Model-based Engineering Research
Our research in model-based engineering is helping engineers refine systems through rigorous modelling.
Our research
We’re developing the next generation of methods and tools to help engineers specify, verify and refine systems through rigorous modelling. We also integrate them into advanced software design paradigms, such as self-adaptive systems or digital twins.
We apply our methods in domains such as:
- cyber-physical systems (railway systems)
- asynchronous circuits
- autonomous systems
- self-protecting systems
Our Advanced Model-Based Engineering and Reasoning (AMBER) group leads our research in model-based engineering.
PrePCo
- Project: Predictability of Rail Network Performance Using Co-simulation and FMI-based Strategies (PrePCo)
- Researcher: Dr Ken Pierce
- Funder: Network Rail
- Funding amount: £399k
- Duration: 2021 – 2024
The project aimed to support Network Rail in identifying and managing minor, but potentially cascading, performance variability on the rail network. The project developed a methodology for analysing and simulating performance variability, using data science and the Functional Mock-up Interface (FMI), with an emphasis on capturing and simulating human performance as a cause of variability.
HUBCAP
- Project: Digital Innovation HUBs and Collaborative Platform for Cyber-Physical Systems (HUBCAP)
- Researcher: Professor John Fitzgerald and Dr Ken Pierce
- Funder: Horizon 2020
- Funding amount: £398k
- Duration: 2020 – 2022
HUBCAP aimed to lower barriers for SMEs to realise the potential of growing autonomy in cyber-physical systems by accessing advanced model-based design technology and providing training and guidance.
It was built on a network of Digital Innovation Hubs in seven European countries, offering SMEs opportunities to:
- undertake experiments
- seek investment
- access expertise and training
- form new business links
The project ran several open calls to provide cascading funding to 92 SMEs to support these experiments. It built a platform to allow businesses to offer models, tools and other assets, and permits for others to access these on a pay-per-use basis in a sandbox environment promoting collaboration and experimentation.
STRATA
- Project: STRATA
- Researcher: Professor Alexander Romanovsky and Professor Cliff Jones
- Funder: EPSRC
- Funding amount: £965k
- Duration: 2016 – 2021
STRATA was a "Platform Grant" that enabled us to continue collaborations with Professor Alan Burns (York) and Professor Alex Yakovlev (Newcastle Engineering). The focus was on Trustworthy Ambient Systems. It included concerns about the resources such as power. Jones' collaboration with Alan Burns continues to produce publications.
DECIDe
- Project: Digital Environment for Collaborative Intelligent De-carbonisation (DECIDe)
- Researcher: Dr Ken Pierce
- Funder: Rail Systems Safety Board
- Funding amount: £100k
- Duration: 2019 – 2020
This project examined the technical feasibility of applying the Functional Mock-up Interface (FMI) and co-simulation methodology to support rail decarbonisation, the conceptual feasibility of applying this methodology through a cloud-based ‘marketplace’, and the associated organisational motivations, barriers and enablers.
