Chairman's Welcome & Introduction
By Tim Morris, 7 December 2011
Identifying and quantifying sources of uncertainty
By Louise Wright
Analysis of the Stochastic Behaviour of Crash Simulation Results
By Clemens-August Thole
NPL aims to raise awareness of the principles of probabilistic and stochastic Finite Element Analysis (FEA), and demonstrate a range of methods that include random effects in simulations.
In partnership with NAFEMS, we are demonstrating the value and worth in the technology and establishing how it can be universally applied to every problem.
We would like to raise awareness of:
- the potential impact of uncertainty on product design
- the applications and benefits of probabilistic and stochastic FEA via analysis and robust optimisation case studies, and practical activities
- how to manage uncertainty due to natural variability
- how to improve product robustness and reliability
while reducing the risk by using stochastic simulation.
For more information, please contact: firstname.lastname@example.org
Finite Element Modelling
NPL has a wealth of expertise in materials testing, enabling the measurement of accurate materials property data for inclusion in FE analyses.
The aim of multiscale modelling is to predict the behaviour of complex materials, including biomaterials such as proteins, across a range of length and time scales.
Modelling Heat Transfer in Polymer Processing
Modelling can help predict cycle times in injection moulding, which can cut manufacturing costs.
Modelling Heat Transfer with Phase Changes
NPL developed software packages TherMOL 3D and MTDATA have been successfully linked to provide a powerful system capable of modelling transient heat transfer.
A model approach
An article in Materials World magazine highlights how NPL's mathematical modelling capability helps manufacturers avoid mistakes and reduce cost (subscription required)
Please note that the information will not be divulged to third parties, or used without your permission