Felix Grimm

The Fast Random Particle Method for Combustion Noise Prediction

A new, highly efficient approach for combustion noise prediction is introduced. The model is based on a mechanism for stochastic sound source reconstruction that reshapes turbulent dynamics via statistical input from steady CFD-RANS calculations. The utilized source term formulation is based on turbulent temperature fluctuations. The methodology includes the computation of sound propagation with linearized Euler equations in the time-domain, where the stochastic method delivers the temperature variance based unsteady sources as right hand side pressure equation terms. The source reconstruction and sound pressure level prediction capability of the hybrid method including the FRPM (Fast Random Particle Method) in conjunction with combustion noise monopole sources (FRPM-CN) is verified with a semi-analytical approach. The application cases DLR-A, -B and H3 flame are employed for validation purposes with experimental sound pressure spectra and to prove the method’s ability to account for Reynolds scalability. In the same context, a semi-analytical approach based on CFD-RANS statistics is introduced to predict the shape of jet flame noise spectra. A second order Langevin decorrelation model for evolving turbulence is incorporated.

Direct Combustion Noise Simulation of a Lean Premixed Swirl Flame using Stochastic Sound Sources

A lean, swirl-stabilized gas turbine model combustor is simulated with a stochastic approach for combustion noise prediction. The employed hybrid and particle based method, FRPM-CN (Fast Random Particle Method for Combustion Noise Prediction) reconstructs temperature variance based direct combustion noise sources from local CFD-RANS turbulence and flow field statistics. Those monopole sound sources are used as right hand side forcing of the Linearized Euler Equations. First, findings from steady state CFD simulations are validated with experimental results. It is shown that the employed RANS models accurately reproduce the experimental flow field and combustion. Turbulence is treated with a two equation model and a global reaction mechanism is utilized for combustion. Subsequently, the specifications of the CCA (Computational Combustion Acoustics) setup is introduced and selected pressure spectra of the acoustics simulations are compared to experimental results, showing that FRPM-CN is able to deliver absolute combustion noise levels for the investigated burner at low computational costs.

Efficient Full 3D Turbulent Combustion Noise Simulation Based on Stochastic Sound Sources

A combustion noise simulation approach with full dimensional treatment of time-domain sound source modeling and sound propagation is introduced. The hybrid, highly efficient method FRPM-CN (Fast Random Particle Method for Combustion Noise prediction) contains a stochastic sound source reconstruction algorithm. Sources are built according to turbulence statistics which can be derived from reacting CFD-RANS simulations. Sound propagation is modeled via Linearized Euler Equations with accountance for the local CFD mean flow field and combustion induced sources as right hand side forcing of the pressure equation in the acoustic near field. Verification of the approach is carried out on a generic testcase for local oneand two-point source field statistics reproduction ability as well as for analytically derived far-field spectra. The approach is validated for the nonpremixed DLR-A and DLR-B jet flames: The results of CFD-RANS simulations are compared to experimental data, giving a sufficiently accurate representation. Subsequently, numerical results with FRPM-CN for full 3D source modeling and sound propagation are presented. It is shown that the temperature-variance based ansatz pursued in this work delivers accurate absolute sound pressure levels without significant artificial correction. Furthermore, Reynolds-scalability of FRPM-CN for low Mach number jet flames is analyzed by incorporating a Mach number scaling law.

Efficient Combustion Noise Simulation of a Gas Turbine Model Combustor Based on Stochastic Sound Sources

A gas turbine model combustor is simulated with a hybrid, stochastic and particle-based method for combustion noise prediction with full 3D sound source modeling and sound propagation. Alongside, an incompressible LES simulation of the burner is considered for the investigation of the performance of the hybrid approach. The highly efficient time-domain method consists of a stochastic sound source reconstruction algorithm, the Fast Random Particle Method (FRPM) and sound wave propagation via Linearized Euler Equations (LEEs). In the context of this work, the method is adapted and tested for Combustion Noise (CN) prediction. Monopole sound sources are reconstructed by using an estimation of turbulence statistics from reacting CFD-RANS simulations. First, steady state and unsteady CFD calculations of flow field and combustion of the model combustor are evaluated and compared to experimental results. Two equation modeling for turbulence and the EDM (Eddy Dissipation Model) with FRC (Finite Rate Chemistry) for combustion are employed. In a second step, the acoustics simulation setup for the model combustor is introduced. Selected results are presented and FRPM-CN pressure spectra are compared to experimental levels.Copyright

