Characterizing seismic noise in the 2–20 Hz band at a gravitational wave observatory

Coward, D. M.; Turner, Jane; Blair, David; Galybin, Konstantin

doi:10.1063/1.1876952

Cited by 11 publications

(6 citation statements)

References 4 publications

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“…Some channels, like from Upper Sand Hill, also showed minor, narrow frequency peaks. Characteristics of high frequency seismic noise at any one location could be related to varying road features (road turn, stop sign, stop light), nontransportation seismic sources such as building resonance, hydrological pumps or mechanical motors (Coward et al, 2005), soil thickness, and seismic velocity in the upper 30 m (Dou et al, 2017; Nakamura, 1989), the coupling condition of the fiber sensor at that position in the array (Ajo‐Franklin et al, 2019). Significant PSD reductions of up to 7 dB were observed at most channels beginning after the first week in March (black traces) to the last day (solid color; transparency decreases with time) in Figure 2b (analyzed in greater detail below).…”

Section: Resultsmentioning

confidence: 99%

City‐Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID‐19 Pandemic

Lindsey

Yuan

Lellouch

et al. 2020

Geophysical Research Letters

109

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Throughout the recent COVID‐19 pandemic, real‐time measurements about shifting use of roads, hospitals, grocery stores, and other public infrastructure became vital for government decision makers. Mobile phone locations are increasingly assimilated for this purpose, but an alternative, unexplored, natively anonymous, absolute method would be to use geophysical sensing to directly measure public infrastructure usage. In this paper, we demonstrate how fiber‐optic distributed acoustic sensing (DAS) connected to a telecommunication cable beneath Palo Alto, CA, successfully monitored traffic over a 2‐month period, including major reductions associated with COVID‐19 response. Continuous DAS recordings of over 450,000 individual vehicles were analyzed using an automatic template‐matching detection algorithm based on roadbed strain. In one commuter sector, we found a 50% decrease in vehicles immediately following the order, but near Stanford Hospital, the traffic persisted. The DAS measurements correlate with mobile phone locations and urban seismic noise levels, suggesting geophysics would complement future digital city sensing systems.

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Section: Resultsmentioning

confidence: 99%

City‐Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID‐19 Pandemic

Lindsey

Yuan

Lellouch

et al. 2020

Geophysical Research Letters

109

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“…16.7 Hz) are sinusoidal‐type seismic waves most probably excited by rotating machinery at sharp frequencies. Examples are electrical motors and gearboxes of industrial machinery (Plesinger & Wielandt 1974; Bokelmann & Baisch 1999; Kar & Mohanty 2006), power generators and building services machinery (Coward et al 2005). Due to gear boxes and frequency converters such sinusoidal signals can be observed in the whole frequency range from 1 Hz up to the power frequency (50 Hz) but predominantly around 12.5 Hz (eight poles engines), 16.67 Hz (six poles), 25 Hz (four poles) and 50 Hz (two poles).…”

Section: Variability Of Urban Seismic Noisementioning

confidence: 99%

Time domain classification and quantification of seismic noise in an urban environment

