Investigation on polynomial integrators for time-domain electromagnetics using a high-order discontinuous Galerkin method

International audienceIn this work, we investigate the application of polynomial integrators in a high-order discontinuous Galerkin method for solving the time-domain Maxwell equations. After the spatial discretization, we obtain a time-continuous system of ordinary differential equations of the form, ∂tY(t)=HY(t), where Y(t) is the electromagnetic field, H is a matrix containing the spatial derivatives, and t is the time variable. The formal solution is written as the exponential evolution operator, exp(tH), acting on a vector representing the initial condition of the electromagnetic field. The polynomial integrators are based on the approximation of exp(tH) by an expansion of the form ∑ _m=0^\infinity gm(t) Pm(H), where gm(t) is a function of time and Pm(H) is a polynomial of order m satisfying a short recursion. We introduce a general family of expansions of exp(tH) based on Faber polynomials. This family of expansions is suitable for non-Hermitian matrices, and consequently the proposed integrators can handle absorbing media and conductive materials. We discuss the efficient implementation of this technique, and based on some test problems, we compare the virtues and shortcomings of the algorithm. We also demonstrate how this scheme provides an efficient alternative to standard explicit integrators

Global and Koopman modes analysis of sound generation in mixing layers

It is now well established that linear and nonlinear instability waves play a significant role in the noise generation process for a wide variety of shear flows such as jets or mixing layers. In that context, the problem of acoustic radiation generated by spatially growing instability waves of two-dimensional subsonic and supersonic mixing layers are revisited in a global point of view, i.e., without any assumption about the base flow, in both a linear and a nonlinear framework by using global and Koopman mode decompositions. In that respect, a timestepping technique based on disturbance equations is employed to extract the most dynamically relevant coherent structures for both linear and nonlinear regimes. The present analysis proposes thus a general strategy for analysing the near-field coherent structures which are responsible for the acoustic noise in these configurations. In particular, we illustrate the failure of linear global modes to describe the noise generation mechanism associated with the vortex pairing for the subsonic regime whereas they appropriately explain the Mach wave radiation of instability waves in the supersonic regime. By contrast, the Dynamic Mode Decomposition (DMD) analysis captures both the near-field dynamics and the far-field acoustics with a few number of modes for both configurations. In addition, the combination of DMD and linear global modes analyses provides new insight about the influence on the radiated noise of nonlinear interactions and saturation of instability waves as well as their interaction with the mean flow

Stability, sensitivity and optimisation of chaotic acoustic oscillations

In an acoustic cavity with a heat source, such as a flame in a gas turbine, the thermal energy of the heat source can be converted into acoustic energy, which may generate a loud oscillation. If uncontrolled, these nonlinear acoustic oscillations, also known as thermoacoustic instabilities, can cause large vibrations up to structural failure. Numerical and experimental studies showed that thermoacoustic oscillations can be chaotic. It is not yet known, however, how to minimise such chaotic oscillations. We propose a strategy to analyse and minimise chaotic acoustic oscillations, for which traditional stability and sensitivity methods break down. We investigate the acoustics of a nonlinear heat source in an acoustic resonator. First, we propose covariant Lyapunov analysis as a tool to calculate the stability of chaotic acoustics making connections with eigenvalue and Floquet analyses. We show that covariant Lyapunov analysis is the most general flow stability tool. Second, covariant Lyapunov vector analysis is applied to a chaotic system. The time-averaged acoustic energy is investigated by varying the heat-source parameters. Thermoacoustic systems can display both hyperbolic and non-hyperbolic chaos, as well as discontinuities in the time-averaged acoustic energy. Third, we embed sensitivities of the time-averaged acoustic energy in an optimisation routine. This procedure achieves a significant reduction in acoustic energy and identifies the bifurcations to chaos. The analysis and methods proposed enable the reduction of chaotic oscillations in thermoacoustic systems by optimal passive control. The techniques presented can be used in other unsteady fluid-dynamics problems with virtually no modification

Seismic wave propagation, attenuation and scattering in porous media across various scales

The theory of poroelasticity describes the mechanics of fluid saturated deformable porous solids. Poroelastic theory accurately model the seismic wave propagation in oil and gas reservoirs with an extension to other porous medium e.g. living bones and soft tissues. The poroelastic theory also incorporates the attenuation of energy caused by the relative motion between solid and fluid excited by a point source perturbation.First and foremost, this thesis presents a comprehensive description of seismic attenuation in a viscoacoustic medium by using a fractional derivative approach. Representation of attenuation by using a fractional derivative avoids the solution of augmented system represented by memory process i.e. convolution. In this thesis, a highly accurate time integration scheme, known as rapid expansion method, with a spectral accuracy is implemented to solve the viscoacoustic wave equation.Next, this thesis describes the implementation of a high-order weight-adjusted discontinuous Galerkin (WADG) scheme for the numerical solution of two and three-dimensional (3D) wave propagation problems in anisotropic porous media. The use of a penalty-based numerical flux avoids the diagonalization of Jacobian matrices into polarized wave constituents necessary when solving element-wise Riemann problems.Additionally, a system of hyperbolic partial differential equations describing Biot's poroelastic wave equation for quasi-static Poisseulle and potential flow is also introduced. To incorporate effects from micro-heterogeneities due to pores, we have used the Johnson-Koplik-Dashen (JKD) model of dynamic permeability, which also account for frequency-dependent viscous dissipation caused by wave-induced pore fluids.Next, this thesis uses a model to quantify capillary effects on velocity and attenuation. Studies that have attempted to extend Biot's poroelasticity to include capillary effects found changes in fast P-wave velocity of up to 5 % between the sonic and ultrasonic frequency ranges

The reflection and scattering of sound from the seabed

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN041535 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Computational Inverse Problems for Partial Differential Equations

The problem of determining unknown quantities in a PDE from measurements of (part of) the solution to this PDE arises in a wide range of applications in science, technology, medicine, and finance. The unknown quantity may e.g. be a coefficient, an initial or a boundary condition, a source term, or the shape of a boundary. The identification of such quantities is often computationally challenging and requires profound knowledge of the analytical properties of the underlying PDE as well as numerical techniques. The focus of this workshop was on applications in phase retrieval, imaging with waves in random media, and seismology of the Earth and the Sun, a further emphasis was put on stochastic aspects in the context of uncertainty quantification and parameter identification in stochastic differential equations. Many open problems and mathematical challenges in application fields were addressed, and intensive discussions provided an insight into the high potential of joining deep knowledge in numerical analysis, partial differential equations, and regularization, but also in mathematical statistics, homogenization, optimization, differential geometry, numerical linear algebra, and variational analysis to tackle these challenges