Faculty of Engineering
   
   
  
 

Stewart McWilliam

Associate Professor, Faculty of Engineering

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Expertise Summary

Dr McWilliam has research expertise in structural dynamics and stochastic mechanics, including: structural vibration, random vibration, structural reliability, and uncertainty analysis. In general, this research is involved in the development and application of analytical and numerical (e.g. Finite Element Method) analysis methods to predict and better understand the performance of engineering structures. Engineering applications relate to the dynamics of offshore structures, aerospace and automotive structures, and include the analysis of offshore mooring systems; sensors, actuators and Microsystems; and gas turbine transmission systems. Further details of Dr McWilliam's expertise can be found under the heading "Current Research".

Research Summary

Dr McWilliam is a core member of the Structural Integrity & Dynamics Group at the University of Nottingham and has extensive research experience in the areas of structural dynamics, random… read more

Selected Publications

Current Research

Dr McWilliam is a core member of the Structural Integrity & Dynamics Group at the University of Nottingham and has extensive research experience in the areas of structural dynamics, random vibration, structural reliability and uncertainty analysis. In general, this research is involved in the development and application of analytical and numerical (e.g. Finite Element Method) analysis techniques to predict and understand the performance of engineering structures. Current areas of interest include:

Dynamics and reliability of large-volume offshore structures - Dr McWilliam has used and developed mathematical techniques (e.g. functional techniques and the FPK equation) for predicting the probability of failure of structures subjected to stochastic loading (Gaussian and second order Volterra processes). Some of this work was developed in conjunction with the offshore industry and the general aim is to assess the reliability of compliant offshore structures moored in random seas.

Design, modelling and analysis of MEMS resonators - The majority of this work relates to the development of mathematical models of silicon ring resonators to predict the performance of miniaturised vibrating gyroscopes used to detect angular velocity, and is performed in conjunction with BAE systems (Plymouth and Sowerby). Research strands include: the development of new sensor concepts; understanding the influence of (deterministic and statistical) manufacturing uncertainty on device performance; developing strategies to nullify the effects of uncertainty to improve device performance; quantifying the influence of non-linearity (geometric and electrostatic) and damping mechanisms (thermoelastic, squeeze-film and support loss); and designing for improved performance using mathematical optimization (genetic algorithms) and robust design theory.

Uncertainty in Engineering - Arising from interests in the stochastic response of structures and the influence of manufacturing imperfections on MEMS devices, a distinct focus of Dr McWilliam's current research is the development of mathematical methods (montonic method, convex modelling) for analysing the influence of uncertainty (particularly interval parameter uncertainty) on the performance of vibrating structures.

Future Research

Dr McWilliam's future research will focus on the areas of MEMS and uncertainty analysis. MEMS technology is fundamental to the development of sensors and actuators for future generations, and Dr McWilliam aims to contribute to these developments by applying his research expertise to the development of new device concepts and analysis tools to aid the manufacture of high-performance, high-yield devices. A particularly important area for consideration is the presence of structural, process and material uncertainties, which can severely degrade device performance and reduce yield. Dr McWilliam's future research aims to develop analysis techniques that are capable of analysing the effects of such uncertainties on the performance of micro-engineered systems, and aid the development of MEMS designs that are robust to manufacturing uncertainty.

Faculty of Engineering

The University of Nottingham
University Park
Nottingham, NG7 2RD



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