Naturally variability and randomnes affect every real-world process, but how should their effects be included in simulations? This seminar raised awareness of the principles of probabilistic & stochastic FEA. Presentations were given from a range of methods that included random effects in simulations, as well as presenting its application as an emerging technology. All of this was presented in an easy to understand manner which focussed on practical application of the technology.
Throughout the seminar, presentations and case studies were shown demonstrating the value and worth in the technology and why every organisation should be utilising it. The seminar seeked to reduce any reservations about the technology and established how it can be universally applied to every problem.
The video podcasts from this meeting can be found at
Simulation in the Presence of Variability: Past, Present and Future Trends
Jacek Marczyk, ONTONIX S.r.l.
Identifying and Measuring Sources of Uncertainty
Louise Wright, National Physical Laboratory
Uncertainty Assessment of Aircraft Components by Simulation
Dietmar Vogt, EADS Innovation Works
Using Data Reduction Technologies for the Analysis of the Stochastic Behaviour of Crash Simulation Results
Clemens-August Thole, Fraunhofer Gesellschaft
Application of Robustness and Variability Analysis at Jaguar Land Rover
Richard Brown Jaguar Land Rover
Stochastic Analysis of the Herschel Telescope Cryo-Focus Problem
Dominic Doyle, European Space Agency
Quantifying and Managing Uncertainty with Gaussian Process Emulators
Tony O'Hagan, University of Sheffield
We are pleased to confirm that this is the first in a series of events on a similar subject and follow on events will include:-
Engineering Optimisation for Industrial Applications Seminar
To be held on 21st March 2012 at a venue to be confirmed in The Midlands the NAFEMS seminar on Engineering Optimisation for Industrial Applications aims to provide an overview of optimisation methods and techniques currently available, ranging from the classical approaches such as gradient and simplex methods through to more sophisticated, methods such genetic algorithms and response surface modelling.
A workshop will follow in early July 2012, with the aim of describing and demonstrating the practical implementation of probabilistic & stochastic methods. Vendors will be available to deliver a ‘hands on’ demonstration of the simplicity of a stochastics simulation and its results.