Methane Clathrate Hydrate Nucleation Mechanism by Advanced Molecular Simulations

The nucleation mechanisms of methane hydrates are studied using well-tempered metadynamics and restrained molecular dynamics. The collective variables we used to follow the process are the methane-methane and methane-water coordination numbers, from which we computed the corresponding Landau free energy surface. This surface is characterized by two minima, corresponding to the two-phase methane bubble/water solution and clathrate crystal, and a transition state.

Clathrate structure-type recognition: Application to hydrate nucleation and crystallisation

For clathrate-hydrate polymorphic structure-type (sI versus sII), geometric recognition criteria have been developed and validated. These are applied to the study of the rich interplay and development of both sI and sII motifs in a variety of hydrate-nucleation events for methane and H2S hydrate studied by direct and enhanced-sampling molecular dynamics (MD) simulations.

Source modelling of ElectroCorticoGraphy (ECoG) data: stability analysis and spatial filtering

Electrocorticography (ECoG) is a neurophysiological modality that measures the distribution of electrical potentials, associated with either spontaneous or evoked neural activity, by means of electrodes grids implanted close to the cortical surface. A full interpretation of ECoG data, however, requires solving the ill-posed inverse problem of reconstructing the spatio-temporal distribution of neural currents responsible for the recorded signals.

Impact of the Peterlin approximation on polymer dynamics in turbulent flows

We study the impact of the Peterlin approximation on the statistics of the end-to-end separation of polymers in a turbulent flow. The finitely extensible nonlinear elastic (FENE) model and the FENE model with the Peterlin approximation (FENE-P) are numerically integrated along a large number of Lagrangian trajectories resulting from a direct numerical simulation of three-dimensional homogeneous isotropic turbulence. Although the FENE-P model yields results in qualitative agreement with those of the FENE model, quantitative differences emerge.

Mesoscopic Simulation Study of Wall Roughness Effects in Micro-channel Flows of Dense Emulsions

We study the Poiseuille flow of a soft-glassy material above the jamming point, where the material flows like a complex fluid with Herschel-Bulkley rheology. Microscopic plastic rearrangements and the emergence of their spatial correlations induce cooperativity flow behavior whose effect is pronounced in presence of confinement. With the help of lattice Boltzmann numerical simulations of confined dense emulsions, we explore the role of geometrical roughness in providing activation of plastic events close to the boundaries.

Inertial particle acceleration in strained turbulence

The dynamics of inertial particles in turbulence is modelled and investigated by means of direct numerical simulation of an axisymmetrically expanding homogeneous turbulent strained flow. This flow can mimic the dynamics of particles close to stagnation points. The influence of mean straining flow is explored by varying the dimensionless strain rate parameter Sk(0)/epsilon(0) from 0.2 to 20, where S is the mean strain rate, k(0) and epsilon(0) are the turbulent kinetic energy and energy dissipation rate at the onset of straining.

A hierarchical Krylov-Bayes iterative inverse solver for MEG with physiological preconditioning

Magnetoencephalopgraphy (MEG) is a non-invasive functional imaging modality for mapping cerebral electromagnetic activity from measurements of the weak magnetic field that it generates. It is well known that the MEG inverse problem, i.e. the problem of identifying electric currents from the induced magnetic fields, is a severely underdetermined problem and, without complementary prior information, no unique solution can be found.

Numerical methods for pricing options under stochastic volatility models.

Partial integro-differential equation (PIDE) formulations are often preferable for pricing options under models with stochastic volatility and jumps. In this talk, we consider the numerical approximation of such models. On one hand, due to the non-local nature of the integral term, we propose to use Implicit-Explicit (IMEX) Runge-Kutta methods for the time integration to solve the integral term explicitly, giving higher order accuracy schemes under weak stability time-step restrictions.

Numerical solution of the nonlinear Schrodinger equation using smoothed-particle hydrodynamics

We formulate a smoothed-particle hydrodynamics numerical method, traditionally used for the Euler equations for fluid dynamics in the context of astrophysical simulations, to solve the nonlinear Schrodinger equation in the Madelung formulation. The probability density of the wave function is discretized into moving particles, whose properties are smoothed by a kernel function. The traditional fluid pressure is replaced by a quantum pressure tensor, for which a robust discretization is found.

Numerical simulations of aggregate breakup in bounded and unbounded turbulent flows

Breakup of small aggregates in fully developed turbulence is studied by means of direct numerical simulations in a series of typical bounded and unbounded flow configurations, such as a turbulent channel flow, a developing boundary layer and homogeneous isotropic turbulence. The simplest criterion for breakup is adopted, whereby aggregate breakup occurs when the local hydrodynamic stress "1=2, with " being the energy dissipation at the position of the aggregate, overcomes a given threshold cr, which is characteristic for a given type of aggregate.