By Prof Guido De Roeck (KU Leuven), external advisor and project partner at LDTRC
With more than 500 scientific journal and conference papers, Prof. De Roeck is a world-famous expert in vibration based damage detection, dynamic system identification and soil structure interaction and vehicle bridge interaction. In this short talk, Prof. De Roeck addresses relevant topics in our Newton Fund project on digital twin for structural health monitoring (SHM) between Middlesex Uni (UK) and Uni. of Transport and Communications (Vietnam), in which KU Leven is an associated partner.
He outlines recent development in sensoring techniques in SHM, non-model and model-based methods for vibration-based damage detection. For example, the non-model based methods can be the alarm/alerting just based on the pure or preprocessed measurement data, or the stochastic treatment to distinguish temperature influence from real structural damage. The model based approach can be the digital twin structure that is adapted according to measurement results. The adaptation, updating, calibration can use global optimization methods like Particle Swarm Optimization (PSO) , Genetic Algorithm (GA). Prof. De Roeck also discusses the digital transformation (with references to relevant projects in Europe) for predictive maintenance of important infrastructures in case of extreme events, such us, earthquakes, collapse of Morandi Bridge in Genova, Italy in 2018.
The London Digital Twin Research Centre would like to extend an invitation to all the Digital Twin researchers and enthusiasts from industry and academia to attend our annual 2021 workshop which is held online on June 4th, 2021. This virtual “Workshop on Transforming Industry and Society with Digital Twins” brings together experts from industry and academia to share their valuable insights regarding the adoption of the Digital Twin technology across different industries, from structural health monitoring, pandemic management, smart campuses through to health and wellbeing. The domains covered in this event provide opportunities and research challenges that the future maturation of digital twin technology demands. The virtual workshop represents an excellent opportunity for networking for Digital Twin enthusiasts to share ideas for future developments in digital twins.
In a continuation of a series of Middlesex-Egypt collaborations, London Digital Twin Research Centre (Middlesex University) has won a new Institutional Links grant under the Newton Fund Impact Scheme. The grant is led by Dr. Noha Saleeb, Associate Professor in Digital Technologies and Construction in partnership with Prof. Mohamed Marzouk, Professor of Construction Engineering and Management, Cairo University Egypt. The funding delivered by the British Council supports activities that aid in the development of Egypt’s economy using new digital twin technologies in alignment with the UN’s sustainability goals.
The project will be conducted simultaneously with the case study on Heritage assets in the UK and Egypt for mutual national benefits with the collaboration of industry and government parties namely Historic Environment Scotland, BurroHappold and Ministry of Housing Egypt.
Prof. Nguyen said “It is amazing to find out that the development of a DT framework at our LDTRC to unify different twins is very much aligning with the ‘connecting the Twins’ work task at the National Digital Twin programme. We see great opportunities to work together to achieve common goals set out at both Centres towards developing a national Digital Twin.”
by Dr. Hrishikesh Venkataraman, External Collaborator and Project Partner, Indian Institute of Information Technology (IIIT)
The Indian Institute of Information Technology (IIIT), represented by Dr. Hrishikesh Venkataraman and Dr. Raja Vara Prasad, is an international collaborator of the London Digital Twin Research Centre (LDTRC). The research conducted in Sri City, India, aims to support and drive forward the advancements in our Digital Twin for Industry 4.0 project, with an extended focus on anomaly detection mechanisms that can be integrated in the Digital Twin for manufacturing processes.
As part of the project activity funded by the UK-India Education and Research Initiative (UKIERI) and the Department of Science and Technology (DST), India, the research paper “CATS: Cluster-Aided Two-Step Approach for Anomaly Detection in Smart Manufacturing” was accepted for publication in The Fourth International Conference on Computing and Network Communications (CoCoNet’20).
Digital Twins embody the driving force behind the Fourth Industrial Revolution, that is the promise of bridging the physical world and its virtual counterpart in a way that enables full-duplex, real-time, reliable communication between the two entities. With the advent of Big Data, IIoT, Cyber Physical Factories, and Artificial Intelligence, this no longer looks like a far-fetched idea, becoming instead an increasingly relevant objective for researchers to achieve. However, building such a complex system requires a strong grasp of the technologies involved and good foresight into risks and issues that might pose a challenge along the way. In this context, this week’s meeting of the London Digital Twin Research Centre focused on discussing one of the most prominent challenges in Machine Learning: the Bias/Variance Trade-Off. Continue reading “Insight of the Week: Supervised Machine Learning and the Bias/Variance Trade-Off”
This month, the London Digital Twin Research Centre (LDTRC) was launched at MDX with a workshop featuring talks by international academic and industry specialists on the potential of digital twin technology and its benefits to businesses.