Noise source distribution in supersonic jets

2006 ◽  
Vol 291 (1-2) ◽  
pp. 192-201 ◽  
Author(s):  
Christopher K.W. Tam ◽  
Nikolai N. Pastouchenko ◽  
Robert H. Schlinker
Keyword(s):  
Noise Source ◽  
Supersonic Jets ◽  
Source Distribution

Noise Reduction of Blade-Passing Frequency Components in a Centrifugal Blower

2004 ◽  
Author(s):  
Yutaka Ohta ◽  
Eisuke Outa
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Noise Source ◽  
Higher Order ◽  
Pressure Level ◽  
Source Distribution ◽  
Centrifugal Blower ◽  
Blade Passing Frequency ◽  
Active Cancellation ◽  
Frequency Components

A hybrid-type noise control method is applied to fundamental and higher-order blade-passing frequency components, abbreviated to BPF components, radiated from a centrifugal blower. An active cancellation of the BPF noise source is conducted based on a detailed investigation of the noise source distribution by using correlation analysis. The sound pressure level of 2nd- and/or 3rd-order BPF can be reduced by more than 15 decibels and discrete tones almost eliminate from the power spectra of blower-radiated noise. On the other hand, the sound pressure level of the fundamental BPF is difficult to reduce effectively by the active cancellation method because of the large amplitude of the noise source fluctuation. However, the fundamental BPF is largely influenced by the frequency-response characteristics of the noise transmission passage, and is passively reduced by appropriate adjusting of the inlet duct length. Simultaneous reduction of BPF noise, therefore, can be easily made possible by applying passive and active control methods on the fundamental and higher-order BPF noise, respectively. We also discuss the distribution pattern of BPF noise sources by numerical simulation of flow fields around the scroll cutoff.

Wavepacket noise source model for microphone array data analysis of hot supersonic jets

2013 ◽  
Vol 134 (5) ◽  
pp. 4127-4127 ◽  
Author(s):  
Philip Morris ◽  
Robert Dougherty ◽  
Chris Nelson ◽  
Alan Cain ◽  
Kenneth Brentner
Keyword(s):  
Data Analysis ◽  
Noise Source ◽  
Microphone Array ◽  
Source Model ◽  
Supersonic Jets ◽  
Array Data

Effect of Velocity Ratio on Noise Source Distribution of Coaxial Jets

AIAA Journal ◽  
2010 ◽  
Vol 48 (7) ◽  
pp. 1504-1512 ◽  
Author(s):  
Dimitri Papamoschou ◽  
Sara Rostamimonjezi
Keyword(s):  
Noise Source ◽  
Velocity Ratio ◽  
Source Distribution ◽  
Coaxial Jets

Jet Noise Source Distribution from Far-Field Cross Correlations

AIAA Journal ◽  
1977 ◽  
Vol 15 (6) ◽  
pp. 771-772 ◽  
Author(s):  
L. Maestrello ◽  
Chen-Huei Liu
Keyword(s):  
Noise Source ◽  
Jet Noise ◽  
Source Distribution ◽  
Far Field ◽  
Cross Correlations

Effects of Jet Noise Source Distribution on Acoustic Far-Field Measurements

2012 ◽  
Vol 11 (7-8) ◽  
pp. 885-915 ◽  
Author(s):  
Ching-Wen Kuo ◽  
Jérémy Veltin ◽  
Dennis K. McLaughlin
Keyword(s):  
Noise Source ◽  
Jet Noise ◽  
Field Measurements ◽  
Source Distribution ◽  
Far Field

Incorporating spatial gradient observations into seismic noise interferometry

2021 ◽  
Author(s):  
Patrick Paitz ◽  
Korbinian Sager ◽  
Christian Boehm ◽  
Andreas Fichtner
Keyword(s):  
Noise Source ◽  
Source Distribution ◽  
Seismic Interferometry ◽  
Spatial Gradient ◽  
Source Inversion ◽  
Common Assumption ◽  
Wide Range ◽  
The Common ◽  
Arbitrary Noise ◽  
Public Datasets

<p>With an increasing availability of next-generation instruments in seismology such as Distributed Acoustic Sensing (DAS) interrogators and rotation sensors, as well as public datasets from these instruments, there is a demand for incorporating these new gradient observables into the workflows of seismic interferometry and noise source inversion.</p><p>Dropping the common assumption of Green’s function retrieval, we derive a generalized formulation for seismic interferometry that can utilize not only displacement measurements but also spatial and temporal gradients thereof – including velocity, strain and rotation.</p><p>Based on this formulation, we are able to simulate interferometric wavefields of displacement and gradient observations or arbitrary combinations of these observables, for heterogeneous visco-elastic media, and for arbitrary noise source distributions.</p><p>We demonstrate how to derive adjoint-based expressions for finite-frequency sensitivity kernels of the interferometric wavefields with respect to subsurface structure and noise source distributions, for a wide range of observed quantitates and combinations thereof. We provide numerical examples of such sensitivity kernels.</p><p>Especially in environments where the common assumption of a homogeneous noise source distribution is violated, our formulation enables correlation-wavefield based inversions, combining different seismic observables.</p><p>The discussed theoretical and numerical developments bring us one step closer to multi-observational full waveform ambient noise inversion, underlining the potential and possible impact of recent developments in seismic instrumentation to seismology across all scales.</p>

