Unsteady RANS and scale adaptive simulations of a turbulent spray flame in a swirled-stabilized gas turbine model combustor using tabulated chemistry
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Bibliographic record
Abstract
Purpose – The purpose of this paper is to numerically investigate the three-dimensional (3D) reacting turbulent two-phase flow field of a scaled swirl-stabilized gas turbine combustor using the commercial computational fluid dynamic (CFD) software ANSYS FLUENT. The first scope of the study aims to explicitly compare the predictive capabilities of two turbulence models namely Unsteady Reynolds Averaged Navier-Stokes and Scale Adaptive Simulation for a reasonable trade-off between accuracy of results and global computational cost when applied to simulate swirl-stabilized spray combustion. The second scope of the study is to couple chemical reactions to the turbulent flow using a realistic chemistry model and also to model the local chemical non-equilibrium(NEQ) effects caused by turbulent strain such as flame stretching. Design/methodology/approach – Standard Eulerian and Lagrangian formulations are used to describe both gaseous and liquid phases, respectively. The computing method includes a two-way coupling in which phase properties and spray source terms are interchanging between the two phases within each coupling time step. The fuel used is liquid jet-A1 which is injected in the form of a polydisperse spray and the droplet evaporation rate is calculated using the infinite conductivity model. One-component (n-decane) and two-component fuels (n-decane+toluene) are used as jet-A1 surrogates. The combustion model is based on the mean mixture fraction and its variance, and a presumed-probability density function is used to model turbulent-chemistry interactions. The instantaneous thermochemical state necessary for the chemistry tabulation is determined by using initially the equilibrium (EQ) assumption and thereafter, detailed NEQ calculations through the steady flamelets concept. The combustion chemistry of these surrogates is represented through a reduced chemical kinetic mechanism (CKM) comprising 1,045 reactions among 139 species, derived from the detailed jet-A1 surrogate model, JetSurf 2.0 using a sensitivity based method, Alternate Species Elimination. Findings – Numerical results of the gas velocity, the gas temperature and the species molar fractions are compared with their experimental counterparts obtained from a steady state flame available in the literature. It is observed that, SAS coupled to the tabulated flamelet-based chemistry, predicts reasonably the main flame trends, while URANS even provided with the same combustion model and computing resources, leads to a poor prediction of the global flame trends, emphasizing the asset of a proper resolution when simulating spray flames. Research limitations/implications – The steady flamelet model even coupled with a robust turbulence model does not reproduce accurately the trend of species with slow oxidation kinetics such as CO and H2, because of the restrictiveness of the solutions space of flamelet equations and the assumption of unity Lewis for all species. Practical implications – This work is adding a contribution for spray flame modeling and can be seen as an extension to the significant efforts for the modeling of gaseous flames using robust turbulence models coupled with the tabulated flamelet-based chemistry approach to considerably reduce computing cost. The exclusive use of a commercial CFD code widely used in the industry allows a direct application of this simulation approach to industrial configurations while keeping computing cost reasonable. Originality/value – This study is useful to engineers interested in designing combustors of gas turbines and others combustion systems fed with liquid fuels.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it