Abstract
Humans have an insatiable desire to model physical phenomena and to continuously improve those models, be it modeling weather patterns for forecasting, molecular modeling in pharmaceutical research, or even biscuits baking in an oven.1 Of particular interest, especially given the nature of this book, is the modeling of combustion and combustion systems. Modeling of combustion comes in many forms, ranging from simple stoichiometry of global reactions, to detailed kinetic modeling of elementary reactions in a combustion mechanism, to one-dimensional reactor models, to full-blown transient three-dimensional models using Computational Fluid Dynamics (CFD).
Introduction
Humans have an insatiable desire to model physical phenomena and to continuously improve those models, be it modeling weather patterns for forecasting, molecular modeling in pharmaceutical research, or even biscuits baking in an oven.1 Of particular interest, especially given the nature of this book, is the modeling of combustion and combustion systems. Modeling of combustion comes in many forms, ranging from simple stoichiometry of global reactions, to detailed kinetic modeling of elementary reactions in a combustion mechanism, to one-dimensional reactor models, to full-blown transient three-dimensional models using Computational Fluid Dynamics (CFD).
CFD is an area of fluid mechanics that deals with the computer simulation of fluid flow, heat transfer, combustion, etc. CFD is rooted in solving the fundamental governing equations for continuity, momentum, and energy. The volume of interest is discretized into a finite number of volume elements called cells. A single model may have many millions, or even billions, of cells. Appropriate models for turbulence, combustion, radiation, etc. are selected. The knowledge of which particular models are most applicable for a given simulation is a skill acquired through both schooling and experience running CFD simulations. Boundary conditions are then applied to the various boundaries in the model. Then the governing equations in each cell are solved. This is the most computationally intensive task, as all of the equations are coupled to each other in a complicated and nonlinear fashion. Even mid-sized steady-state models, with 20–30 million cells, can take several days on a large computing cluster to solve. If, instead of running the models on a computing cluster, they were run on a single desktop, these models could take more than a year to solve! For larger models and/or transient models (time varying), the computational requirements are even larger, often requiring tens of thousands or even hundreds of thousands of core-hours to solve.
CFD simulations are increasingly becoming a mainstay in the analysis of combustion systems, both in academic/research settings as well as industrial settings. Combustion CFD simulations allow for deeper insight into systems – solving for velocity, temperature, pressure, and species concentrations everywhere in the volume instead of just at a few probe points with experimental apparatus. Additionally, it allows for full-scale simulation of equipment, where full-scale testing is typically prohibitively expensive and challenging (if possible at all). Finally, because combustion CFD simulations predict variables in all locations, it allows for the prediction of quantities that cannot be measured in an experimental apparatus (e.g., vorticity).
The following images demonstrate a variety of applications of combustion CFD simulations from a diverse set of contributors. The images correspond loosely to the following categories (in order): gas turbines, burners in isolation, rocket engines, industrial applications of combustion, emissions reduction, and explosions.
2.1 LES Simulation of a Gas Turbine Combustor
Transient LES simulation of turbulent combustion in a steadily burning annular gas turbine combustor, using Simcenter STAR-CCM+ from Siemens. The combustion chamber is 16.5 cm long with a height of 6 cm. The simulation is run for one sector and visually duplicated through a periodic transform. The sector is discretized using a 316,000-cell polyhedral mesh. An inlet mass flow of air at 500 K is provided through the plenum inlet, whereof a portion is reaching the combustion chamber through swirler and dilution holes, at velocities of around 100 m/s. The swirler walls and dilution holes are visualized in the illustration. JP10 is injected at 300 K at a mass flow rate of 1 g/s in the center of the swirler using a lagrangian injector. The LES WALE turbulence model is used and the mass averaged Reynolds number is 5 × 104. The Flamelet Generated Manifold combustion model is applied with FGM Kinetic Rate for flame propagation. The blue field visualizes areas with high fuel concentration, where the fuel–air mixture fraction is higher than 0.18. The flame front is visualized through volume rendering, highlighting areas where the combustion progress variable lies between 0.93 and 0.96. The redder the color, the higher the progress variable.
2.2 Annular Burner Ignition
This image shows an instantaneous view of the propagating flame in the annular burner experimentally studied in Ref 1. A 0.74 equivalence ratio mixture of propane and air is injected at ambient temperature and pressure through 16 swirled injectors (swirl number 0.82). Results are analyzed in detail in Ref 2.
The authors would like to acknowledge PRACE for awarding access to computing resource of TGCC (France).
2.3 Numerical Simulation of a Spray
The atmospheric swirled spray flame corresponds to the experimental setup of Ref 1. The image is a visualization of the fuel droplets and the flame surface.
The liquid fuel is n-heptane, injected at a mass flow rate of 0.12 g/s and at ambient pressure and temperature. The global equivalence ratio of the burner is 0.17.
The resulting flame has a complex, partially premixed structure. In addition, a non-negligible part of droplets is able to cross the flame front and ignite in the burnt gas to form individually burning droplets.
The support of SAFRAN is acknowledged.
2.4 Flame Ignition and Propagation in Aeronautical Swirled Multi-burners
The experimental configuration was designed by CORIA in the context of the European project KIAI (Knowledge for Ignition, Acoustics and Instabilities – 7th Framework Program – 2009/2013). The setup allows to vary the separation distance between the burners. Methane and air mass flow rates are, respectively, 0.192 g/s and 5 g/s for each individual injector, leading to a global equivalence ratio of 0.66. The radial swirler is composed of 18 vanes inclined at 45°, leading to a swirl number of 0.76. The burner operates at ambient conditions. The images show a visualization of the flame surface from a side view (top image) and top view (bottom image). Results show the importance of burner spacing on the ignition sequence and the partially premixed flame structure.
The research leading to these results has received funding from the European Community’s 7th Framework Program (FP7/2007–2013) under Grant Agreement No. ACP8-GA-2009-234009. This work was granted access to the HPC resources of [CCRT/IDRIS] under the allocation 2013-x20132b5031 made by GENCI (Grand Equipement National de Calcul Intensif). This research is also part of a 2013 INCITE award of the Department of Energy, and used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02–06CH11357.
