Effects of turbulent reynolds number on the displacement speed statistics in the thin reaction zones regime of turbulent premixed combustion

The effects of turbulent Reynolds number on the statistical behaviour of the displacement speed have been studied using three-dimensional Direct Numerical Simulation of statistically planar turbulent premixed flames. The probability of finding negative values of the displacement speed is found to increase with increasing turbulent Reynolds number when the Damkhler number is held constant. It has been shown that the statistical behaviour of the Surface Density Function, and its strain rate and curvature dependence, plays a key role in determining the response of the different components of displacement speed. Increasing the turbulent Reynolds number is shown to reduce the strength of the correlations between tangential strain rate and dilatation rate with curvature, although the qualitative nature of the correlations remains unaffected. The dependence of displacement speed on strain rate and curvature is found to weaken with increasing turbulent Reynolds number when either Damkhler or Karlovitz number is held constant, but the qualitative nature of the correlation remains unaltered. The implications of turbulent Reynolds number effects in the context of Flame Surface Density (FSD) modelling have also been addressed, with emphasis on the influence of displacement speed on the curvature and propagation terms in the FSD balance equation. © 2011 Nilanjan Chakraborty et al.

The Gaussian process density sampler

We present the Gaussian Process Density Sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a fixed density function that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We can also infer the hyperparameters of the Gaussian process. We compare this density modeling technique to several existing techniques on a toy problem and a skullreconstruction task.

The structure of turbulent stratified and premixed methane/air flames I: Non-swirling flows

A series of flames in a turbulent methane/air stratified swirl burner is presented. The degree of stratification and swirl are systematically varied to generate a matrix of experimental conditions, allowing their separate and combined effects to be investigated. Non-swirling flows are considered in the present paper, and the effects of swirl are considered in a companion paper (Part II). A mean equivalence ratio of φ=0.75 is used, with φ for the highest level of stratification spanning 0.375-1.125. The burner features a central bluff-body to aid flame stabilization, and the influence of the induced recirculation zone is also considered. The current work focuses on non-swirling flows where two-component particle image velocimetry (PIV) measurements are sufficient to characterize the main features of the flow field. Scalar data obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution allow the behavior of key combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. Simultaneous cross-planar OH-PLIF is used to determine the orientation of the instantaneous flame normal in the scalar measurement window, allowing gradients in temperature and progress variable to be angle corrected to their three dimensional values. The relationship between curvature and flame thickness is investigated using the OH-PLIF images, as well as the effect of stratification on curvature.The main findings are that the behavior of the key combustion species in temperature space is well captured on the mean by laminar flame calculations regardless of the level of stratification. H 2 and CO are significant exceptions, both appearing at elevated levels in the stratified flames. Values for surface density function and by extension thermal scalar dissipation rate are found to be substantially lower than laminar values, as the thickening of the flame due to turbulence dominates the effect of increased strain. These findings hold for both premixed and stratified flames. The current series of flames is proposed as an interesting if challenging set of test cases for existing and emerging turbulent flame models, and data are available on request. © 2012 The Combustion Institute.

The structure of turbulent stratified and premixed methane/air flames II: Swirling flows

Experimental results are presented from a series of turbulent methane/air stratified flames stabilized on a swirl burner. Nine operating conditions are considered, systematically varying the level of stratification and swirl while maintaining a lean global mean equivalence ratio of φ̄=0.75. Scalar data are obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution, allowing the behavior of the major combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. The corresponding three-dimensional surface density function and thermal scalar dissipation rate are investigated, along with geometric characteristics of the flame such as curvature and flame thickness. Hydrogen and carbon monoxide levels within the flame brush are raised by stratification, indicating models with laminar premixed flame chemistry may not be suitable for stratified flames. However, flame surface density, scalar dissipation and curvature all appear insensitive to the degree of stratification in the flames surveyed. © 2012 The Combustion Institute.

