# Validating Confined Flame Noise Simulation Using External Sensor

^{1}

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Experimental Methods

_{4}and air into a burner (Figure 1) which was placed in confined space. The diagram of the setup is shown in Figure 2, and photographs of the experiment are shown in Figure 3. An external sensor (model UMIK-1 USB measurement-calibrated microphone) and a sound pressure level (SPL) meter (model Larson Davis 831) were placed a distance $\overrightarrow{r}=$ (3, 3, 6) inches from the center line of the outlet plane. The placement of the sensor can affect the amplitude of the measurements, particularly at the lower frequencies that are produced by combustion. The microphone must be placed in the far-field for its position which is accurately measured to be modeled with the acoustic analogy. The microphone was connected to the computer, and it simultaneously recorded the sound and measured the SPL spectrum using the REW software [17]. The SPL meter recorded the internal memory, then, the recorded data were transferred to the computer.

_{2}was used to purge the system post-combustion to remove any combustible gases from the setup and for calibrating the Bronkhorst mass flow controllers: 10 L/min for the air and 1 L/min for the CH

_{4}. The mass flow controllers were pre-loaded with the capability for measuring the liter per minute of air and CH

_{4}. The lean mixture was delivered with an air-to-fuel equivalence ratio $\mathsf{\lambda}$ = 1.05 at a flow rate of 7.7 L/min. The burner was placed in a (1.5 × 2.5 × 0.25) inch square pipe that was made from stainless steel 304 with rounded corners. The viewing chamber was aluminum with quartz windows. A digital single reflex lens (DSLR) camera was placed to record video and photos of the flame. The area from the base of the viewing chamber to the outlet of the square pipe was 27.5 inches. The burner outlet was a standard Bunsen burner design with a stabilizer, and it was positioned 7 inches from the bottom of the experimental duct.

## 3. Computational Methods

#### 3.1. Burner Geometry and Computation Grid

#### 3.2. Simulation Settings

^{−10}to resolve the small pressure perturbations, but not to slow down the simulation too greatly. The time step was set to 10 $\mathsf{\mu}\mathrm{s}$ to ensure stability and to reduce the computational time.

^{+}for the burner interior was consistently less than 5, with there being a maximum of 6.8. The y

^{+}for the burner exterior and pipe wall was less than 1 for all of the cells. A compressible wall function was utilized to calculate the thermal diffusivity based on the turbulent viscosity and turbulent Prandtl number.

^{−6}, and the kinetic energy and turbulent dissipation can be estimated from the burner geometry, and with these the mixing constant was estimated, ${C}_{mix}\approx $ 0.1.