Broadband Combustion Noise Prediction With the Fast Random Particle Method

A new highly efficient, hybrid CFD/CAA approach for broadband combustion noise modeling is introduced. The inherent sound source generation mechanism is based on turbulent flow field statistics, which are determined from reacting RANS calculations. The generated sources form the right-hand side of the linearized Euler equations for the calculation of sound fields. The stochastic time-domain source reconstruction algorithm is briefly described with emphasis on two different ways of spatial discretization, RPM (Random Particle Method) and the newly developed FRPM (Fast RPM). The application of mainly the latter technique to combustion noise (CN) prediction and several methodical progressions are presented in the paper.(F)RPM-CN is verified in terms of its ability to accurately reproduce prescribed turbulence-induced one- and two-point statistics for a generic test and the DLR-A jet flame validation case. Former works on RPM-CN have been revised and as a consequence methodical improvements are introduced along with the progression to FRPM-CN: A canonical CAA setup for the applications DLR-A, -B and H3 flame is used. Furthermore, a second order Langevin decorrelation model is introduced for FRPM-CN, to avoid spurious high frequency noise. A new calibration parameter set for reacting jet noise prediction with (F)RPM-CN is proposed. The analysis shows the universality of the data set for 2D jet flame applications and furthermore the method’s accountance for Reynolds scalability. In this context, a Mach number scaling law is used to conserve Strouhal similarity of the jet flame spectra. Finally, the numerical results are compared to suitable similarity spectra.Copyright

Broadband Combustion Noise Simulation of the PRECCINSTA Burner Based on Stochastic Sound Sources

Combustion noise in the laboratory scale PRECCINSTA burner is simulated with a new, robust and highly efficient approach for combustion noise prediction. The applied hybrid method FRPM-CN (Fast Random Particle Method for Combustion Noise prediction) relies on a stochastic, particle based sound source reconstruction approach. Turbulence statistics from reacting CFD-RANS simulations are used as input for the stochastic method, where turbulence is synthesized based on a first order Langevin ansatz. Sound propagation is modeled in the time domain with a modified set of linearized Euler equations and monopole sound sources are incorporated as right hand side forcing of the pressure equation at every timestep of the acoustics simulations. First, reacting steady state CFD simulations are compared to experimental data, showing very good agreement. Subsequently, the computational combustion acoustics setup is introduced, followed by comparisons of numerical with experimental pressure spectra. It is shown that FRPM-CN accurately captures absolute combustion noise levels without any artificial correction. Benchmark runs show that the computational costs of FRPM-CN are much lower than that of direct simulation approaches. The robustness and reliability of the method is demonstrated with parametric studies regarding source grid refinement, the choice of either RANS or URANS statistics and the employment of different global reaction mechanisms. Nomenclature Alphanumeric Variables  Amplitude scaling variable of sources GTP-16-1254 / Grimm c ©2016 by ASME. This manuscript version is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by/4.0/ The original publication is available at http://dx.doi.org/10.1115/1.4034236 2 a Thermal diffusivity, m2/s c Speed of sound, m/s f Mixture fraction (CFD), frequency (CCA), Hz G Gaussian filter kernel h Heigth in the combustion chamber, mm k Turbulent kinetic energy, m2/s2 lT Turbulent (integral) lengthscale, m ṁ Mass flow rate, kg/s Pth Thermal power, W p Pressure, Pa

Modelling of combustion acoustics sources and their dynamics in the PRECCINSTA burner test case

A stochastic, hybrid computational fluid dynamics/computational combustion acoustics approach for combustion noise prediction is applied to the PRECCINSTA laboratory scale combustor (prediction and control of combustion instabilities in industrial gas turbines). The numerical method is validated for its ability to accurately reproduce broadband combustion noise levels from measurements. The approach is based on averaged flow field and turbulence statistics from computational fluid dynamics simulations. The three-dimensional fast random particle method for combustion noise prediction is employed for the modelling of time-resolved dynamics of sound sources and sound propagation via linearised Euler equations. A comprehensive analysis of simulated sound source dynamics is carried out in order to contribute to the understanding of combustion noise formation mechanisms. Therefrom gained knowledge can further on be incorporated for the investigation of onset of thermoacoustic phenomena. The method-inherent stochastic Langevin ansatz for the realisation of turbulence related source decay is analysed in terms of reproduction ability of local one- and two-point statistical input and therefore its applicability to complex test cases. Furthermore, input turbulence statistics are varied, in order to investigate the impact of turbulence on the resulting sound pressure spectra for a swirl stabilised, technically premixed combustor.