Experimental GT-POWER Correlation Techniques and Best Practices Low Frequency Acoustic Modeling of the Exhaust System of a Naturally Aspirated Engine

2017 ◽  
Author(s):  
William Seldon ◽  
Amer Shoeb ◽  
Daniel Schimmel ◽  
Jared Cromas
Keyword(s):  
Best Practices ◽  
Low Frequency ◽  
Exhaust System ◽  
Acoustic Modeling ◽  
Correlation Techniques

scholarly journals How Sensitive are EEG Results to Preprocessing Methods: A Benchmarking Study

2020 ◽  
Author(s):  
Kay A. Robbins ◽  
Jonathan Touryan ◽  
Tim Mullen ◽  
Christian Kothe ◽  
Nima Bigdely-Shamlo
Keyword(s):  
Best Practices ◽  
General Structure ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
Spectral Features ◽  
Eeg Analysis ◽  
Research Reporting ◽  
Automated Processing ◽  
Open Question

AbstractAlthough several guidelines for best practices in EEG preprocessing have been released, even those studies that strictly adhere to those guidelines contain considerable variation in the ways that the recommended methods are applied. An open question for researchers is how sensitive the results of EEG analyses are to variations in preprocessing methods and parameters. To address this issue, we analyze the effect of preprocessing methods on downstream EEG analysis using several simple signal and event-related measures. Signal measures include recording-level channel amplitudes, study-level channel amplitude dispersion, and recording spectral characteristics. Event-related methods include ERPs and ERSPs and their correlations across methods for a diverse set of stimulus events. Our analysis also assesses differences in residual signals both in the time and spectral domains after blink artifacts have been removed. Using fully automated pipelines, we evaluate these measures across 17 EEG studies for two ICA-based preprocessing approaches (LARG, MARA) plus two variations of Artifact Subspace Reconstruction (ASR). Although the general structure of the results is similar across these preprocessing methods, there are significant differences, particularly in the low-frequency spectral features and in the residuals left by blinks. These results argue for detailed reporting of processing details as suggested by most guidelines, but also for using a federation of automated processing pipelines and comparison tools to quantify effects of processing choices as part of the research reporting.

Bias and Variance in the Estimate of the Doppler Frequency Induced by a Wall Motion Filter

1989 ◽  
Vol 11 (3) ◽  
pp. 215-225 ◽  
Author(s):  
J.C. Willemetz ◽  
A. Nowicki ◽  
J.J. Meister ◽  
F. De Palma ◽  
G. Pante
Keyword(s):  
Wall Motion ◽  
Low Frequency ◽  
Doppler Frequency ◽  
Correlated Noise ◽  
Pulsed Doppler ◽  
Flow Mapping ◽  
Frequency Shifts ◽  
Doppler Signals ◽  
Frequency Aliasing ◽  
Correlation Techniques

In pulsed Doppler flowmeters, processing of the Doppler signals is often done digitally. The first step in the analysis of the echoes is the filtering which is needed to remove stationary components and low frequency shifts induced by wall motion. This preliminary step is of utmost importance. The influence of uncorrelated noise on the measurement of Doppler signals at the input of this filter is analysed. The frequencies of the Doppler signals are extracted by an algorithm based on correlation techniques. We observed that the filter induces a correlated noise term, which results in an overestimation of the frequency. An effect similar to frequency aliasing may appear. The level of the bias is dependent on filter characteristics and noise level. Our study was carried out on simulated Doppler signals using first and second order filters. An especially desirable solution in flow mapping is proposed in order to decrease this error.

The Reduction of Low Frequency Gas Turbine Exhaust Noise: A Case Study

1996 ◽  
Author(s):  
William C. Lucas ◽  
George F. Hessler
Keyword(s):  
Gas Turbines ◽  
Low Frequency ◽  
Development Program ◽  
Exhaust System ◽  
Field Testing ◽  
Frequency Noise ◽  
Airborne Noise ◽  
Exhaust Noise ◽  
Gas Turbine Exhaust ◽  
Turbine Exhaust

A well reported, industry-wide problem with simple cycle peaking gas turbines installed near residences is excessive low frequency airborne noise, sometimes termed “infrasound.” If the noise level is high enough, it can cause perceptible vibration of windows and frame buildings, and provoke an adverse response from the community. Such a situation recently occurred after construction of a four unit GT 11N1 peaking station. A team of specialists and outside consultants was formed to investigate the problem, and a development program found that a thick absorber could be effective against infrasound. This led to the design of a thick panel absorber which was installed at the rear of a 90 degree turn in the exhaust system. Field testing verified that the low frequency noise from the turbine exhaust was reduced by 5.9 and 6.7 dB in the 31.5 and 63 Hz octave bands respectively, and by 5.5 dB(C) overall.

Multiple regression and correlation techniques: Recent controversies and best practices.

2008 ◽  
Vol 53 (3) ◽  
pp. 321-339 ◽  
Author(s):  
William T. Hoyt ◽  
Zac E. Imel ◽  
Fong Chan
Keyword(s):  
Best Practices ◽  
Multiple Regression ◽  
Correlation Techniques

Flow and Noise Investigations of a Separate Flow Exhaust System

2005 ◽  
Author(s):  
Mihai Mihaˇescu ◽  
Ro´bert-Zolta´n Sza´sz ◽  
Laszlo Fuchs ◽  
Ephraim Gutmark
Keyword(s):  
Flow Field ◽  
Numerical Study ◽  
Near Field ◽  
Low Frequency ◽  
Exhaust System ◽  
Separate Flow ◽  
Test Facility ◽  
Frequency Noise ◽  
Frequency Spectra ◽  
Field Source

A major component of aircraft noise is the jet noise created by the high velocity hot stream exhausting from a jet engine, interacting with itself and with the surrounding cold air. In the present paper the flow and acoustic fields that are generated by two coaxial jets are considered. Numerically, the problem is divided into a flow related part (Navier-Stokes system of equation) and an acoustic part (an inhomogeneous wave equation). The flow field is handled by well resolved Large Eddy Simulation (LES). The acoustical sources can then be computed from the flow field calculations, on the near-field “source” grid. The acoustic field is solved, on the same or even on a larger separate grid, by using an acoustic approximation with appropriate acoustic boundary conditions. The computed flow and acoustical fields are compared to those measured on the separate flow nozzle test facility. The comparisons in terms of velocity and sound pressure levels are shown to validate the used approach. Frequency spectra of the acoustic density fluctuation are presented in order to indicate the locations where the high- or low- frequency noise dominates. The numerical study is focused as well on the Reynolds number effects on the flow and acoustics.

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