A probabilistic data assimilation framework to reconstruct finite element error fields from sparse error estimates: Application to sub-modeling

Rouse, James Paul; Kerfriden, Pierre; Hamadi, Maxime

doi:10.1002/nme.7090

All Outputs (3)

The Estimation of Taylor-Quinney Coefficients Using Small Ring Specimens (2022)
Journal Article

Background: The use of the Taylor-Quinney coefficient for introducing a thermal dissipation term into material models relies on understanding its dependencies. These are usually determined through extensive experimentation, wherein temperature variat... Read More about The Estimation of Taylor-Quinney Coefficients Using Small Ring Specimens.

An inverse analysis method for determining abradable constitutive properties (2022)
Journal Article

Abradable coatings enable small tip clearances within gas turbine engines to be achieved. These coatings allow blades to cut their ideal paths during engine running-in and act as a sacrificial layer during unforeseen blade-casing interactions, minimi... Read More about An inverse analysis method for determining abradable constitutive properties.

A probabilistic data assimilation framework to reconstruct finite element error fields from sparse error estimates: Application to sub-modeling (2022)
Journal Article

The present work proposes a computational approach that recovers full finite element error fields from a small number of estimates of errors in scalar quantities of interest. The approach is weakly intrusive and is motivated by large scale industrial... Read More about A probabilistic data assimilation framework to reconstruct finite element error fields from sparse error estimates: Application to sub-modeling.