Computational Modelling Group

Aerofoil noise

Richard Sandberg (Investigator)

High-performance computing is used to identify noise sources on aerofoils.

Computational Methods for Aircraft Noise Prediction

Gwenael Gabard (Investigator), Albert Prinn

The aim of this project is to develop and test an efficient flow acoustics solver based on the finite element method and the potential flow theory.

Development of a novel Navier-Stokes solver (HiPSTAR)

Richard Sandberg (Investigator)

Development of a highly efficient Navier-Stokes solver for HPC.

Investigation of acoustic radiation forces on micro-particles and cells in ultrasonic particle manipulation

Martyn Hill (Investigator), Puja Mishra

A Finite Element model is developed to investigate the force generated on a particle of arbitrary geometry and composition in a sound field. The model overcame the drawbacks of existing analytical solutions of size restriction and provided the flexibility of particle representation. This suggested useful results on shape dependency, effect of elasticity of particle and dominancy of nucleus in a cell in estimating the force on a single particle.

Jet noise

Richard Sandberg (Investigator), Neil Sandham

Direct numerical simulations are used to investigate jet noise.

Numerical investigation of the true sources of jet noise

Anurag Agarwal (Investigator), Samuel Sinayoko

Aircraft noise severely impacts the quality of life of people living close to airports. Noise generation by aircrafts is especially large during take-off. Jet noise is the dominant noise source during take-off. It is produced by the high speed flow generated by the engine. However, the actual source of sound remains unknown. A deeper understanding of the sources of jet noise is need to be able to reduce the noise. The aim of this project is to implement a innovative method that would allow to identify the sources of jet noise.

Partial Discharge Signal Extraction using Spectral Methods

Condition based maintenance of 3 phase belted cables is increasing in demand as asset lifetimes approach their end...(some more info on the relevance of analysing belted cables).
The application of hard thresholding methods for Partial Discharge [PD] data extraction in high noise-ratio signals may produce series of PD trains with missing events and conversely correct events interlinked with noise. Subsequent analysis of the series will potentially be fraudulent and may lead to inaccurate conclusions. In this work, spectral methods for PD data extraction from very noisy environments are presented and a previously derived PD source classification technique is employed. Tests were conducted on a large set of wide bandwidth field data from three phase belted cables placed around London (UK) and Cyprus, and compared with accelerated aging experimental data. In the search of deeper insights, the deterministic origins of the produced sets of spike trains are explored and some linear and non-linear characteristics derived.

Stochastic computational methods for aero-acoustics

Gwenael Gabard (Investigator), Martina Dieste

Stochastic methods are used to synthesize a turbulent flow which is then used to model the sound radiated by an airfoil interacting with this turbulence. This approach is faster than performing a complete simulation of the flow field.

Structured low-rank approximation

Ivan Markovsky

Today's state-of-the-art methods for data processing are model based. We propose a fundamentally new approach that does not depend on an explicit model representation and can be used for model-free data processing. From a theoretical point of view, the prime advantage of the newly proposed paradigm is conceptual unification of existing methods. From a practical point of view, the proposed paradigm opens new possibilities for development of computational methods for data processing.

Wave-based discontinuous Galerkin methods

Gwenael Gabard (Investigator), Greg Kennedy

Wave-based computational methods are developed to model sound propagation in moving inhomogeneous media.