Broadband Combustion Noise Prediction With the Fast Random Particle Method

2014 ◽  
Author(s):  
Felix Grimm ◽  
Roland Ewert ◽  
Jürgen Dierke ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Scaling Law ◽  
Particle Method ◽  
Reconstruction Algorithm ◽  
Combustion Noise ◽  
Frequency Noise ◽  
Noise Prediction ◽  
Data Set ◽  
Jet Flame ◽  
The Right ◽  
Random Particle

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.

The Fast Random Particle Method for Combustion Noise Prediction

2014 ◽  
Author(s):  
Felix Grimm ◽  
Roland Ewert ◽  
Juergen Dierke ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Particle Method ◽  
Combustion Noise ◽  
Noise Prediction ◽  
Random Particle

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

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Felix Grimm ◽  
Duncan Ohno ◽  
Berthold Noll ◽  
Manfred Aigner ◽  
Roland Ewert ◽  
...  
Keyword(s):  
Gas Turbines ◽  
Sound Propagation ◽  
Particle Method ◽  
Combustion Noise ◽  
Navier Stokes ◽  
Noise Prediction ◽  
Sound Sources ◽  
Linearized Euler Equations ◽  
Industrial Gas Turbines ◽  
The Time Domain

Combustion noise in the laboratory scale PRECCINSTA (prediction and control of combustion instabilities in industrial gas turbines) 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 (computational fluid dynamics–Reynolds-Averaged Navier–Stokes) 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, the reacting steady-state CFD simulations are compared to experimental data, showing very good agreement. Subsequently, the computational combustion acoustics (CCA) 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.

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

2017 ◽  
Vol 9 (4) ◽  
pp. 330-348 ◽  
Author(s):  
Felix Grimm ◽  
Jürgen Dierke ◽  
Roland Ewert ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Turbines ◽  
Sound Propagation ◽  
Particle Method ◽  
Combustion Noise ◽  
Formation Mechanisms ◽  
Noise Prediction ◽  
Turbulence Statistics ◽  
The Impact

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.

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

2016 ◽  
Author(s):  
Felix Grimm ◽  
Duncan Ohno ◽  
Roland Ewert ◽  
Jürgen Dierke ◽  
Berthold Noll ◽  
...  
Keyword(s):  
Sound Propagation ◽  
Particle Method ◽  
Combustion Noise ◽  
Noise Prediction ◽  
Sound Sources ◽  
Linearized Euler Equations ◽  
Noise Simulation ◽  
Parametric Studies ◽  
Global Reaction ◽  
The Time Domain

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.

An experimental study of strongly nonlinear waves in a rotating system

1987 ◽  
Vol 177 ◽  
pp. 381-394 ◽  
Author(s):  
Dominique P. Renouard ◽  
Gabriel Chabert D'Hières ◽  
Xuizhang Zhang
Keyword(s):  
Equilibrium Shape ◽  
Scaling Law ◽  
Maximum Amplitude ◽  
Rotating Platform ◽  
Coriolis Parameter ◽  
Rotating System ◽  
Height Variation ◽  
Experimental Conditions ◽  
Strongly Nonlinear ◽  
The Right

The influence of rotation upon internal solitary waves is studied in a (10 m × 2 m × 0.6 m) channel located on the large rotating platform at Grenoble University. We observe an intumescence which moves along the right-hand side of the channel with respect to its direction of propagation. Along the side, once the intumescence reaches its equilibrium shape, the height variation of the interface with time is correctly described by the sech2 function, and the characteristic KdV scaling law linking the maximum amplitude and the wavelength along the side is fulfilled. The intumescence is a stable phenomenon which moves as a whole without deformation apart from the viscous damping. For identical experimental conditions, the amplitude of the intumescence along the side increases with increasing Coriolis parameter, and at a given period of rotation of the platform, the celerity along the side increases with increasing amplitude. But for identical conditions, we found that the celerity along the side is equal to the celerity that the wave would have for such conditions without rotation. The amplitude of the intumescence in a plane perpendicular to the wall decreases exponentially with increasing distance from the side, but the crest of the wave is curved backward.

scholarly journals Wind Speed Retrieval from Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data for Marine Application

2019 ◽  
Vol 11 (14) ◽  
pp. 1682 ◽  
Author(s):  
Torsten Geldsetzer ◽  
Shahid K. Khurshid ◽  
Kerri Warner ◽  
Filipe Botelho ◽  
Dean Flett
Keyword(s):  
Wind Speed ◽  
Low Noise ◽  
Quality Data ◽  
Band Model ◽  
Data Set ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Geophysical Model ◽  
The Right ◽  
Quality Threshold

RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys on the West and East coasts of Canada. Wind speeds up to 18 m/s were included. CP and linear polarization parameters were related to the C-band model (CMOD) geophysical model functions CMOD-IFR2 and CMOD5n. These were evaluated for their wind retrieval potential in each RCM mode. The CP parameter Conformity was investigated to establish a data-quality threshold (>0.2), to ensure high-quality data for model validation. An accuracy analysis shows that the first Stokes vector (SV0) and the right-transmit vertical-receive backscatter (RV) parameters were as good as the VV backscatter with CMOD inversion. SV0 produced wind speed retrieval accuracies between 2.13 m/s and 2.22 m/s, depending on the RCM mode. The RCM Medium Resolution 50 m mode produced the best results. The Low Resolution 100 m and Low Noise modes provided similar results. The efficacy of SV0 and RV imparts confidence in the continuity of robust wind speed retrieval with RCM CP data. Three image-based case studies illustrate the potential for the application of CP parameters and RCM modes in operational wind retrieval systems. The results of this study provide guidance to direct research objectives once RCM is launched. The results also provide guidance for operational RCM data implementation in Canada’s National SAR winds system, which provides near-real-time wind speed estimates to operational marine forecasters and meteorologists within Environment and Climate Change Canada.

