructure to Meteorological Shocks) presented by Dr Nikolaos Reppas, Research fellow at University of Birmingham and led by Dr Xilin Xia, Assistant Professor in Resilience Engineering, School of Engineering, University of Birmingham.
Plans to make energy data more accessible for energy systems modellers wishing to work with weather and climate data is being explored in BRINES (Building Risk-Informed redundancy for Net-zero Energy Systems), a collaborative project led by and presented by Dr Hannah Bloomfield NUAcT Fellow: Climate resilient energy systems from Newcastle University. The project proposes addressing higher variability and higher correlations in weather events, power generation, and demand.
Forecasting energy data usage at household level, taking into account data and behaviour of individuals, in ForNet (FORecasting Services for Energy NETworks), presented by and led by Professor Konstantinos (Kostas) Nikolopoulos, Professor in Business Information Systems & Analytics of Durham University.
How a new road, rail or bus route could impact on travel to work choices in the long term is under the microscope in SCQUAIR (Small Changes and Computer-Generated Spatial Interaction Modelling with QUANT) using a travel to work model and led and presented by Dr Richard Milton Senior Research Fellow of CASA UCL.
Adding uncertainty quantification and sensitivity analysis into DAFNI through the USARIS project (Uncertainty quantification and sensitivity analysis for resilient infrastructure systems), presented by Saskia Salwey, Research Associate from University of Bristol in a project led by Francesca Pianosi, Senior Lecturer in Water and Environmental Engineering based in the School of Civil, Aerospace and Design Engineering at the University of Bristol.
The CITCOM Framework for Testing Computational Models was presented by Dr Neil Walkinshaw, Senior Lecturer in Testing at the University of Sheffield, the project aims to increase trust in software models, particularly those that are used to support public policy, by carrying out additional testing and inspecting the coding, enabling and promoting best practices for responsible modelling.
National infrastructure resilience and stress testing, looking at how risks from one network transmit to another and using historical real event data such as flooding, are being examined in the NIRD (National Infrastructure Resilience Demonstrator) project led and presented by Dr Raghav Pant, Senior Research Associate at the Environmental Change Institute, University of Oxford.
Electric vehicle networks and infrastructure in project D-RES (Provision of distributed grid resilience using EVs during extreme weather events), was presented and is led by Dr. Laiz Souto, Senior Research Associate in Future Energy Networks at the University of Bristol and part of the academic team of the EPSRC Supergen Energy Networks Hub.
Modelling airport resilience scenarios and the knock on impact of planes being detoured from their original route to an unforeseen stop at a different airport being researched in project MARS (Modelling Aviation Resilience Scenarios), presented by Dr Irene Moulitsas, Director of Computational and Software Techniques in Engineering at Cranfield University and led by Dr Fabian Steinmann, Lecturer in Organizational Resilience and Change at Cranfield.
Forecasting the resilience of rail to weather-related disruptions or asset failures and whether credible forecasts can be made a few hours or a day ahead, to allow for pre-planned re-routing in the ClimaTracks project presented by Dr Ji-Eun Byun, Lecturer in Smart Sustainable and Resilient Infrastructure and led by Giuliano Punzo, Lecturer from The University of Sheffield.
Dr Tom Russell, Senior Research Software Engineer at University of Oxford, is a long-time user of DAFNI and presented his experiences in using DAFNI in areas such as transferring information between models at different scales, managing mismatches between resolutions and scale, and adding models to the DAFNI platform.
Join us at the DAFNI Conference 2024
DAFNI users and other interested parties will have another opportunity to gain updates on DAFNI projects and to hear from luminaries in the infrastructure space this year at the DAFNI conference on 10th September 2024, in Birmingham.