Bulletin of the American Physical Society
76th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 19–21, 2023; Washington, DC
Session L40: Reacting Flows: General I 
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Chair: Hessam Babaee, University of Pittsburgh, Mechanical and Materials Science Room: 204C 
Monday, November 20, 2023 8:00AM  8:13AM 
L40.00001: Experimental evidence of the multiplicity of stationary solutions in ultralean hydrogen flames Daniel MartínezRuiz, Rubén PalomequeSantiago, Alba DomínguezGonzález, Mariano RubioRubio, Eduardo FernándezTarrazo, Mario SánchezSanz The morphology and propagation speed of premixed flames are mainly controlled by the fuelair concentration and by the environmental conditions (temperature, pressure and geometry). Changes in these parameters induce large variations of the flame shape and speed compared to the theoretical planar construct. As shown in recent numerical simulations, very lean hydrogen flames in narrow confined geometries can form either circular or doublecell isolated flames propagating at different velocities under the same controlling parameters. In this work, we show numerical and experimental evidences of this multiplicity of flame solutions and, using the equivalence ratio φ as the controlling parameter, we determine the critical values of φ that define the flame characteristics in a bifurcation diagram. 
Monday, November 20, 2023 8:13AM  8:26AM 
L40.00002: Extinction behavior of counterflow premixed flames with heterogeneous inlet composition Fuga Sato, Xinyu Zhao Onedimensional premixed laminar counterflow flames with heterogeneous inlet composition are investigated numerically for methane/air and Jet A/air mixtures. Different mass flow rates and equivalence ratios into the two opposing nozzles are prescribed such that identical total mass flow rates of air and fuel and total mass flow rates of fuel are maintained across different cases. The effects of heterogeneous inlet compositions on the extinction behavior are then discussed for various sets of inlet equivalence ratio. Budget analysis and chemical explosive mode analysis are employed to understand flame dynamics and to identify the major species contributing to the diffusion. It has been found that heterogeneous inlets can increase the extinction limit due to the back support from the opposing flame. Finally, insights obtained from the onedimensional counterflow flames are utilized to construct a simple model to mimic the extinction behavior and to enable parametric studies. 
Monday, November 20, 2023 8:26AM  8:39AM 
L40.00003: Periodic ignition phenomena in flames approaching lean blow off Tong Su, Samuel M Wiseman, James R Dawson, Nicholas A Worth A periodic ignition phenomena in a premixed bluffbody stabilized flame approaching lean blowoff was investigated experimentally. Simultaneous highspeed PIV and OHPLIF or OH*chemiluminescence have been employed to obtain timeaveraged and timeresolved flame images and flow fields, in which OH* intensities, velocity profiles and other turbulent flow characteristics can be obtained. The lean blowoff (LBO) limits are measured and compared using both methane and decomposed ammonia fuel blends with different ammonia volume fractions in both a long and short enclosure geometry. Flames in the long enclosures have wider LBO limits which may be related to changes in heat loss. Furthermore, for NH_{3}/H_{2}/N_{2} fuel blends, the higher the percentage of H_{2}, the wider the LBO limits. The near lean blowoff oscillation behavior only happens in the long enclosure fueled with both CH_{4} and NH_{3}/H_{2}/N_{2} blends. The oscillation frequency has a linear relationship with the bulk velocity and the Strouhal number range in this study is 0.04 to 0.07, which indicates the oscillation might be related to the jet precession behavior near lean blowoff. The global oscillation behavior will be presented, with a focus on the jet flow deflection, which can lead to the occurrence of alternative asynchronous flame pockets on the left and right hand sides of the enclosure. 
Monday, November 20, 2023 8:39AM  8:52AM 
L40.00004: Evolution of the soot particle size distribution in a turbulent nonpremixed bluff body flame Hernando Maldonado Colmán, Michael E Mueller The new Bivariate MultiMoment Sectional Method (BMMSM) has recently shown its potential of tracking the evolution of the soot size distribution in Large Eddy Simulation (LES) of a turbulent nonpremixed jet flame. BMMSM characterizes the soot size distribution by considering soot sections and three volumesurface moments per section, which accounts for soot's fractal aggregate morphology. BMMSM is as accurate as but requires fewer degrees of freedom compared to traditional sectional methods. In this work, BMMSM is used to investigate the evolution of the soot size distribution in a turbulent nonpremixed bluff body flame, which is characterized by very different timetemperaturecomposition histories compared to a jet flame. Global soot quantities are first validated against experiments and compared against previous computations using a moment method. The evolution of the soot distribution is then analyzed in detail and used to reveal the underlying mechanisms. Additionally, computational considerations of BMMSM will be discussed. 
