Modelling, Risk and Design for Reliability

Group Leader(s): Professor Michael Todinov

About us

We conduct world-leading research in mathematical modelling in engineering. Members of the group have strong experience in:

Probability and statistics
Data analysis and the application of topological methods to data analysis
Modelling based on algebraic inequalities
Monte Carlo simulation and queuing theory
Control and Automation
Operations research
Design for reliability.
Renewable energy systems and storage
Advanced solar thermal systems
Thermal management of battery packs
Applications of abstract algebra
Artificial Intelligence

Abstract image - signal representing time series

Part of

School of Engineering, Computing and Mathematics

Related courses

Engineering (MPhil / PhD / Masters by Research / PhD by Published Work)

Membership

Staff

Staff

Name	Role	Email
Dr Aydin Azizi	Senior Lecturer	aydin.azizi@brookes.ac.uk
Dr Eleni Elia	Senior Lecturer in Statistics	eelia@brookes.ac.uk
Paul Henshall	Lecturer in Mathematical Sciences	phenshall@brookes.ac.uk
Dr James Maunder	Lecturer in Mathematics	jmaunder@brookes.ac.uk
Professor Michael Todinov	Professor in Mechanical Engineering	mtodinov@brookes.ac.uk

Research areas

Advanced statistical modelling involving medical data and engineering data
Generating new knowledge and optimising systems/processes using algebraic inequalities
Scheduling using queuing theory
Artificial Intelligence and Simulation Techniques; Monte Carlo simulation
Modelling repairable flow networks and stochastic networks
Control and Automation; Control and optimising complex systems
Methods for improving reliability and reducing risk by using domain-independent methods
Renewable energy systems and storage
Statistical Genetics, Unsupervised learning, Evidence synthesis
Advanced solar thermal systems
Thermal management of battery packs
The application of topological methods to data analysis
Applications of abstract algebra

3 dimension graph of a two-variable mathematical function

Published research monographs

Risk and Uncertainty Reduction by Using Algebraic Inequalities

Covers the application of algebraic inequalities for reliability improvement and for risk and uncertainty reduction. Algebraic inequalities present a new generation, highly effective tool for dealing with deep uncertainty related to key parameters of systems and processes. They permit meaningful interpretation and inference of new knowledge and unknown properties related to real physical systems and processes. The method of algebraic inequalities transcends engineering and can be used in diverse domains of human activity.

Flow Networks

Develops the theory, algorithms and applications related to repairable flow networks and networks with disturbed flows. The results presented in the book lay the foundations of a new generation of ultra-fast algorithms for optimising the flow in networks after failures or congestion, and the high computational speed creates the possibility of optimal control of very large and complex networks in real time.

Furthermore, the possibility for re-optimising the network flows in real time increases significantly the yield from real production networks and reduces to a minimum the flow disruption caused by failures.The potential application of repairable flow networks reaches across many large and complex systems, including active power networks, telecommunication networks, oil and gas production networks, transportation networks, water supply networks, emergency evacuation networks, and supply networks.

Methods for Reliability Improvement and Risk Reduction

Introduces a new generation, domain-independent reliability improvement and risk reducing methods applicable in any area of human activity. Among these are the methods of separation, segmentation, self-reinforcement, inversion, permutation, substitution and comparative methods based on algebraic inequalities.

The domain-independent methods for reliability improvement and risk reduction do not rely on past failure data or knowledge of the failure mechanisms underlying the failure modes. Using the proven methods in the book, any company can greatly enhance the reliability of its products and operations.