Reconstruction subgrid models for nonpremixed combustion

Large-eddy simulation of combustion problems involves highly nonlinear terms that, when filtered, result in a contribution from subgrid fluctuations of scalars, Z, to the dynamics of the filtered value. This subgrid contribution requires modeling. Reconstruction models try to recover as much information as possible from the resolved field Z, based on a deconvolution procedure to obtain an intermediate field ZM. The approximate reconstruction using moments (ARM) method combines approximate reconstruction, a purely mathematical procedure, with additional physics-based information required to match specific scalar moments, in the simplest case, the Reynolds-averaged value of the subgrid variance. Here, results from the analysis of the ARM model in the case of a spatially evolving turbulent plane jet are presented. A priori and a posteriori evaluations using data from direct numerical simulation are carried out. The nonlinearities considered are representative of reacting flows: power functions, the dependence of the density on the mixture fraction (relevant for conserved scalar approaches) and the Arrhenius nonlinearity (very localized in Z space). Comparisons are made against the more popular beta probability density function (PDF) approach in the a priori analysis, trying to define ranges of validity for each approach. The results show that the ARM model is able to capture the subgrid part of the variance accurately over a wide range of filter sizes and performs well for the different nonlinearities, giving uniformly better predictions than the beta PDF for the polynomial case. In the case of the density and Arrhenius nonlinearities, the relative performance of the ARM and traditional PDF approaches depends on the size of the subgrid variance with respect to a characteristic scale of each function. Furthermore, the sources of error associated with the ARM method are considered and analytical bounds on that error are obtained

Estimating fugitive bioaerosol releases from static compost windrows: feasibility of portable wind tunnel approach

An assessment of the fugitive release of bioaerosols from static compost piles was conducted at a green waste composting facility in South East England; this representing the initial stage of a programme of research into the influence of process parameters on bioaerosol emission flux. Wind tunnel experiments conducted on the surface of static windrows generated specific bioaerosol emission rates (SBER2s) at ground level of between 13 - 22 x10 3 cfu/m 2 /s for mesophilic actinomycetes and between 8 - 11 x10 3 cfu/m 2 /s for Aspergillus fumigatus. Air dispersion modelling of these emissions using the SCREEN3 air dispersion model in area source term mode was used to generate source depletion curves downwind of the facility for comparative purposes

Exact Solution of a Electron System Combining Two Different t-J Models

A new strongly correlated electron model is presented. This is formed by two types of sites: one where double occupancy is forbidden, as in the t-J model, and the other where double occupancy is allowed but vacancy is not allowed, as an inverse t-J model. The Hamiltonian shows nearest and next-to-nearest neighbour interactions and it is solved by means of a modified algebraic nested Bethe Ansatz. The number of sites where vacancy is not allowed, may be treated as a new parameter if the model is looked at as a t-J model with impurities. The ground and excited states are described in the thermodynamic limit.Comment: Some corrections and references added. To be published in J. Phys.

Evolution of induced axial magnetization in a two-component magnetized plasma

In this paper, the evolution of the induced axial magnetization due to the propagation of an electromagnetic (em) wave along the static background magnetic field in a two-component plasma has been investigated using the Block equation. The evolution process induces a strong magnetic anisotropy in the plasma medium, depending nonlinearly on the incident wave amplitude. This induced magnetic anisotropy can modify the dispersion relation of the incident em wave, which has been obtained in this paper. In the low frequency Alfven wave limit, this dispersion relation shows that the resulting phase velocity of the incident wave depends on the square of the incident wave amplitude and on the static background magnetic field of plasma. The analytical results are in well agreement with the numerically estimated values in solar corona and sunspots.Comment: 7 pages, 1 figur

In-medium vector mesons and low mass lepton pairs from heavy ion collisions

The rho and omega meson self-energy at finite temperature and baryon density have been analysed for an exhaustive set of mesonic and baryonic loops in the real time formulation of thermal field theory. The large enhancement of spectral strength below the nominal rho mass is seen to cause a substantial enhancement in dilepton pair yield in this mass region. The integrated yield after space-time evolution using relativistic hydrodynamics with quark gluon plasma in the initial state leads to a very good agreement with the experimental data from In-In collisions obtained by the NA60 collaboration.Comment: Invited Talk at the DAE-BRNS Workshop on Hadron Physics, Bhabha Atomic Research Centre, Mumbai, India, October 31-November 4, 201

Thermal Radiation from Nucleons and Mesons

Thermal photon emission rates due to meson-nucleon interactions have been evaluated. An exhaustive set of reactions involving p(\bar p), n(\bar n), rho, omega, a_1, pi and eta is seen to provide a sizeable contribution to the emission rate from hot hadronic matter. Contributions from baryonic resonances are found to be negligibly small

Enhanced Shot Noise in Tunneling through a Stack of Coupled Quantum Dots

We have investigated the noise properties of the tunneling current through vertically coupled self-assembled InAs quantum dots. We observe super-Poissonian shot noise at low temperatures. For increased temperature this effect is suppressed. The super-Poissonian noise is explained by capacitive coupling between different stacks of quantum dots

Handling oversampling in dynamic networks using link prediction

Oversampling is a common characteristic of data representing dynamic networks. It introduces noise into representations of dynamic networks, but there has been little work so far to compensate for it. Oversampling can affect the quality of many important algorithmic problems on dynamic networks, including link prediction. Link prediction seeks to predict edges that will be added to the network given previous snapshots. We show that not only does oversampling affect the quality of link prediction, but that we can use link prediction to recover from the effects of oversampling. We also introduce a novel generative model of noise in dynamic networks that represents oversampling. We demonstrate the results of our approach on both synthetic and real-world data.Comment: ECML/PKDD 201