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Kolla, H.

Publications and source records attributed to Kolla, H..

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Topology of pocket formation in turbulent premixed flames

In turbulent premixed flame propagation, the formation of isolated pockets of reactants or products is associated with flame pinch–off events which cause rapid changes in the flame surface area. Previous topological analysis of these phenomena has been carried out based on Morse theory and Direct Numerical Simulation (DNS) in two spatial dimensions. The present work extends the topological analysis to three dimensions with emphasis on the formation and subsequent burnout of reactant pockets. Singular behaviour observed previously for terms of the Surface Density Function (SDF) transport equation in the two–dimensional case is shown to occur also in three dimensions. Further singular behaviour is observed in the displacement speed close to reactant pocket burnout. In conclusion, the theory is compared against DNS data from hydrogen–air flames and good agreement is obtained.

42 ENGINEERING↗
DOE OSTI2014

On velocity and reactive scalar spectra in turbulent premixed flames

Abstract Kinetic energy and reactive scalar spectra in turbulent premixed flames are studied from compressible three-dimensional direct numerical simulations (DNS) of a temporally evolving rectangular slot-jet premixed flame, a statistically one-dimensional configuration. The flames correlate to a lean premixed hydrogen–air mixture at an equivalence ratio of 0.7, preheated to 700 K and at 1 atm, and three DNS are considered with a fixed jet Reynolds number of 10 000 and a jet Damköhler number varying between 0.13 and 0.54. For the study of spectra, motivated by the need to account for density change, which can be locally strong in premixed flames, a new density-weighted definition for two-point velocity/scalar correlations is proposed. The density-weighted two-point correlation tensor retains the essential properties of its constant-density (incompressible) counterpart and recovers the density-weighted Reynolds stress tensor in the limit of zero separation. The density weighting also allows the derivation of balance equations for velocity and scalar spectrum functions in the wavenumber space that illuminate physics unique to combusting flows. Pressure–dilatation correlation is a source of kinetic energy at high wavenumbers and, analogously, reaction rate–scalar fluctuation correlation is a high-wavenumber source of scalar energy. These results are verified by the spectra constructed from the DNS data. The kinetic energy spectra show a distinct inertial range with a $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}-5/3$ scaling followed by a ‘diffusive–reactive’ range at higher wavenumbers. The exponential drop-off in this range shows a distinct inflection in the vicinity of the wavenumber corresponding to a laminar flame thickness, $\delta _L$ , and this is attributed to the contribution from the pressure–dilatation term in the energy balance in wavenumber space. Similarly, a clear spike in spectra of major reactant species (hydrogen) arising from the reaction-rate term is observed at wavenumbers close to $\delta _L$ . It appears that in the inertial range classical scaling laws for the spectra involving the Kolmogorov scale are applicable, but in the high-wavenumber range where chemical reactions have a strong signature the laminar flame thickness produces a better collapse. It is indicated that a full scaling should perhaps involve the Kolmogorov scale, laminar flame thickness, Damköhler number and Karlovitz number.

42 ENGINEERING↗
DOE OSTI2014

Fast Multiresolution Reads of Massive Simulation Datasets

Today’s massively parallel simulation codes can produce output ranging up to many terabytes of data. Utilizing this data to support scientific inquiry requires analysis and visualization, yet the sheer size of the data makes it cumbersome or impossible to read without computational resources similar to the original simulation. We identify two broad classes of problems for reading data and present effective solutions for both. The first class of data reads depends on user requirements and available resources. Tasks such as visualization and user-guided analysis may be accomplished using only a subset of variables with a restricted spatial extent at a reduced resolution. The other class of reads requires full resolution multivariate data to be loaded, for example to restart a simulation. We show that utilizing the hierarchical multiresolution IDX data format enables scalable and efficient serial and parallel read access on a variety of hardware from supercomputers down to portable devices. Here, we demonstrate interactive view-dependent visualization and analysis of massive scientific datasets using low-power commodity hardware, and we compare read performance with other parallel file formats for both full and partial resolution data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Determination of three-dimensional quantities related to scalar dissipation rate and its transport from two-dimensional measurements: Direct Numerical Simulation based validation

