Bulletin of the American Physical Society
72nd Annual Meeting of the APS Division of Fluid Dynamics
Volume 64, Number 13
Saturday–Tuesday, November 23–26, 2019; Seattle, Washington
Session A06: Novel Techniques for Combustion Modeling |
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Chair: Eric Climent, Institut de Mecanique des Fluides de Toulouse Room: 205 |
Saturday, November 23, 2019 3:00PM - 3:13PM |
A06.00001: Simulation of combustion processes using the DSMC method Shrey Trivedi, R. Stewart Cant, John K. Harvey A novel molecular simulation technique, namely the Direct Simulation Monte Carlo (DSMC) method, is used to simulate hydrogen-air combustion. This method uses simulation particles that represent a set of real molecules. These simulation particles emulate the motion of real molecules and their properties can be averaged to evaluate the bulk flow properties. The Quantum-kinetic (QK) model, which uses total collision energy, molecular dissociation energy, quantized vibrational energy levels and the principle of molecular reversibility, is employed to account for the reactions. A distinct advantage of DSMC is that, because of the use of molecular level simulations, it avoids using continuum Arrhenius reaction rates and simplified gradient laws for the diffusivities of mass, momentum and heat. One-dimensional and two-dimensional hydrogen-air flames are simulated using a detailed 21-step chemical scheme and the validation of the properties of these flames is provided using the standard results in the literature. DSMC is suggested as an effective tool to provide the reaction rates and more importantly, the diffusivities for more complex, lesser known combustion schemes. [Preview Abstract] |
Saturday, November 23, 2019 3:13PM - 3:26PM |
A06.00002: Reduced order description of diffusion flames with inertial manifold theory Maryam Akram, Venkat Raman Resolving all dynamical scales in reacting turbulent flows with direct numerical simulation (DNS) is intractable even for simple fuels and geometries. Further, the complexity of engineering applications escalates the cost of DNS for their predictive analysis. Modeling is, therefore, inevitable to control such systems. Reacting turbulent flows are modeled mostly by methods developed for turbulence, where there is a forward cascade of energy, and statistical quantities of small scales are universal. While statistically stationary flows are modeled successfully with these methods, they fail to predict extreme events. A dynamical system approach can be more insightful on describing the small scale features. One such approach is based on the inertial manifold (IM) theory. The existence of IM has been proven for many dissipative systems. However, the theory does not provide an explicit form for the IM, and an approximation is necessary. The dynamical system is split into resolved and unresolved scales, where the information of the resolved scales approximates the small scales. The model has been tested on turbulent flows. In this work, the approximate IM is applied to diffusion flames in homogeneous isotropic turbulence. [Preview Abstract] |
Saturday, November 23, 2019 3:26PM - 3:39PM |
A06.00003: Numerical and Experimental Study of Piloted Liquid Spray Flames Dorrin Jarrahbashi, Yejun Wang, Salar Taghizadeh, Waruna Kulatilaka Liquid-fuel spray flames are the primary mode of energy conversion in many high-power-density practical combustion devices. A modified, flat-flame McKenna burner fitted with a direct-injection high-efficiency nebulizer is used to produce piloted liquid-methanol spray flames. A 3D computational model is developed which comprised of compressible continuous gas phase using URANS in conjunction with two-way coupled Eulerian-Lagrangian spray modeling approach along with a partially-stirred reactor combustion model. Model predictions of Hydroxyl (OH) and carbon monoxide (CO) in the radial and axial directions at different flame locations are compared with laser-based imaging measurements. OH profiles are obtained using nanosecond planar laser-induced fluorescence (PLIF) for characterizing the reaction zone and temperature, while 2D images of CO are obtained via two-photon laser-induced fluorescence (TPLIF) using femtosecond-duration laser pulses. The computational model predicts the general trends of OH, temperature and CO profiles well at certain heights above the burner surface. The sensitivity of the model to the droplet size distribution, pilot flame temperature, and the co-flow temperature are discussed. [Preview Abstract] |
Saturday, November 23, 2019 3:39PM - 3:52PM |
