Jack S. Hale

Learn More
Containers are an emerging technology that hold promise for improving productivity and code portability in scientific computing. We examine Linux container technology for the distribution of a non-trivial scientific computing software stack and its execution on a spectrum of platforms from laptop computers through to high performance computing (HPC)(More)
We discuss Bayesian inference (BI) for the probabilistic identification of material parameters. This contribution aims to shed light on the use of BI for the identification of elastoplastic material parameters. For this purpose a single spring is considered, for which the stress-strain curves are artificially created. Besides offering a didactic(More)
Bayesian inference (BI) can be used for the probabilistic identification of material parameters. For inverse models for instance, BI may be considered convenient as it introduces a statistically regularisation, which is not present in alternative approaches. Understanding the concepts and the application of BI is however not trivial if one is only familiar(More)
  • 1