Three-dimensional compressible Direct Numerical Simulation (DNS) data of freely propagating statistically planar and statistically stationary slot-jet turbulent premixed flames has been used to assess the accuracy of the isotropy-derived correction factors, which relate the two-dimensional projections of the different terms of the Favre-averaged scalar dissipation rate transport equation with their corresponding actual three-dimensional counterparts. The accuracy of these correction factors is assessed using both simplified and detailed chemistry-based DNS data, for a range of values of Karlovitz number Ka, heat release parameter tau, and turbulent Reynolds number Re-t. It is shown that the isotropic distribution of the probability density function (pdf) of the angle, phi, between the normal vectors of the measurement plane and of the flame surface provides a simple algebraic relation between the scalar dissipation rates evaluated in two and three dimensions (i.e. (N) over tilde (c) and (N) over tilde (2D)(c)), independent of the considered values of Ka, tau and Re-t. The isotropic relations between two-dimensional and three-dimensional counterparts of the curvature and propagation terms in the transport equation of (N) over tilde (c) are also found to work well for all the values of Ka, tau and Re-t considered here. However, the relation between the value obtained from two-dimensional projection and the true three-dimensional value for the strain rate term in the (N) over tilde (c) transport equation works well only for large values of Re-t and the reasons for this behaviour are explained in detail. It is found that the threshold value of Ret above which the assumption of isotropy yields an accurate relation between two-dimensional projection and three-dimensional values for the strain rate term of the dissipation rate transport equation depends on the regime of the prevailing combustion process.

Energy & Fuels↗
DOE OSTI2012

Combining In-situ and In-transit Processing to Enable Extreme-Scale Scientific Analysis

With the onset of extreme-scale computing, I/O constraints make it increasingly difficult for scientists to save a sufficient amount of raw simulation data to persistent storage. One potential solution is to change the data analysis pipeline from a post-process centric to a concurrent approach based on either in-situ or in-transit processing. In this context computations are considered in-situ if they utilize the primary compute resources, while in-transit processing refers to offloading computations toa set of secondary resources using asynchronous data transfers. In this paper we explore the design and implementation of three common analysis techniques typically performed on large-scale scientific simulations: topological analysis, descriptive statistics, and visualization. We summarize algorithmic developments, describe a resource scheduling system to coordinate the execution ofvarious analysis workflows, and discuss our implementation using the DataSpaces and ADIOS frameworks that support efficient data movement between in-situ and in-transit computations. Wedemonstrate the efficiency of our lightweight, flexible framework by deploying it on the Jaguar XK6 to analyze data generated by S3D, a massively parallel turbulent combustion code. Our framework allows scientists dealing with the data deluge at extreme scale to perform analyses at increased temporal resolutions, mitigate I/O costs, and significantly improve the time to insight.

Bennett, Janine C.↗
DOE OSTI2012

On the use of graph search techniques for the analysis of extreme-scale combustion simulation data

With the continuous increase in high performance computing capabilities, simulations are becoming ever larger and more complex, using bigger domains, tracking more variables, and producing more time steps. This increase in the ranges of spatial and temporal simulation scales results in data that presents significant challenges to as well as new opportunities for the visualization and data analysis community. For example, highly-localized, intermittent events (such as the formation of ignition kernels in turbulent combustion) may be caused by interactions between multiple variables across a series of time steps, making both their definition and their extraction difficult, particularly at scale. This paper introduces an intuitive framework to support the identification, characterization, and tracking of such complex, multivariate, temporally evolving events in large-scale simulations. In a pre-processing step, we use topological techniques to create a hierarchical family of feature definitions for each variable of interest. Subsequently, we select a particular set of features for analysis and, using overlap-based metrics, we generate an attributed relational graph (ARG) capturing the relationships between different variables both within one and across multiple time steps. Finally, we leverage subgraph-isomorphism search heuristics to identify patterns in the ARG that characterize interesting events. We demonstrate the power of this approach by analyzing a large-scale turbulent combustion simulation.

McLendon, W. C.↗