Groos¹,

Ritter²

2009

Geophysical Journal International

137

108

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S U M M A R YBroad-band urban seismic noise (USN) must be considered as a temporally and spatially non-stationary random process. Due to the high variability of USN a single measure like the standard deviation of a seismic noise time-series or the power spectral density at a given frequency is not enough to characterize a sample (time-series) of USN comprehensively. Therefore, we use long-term spectrograms and propose an automated statistical classification in the time domain to quantify and characterize USN. Long-term spectrograms of up to 28 d duration are calculated from a broad-band seismic data set recorded in the metropolitan area of Bucharest, Romania, to identify the frequency-dependent behaviour of the timevariable processes contributing to USN. Based on the spectral analysis eight frequency ranges between 8 mHz and 45 Hz are selected for our proposed time domain classification. The classification scheme identifies deviations from the Gaussian distribution of 4-hr-long timeseries of USN. Our classification is capable to identify Gaussian distributed seismic noise timeseries as well as time-series dominated by transient or periodic signals using six noise classes. Four additional noise classes are introduced to identify corrupt time-series. The performance of the method is tested with a synthetic data set. We also apply the statistical classification for the data set from Bucharest in three time windows (0-4, 8-12 and 13-17 EET) at 11 d in the eight frequency ranges. Only 40 per cent of the analysed time-series are observed to be Gaussian distributed. Most common deviations from the Gaussian distribution (∼47 per cent) are due to the influence of large-amplitude transient signals. In all frequency ranges between 0.04 and 45 Hz significant variations of the statistical properties of USN are observed with daytime, indicating the broad-band human influence on USN. We observe the human activity as a dominant influence on the USN above and below the frequency band of ocean-generated microseism between 0.04 and 0.6 Hz. Our time domain classification and quantification is furthermore capable to resolve the influence of wind on seismic noise and a known site effect variation in the metropolitan area of Bucharest. The information about noise amplitudes and statistical properties derived automatically from broad-band seismic data can be used to select time windows containing adequate data for seismic noise utilization like H/V-studies or ambient noise tomography.

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“…Following the discussion in Coward et al [32] )). For real (noisy) measurements at small values of dR, the material attenuation is difficult to determine, and, as will be shown below, the measurements in this paper do not show the exponential decay implied by Eq.…”

Section: Current Empirical Criteria For Estimating Cosmetic Building mentioning

confidence: 99%

Ground vibrations produced by surface and near-surface explosions

et al. 2013

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a b s t r a c tMeasurements of seismic signatures produced by airborne, near-surface detonations of explosive charges over a variety of ground types show two distinct ground vibration arrivals. In all cases, the earlier arrival (precursor), has a time of arrival consistent with a predominantly underground path and coupling of blast sound to the ground close to the source and is always much smaller than the later vibration, the time of arrival of which is consistent with coupling from the air blast arrival at the receiver. The ratio of the seismic particle velocity to the acoustic pressure at the surface for the air-coupled seismic wave is constant with respect to distance and maximum pressure at a given location, but varies from site to site, with values usually between 1 and 13 lm s A numerical code enabling calculations of the fields due to an impulsive source above a layered poroelastic ground is described. Predictions of the air pressure spectrum above ground and the vertical and radial components of solid particle velocity near the ground surface are found to compare tolerably well with the measured spectra and waveforms of acoustic and seismic pulses at about 100 m range in seismically-hard and -soft soils and with a snow cover present. The predicted seismic responses in 'soft' soil confirm that the existence of a near-surface S-wave speed less than that in air is responsible for the observed 'ringing', i.e. a long low-frequency wavetrain associated with coupling to the dispersive Rayleigh wave. The predicted seismic pulses in the presence of the shallow snow cover explain the observed phenomenon whereby a high frequency ground vibration is modulated by a lower frequency layer resonance.An empirical equation relating ground vibration from explosions to distance predicts that the commonly-used vibrational damage peak velocity criterion of 12 or 25 mm s À1 will be exceeded when the peak positive pressure exceeds 480 Pa (147.6 dB) or 1 kPa (154.0 dB), respectively. Either of these levels is much higher than the current U.S. Army overpressure damage criterion of 159 Pa (138 dB). Thus in most situations damage from blast overpressure will occur long before damaging levels of ground vibration are reached, so it is likely that civilian perceptions of vibration are produced by coupling from the airblast.Published by Elsevier Ltd.

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Characterizing seismic noise in the 2–20 Hz band at a gravitational wave observatory

Cited by 11 publications

References 4 publications

City‐Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID‐19 Pandemic

City‐Scale Dark Fiber DAS Measurements of Infrastructure Use During the COVID‐19 Pandemic

Time domain classification and quantification of seismic noise in an urban environment

Ground vibrations produced by surface and near-surface explosions

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