Filtered density function simulation of a realistic swirled combustor

Ansari, Naseem; Strakey, Peter; Goldin, Graham M.; Givi, Peyman

doi:10.1016/j.proci.2014.05.042

Cited by 26 publications

(7 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A widely studied test case providing a solid basis for the validation of LES combustion models is the PRECCINSTA (Prediction and Control of Combustion Instabilities in Industrial Gas Turbines) burner. This gas turbine model combustor was experimentally investigated (e.g., [7][8][9][10][11][12]) and has been the focus of a number of computational simulations in the past (e.g., [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]). Comparisons between experiments and LES were first reported by Galpin et al [14] whose simulations predicted a higher burning rate -manifesting itself in a shortened flame length -and overestimated temperatures in the outer recirculation zone (ORZ).…”

Section: Introductionmentioning

confidence: 99%

The stochastic fields method applied to a partially premixed swirl flame with wall heat transfer

Fredrich

Jones

Marquis

2019

Combustion and Flame

View full text Add to dashboard Cite

Large eddy simulations of a partially premixed flame are performed with the purpose of predicting the reacting flow in a swirl-stabilised, low emissions industrial gas turbine combustor. The corresponding sub-grid scale turbulence-chemistry interactions are modelled using a probability density function transport equation, which is solved by the stochastic fields method. A 15-step reduced, but accurate, methane mechanism including 19 species is employed for the description of all chemical reactions. The test case involves a combustor with complex geometry and simulations are carried out for two different combustor operating conditions. Overall, results of the velocity, temperature and species mass fractions (including carbon monoxide) as well as the instantaneous thermochemical properties are shown to be in good agreement with experimental data, demonstrating the capabilities of the applied stochastic fields method. The inclusion of wall heat transfer in the combustion chamber is found to improve temperature and species predictions, especially in the near-wall regions. Comparisons between an oscillating and a 'stable' flame case furthermore highlight the influence of experimentally observed thermo-acoustic instabilities on the scalar fluctuations near the combustor centreline. None of the default model parameters were adjusted and the results showcase the accuracy and flexibility of the present large eddy simulation method for an application to complex, partially premixed combustion problems; this being particularly important for the designers of new generation low emission gas turbine combustors.

show abstract

Section: Introductionmentioning

confidence: 99%

The stochastic fields method applied to a partially premixed swirl flame with wall heat transfer

Fredrich

Jones

Marquis

2019

Combustion and Flame

View full text Add to dashboard Cite

show abstract

“…Further analysis was carried out by Franzelli et al [8] with the same setup and combustion model, but with focus on the evaluation of different reduced kinetics. Ansari et al [6] used this test case in non-premixed conditions for validation of a combustion model based on the Scalar Filtered Mass Density Function (SFMDF) methodology [6]. To the authors knowledge, non-premixed modeling attempts of the current test case using a turbulent combustion model based on tabulated chemistry have not been reported in literature yet.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Partial Premixing and Heat Loss on the Reacting Flow Field Prediction of a Swirl Stabilized Gas Turbine Model Combustor

Gövert

Mira

Kok

et al. 2017

Flow Turbulence Combust

View full text Add to dashboard Cite

This work addresses the prediction of the reacting flow field in a swirl stabilized gas turbine model combustor using large-eddy simulation. The modeling of the combustion chemistry is based on laminar premixed flamelets and the effect of turbulence-chemistry interaction is considered by a presumed shape probability density function. The prediction capabilities of the presented combustion model for perfectly premixed and partially premixed conditions are demonstrated. The effect of partial premixing for the prediction of the reacting flow field is assessed by comparison of a perfectly premixed and partially premixed simulation. Even though significant mixture fraction fluctuations are observed, only small impact of the non-perfect premixing is found on the flow field and flame dynamics. Subsequently, the effect of heat loss to the walls is assessed assuming perfectly premixing. The adiabatic baseline case is compared to heat loss simulations with adiabatic and non-adiabatic chemistry tabulation. The results highlight the importance of considering the effect of heat loss on the chemical kinetics for an accurate prediction of the flow features. Both heat loss simulations significantly improve the temperature prediction, but the non-adiabatic chemistry tabulation is required to accurately capture the chemical composition in the reacting layers.

show abstract

“…This example has substantial applications in practical engineering combustion systems. In the near future, it is expected that the current classical turbulent combustion simulations [49,50], exemplified by Fig. 5 can benefit from quantum speed-up.…”

Section: B Quantum Computing For Combustionmentioning

confidence: 99%

Computational Turbulent Combustion in the Age of Artificial Intelligence and Quantum Information

Givi¹

2021

ijmph

View full text Add to dashboard Cite

The impact of high-performance computing on the society has been enormous, but it is easy to be taken for granted. In today's world, it is virtually impossible to imagine system design or major decision making not aided via predictive modeling and simulation. Now that we are experiencing the Data Revolution and the emergence of the Second Quantum Revolution, it is wise to consider both of these elements in computational science and engineering. Data-driven modeling approaches and demonstrated speed-ups of quantum algorithms have the potential to transform scientific discovery. This will affect the fabrics of industrialized societies in diverse disciplines. A research arena which can substantially benefit from these technologies is combustion. This field has been the subject of heavy computational research for many decades now. In this review, some examples taken from the previous works of the author are presented to demonstrate how the field of computational turbulent combustion is benefiting from modern developments in machine learning (ML) and quantum computing (QC).

show abstract

Filtered density function simulation of a realistic swirled combustor

Cited by 26 publications

References 30 publications

The stochastic fields method applied to a partially premixed swirl flame with wall heat transfer

The stochastic fields method applied to a partially premixed swirl flame with wall heat transfer

The Effect of Partial Premixing and Heat Loss on the Reacting Flow Field Prediction of a Swirl Stabilized Gas Turbine Model Combustor

Computational Turbulent Combustion in the Age of Artificial Intelligence and Quantum Information

Contact Info

Product

Resources

About