Heterogeneous cloud-supercomputing framework for daily seismic noise source inversion

2020 ◽  
Author(s):  
Alexey Gokhberg ◽  
Laura Ermert ◽  
Jonas Igel ◽  
Andreas Fichtner
Keyword(s):  
Real Time ◽  
Seismic Noise ◽  
Cross Correlation ◽  
Noise Source ◽  
Workflow Management ◽  
Source Distribution ◽  
Ambient Seismic Noise ◽  
Source Inversion ◽  
Finite Frequency ◽  
Noise Sources

<p>The study of ambient seismic noise sources and their time- and space-dependent distribution is becoming a crucial component of the real-time monitoring of various geosystems, including active fault zones and volcanoes, as well as geothermal and hydrocarbon reservoirs. In this context, we have previously implemented a combined cloud - HPC infrastructure for production of ambient source maps with high temporal resolution. It covers the entire European continent and the North Atlantic, and is based on seismic data provided by the ORFEUS infrastructure. The solution is based on the Application-as-a-Service concept and includes (1) acquisition of data from distributed ORFEUS data archives, (2) noise source mapping, (3) workflow management, and (4) front-end Web interface to end users.</p><p>We present the new results of this ongoing project conducted with support of the Swiss National Supercomputing Centre (CSCS). Our recent goal has been transitioning from mapping the seismic noise sources towards modeling them based on our new method for near real-time finite-frequency ambient seismic noise source inversion. To invert for the power spectral density of the noise source distribution of the secondary microseisms we efficiently forward model global cross-correlation wavefields for any noise distribution. Subsequently, a gradient-based iterative inversion method employing finite-frequency sensitivity kernels is implemented to reduce the misfit between synthetic and observed cross correlations.</p><p>During this research we encountered substantial challenges related to the large data volumes and high computational complexity of involved algorithms. We handle these problems by using the CSCS massively parallel heterogeneous supercomputer "Piz Daint". We also apply various specialized numeric techniques which include: (1) using precomputed Green's functions databases generated offline with Axisem and efficiently extracted with Instaseis package and (2) our previously developed high performance package for massive cross correlation of seismograms using GPU accelerators. Furthermore, due to the inherent restrictions of supercomputers, some crucial components of the processing pipeline including the data acquisition and workflow management are deployed on the OpenStack cloud environment. The resulting solution combines the specific advantages of the supercomputer and cloud platforms thus providing a viable distributed platform for the large-scale modeling of seismic noise sources.</p>

scholarly journals The sources of jet noise: experimental evidence

2008 ◽  
Vol 615 ◽  
pp. 253-292 ◽  
Author(s):  
CHRISTOPHER K. W. TAM ◽  
K. VISWANATHAN ◽  
K. K. AHUJA ◽  
J. PANDA
Keyword(s):  
High Speed ◽  
Noise Source ◽  
Jet Noise ◽  
Polar Angle ◽  
Sound Field ◽  
Source Distribution ◽  
Far Field ◽  
Noise Sources ◽  
Directional Information ◽  
Jet Mixing

The primary objective of this investigation is to determine experimentally the sources of jet mixing noise. In the present study, four different approaches are used. It is reasonable to assume that the characteristics of the noise sources are imprinted on their radiation fields. Under this assumption, it becomes possible to analyse the characteristics of the far-field sound and then infer back to the characteristics of the sources. The first approach is to make use of the spectral and directional information measured by a single microphone in the far field. A detailed analysis of a large collection of far-field noise data has been carried out. The purpose is to identify special characteristics that can be linked directly to those of the sources. The second approach is to measure the coherence of the sound field using two microphones. The autocorrelations and cross-correlations of these measurements offer not only valuable information on the spatial structure of the noise field in the radial and polar angle directions, but also on the sources inside the jet. The third approach involves measuring the correlation between turbulence fluctuations inside a jet and the radiated noise in the far field. This is the most direct and unambiguous way of identifying the sources of jet noise. In the fourth approach, a mirror microphone is used to measure the noise source distribution along the lengths of high-speed jets. Features and trends observed in noise source strength distributions are expected to shed light on the source mechanisms. It will be shown that all four types of data indicate clearly the existence of two distinct noise sources in jets. One source of noise is the fine-scale turbulence and the other source is the large turbulence structures of the jet flow. Some of the salient features of the sound field associated with the two noise sources are reported in this paper.

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