On representing chemical environments

We review some recently published methods to represent atomic neighbourhood environments, and analyse their relative merits in terms of their faithfulness and suitability for fitting potential energy surfaces. The crucial properties that such representations (sometimes called descriptors) must have are differentiability with respect to moving the atoms, and invariance to the basic symmetries of physics: rotation, reflection, translation, and permutation of atoms of the same species. We demonstrate that certain widely used descriptors that initially look quite different are specific cases of a general approach, in which a finite set of basis functions with increasing angular wave numbers are used to expand the atomic neighbourhood density function. Using the example system of small clusters, we quantitatively show that this expansion needs to be carried to higher and higher wave numbers as the number of neighbours increases in order to obtain a faithful representation, and that variants of the descriptors converge at very different rates. We also propose an altogether new approach, called Smooth Overlap of Atomic Positions (SOAP), that sidesteps these difficulties by directly defining the similarity between any two neighbourhood environments, and show that it is still closely connected to the invariant descriptors. We test the performance of the various representations by fitting models to the potential energy surface of small silicon clusters and the bulk crystal.

Gaussian Process Vine Copulas for Multivariate Dependence

Copulas allow to learn marginal distributions separately from the multivariate dependence structure (copula) that links them together into a density function. Vine factorizations ease the learning of high-dimensional copulas by constructing a hierarchy of conditional bivariate copulas. However, to simplify inference, it is common to assume that each of these conditional bivariate copulas is independent from its conditioning variables. In this paper, we relax this assumption by discovering the latent functions that specify the shape of a conditional copula given its conditioning variables We learn these functions by following a Bayesian approach based on sparse Gaussian processes with expectation propagation for scalable, approximate inference. Experiments on real-world datasets show that, when modeling all conditional dependencies, we obtain better estimates of the underlying copula of the data.

Statistics of reaction progress variable and mixture fraction gradients from DNS of turbulent partially premixed flames

Statistically planar turbulent partially premixed flames for different initial intensities of decaying turbulence have been simulated for global equivalence ratios = 0.7 and 1.0 using three-dimensional, simplified chemistry-based direct numerical simulations (DNS). The simulation parameters are chosen such that the flames represent the thin reaction zones regime combustion. A random bimodal distribution of equivalence ratio is introduced in the unburned gas ahead of the flame to account for the mixture inhomogeneity. The results suggest that the probability density functions (PDFs) of the mixture fraction gradient magnitude |Δξ| (i.e., P(|Δξ|)) can be reasonably approximated using a log-normal distribution. However, this presumed PDF distribution captures only the qualitative nature of the PDF of the reaction progress variable gradient magnitude |Δc| (i.e., P(|Δc|)). It has been found that a bivariate log-normal distribution does not sufficiently capture the quantitative behavior of the joint PDF of |Δξ| and |Δc| (i.e., P(|Δξ|, |Δc|)), and the agreement with the DNS data has been found to be poor in certain regions of the flame brush, particularly toward the burned gas side of the flame brush. Moreover, the variables |Δξ| and |Δc| show appreciable correlation toward the burned gas side of the flame brush. These findings are corroborated further using a DNS data of a lifted jet flame to study the flame geometry dependence of these statistics. © 2013 Copyright Taylor and Francis Group, LLC.

Local strain rate and curvature dependences of scalar dissipation rate transport in turbulent premixed flames: A direct numerical simulation analysis

The statistical behaviours of the instantaneous scalar dissipation rate Nc of reaction progress variable c in turbulent premixed flames have been analysed based on three-dimensional direct numerical simulation data of freely propagating statistically planar flame and V-flame configurations with different turbulent Reynolds number Ret. The statistical behaviours of N c and different terms of its transport equation for planar and V-flames are found to be qualitatively similar. The mean contribution of the density-variation term T1 is positive, whereas the molecular dissipation term (-D2) acts as a leading order sink. The mean contribution of the strain rate term T2 is predominantly negative for the cases considered here. The mean reaction rate contribution T3 is positive (negative) towards the unburned (burned) gas side of the flame, whereas the mean contribution of the diffusivity gradient term (D) assumes negative (positive) values towards the unburned (burned) gas side. The local statistical behaviours of Nc, T1, T2, T 3, (-D2), and f(D) have been analysed in terms of their marginal probability density functions (pdfs) and their joint pdfs with local tangential strain rate aT and curvature km. Detailed physical explanations have been provided for the observed behaviour. © 2014 Y. Gao et al.

Performance of low density parity check codes as a function of actual and assumed noise levels

We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. © 2004 Elsevier B.V.

Performance of low density parity check codes as a function of actual and assumed noise levels

We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. ©2003 Published by Elsevier Science B. V.

Auxiliary particle implementation of the probability hypothesis density filter

Optimal Bayesian multi-target filtering is, in general, computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), we present a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency. Numerical examples are presented for two scenarios, including a challenging nonlinear observation model.