A06.00004: A novel deep learning framework for efficient parameterization of high-dimensional flamelet manifolds Opeoluwa Owoyele, Prithwish Kundu, Pinaki Pal Tabulated flamelet models are limited by the curse of dimensionality, wherein the computational memory required to store multidimensional flamelet lookup tables grows exponentially as the number of independent variables increases. In addition, it requires a vast increase in code complexity to perform interpolations in higher dimensions. One promising technique is to train an ANN \textit{apriori} based on the flamelet table, and use the trained model during run-time to obtain the species mass fractions as functions of the independent variables. Results from a previous study showed that training accuracy and inference speed can be improved if the multidimensional data set is bifurcated and separate ANNs are used for different regions. In this work, an \textit{apriori} study is performed using a physically meaningful divide-and-conquer approach, where an ensemble of deep neural networks is trained to represent the relevant physics in different regions of the flamelet manifold, as supervised by a gating network. The method is applied to 4-dimensional and 5-dimensional flamelet tables representing spray combustion in a constant volume chamber (ECN spray A) and a compression-ignition engine, respectively. The technique is demonstrated to result in a further decrease in the computational cost for a given accuracy. Moreover, the physical meaning of the obtained partitions is also discussed. [Preview Abstract] |
Saturday, November 23, 2019 3:52PM - 4:05PM |
A06.00005: Mass transfer coupled to chemical reaction through a random array of fixed porous particles Eric Climent, Mostafa Sulaiman, Abdelkader Hammouti, Anthony Wachs We have studied by means of numerical simulations the effect of a first order irreversible chemical reaction on mass transfer for two-phase flow systems in which the continuous phase is a fluid and the dispersed phase consists in catalyst spherical particles. The reactive solute is transported by the fluid flow and penetrates through the particle surface by diffusion. The chemical reaction takes place within the bulk of the particle. We handle the problem by coupling mass balance equations for internal-external transfers through the particle surface. We propose a model to predict mass transfer coefficient accounting for the external convection-diffusion along with internal diffusion-reaction. For the simulation of multi-particle systems, we have implemented a Sharp Interface Method to handle strong concentration gradients in DLM/FD framework. We validated the method thoroughly thanks to comparison with analytical solutions in case of diffusion, diffusion-reaction and by comparison with previously established correlations for convection-diffusion mass transfer. Finally, we study the configuration of a fixed bed of catalyst particles. We introduce a model that accounts for the solid volume fraction, in addition to the aforementioned effects and compare to numerical simulations. [Preview Abstract] |
Saturday, November 23, 2019 4:05PM - 4:18PM |
A06.00006: Quasi-static Eulerian framework for thermomechanical heterogeneous solid propellant simulations Tadbhagya Kumar, Thomas Jackson Heterogeneous solid propellants find prevalent use in space missions and thus underlying physics that influences their performance becomes critical to design. Numerical simulation of propellant combustion is complex owing to multiphysics nature with a burning surface that propagates through pyrolysis law. Of interest is to predict the thermomechanical stresses and strains that might lead to damage/failure of the constituent materials of the propellant under combustion. In this work, a Eulerian framework for thermomechanical simulations of propellant combustion using the hypoelastic equation is presented. A quasi-static projection method is motivated through scaling analysis and a finite element based weak form is employed to deal with material moduli differences. The simulations are carried out in two-dimensional propellant packs and results are presented for the temperature, stress, and their effect on propellant burn rate. [Preview Abstract] |
Saturday, November 23, 2019 4:18PM - 4:31PM |
A06.00007: A Novel Experiment-Based Framework for Turbulent Combustion Modeling Rishikesh Ranade, Tarek Echekki A novel framework for turbulent combustion modeling is presented. The framework is based on the construction of conditional means and joint scalar PDFs from multiscalar measurements in flames based on the parameterization of composition space using principal component analysis (PCA). The resulting principal components (PCs) act as both conditioning and transported variables. Their chemical source terms are constructed starting from instantaneous temperature and species measurements using a variant of the pairwise mixing stirred reactor (PMSR) approach. A multi-dimensional kernel density estimation (KDE) approach is used to construct the joint PDFs in PC space. The PDFs' dimension corresponds to the number of retained PCs that represent the composition space. Convolutions of these joint PDFs with conditional means provide measures of the unconditional means for the closure terms: the mean PCs chemical source terms and the density. The framework is demonstrated a priori and a posteriori using data from different flames. [Preview Abstract] |
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