A modeling paradigm is developed to augment predictive models of turbulence by effectively
using limited data generated from physical experiments. The key components of the current …

A tangible computer readable medium encoded with instructions for automatically
generating metadata, wherein said execution of said instructions by one or more processors …

Solving computational fluid dynamics problems requires using large computational
resources. The computational time and memory requirements to solve realistic problems …

Deep learning models are not yet fully applied to fluid dynamics predictions, while they are
the state-of-the-art solution in many other areas ie video and language processing, finance …

This work aims to improve fuel chamber injectors' performance in turbofan engines, thus
implying improved performance and reduction of pollutants. This requires the development …

This is the first comprehensive text on African Mathematics that can be used to address
some of the problematic issues in this area. These issues include attitudes, curriculum …

Swirl-stabilized gas turbine combustors often use turbulence modeling through Scale-
Resolved Simulations (SRS), like Large Eddy Simulations (LES). However, LES is …

In the context of the contemporary push for “big data” in many fields, we review recent
experiences building large databases for turbulence research. We consider data from direct …

Purpose–After almost three centuries of employing western educational approaches, many
African societies are still characterized by low western literacy rates, civil conflicts, and …

For swirl-stabilized gas turbine combustors, turbulence modelling is generally undertaken
using Scale-Resolved Simulations (SRS) methods such as Large Eddy Simulations (LES) …