28 citations · 85 across the 19 of their papers we have counts for
6 papers · 1 filter
Density reconstruction from schlieren images through Bayesian nonparametric models
Bryn Noel Ubald, Pranay Seshadri, Andrew Duncan
This study proposes a radically alternate approach for extracting quantitative information from schlieren images. The method uses a scaled, derivative enhanced Gaussian process mod…
Polynomial Ridge Flowfield Estimation
Ashley Scillitoe, Pranay Seshadri, Chun Yui Wong +1
Computational fluid dynamics plays a key role in the design process across many industries. Recently, there has been increasing interest in data-driven methods, in order to exploit…
Bayesian Mass Averaging in Rigs and Engines
Pranay Seshadri, Andrew Duncan, George Thorne
This paper introduces the Bayesian mass average and details its computation. Owing to the complexity of flow in an engine and the limited instrumentation and the precision of the s…
Uncertainty Quantification for Data-driven Turbulence Modelling with Mondrian Forests
Ashley Scillitoe, Pranay Seshadri, Mark Girolami
Data-driven turbulence modelling approaches are gaining increasing interest from the CFD community. However, the introduction of a machine learning (ML) model introduces a new sour…
Numerical Evaluation of Entropy Generation in Isolated Airfoils and Wells Turbines
Tiziano Ghisu, Francesco Cambuli, Pierpaolo Puddu +3
In recent years, a number of authors have studied entropy generation in Wells turbines. This is potentially a very interesting topic, as it can provide important insights into the…
An Aerodynamic Analysis of a Robustly Redesigned Modern Aero-Engine Fan
Pranay Seshadri, Geoffrey Parks, Shahrokh Shahpar
This paper documents results from a recent computational study aimed at de-sensitizing fan stage aerodynamics---in a modern, high bypass ratio aero-engine---to the effects of rear-…