Networks and resources

UMRIDA is a Level 1 collaborative project within the European Commission's Seventh Framework Programme. It involves a consortium of 21 partners from the industrial aeronautics sector, leading research institutes and universities as well as SME's.
The SIAM/ASA Journal on Uncertainty Quantification publishes research articles presenting significant mathematical, statistical, algorithmic, and application advances in uncertainty quantification, defined as the interface of complex modeling of processes and data, especially characterizations of the uncertainties inherent in the use of such models.
The worlds foremost repository of structured knowledge and advice designed to underpin quality and trust in the industrial application of CFD
This page is dedicated to the dissemination of information related to the NASA Langley Multidisciplinary Uncertainty Quantification Challenge
NAFEMS - Stochastics

The NAFEMS Stochastics Working Group aim to accelerate the adoption and further the development of stochastic methods. Uncertainty enters into numerical simulation from a variety of sources, such as variability in input parameters. Knowledge of the effect of uncertainties can lead the analyst to drastically different conclusions regarding which input parameters are most important. Quantifying the effect of uncertainty provide the analyst with an estimate of the true performance of a design.




The MUCM Community has grown out of the MUCM Project which drew to a close at the end of 2012, after 6 and a half years of supporting research in this area. The new MUCM Community and its Steering Group will take over responsibility of some of those community aspects that the MUCM Project initiated including the Toolkit, the UCM mailing list and News Digests and potentially future UCM Conferences


National Physical Laboratory

Measurement provides data that is used as the basis for making inferences, informing decisions and controlling systems. These activities depend on the reliability, traceability and mutual recognition of measurement results derived from the data, which are established through modelling, mathematical and statistical methods of data analysis implemented in validated software, and valid statements of measurement uncertainty. We undertake research to build mathematical, statistical and computational capability in the areas of metrology data analysis and measurement uncertainty evaluation. We influence standardisation and regulatory bodies through the maintenance and development of Standards and Guides. We disseminate good practice through journal papers, guides, reports, training and validated software.

Novel Mathematical and Statistical Approaches to Uncertainty Evaluation : Best Practice Guide to Uncertainty Evaluation  For Computaionally Expensive Models: Best Practice Guide to Uncertainty Evaluation for Computationally Expensive Models


Sandia National Laboratories
This is the main page for the 2014 Sandia Verifcation & Validation Challenge Workshop organised by the V&V, UQ & Credibility Processes Department at Sandia National Laboratories.