A mixture-fraction-based hybrid binomial Langevin-multiple mapping conditioning model
| Autor: | Andrew P. Wandel, R. Peter Lindstedt |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Technology
Engineering Chemical Turbulent combustion Energy & Fuels General Chemical Engineering TURBULENT FLAME Scalar (mathematics) 0904 Chemical Engineering FINITE RATE CHEMISTRY Probability density function 0902 Automotive Engineering LIMIT PROBABILITY DENSITY-FUNCTION Engineering Statistical physics Physical and Theoretical Chemistry MMC Physical quantity Mathematics Langevin models REIGNITION Curl (mathematics) Science & Technology Multiple Mapping Conditioning LARGE-EDDY SIMULATION Turbulence Mechanical Engineering Engineering Mechanical EXTINCTION Mixture fraction Lifted flame Physical Sciences CLOSURE Thermodynamics Conditioning 0913 Mechanical Engineering Large eddy simulation |
| Zdroj: | Proceedings of the Combustion Institute. 37:2151-2158 |
| ISSN: | 1540-7489 |
| DOI: | 10.1016/j.proci.2018.06.122 |
| Popis: | Generalized Multiple Mapping Conditioning (MMC) allows for the use of any physical quantity to represent the required reference variable provided that it delivers the desired behavior. The binomial Langevin model (BLM) has been shown to predict higher statistical moments with good accuracy. However, joint-scalar modeling for many scalars becomes problematic because scalar bounds must be specified as conditional on other scalars to preserve elemental balances. The resulting volumes in state space become exceptionally complex for realistic problem sizes. In the current work, this central difficulty is avoided by using only velocity and mixture fraction statistics from the BLM with the latter used as the MMC reference variable. The principal advantage of this method is that the implementation of the binomial Langevin mixture fraction is relatively straightforward and provides a direct physical link to MMC. The MMC model is closed using an augmented modified Curl’s model where the selection of particle pairs for (turbulent) mixing ensures proximity in reference space and a corresponding closeness in physical space. The method is evaluated for a lifted methane jet flame undergoing auto-ignition in a vitiated coflow. Most of the major features of the flow are well reproduced and found to generally outperform other modeling approaches, including Large Eddy Simulations using simplified treatments of turbulence–chemistry interactions such as unsteady flamelet/progress variable descriptions. |
| Databáze: | OpenAIRE |
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