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Dr. Cuong Dao

Assistant Professor

Area
School of Engineering
Faculty of Eng & Digital Technologies
E-mail
D.C.Dao@bradford.ac.uk
Phone
+441274233040
Link
https://www.bradford.ac.uk/staff/dcdao/
Dr. Cuong Dao
6 research projects
24 publications

Biography

Dr Cuong Dao (BSc '06, MSc '09, & PhD '16) obtained his PhD in Reliability and Maintenance Engineering from the University of Alberta, Canada. Prior to joining Bradford University, he was a Post-Doctoral Research Associate at the Department Engineering, Durham University (2018-2020) and a Postdoc Researcher at the University of Twente, The Netherlands (2016-2018). He also served as a Mechanical Engineer at Canon Vietnam Ltd. and Reliability Engineer at Enmax Generation Canada. 

Dr Dao is currently a Programme Leader of MSc programme Renewable and Sustainable Energy and was previously a Programme Leader for BEng/MEng Mechanical Engineering (2021/22 and 2022/23). He has been teaching several UG/PG modules in the Faculty of Engineering and Digital Technologies, University of Bradford as well as in his previous academic institutions.

Dr Dao is an active researcher in the reliability, digital modelling and simulation, planning, control, operation and maintenance management of mechanical engineering and sustainable energy systems. If you are passionate about doing research in this area or have any questions related to our programmes, please send an inquiry to d.c.dao@bradford.ac.uk.

Research

Dr Cuong Dao research focuses on reliability analysis, digital modelling, planning, control and maintenance management of mechanical engineering and renewable energy systems. He has rich experience in working with industry and bringing academic research to practice through his current and previous research projects as well as his past role as an engineer. He has involved in several interdisciplinary research projects in wind energy, system planning, digital modelling, operation & maintenance, engineering asset lifecycle management, AI and reliability-based optimisation of automotive components. He has papers published in Reliability Engineering & System Safety, IEEE Transactions on Reliability, Wind Energy, Journal of Infrastructure Systems, and Journal of Transportation Engineering and is a reviewer for several journals & academic conferences in the field of Mechanical, Reliability, Maintenance, and Renewable Energy Engineering.

Research Interests:

  • Renewable and sustainable energy systems
  • Reliability data analysis 
  • Intelligent modelling and digitalisation
  • Operation simulation 
  • Maintenance management 

Dr Cuong Dao is currently supervising/co-supervising 4 PhD researchers in the above research areas. For further research interests and PhD student inquiries, please contact d.c.dao@bradford.ac.uk and find more about research degrees at the University of Bradford here:
https://www.bradford.ac.uk/postgraduate/research-degrees/

I am currently recruiting a KTP Associate in Intelligent Digital Modelling of Heat Networks, starting in mid-2025. This project is to develop an energy digital twin model to support diagnostic, prognostic and predictive maintenance of heat networks. The candidate must already have a PhD (or be completing the PhD in 2025). If you are interested, please send an email to d.c.dao@bradford.ac.uk.

I do not have funds to provide financial support to PhD Students at the moment. If you are self-funded or holding an external scholarship, you are welcome to contact me to further discuss your research ideas, plan and supports.

Research projects

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Co-PI

Using Engineering as a subject platform, the project will deliver three activities: (1) research activities focusing on marine renewable energy, offshore wind energy and tidal stream energy; urban flooding prediction, water pipeline leakage, and river flows. (2) workshops exploring China's unique geographical advantages in developing and utilising offshore renewable energy; and debating the sustainability goals in engineering - United Nations Goals & Sustainability concepts. (3) a study abroad and exchange good practices handbook on cultural awareness, equality, diversity and inclusion, and sustainability.

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PI

The KTP project is to develop an integrated Energy Digital Twin (EDT) model for Switch2'sc community heat network that can support reliable and efficient system operations and maintenance. The model will be able to support future system designs, upgrades and optimisation via 'hardware-in-the-loop' testing and development of realistic use case validation.