scholarly journals Complex networks of earthquakes and aftershocks

2005 ◽  
Vol 12 (1) ◽  
pp. 1-11 ◽  
Author(s):  
M. Baiesi ◽  
M. Paczuski
Keyword(s):  
Complex Networks ◽  
Time Windows ◽  
Scaling Law ◽  
Relative Strength ◽  
Modern Theory ◽  
Significant Information ◽  
Data Set ◽  
Scale Free ◽  
Main Shocks ◽  
Aftershock Sequences

Abstract. We invoke a metric to quantify the correlation between any two earthquakes. This provides a simple and straightforward alternative to using space-time windows to detect aftershock sequences and obviates the need to distinguish main shocks from aftershocks. Directed networks of earthquakes are constructed by placing a link, directed from the past to the future, between pairs of events that are strongly correlated. Each link has a weight giving the relative strength of correlation such that the sum over the incoming links to any node equals unity for aftershocks, or zero if the event had no correlated predecessors. A correlation threshold is set to drastically reduce the size of the data set without losing significant information. Events can be aftershocks of many previous events, and also generate many aftershocks. The probability distribution for the number of incoming and outgoing links are both scale free, and the networks are highly clustered. The Omori law holds for aftershock rates up to a decorrelation time that scales with the magnitude, m, of the initiating shock as tcutoff~10β m with β~-3/4. Another scaling law relates distances between earthquakes and their aftershocks to the magnitude of the initiating shock. Our results are inconsistent with the hypothesis of finite aftershock zones. We also find evidence that seismicity is dominantly triggered by small earthquakes. Our approach, using concepts from the modern theory of complex networks, together with a metric to estimate correlations, opens up new avenues of research, as well as new tools to understand seismicity.

scholarly journals There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics

2016 ◽  
Vol 42 (4) ◽  
pp. 637-660 ◽  
Author(s):  
Germán Kruszewski ◽  
Denis Paperno ◽  
Raffaella Bernardi ◽  
Marco Baroni
Keyword(s):  
Large Data ◽  
Semantic Space ◽  
The Other ◽  
Similarity Function ◽  
Distributional Semantics ◽  
Application Domain ◽  
Data Set ◽  
Logical Negation ◽  
The One ◽  
The Right

Logical negation is a challenge for distributional semantics, because predicates and their negations tend to occur in very similar contexts, and consequently their distributional vectors are very similar. Indeed, it is not even clear what properties a “negated” distributional vector should possess. However, when linguistic negation is considered in its actual discourse usage, it often performs a role that is quite different from straightforward logical negation. If someone states, in the middle of a conversation, that “This is not a dog,” the negation strongly suggests a restricted set of alternative predicates that might hold true of the object being talked about. In particular, other canids and middle-sized mammals are plausible alternatives, birds are less likely, skyscrapers and other large buildings virtually impossible. Conversational negation acts like a graded similarity function, of the sort that distributional semantics might be good at capturing. In this article, we introduce a large data set of alternative plausibility ratings for conversationally negated nominal predicates, and we show that simple similarity in distributional semantic space provides an excellent fit to subject data. On the one hand, this fills a gap in the literature on conversational negation, proposing distributional semantics as the right tool to make explicit predictions about potential alternatives of negated predicates. On the other hand, the results suggest that negation, when addressed from a broader pragmatic perspective, far from being a nuisance, is an ideal application domain for distributional semantic methods.

scholarly journals Making sense of the link between tiller density and pasture production

1995 ◽  
pp. 83-87
Author(s):  
C. Matthew ◽  
A. Hernandez-Garay ◽  
J. Hodgson
Keyword(s):  
Leaf Area ◽  
Shoot Density ◽  
Logarithmic Scale ◽  
Data Set ◽  
Pasture Production ◽  
Density Data ◽  
Density Compensation ◽  
Area Effect ◽  
The Right ◽  
Tiller Density

Interpretation of tiller or shoot density data requires resolution of two independent, confounding effects, namely size/density compensation and what is here called the "leaf area effect". Size/density compensation implies that at higher herbage mass, individual tillers or shoots are larger, but the population density is correspondingly decreased. The leaf area effect represents difference in sward leaf area for two tiller populations. Such leaf area differences may be environmentally or genetically determined, but must of necessity be expressed through change in tiller size and/or tiller density as "yield components" of leaf area. The theoretical basis for distinguishing between size/density compensation and the leaf area effect is to consider tiller or shoot density and herbage yield, respectively, as X,Y co-ordinates in a size/density plot. When such a plot is drawn on a logarithmic scale, points along a line of -l/2 slope show size/ density compensation with respect to each other. Movement of points to the right or left of the size/ density compensation line is evidence of a leaf area effect. It is shown that when the size/density effects are removed from a data set in this way, rankings of experimental treatments for the leaf area effect can often be reversed compared with the ranking of uncorrected tiller density. Tiller density data corrected for size/density compen-. sation in this way appear to be a useful indicator of sward productivity. Keywords: sizeldensity compensation, sward productivity, tiller density

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