## 4. Results and Discussion

#### 4.1. Flow Visualization

#### 4.2. Noise Results

## 5. Concluding Remarks

## Author Contributions

## Funding

## Institutional Review Board Statement

## Conflicts of Interest

## Nomenclature

${C}_{mix}$ | PaSR model mixing coefficient |

$k$ | Turbulent kinetic energy |

$\overrightarrow{r}$ | Distance vector |

$\dot{V}$ | Volumetric flow rate |

${y}^{+}$ | Dimensionless wall distance |

${\alpha}_{t}$ | Thermal diffusivity |

$\u03f5$ | Turbulent dissipation |

$\lambda $ | Fuel Equivalence Ratio |

${\nu}_{t}$ | Turbulent viscosity |

## References

- Strahle, W.C. Combustion noise. Prog. Energy Combust. Sci.
**1978**, 4, 157–176. [Google Scholar] [CrossRef] - Pillai, A.L.; Inoue, S.; Shoji, T.; Tachibana, S.; Yokomori, T.; Kurose, R. Investigation of combustion noise generated by an open lean-premixed H
_{2}/air low-swirl flame using the hybrid LES/APE-RF framework. Combust. Flame**2022**, 245, 112360. [Google Scholar] [CrossRef] - Zheng, K.; Zhu, M.; Zheng, X.; Song, S.; Xu, H. Research on the sharpness of combustion noise of three-cylinder GDI engine based on adaptive cyclic Wiener filter method. AIP Adv.
**2022**, 12, 025320. [Google Scholar] [CrossRef] - Hameed, N.A.; Kurien, C.; Jaychandra, R.K.; Mittal, M. Effect of biomethane substitution on combustion noise and performance of a dual fuel common rail direct injection diesel engine. Environ. Prog. Sustain. Energy
**2022**, e13915. [Google Scholar] [CrossRef] - d’Ambrosio, S.S.; Ferrari, A.; Jin, Z. Time-frequency analysis application to the evaluation of instantaneous combustion noise. Fuel
**2022**, 312, 122655. [Google Scholar] [CrossRef] - Zandie, M.; Ng, H.K.; Gan, S.; Said, M.F.M.; Cheng, X. Review of the advances in integrated chemical kinetics-computational fluid dynamics combustion modelling studies of gasoline-biodiesel mixtures. Transp. Eng.
**2022**, 7, 100102. [Google Scholar] [CrossRef] - Dowling, P.; Mahmoudi, Y. Combustion noise. Proc. Combust. Inst.
**2015**, 35, 65–100. [Google Scholar] [CrossRef] [Green Version] - Ihme, M. Combustion and engine-core noise. Annu. Rev. Fluid Mech.
**2017**, 49, 277–310. [Google Scholar] [CrossRef] - Tam, K.; Bake, F.; Hultgren, L.S.; Poinsot, T. Combustion noise: Modeling and prediction. CEAS Aeronaut. J.
**2019**, 10, 101–122. [Google Scholar] [CrossRef] [Green Version] - Candel, S.; Durox, D.; Ducruix, S.; Birbaud, A.-L.; Noiray, N.; Schuller, T. Flame Dynamics and combustion noise: Progress and challenges. Int. J. Aeroacoustics
**2009**, 8, 1–56. [Google Scholar] [CrossRef] - Huet, M.; Geiger, L. Modeling of indirect combustion noise through a stator. J. Sound Vib.
**2022**, 540, 117296. [Google Scholar] [CrossRef] - Tam, K.W. Computational aeroacoustics: An overview of computational challenges and applications. Int. J. Comput. Fluid Dyn.
**2004**, 18, 547–567. [Google Scholar] [CrossRef] - Wang, M.; Freund, J.B.; Lele, S.K. Computational prediction of flow-generated sound. Annu. Rev. Fluid Mech.
**2006**, 38, 483–512. [Google Scholar] [CrossRef] [Green Version] - Lighthill, M.J. On sound generated aerodynamically I. General theory. Proc. R. Soc. London. Ser. A. Math. Phys. Sci.
**1952**, 211, 564–587. [Google Scholar] - Lighthill, M.J. On sound generated aerodynamically II. turbulence as a source of sound. Proc. R. Soc. London. Ser. A. Math. Phys. Sci.
**1954**, 222, 1–32. [Google Scholar] - Freidhager, C.; Maurerlehner, P.; Roppert, K.; Heinisch, M.; Renz, A.; Schoder, S.; Kaltenbacher, M. Predicting Spatial Distributions of Lighthill’s Aeroacoustic Source Terms Using Steady-State RANS Simulations in Turbocharger Compressors. J. Aerosp. Eng.
**2022**, 35, 04021101. [Google Scholar] [CrossRef] - Mulcahy, J. REW Room Acoustics and Audio Device Measurement and Analysis Software. Room EQ Wizard Room Acoustics Software. Available online: https://www.roomeqwizard.com/ (accessed on 10 April 2022).
- Weller, G.H.G.; Tabor, H.; Jasak, C.; Fureby, A. tensorial approach to computational continuum mechanics using object-oriented techniques. Comput. Phys.
**1998**, 12, 6. [Google Scholar] [CrossRef] - OpenFOAM. Available online: https://www.openfoam.com/ (accessed on 7 April 2022).
- Epikhin, A.; Evdokimov, I.; Kraposhin, M.; Kalugin, M.; Strijhak, S. Development of a dynamic library for computational aeroacoustics applications using the OpenFOAM Open Source Package. Procedia Comput. Sci.
