3 papers
math.NA2024
SeAr PC: Sensitivity Enhanced Arbitrary Polynomial Chaos
Nick Pepper, Francesco Montomoli, Kyriakos Kantarakias
This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme…
eess.SY2023
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks
Nick Pepper, George De Ath, Marc Thomas +2
Trajectory prediction (TP) plays an important role in supporting the decision-making of Air Traffic Controllers (ATCOs). Traditional TP methods are deterministic and physics-based,…
cs.CE2023
Probabilistic Machine Learning to Improve Generalisation of Data-Driven Turbulence Modelling
Joel Ho, Nick Pepper, Tim Dodwell
A probabilistic machine learning model is introduced to augment the turbulence model in order to improve the modelling of separated flows and the generalisability of lear…