Robust modelling of noisy ARMA signals

In this paper methods are developed for enhancement and analysis of autoregressive moving average (ARMA) signals observed in additive noise which can be represented as mixtures of heavy-tailed non-Gaussian sources and a Gaussian background component. Such models find application in systems such as atmospheric communications channels or early sound recordings which are prone to intermittent impulse noise. Markov Chain Monte Carlo (MCMC) simulation techniques are applied to the joint problem of signal extraction, model parameter estimation and detection of impulses within a fully Bayesian framework. The algorithms require only simple linear iterations for all of the unknowns, including the MA parameters, which is in contrast with existing MCMC methods for analysis of noise-free ARMA models. The methods are illustrated using synthetic data and noise-degraded sound recordings.

Towards identification of a general model of damping

Characterization of damping forces in a vibrating structure has long been an active area of research in structural dynamics. In spite of a large amount of research, understanding of damping mechanisms is not well developed. A major reason for this is that unlike inertia and stiffness forces it is not in general clear what are the state variables that govern the damping forces. The most common approach is to use `viscous damping' where the instantaneous generalized velocities are the only relevant state variables. However, viscous damping by no means the only damping model within the scope of linear analysis. Any model which makes the energy dissipation functional non-negative is a possible candidate for a valid damping model. This paper is devoted to develop methodologies for identification of such general damping models responsible for energy dissipation in a vibrating structure. The method uses experimentally identified complex modes and complex natural frequencies and does not a-priori assume any fixed damping model (eg., viscous damping) but seeks to determine parameters of a general damping model described by the so called `relaxation function'. The proposed method and several related issues are discussed by considering a numerical example of a linear array of damped spring-mass oscillators.

Active learning of model evidence using Bayesian quadrature

Numerical integration is a key component of many problems in scientific computing, statistical modelling, and machine learning. Bayesian Quadrature is a modelbased method for numerical integration which, relative to standard Monte Carlo methods, offers increased sample efficiency and a more robust estimate of the uncertainty in the estimated integral. We propose a novel Bayesian Quadrature approach for numerical integration when the integrand is non-negative, such as the case of computing the marginal likelihood, predictive distribution, or normalising constant of a probabilistic model. Our approach approximately marginalises the quadrature model's hyperparameters in closed form, and introduces an active learning scheme to optimally select function evaluations, as opposed to using Monte Carlo samples. We demonstrate our method on both a number of synthetic benchmarks and a real scientific problem from astronomy.

Three-dimensional direct numerical simulations of autoignition in turbulent non-premixed flows with simple and complex chemistry

3D Direct Numerical Simulations (DNS) of autoignition in turbulent non-premixed flows between fuel and hotter air have been carried out using both 1-step and complex chemistry consisting of a 22 species n-heptane mechanism to investigate spontaneous ignition timing and location. The simple chemistry results showed that the previous findings from 2D DNS that ignition occurred at the most reactive mixture fraction (ξMR) and at small values of the conditional scalar dissipation rate (N|ξMR) are valid also for 3D turbulent mixing fields. Performing the same simulation many times with different realizations of the initial velocity field resulted in a very narrow statistical distribution of ignition delay time, consistent with a previous conjecture that the first appearance of ignition is correlated with the low-N content of the conditional probability density function of N. The simulations with complex chemistry for conditions outside the Negative Temperature Coefficient (NTC) regime show behaviour similar to the single-step chemistry simulations. However, in the NTC regime, the most reactive mixture fraction is very rich and ignition seems to occur at high values of scalar dissipation. Copyright © 2006 by ASME.

On separating propagating and non-propagating dynamics in fluid-flow equations

The ability to separate acoustically radiating and non-radiating components in fluid flow is desirable to identify the true sources of aerodynamic sound, which can be expressed in terms of the non-radiating flow dynamics. These non-radiating components are obtained by filtering the flow field. Two linear filtering strategies are investigated: one is based on a differential operator, the other employs convolution operations. Convolution filters are found to be superior at separating radiating and non-radiating components. Their ability to decompose the flow into non-radiating and radiating components is demonstrated on two different flows: one satisfying the linearized Euler and the other the Navier-Stokes equations. In the latter case, the corresponding sound sources are computed. These sources provide good insight into the sound generation process. For source localization, they are found to be superior to the commonly used sound sources computed using the steady part of the flow. Copyright © 2009 by S. Sinayoko, A. Agarwal, Z. Hu.

On computing the physical sources of jet noise

We derive a closed system of equations that relates the acoustically radiating flow variables to the sources of sound for homentropic flows. We use radiating density, momentum density and modified pressure as the dependent variables which leads to simple source terms for the momentum equations. The source terms involve the non-radiating parts of the density and momentum density fields. These non-radiating components are obtained by removing the radiating wavenumbers in the Fourier domain. We demonstrate the usefulness of this new technique on an axi-symmetric jet solution of the Navier-Stokes equations, obtained by direct numerical simulation (DNS). The dominant source term is proportional to the square of the non-radiating part of the axial momentum density. We compare the sound sources to that obtained by an acoustic analogy and find that they have more realistic physical properties. Their frequency content and amplitudes are consistent with. We validate the sources by computing the radiating sound field and comparing it to the DNS solution. © 2010 by S. Sinayoko, A. Agarwal.

Reprint of: Flow filtering and the physical sources of aerodynamic sound

The physical sources of sound are expressed in terms of the non-radiating part of the flow. The non-radiating part of the flow can be obtained from convolution filtering, as we demonstrate numerically by using an axi-symmetric jet satisfying the Navier-Stokes equations. Based on the frequency spectrum of the source, we show that the sound sources exhibit more physical behaviour than sound sources based on acoustic analogies. To validate the sources of sound, one needs to let them radiate within the non-radiating flow field. However, our results suggest that the traditional Euler operator linearized about the time-averaged part of the flow should be sufficient to compute the sound field. © 2010 Published by Elsevier Ltd.

Transient ventilation dynamics induced by heat sources of unequal strength

We examine theoretically the transient displacement flow and density stratification that develops within a ventilated box after two localized floor-level heat sources of unequal strengths are activated. The heat input is represented by two non-interacting turbulent axisymmetric plumes of constant buoyancy fluxes B1 and B2 > B1. The box connects to an unbounded quiescent external environment of uniform density via openings at the top and base. A theoretical model is developed to predict the time evolution of the dimensionless depths λj and mean buoyancies δj of the 'intermediate' (j = 1) and 'top' (j = 2) layers leading to steady state. The flow behaviour is classified in terms of a stratification parameter S, a dimensionless measure of the relative forcing strengths of the two buoyant layers that drive the flow. We find that dδ1/dτ α 1/λ1 and dδ2/dτ α 1/λ2, where τ is a dimensionless time. When S 1, the intermediate layer is shallow (small λ1), whereas the top layer is relatively deep (large λ2) and, in this limit, δ1 and δ2 evolve on two characteristically different time scales. This produces a time lag and gives rise to a 'thermal overshoot', during which δ1 exceeds its steady value and attains a maximum during the transients; a flow feature we refer to, in the context of a ventilated room, as 'localized overheating'. For a given source strength ratio ψ = B1/B2, we show that thermal overshoots are realized for dimensionless opening areas A < Aoh and are strongly dependent on the time history of the flow. We establish the region of {A, ψ} space where rapid development of δ1 results in δ1 > δ2, giving rise to a bulk overturning of the buoyant layers. Finally, some implications of these results, specifically to the ventilation of a room, are discussed. © Cambridge University Press 2013.