**2015**, 66, 150–157. [Google Scholar] [CrossRef] [Green Version] - Curle, N. The influence of solid boundaries upon aerodynamic sound. Proc. R. Soc. London. Ser. A. Math. Phys. Sci.
**1955**, 231, 505–514. [Google Scholar] - Williams, E.F.; Hawkings, D.L. Sound generation by turbulence and surfaces in arbitrary motion. Philos. Trans. R. Soc. London. Ser. A Math. Phys. Sci.
**1969**, 264, 321–342. [Google Scholar] - Wang, Y.; Mikkola, T.; Hirdaris, S. A fast and storage-saving method for direct volumetric integration of FWH acoustic analogy. Ocean. Eng.
**2022**, 261, 112087. [Google Scholar] [CrossRef] - Ge, M.; Svennberg, U.; Bensow, R.E. Investigations on prediction of ship noise using the FWH acoustic analogy with incompressible flow input. Ocean. Eng.
**2022**, 257, 111531. [Google Scholar] [CrossRef] - Farassat, F.; Succi, G.P. A review of propeller discrete frequency noise prediction technology with emphasis on two current methods for time domain calculations. J. Sound Vib.
**1980**, 71, 399–419. [Google Scholar] [CrossRef] - Garrick, I.E.; Watkins, E.W. A Theoretical Study of the Effect of Forward speed on the Free Space Sound Pressure Field Around Helicopters. Tech. Rep.
**1954**, TR-1198. Available online: https://ntrs.nasa.gov/citations/19930092212 (accessed on 7 April 2022). - Unicfdlab—Overview. GitHub. Available online: https://github.com/unicfdlab (accessed on 7 April 2022).
- Casalino, D.; Jacob, M.; Roger, M. Prediction of rod-airfoil interaction noise using the ffowcs-williams-hawkings analogy. AIAA J.
**2003**, 41, 182–191. [Google Scholar] [CrossRef] - Epikhin, A.; Kraposhin, M.; Vatutin, K. The numerical simulation of compressible jet at low Reynolds number using openfoam. E3S Web Conf.
**2019**, 128, 10008. [Google Scholar] [CrossRef] - Epikhin, A.; Kraposhin, M. Prediction of the free jet noise using quasi-gas dynamic equations and acoustic analogy. Lect. Notes Comput. Sci.
**2020**, 12143, 217–227. [Google Scholar] [CrossRef] - Kimmerl, J.; Krasilnikov, V.; Koushan, K.; Mertes, P.; Savio, L.; Felli, M.; Abdel-Maksoud, M.; Göttsche, U.; Reichstein, N. Analysis Methods and Design Measures for the Reduction of Noise and Vibration Induced by Marine Propellers; Universitätsbibliothek der RWTH Aachen: Aachen, Germany, 2019. [Google Scholar] [CrossRef]
- Heydari, M.; Sadat, H.; Singh, R. A computational study on the aeroacoustics of a multi-rotor unmanned aerial system. Appl. Sci.
**2021**, 11, 9732. [Google Scholar] [CrossRef] - Mankbadi, R.R.; Afari, S.O.; Golubev, V.V. High-fidelity simulations of noise generation in a propeller-driven unmanned aerial vehicle. AIAA J.
**2021**, 59, 1020–1039. [Google Scholar] [CrossRef] - Łojek, P.; Czajka, I.; Gołaś, A.; Suder-Dębska, K. Influence of the elastic cavity walls on cavity flow noise. Vib. Phys. Syst.
**2021**, 32, 2021109-1–2021109-8. [Google Scholar] [CrossRef] - Zhang, F.; Habisreuther, P.; Bockhorn, H.; Nawroth, H.; Paschereit, C.O. On prediction of combustion generated noise with the turbulent heat release rate. Acta Acust. United Acust.
**2013**, 99, 940–951. [Google Scholar] [CrossRef] - Zhang, F.; Habisreuther, P.; Hettel, M.; Bockhorn, H. Numerical computation of combustion induced noise using compressible Les and hybrid CFD/CAA methods. Acta Acust. United Acust.
**2012**, 98, 120–134. [Google Scholar] [CrossRef] - Flemming, F.; Sadiki, A.; Janicka, J. Investigation of Combustion Noise using a Les/CAA Hybrid Approach. Proc. Combust. Inst.
**2007**, 31, 3189–3196. [Google Scholar] [CrossRef] - Zhao, W.; Frankel, S.H. Numerical simulations of sound radiated from an axisymmetric premixed reacting jet. Phys. Fluids
**2001**, 13, 2671–2681. [Google Scholar] [CrossRef] - Merk, M.; Polifke, W.; Gaudron, R.; Gatti, M.; Mirat, C.; Schuller, T. Measurement and simulation of combustion noise and dynamics of a confined Swirl Flame. AIAA J.
**2018**, 56, 1930–1942. [Google Scholar] [CrossRef] [Green Version] - Silva, C.F.; Merk, M.; Komarek, T.; Polifke, W. The contribution of intrinsic thermoacoustic feedback to combustion noise and resonances of a confined turbulent premixed flame. Combust. Flame
**2017**, 182, 269–278. [Google Scholar] [CrossRef] - Merk, M.; Gaudron, R.; Silva, C.; Gatti, M.; Mirat, C.; Schuller, T.; Polifke, W. Prediction of combustion noise of an enclosed flame by simultaneous identification of Noise Source and flame dynamics. Proc. Combust. Inst.
**2019**, 37, 5263–5270. [Google Scholar] [CrossRef] [Green Version] - Merk, M.; Jaensch, S.; Silva, C.; Polifke, W. Simultaneous identification of transfer functions and combustion noise of a turbulent flame. J. Sound Vib.
**2018**, 422, 432–452. [Google Scholar] [CrossRef] - Silva, C.F.; Leyko, M.; Nicoud, F.; Moreau, S. Assessment of combustion noise in a premixed swirled combustor via large-eddy simulation. Comput. Fluids
**2013**, 78, 1–9. [Google Scholar] [CrossRef] [Green Version] - Germano, M.; Piomelli, U.; Moin, P.; Cabot, W.H. A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A Fluid Dyn.
**1991**, 3, 1760–1765. [Google Scholar] [CrossRef] [Green Version] - Arya, N.; De, A. Effect of grid sensitivity on the performance of wall adapting SGS models for Les of Swirling and separating–reattaching flows. Comput. Math. Appl.
**2019**, 78, 2035–2051. [Google Scholar] [CrossRef] - Larsson, A.; Zettervall, N.; Hurtig, T.; Nilsson, E.J.; Ehn, A.; Petersson, P.; Alden, M.; Larfeldt, J.; Fureby, C. Skeletal methane–air reaction mechanism for large eddy simulation of turbulent microwave-assisted combustion. Energy Fuels
**2017**, 31, 1904–1926. [Google Scholar] [CrossRef] - Zettervall, N.; Fureby, C.; Nilsson, E.J. Evaluation of chemical kinetic mechanisms for methane combustion: A review from a CFD Perspective. Fuels
**2021**, 2, 210–240. [Google Scholar] [CrossRef]

