Sandpit Transport Funding Announcement

The DAFNI programme is pleased to announce that our expert external panel has awarded funding to three amazing projects under the theme of Transport: ‘ClimaTracks’, ‘Impact’ and ‘Mars’. 

All projects have a focus on resilience which relates to our ‘Building a Secure and Resilient World’ programme funded by our £4m UKRI grant for work on this theme, whilst also addressing our latest funding programme on ‘The Challenges and Opportunities in Data Sharing’ from the Department of Science, Innovation and Technology. 

We would like to congratulate all funded projects and give thanks to all sandpit participants. The sandpits offered participants the opportunity to brainstorm and share ideas, and were a great success due to all of those involved. Thank you for taking the time and effort, we hope you enjoyed it and that they provided an opportunity to grow your network and collaborate. 

The three selected DAFNI Transport Sandpit projects have started this month, we are looking forward to seeing the outputs on DAFNI and sharing with you all. 

The projects’ Principal Investigators will be hosting a webinar on the 22nd of May to introduce their projects, please click here to sign up and find out more about the projects’ research.

Our new sandpit projects are adding great expertise and value to the DAFNI Centre of Excellence. The funded projects are covering rail resilience, flooding, and aviation, find out more below.

We will bring you updates from the Transport Sandpit projects in the DAFNI Conference 2024 (bookings are open!). 

Next month we will be announcing the funding projects from the Energy Sandpits, keep an eye out! 

Learn more about the transport teams below…

Dr Brian Matthews, DAFNI Programme Lead

Book Now for 22nd May Webinar

Transport Sandpit Projects: 12 noon – 1pm

ClimaTracks is a collaboration project led by Giuliano Punzo from the University of Sheffield. The team is made up of Ji-Eun Byun, University of Glasgow, Qian Fu, University of Birmingham, Tohid Erfani, University College London, Iryna Yevseyeva, De Montfort University and Konstantinos Nikolopoulos, Durham University. This project is looking into forecasting the resilience of railway networks through propagating uncertainty.

This project aims to compute risks of weather-related disruptions and asset failures in a railway network. To properly take into account the inevitable effects of uncertainty in railway services, the project focuses on occurrence of uncertainty from weather conditions and asset failures and propagation of uncertainty through interdependent components in a network. To this end, this project will collate relevant datasets, develop a computational model to perform probabilistic analysis on network performance, and make those outcomes available to the public using DAFNI platform.

IMPACT is a collaboration project led by Qiuchen Lu and Tao Cheng from University College London. The team is made up of Tohid Erfani, University College London, Trung Hieu Tran, Cranfield University, Mr Xuhui Lin, University College London and Mr Xianghui Zhang, University College London. This project is looking into IMproving flood disruPted road networks with a dynAmic people-Centric digital Twins (IMPACT).

This project will develop an innovative people-centric digital twin (DT) to evaluate the dynamic congestion risks across multiple transportation modes during flooding events. The proposed DT comprises three distinct layers. Firstly, the Data and Context layer will integrate and contextualise primary multimodal data, encompassing road networks, commuter behaviour patterns, and diverse traffic flows. Secondly, the Mapping and Integration layer will establish connections between topological analyses of road networks and the functional performance of multimodal transportation systems. Lastly, the Evaluation layer will introduce novel indicators for assessing vulnerabilities. By providing a dynamic, multimodal data-supported perspective, this project aims to offer a holistic understanding of the vulnerability of transportation networks, enabling comprehensive insights into the immediate and progressive impacts of flooding.

MARS (Modelling Aviation Resilience Scenarios) is a project led by Dr Fabian Steinmann from Cranfield University along with Dr Irene Moulitsas and Dr Desmond Bisandu from Cranfield University.

The project seeks to explore the resilience of the UK aviation system during mass diversion events. The Cranfield team will develop a computational model of the UK airport network and conduct simulations involving airport closures that result in mass diversions. The project involves data collection and data pre-processing before a computational model of the UK airport network can be built. This model enables the research team to simulate airport closures and investigate the subsequent diversion of aircraft to alternate airports. The work of the Cranfield team will help identify potential bottlenecks during mass diversion events and build a foundation for evaluating the resilience of the UK aviation system. 

DAFNI was originally funded by an £8 million EPSRC investment in the UK Collaboratorium for Research in Infrastructure and Cities (UKCRIC) and a £1.2m grant under EPSRC’s Resource Only Strategic Equipment. Its aim has been to become the national platform to satisfy the computational needs in support of data analysis, infrastructure modelling and visualisation, and encourage whole-system thinking for the UK’s infrastructure research needs.
 
In March 2023 UKRI awarded £4m to STFC Scientific Computing to establish a national Centre of Excellence for Resilient Infrastructure Analysis, and move the Data & Analytics Facility for National Infrastructure (DAFNI) into its new phase.
 
Today, the platform supports research that aims to provide the UK with a world-leading infrastructure system that is more integrated, efficient, powerful, reliable, resilient and affordable. It is enabling the community to conduct research that is able to generate new insights at a higher level of detail and accuracy than ever before.
 
To find out more about DAFNI, visit: www.dafni.ac.uk​