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Co-PI

The scope of SAFI is to design, develop, and market instructional products and services (courses, workshops, demos, etc.) for industry. SAFI is committed to high quality instructional and educational training, and provides a core deliverable of programmes, courses, and learning objects for the distance education, distributed learning, and e-learning markets.

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Co-PI

AiR-FORCE (Artificial Intelligence for Reliability-based Feature Optimisation with Driver Contextual Intelligence), is a collaborative project between Jaguar Land Rover, the Institute of Digital Engineering and the University of Bradford, focusing on real-world vehicle data, including data-over-the-air (DOTA) supports the development of advanced driving behaviour models, which can be implemented in real time Engine Control Unit (ECU) controllers to optimise vehicle reliability and performance.

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PDRA

This project will bring together and consolidate theoretical underpinning research from a variety of disparate prior research work, in different subject areas and at different universities. Advanced robotic monitoring and advanced sensing techniques will be integrated into diagnostic and prognostic schemes which will allow improved information to be streamed into multi-physics operational models for offshore windfarms. Life-time, reliability and physics of failure models will be adapted to provide a holistic view of wind-farms system health and include these new automated information flows. While aspects of the techniques required in this offshore application have been previously used in other fields, they are innovative for the complex problems and harsh environment in this offshore system-of-systems. 'Marinising' these methods is a substantial challenge in itself. The investigation of an integrated monitoring platform and the reformulation of models and techniques to allow synergistic use of data flow in an effective and efficient diagnostic and prognostic model is ambitious and would allow a major step change over present practice.

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Post-doc researcher

The development of an asset life cycle plan that specifies for all components on a track what type of maintenance (e.g., corrective and condition based) to perform, and when to do that, such that the defined KPIs are achieved. Using historical data and physical models of degradation, it can be determined which (critical) failure modes to expect how often. Using quantitative models that combine this (technical) knowledge with life cycle cost data we can determine the optimal asset life cycle plan for a complete track, balancing time for operations and maintenance.

Professional activities

  • Bradford Energy Network Project Committee, (1 January 2024)

Publications

  • Analytical Reliability-based Investment and Operation Model for Post-Failure Network Reconfiguration

    J. A. Marquez, M. A. A. Al-Ja’Afreh, G. Mokryani, S. Kabir, F. Campean, C. Dao, and S. Riaz (2022) International Conference on System Reliability and Safety (ICSRS).

  • Challenges with Providing Reliability Assurance for Self-Adaptive Cyber-Physical Systems

    S. Riaz, S. Kabir, F. Campean, G. Mokryani, C. Dao, J. A. Marquez, and M. A. A. Al-Ja’Afreh (2022) International Conference on System Reliability and Safety (ICSRS).

  • Optimisation of large offshore wind farm layout considering system reliability and cost

    X Li, CD Dao, B Kazemtabrizi, CJ Crabtree (2020) ASME Turbo Expo 2020. NA

  • Availability Analysis for Different Offshore Wind Farm Electrical Connection Topologies

    Li X., Dao C. D., Kazemtabrizi. B., and Crabtree C.J. (2019) WindEurope Offshore conference 2019,. NA

  • Impacts of Reliability and Cost Uncertainties in Offshore Wind Turbine Operational Simulation and Cost of Energy Estimation

    Dao C. D., Kazemtabrizi. B., Crabtree C.J., and Yu X. (2019) WindEurope Offshore conference 2019. NA

  • A maintenance model for equipment subject to varying loading conditions

    Cuong D Dao, Ming J Zuo (2016) Industrial and Systems Engineering Research Conference (ISERC) 2016.

  • Selective maintenance for a multi-component system with two types of failure modes under age-based imperfect maintenance

    M Pandey, MJ Zuo, DD Cuong (2013) International Conference on Reliability and Quality in Design. NA