**Figure 1.**(

**a**) Image of a Bunsen burner stabilizer, (

**b**) dimensional drawing of the stabilizer from the top, (

**c**) section view of the Bunsen burner revealing the small openings in the annulus, and (

**d**) the inverted flow domain for the simulation.

**Figure 5.**Still images from the video recordings demonstrating the wrinkling of the burner’s flame cone.

**Figure 6.**Contour of the flame temperature: (

**a**) LES and (

**b**) URANS in comparison with (

**c**) the experiment.

**Figure 7.**The y–z plane cut of the LES simulation for (

**a**) x-component velocity, (

**b**) y-component velocity, and (

**c**) pressure.

**Figure 8.**The y–z plane cut of the URANS simulation for (

**a**) x-component velocity, (

**b**) y-component velocity, and (

**c**) pressure.

**Figure 9.**The SPL spectrum for combustion in a solid blue line, air flow only in a dotted orange line, and no flow conditions in the dashed green line.

**Figure 10.**The SPL frequency spectrum for the measured noise (solid blue line) in comparison with the LES modeled noise (orange dashed line) and URANS modeled noise (green dash dotted line).

PIMPLE | nOuterCorrectors | 1 |

nCorrectors | 2 | |

nNonOrthogonalCorrectors | 1 | |

Solvers | rho | diagonal PBiCGStab|DILU PCG|DIC |

U|h|k|epsilon|Yi | ||

P | ||

Numerical Schemes | ddtSchemes | Euler |

gradSchemes | linear | |

divSchemes | limitedLinear |

Boundary | Pressure (Pa) | Temperature (K) | Velocity U (m/s) |
---|---|---|---|

Initial Field | uniform 101325 | uniform 300 | uniform (0 0 0) |

outlet | fixedValue | zeroGradient | pressureInletOutletVelocity |

inlet | zeroGradient | uniform 300 | flowRateInletVelocity |

wallPipe | zeroGradient | externalWallHeatFluxTemperature | noSlip |

wallBuner | zeroGradient | zeroGradient | noSlip |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Williamson, A.J.; Srivastava, S.; Sallam, K.A.
Validating Confined Flame Noise Simulation Using External Sensor. *Sensors* **2022**, *22*, 8039.
https://doi.org/10.3390/s22208039

**AMA Style**

Williamson AJ, Srivastava S, Sallam KA.
Validating Confined Flame Noise Simulation Using External Sensor. *Sensors*. 2022; 22(20):8039.
https://doi.org/10.3390/s22208039

**Chicago/Turabian Style**

Williamson, Andrew J., Shubham Srivastava, and Khaled A. Sallam.
2022. "Validating Confined Flame Noise Simulation Using External Sensor" *Sensors* 22, no. 20: 8039.
https://doi.org/10.3390/s22208039