Modelling

Research Profile - Staffordshire Bridges – long-term performance monitoring using fibre optic sensors

22 September 2022

A major rail upgrade programme to remove a bottleneck on the West Coast Main Line saw collaboration between Atkins, Laing O’Rourke, Volker Rail and Network Rail. The Stafford Area Improvement Programme included the construction of 10 new bridges designed by Atkins using Building Information Modelling (BIM) from the outset...

Digital Twin Journeys: smart infrastructure for safety and reliability across the rail network

22 November 2021

When we travel by train, we expect that we will arrive at our destination safely and on time. Safety and performance of their service network is therefore a key priority for Network Rail. Our latest video in the Digital Twin Journeys series tells the story of how researchers have inherited two intensively instrumented...

Infographic showing the IfM digital twin as a cyclical process that draws data from multiple sources and processes it to provide the right information at the right time to the asset manager

Digital Twin Journeys: how digital twins can combine diverse data types to provide better insights to asset managers

19 November 2021

A new infographic , enabled by the Construction Innovation Hub, is published today to bring to life a prototype digital twin of the Institute for Manufacturing (IfM) on the West Cambridge campus. Xiang Xie and Henry Fenby-Taylor discuss the infographic and lessons learned from the project. The research team for the West...

Integrating models of the built and natural environment

17 June 2021

Cross-discipline collaboration, cultural barriers and compelling questions. Better data can help us understand the complex interactions between the urban systems we create and the natural systems in which they operate. Such an understanding would underpin our ability to meet important environmental targets such as Net Zero...

Dr Miguel Angel Bravo-Haro

Research background

I completed my Ph.D. in Earthquake Engineering in 2018 at Imperial College London. I have experience in computational methods for the characterisation of nonlinear structural behaviour and structural dynamics. Additionally, I have worked on probabilistic methods, data-visualisation, software development, information theory, cloud computing, and hardware development for structural health monitoring.

Dr Farhad Huseynov

Research background

Gabriel Martin Hernández

Research background

PhD. Gabriel Martin was a Predoctoral Research Associate with the Hyperspectral Computing Laboratory Cáceres (Spain) and Postdoctoral Researcher in "Instituto de Telecomunicaçoes" Lisbon, Portugal. His research interests include remote sensing image processing, specifically the areas of hyperspectral unmixing and hyperspectral compressive sensing, as well as the efficient processing of remote sensing images in High Performance Computing architectures such as GPUs.

Dr Matthew Danish

Research background

Matthew Danish is a Research Associate within the Networks and Operating Systems group of the Systems Research Group in the Department of Computer Science and Technology. He is interested in systems verification, sensor networks, machine learning, infrastructure and the built environment.

CDBB projects involved with

West Cambridge Digital Twin

Digital Energy Estimation Tool (DEET)

How can buildings’ energy use and embodied energy both be optimized at the design stage? This project aims to enable the generation of real-time data from operational energy use and from energy embedded in building components. It will do this through 3-D computing paradigm at an early building...

Analysing Systems Interdependencies using a Digital Twin

This project investigates how to understand infrastructure complexity, using the digital twin. This work provides a first step toward next-generation systems engineering by demonstrating the feasibility of using a digital twin to generate new insight on systems relationships and interdependencies. ...

Research Profile - Staffordshire Bridges – long-term performance monitoring using fibre optic sensors

Digital Twin Journeys: smart infrastructure for safety and reliability across the rail network

Digital Twin Journeys: how digital twins can combine diverse data types to provide better insights to asset managers

Integrating models of the built and natural environment

Dr Miguel Angel Bravo-Haro

Research background

Dr Farhad Huseynov

Research background

Gabriel Martin Hernández

Research background

Dr Matthew Danish

Research background

CDBB projects involved with

Digital Energy Estimation Tool (DEET)

Analysing Systems Interdependencies using a Digital Twin

Study at Cambridge

About the University

Research at Cambridge