• United Kingdom

Accepting PhD Students

PhD projects

1) Reliable and efficient predictive maintenance tools under uncertainty; 2) Reliable digital simulation tools for improved resilience in Nuclear Power Plants 3) Safety assessment of Hydrogen 4) Resilience Assessment of Interconnected Networks and Smart Infrastructures 5) Human error and Intelligent and Autonomous systems

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Personal profile

Personal Statement

In order to achieve a step-change in the way the design, development, and maintains complex structures and systems it is necessary to effectively characterize and quantify the unavoidable uncertainties. This allows to take riks-informed decisions, design robust and resilient systems able to cope with the current challenges. 

The quantification of uncertainty and the design of efficient and resilient systems capable of recovering from catastrophe is a requirement of numerous industries. Often researchers and practitioners in different disciplines use different languages to describe essentially similar techniques. There is a need for effective strategies and technologies that respond to the current and future needs of our society, and build resilience across a wide range of industrial sectors. 

By adopting virtual engineering frameworks such as digital twinning, and exploiting the capability of efficient and reliable computational strategies supported by machine learning and artificial intelligence we can now understand and predict the behavior of complex real-world problems, effectively design maintain, and managing them, and reducing the overall risks involved.

I am working on computational science and engineering for more than 20 years. I started developing stochastic models for the assessment of the disposal of radioactive waste. Then, I have developed efficient simulation techniques for high fidelity analysis and reliability analysis of computationally expensive models and complex systems with applications in different sectors including Civil, Nuclear, and Aerospace. I have a deep understanding and knowledge of the current challenges (and opportunities) in computation and simulation techniques and the need for verified and reliable tools.

I am working in a truly multidisciplinary environment in collaboration with members from all the university faculties and strong link with world-leading scholars across the world. I am the Chair of the Technical Committee on Simulation for Safety and Reliability Analysis of the European Safety and Reliability Association (ESRA) and Chair of the Technical Committee for the 2019 European Safety and Reliability Conference (ESREL) conference. I am working actively with UK industry including Wood, Airbus, ARUP, EdF UK, AWE,  CCFE and National Nuclear Laboratory. 

 In order to translate the recent development to practicians and industry, we are continuously developing a suite of computational tools:  \href{https://cossan.co.uk}{COSSAN software},

Research Interests

My primary research interests focus on the general area of risk analysis, uncertainty modelling and quantification, sensitivity analysis, nuclear safety, reliability and availability of complex systems. In particular,  the focus is on the development of verified and efficient stochastic computational methods able to model different representation of the uncertainty and providing trustful reliability analysis and risk assessment.
The numerical implementations have resulted in the development of an open-source general-purpose software package for uncertainty quantification and stochastic analysis.

Expertise & Capabilities

  • Uncertainty quantification
  • Bayesian and Credal Networks
  • Resilience assessment of complex infrastructures
  • Nuclear safety
  • Probabilistic risk assessment
  • Human reliability 

Industrial Relevance

  • Nuclear 
  • Aerospace 
  • Transport 
  • Digital design 

Teaching Interests

I am currently teaching:

  • Probability and statistics
  • Structural reliability 
  • Monte Carlo methods
  • Bayesian approaches 
  • FMEA, Fault Tree, Event Tree 

Education/Academic qualification

Doctor of Engineering, Politecnico di Milano

Award Date: 25 May 2006

Keywords

  • Risk Analysis
  • Uncertainty
  • Resilience Engineering
  • Simulation
  • Machine Learning
  • System Modelling and Simulation
  • Reliability
  • Human Factors
  • Digital Twins

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