Monday, November 20, 2023 8:52AM  9:05AM 
L40.00005: On the role of droplet clusters in spray combustion Philipp Weiss, Daniel W Meyer, Patrick Jenny Spray combustion is central, e.g., in internal combustion engines and gas turbines for aviation or power production. To improve the efficiency and lower emissions, we need to better understand the complex interactions of the turbulent carrier gas and the inertial fuel droplets. Since droplet Stokes numbers are typically around one or greater, droplets are centrifuged away from vortex centers and cluster in highstrain regions. While the combustion of fuel droplets has been extensively studied, the impact of clustering has received comparably little attention. In this contribution, we present a systematic direct numerical simulation study of decane droplets that evaporate and burn in turbulent air. To account for the shear flow in real systems, we opted for a planar mixing layer configuration involving a cold central spray jet that is surrounded by two hot stagnant air layers. To arrive at a canonical setup, the boundaries were chosen to be periodic in all three spatial directions. By varying the central jet velocity, the carrier gas Reynolds number could be changed. Moreover, we examined the impact of the droplet loading and Stokes number, where the later controls the clustering of the monodisperse droplets. Depending on the selected parameters, a distinct diffusion flame separates from the spray, which in turn is composed of droplet clusters that are each surrounded by a premixed flame. Large droplets, however, move individually and also tend to burn individually with diffusion flames in their vicinity. 
Monday, November 20, 2023 9:05AM  9:18AM 
L40.00006: LES of biodiesel spray flames using a costeffective Flamelet Generated Manifold methodology Alice Ponet, Miltiadis V Papalexandris

Monday, November 20, 2023 9:18AM  9:31AM 
L40.00007: LowRank Approximation of Filter Density Function Using TimeDependent Bases Aidyn Aitzhan, Peyman Givi, Hessam Babaee A new lowrank approximation based on timedependent bases is developed for reducedorder modeling (ROM) of the scalar filtered density function (FDF). The ROM is based on a unified residualminimization technique and is shown to be superior to conventional PCAbased schemes. This is due to the inherent flexibility of the method in allowing the temporal evolution of its subspace. The resulting model is employed in LESFDF of a nonpremixed CO/H_2 flame in a temporally evolving jet. For combustion chemistry, the syngas model involving 11 species is used. The results are appraised via a posteriori comparisons against data generated via fullrank LESFDF and DNS of the same flame. The model yields excellent predictions of various statistics of the filtered thermochemistry variables. 
Monday, November 20, 2023 9:31AM  9:44AM 
L40.00008: A PhysicsConstrained Neural Ordinary Differential Equations approach for Robust DataDriven Modeling of Chemical Kinetics Tadbhagya Kumar, Pinaki Pal, Anuj Kumar The computational cost of solving for detailed chemistry is one of the major bottlenecks for predictive CFD modeling of turbulent reacting flows. Deep learning approaches have been explored to develop surrogate models for stiff chemical source terms, but are often unstable when coupled with CFD solvers. This is because these techniques minimize the error during training without guaranteeing successful integration with ODE solvers, resulting in undesirable error accumulation over time. In this regard, Owoyele and Pal (Energy & AI, 2021) proposed, for the first time, a robust deep learning approach based on neural ordinary differential equations (NODE), known as ChemNODE, wherein the chemical source terms predicted by the neural networks are integrated during training, and by computing the required derivatives, the neural network weights are adjusted accordingly to minimize the difference between the predicted and groundtruth solution. In this work, the framework is extended to incorporate constraint terms in the loss function (during training) to explicitly enforce element/species mass conservation. Further, the ChemNODE framework is integrated with CONVERGE CFD solver and validation studies are performed for constant pressure homogeneous autoignition of hydrogenair mixtures over a range of composition and thermodynamic conditions. It is shown that incorporation of physicsinformed constrains enhances the robustness and accuracy of ChemNODE. 
Monday, November 20, 2023 9:44AM  9:57AM 
L40.00009: Skeletal Reaction Models for Gasoline Surrogate Combustion Yinmin Liu, Hessam Babaee, Peyman Givi, Harsha Chelliah, Daniel Livescu, Arash G Nouri Skeletal reaction models are derived for a gasoline surrogate model using a localsensitivityanalysis based technique. In this technique, the sensitivities of species mass fractions and temperature with respect to reaction rates are estimated using the sparse forcedoptimally time dependent (sfOTD) method. In sfOTD, the sensitivity matrix is projected onto a lowrank dynamic basis and integrated over time within this lowrank subspace. The sfOTD is augmented with a sparsesampling technique termed the discrete empirical interpolation method (DEIM). This method selects dynamically relevant species and reactions at each time step to update their associated sensitivities, thereby enhancing the computational efficiency and the robustness of the sfOTD. The accuracy and the computational cost of the sfOTD method are assessed by comparisons against the solution of the exact sensitivity equations. A series of reduced models are developed based on the Lawrence Livermore National Lab's gasoline surrogate model with 1389 species and 9603 reactions. Their performances are compared against the detailed model's predictions of ignition delay and flame speed. The results show that reduced models with 500 and more species are able to reproduce the detailed mechanism's prediction within 15% relative errors for a large range of pressures, temperatures, and equivalence ratios. 
Monday, November 20, 2023 9:57AM  10:10AM 
L40.00010: Abstract Withdrawn

Monday, November 20, 2023 10:10AM  10:23AM Author not Attending 
L40.00011: Abstract Withdrawn 
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