Lightning amplitude spectra in the interval from 100 kHz to 20 MHz

1981 ◽  
Vol 8 (8) ◽  
pp. 931-934 ◽  
Author(s):  
C. D. Weidman ◽  
E. P. Krider ◽  
M. A. Uman
Keyword(s):  
Amplitude Spectra

Observation of gliding tremors from the Gulf of Guinea might help solve over 50 year old mystery

2021 ◽  
Author(s):  
Charlotte Bruland ◽  
Sarah Mader ◽  
Céline Hadziioannou
Keyword(s):  
Spectral Analysis ◽  
Volcanic Activity ◽  
Rayleigh Waves ◽  
Spectral Characteristics ◽  
Gulf Of Guinea ◽  
Seismic Amplitude ◽  
Long Period ◽  
Amplitude Spectra ◽  
Using Data ◽  
Over Time

<p>In the 1960's a peak in the seismic amplitude spectra around 26 s was discovered and detected on stations worldwide. The source was located in the Gulf of Guinea, with approximate coordinates (0,0), and was believed to be generated continuously. A source with similar spectral characteristics was discovered near the Vanuatu Islands, at nearly the antipodal location of the Gulf of Guinea source. Since it was located close to the volcanoes in Vanuatu, this source is commonly attributed to magmatic processes. The physical cause of the 26 s microseism, however, remains unclear.</p><p>We investigate the source location and evolution of the 26 s microseim using data from permanent broadband stations in Germany, France and Algeria and temporary arrays in Morocco, Cameroon and Botswana for spectral analysis and 3-C beamforming to get closer to resolving the source mechanism responsible for this enigmatic signal. We find that the signal modulates over time and is not always detectable, but occasionally it becomes so energetic it can be observed on stations worldwide. Such a burst can last for hours or days. The signal is visible on stations globally approximately 30 percent of the time. Our beamforming analysis confirms that the source is located in the Gulf of Guinea, as shown in previous studies, and that the location is temporally stable. Whenever the signal is detectable, both Love and Rayleigh waves are generated. We discover a spectral glide effect associated with the bursts, that so far has not been reported in the literature. </p><p>The spectral glides last for about two days and are observed on stations globally. Although at higher frequencies, very long period tremors and gliding tremors are also observed on volcanoes as Redoubt in Alaska and Arenal in Costa Rica, suggesting that the origin of the 26 s tremor is also volcanic. However, there is no reported volcanic activity in the area where the source appears to be located.</p><p> </p>

Spectral characteristics of central Nevada microearthquakes

1970 ◽  
Vol 60 (5) ◽  
pp. 1547-1559 ◽  
Author(s):  
Bruce M. Douglas ◽  
Alan Ryall ◽  
Ray Williams
Keyword(s):  
Spectral Characteristics ◽  
Propagation Path ◽  
Seismic Signals ◽  
Fourier Amplitude ◽  
Recording Site ◽  
Focal Distance ◽  
Amplitude Spectra ◽  
Spectral Frequency ◽  
Group Characteristics ◽  
Event Magnitude

Abstract Fourier amplitude spectra were computed for 40 central Nevada microearthquakes, selected to consider, independently, effects of azimuth and distance from known sources. Spectra were averaged for groups of events to eliminate peculiarities of individual records and emphasize group characteristics. Spectral characteristics did not behave systematically as a function of azimuth from the recording site to the source, but peak spectral frequency was found to correlate strongly with event magnitude and to some degree also with focal distance. These preliminary results suggest that recordings of small earthquakes and microearthquakes can be used to provide detailed information on the character of seismic signals related to properties of the source and propagation path.

Approximate method to estimate the short-period strong motion spectra on bedrock

1981 ◽  
Vol 71 (2) ◽  
pp. 491-505
Author(s):  
Katsuhiko Ishida
Keyword(s):  
Earthquake Swarm ◽  
Strong Motion ◽  
Fourier Amplitude ◽  
Period Range ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Short Period ◽  
Amplitude Spectra ◽  
Low Pass ◽  
Parkfield Earthquake

abstract The methodology to estimate the strong motion Fourier amplitude spectra in a short-period range (T ≦ 1 to 2 sec) on a bedrock level is discussed in this paper. The basic idea is that the synthetic strong motion Fourier spectrum F˜A(ω) calculated from smoothed rupture velocity model (Savage, 1972) is approximately similar to that of low-pass-filtered strong earthquake ground motion at a site in a period range T ≧ 1 to 2 sec: F˜A(ω)=B˜(ω)·A(ω). B˜(ω) is an observed Fourier spectrum on a bedrock level and A(ω) is a low-pass filter. As a low-pass filter, the following relation, A ( T ) = · a · T n a T n + 1 , ( T = 2 π / ω ) , is assumed. In order to estimate the characteristic coefficients {n} and {a}, the Tokachi-Oki earthquake (1968), the Parkfield earthquake (1966), and the Matsushiro earthquake swarm (1966) were analyzed. The results obtained indicate that: (1) the coefficient {n} is nearly two for three earthquakes, and {a} is nearly one for the Tokachi-Oki earthquake, eight for the Parkfield earthquake, and four for the Matsushiro earthquake swarm, respectively; (2) the coefficient {a} is related with stress drop Δσ as (a = 0.07.Δσ). Using this relationship between {a} and Δσ, the coefficients {a} of past large earthquakes were estimated. The Fourier amplitude spectra on a bedrock level are also estimated using an inverse filtering method of A ( T ) = a T 2 a T 2 + 1 .

Determination of crustal thickness from spectral behavior of SH waves

1969 ◽  
Vol 59 (3) ◽  
pp. 1247-1258
Author(s):  
Abou-Bakr K. Ibrahim
Keyword(s):  
Amplitude Spectrum ◽  
Body Waves ◽  
Multiple Reflections ◽  
Matrix Formulation ◽  
Sh Waves ◽  
Crustal Model ◽  
Amplitude Spectra ◽  
Phase Spectra ◽  
Zero Phase

abstract The amplitude spectrum obtained from Haskell's matrix formulation for body waves travelling through a horizontally layered crustal model shows a sequence of minima and maxima. It is known that multiple reflections within the crustal layers produce constructive and destructive interferences, which are shown as maxima and minima in the amplitude spectrum. Analysis of the minima in the amplitude spectra, which correspond to zero phase in the phase spectra, enables us to determine the thickness of the crust, provided the ratio of wave velocity in the crust to velocity under the Moho is known.

On: “Mineral discrimination and removal of inductive coupling with multifrequency IP” by W. H. Pelton, S. H. Ward, P. G. Hallof, W. R. Sill, and P. H. Nelson (GEOPHYSICS, 43, 588–609).

Geophysics ◽  
1984 ◽  
Vol 49 (9) ◽  
pp. 1556-1557
Author(s):  
Heikki Soininen
Keyword(s):  
Apparent Resistivity ◽  
Dispersion Model ◽  
Constant Factor ◽  
Constant Independent ◽  
Real Constant ◽  
Frequency Range ◽  
Dilution Factor ◽  
Amplitude Spectra ◽  
Polarizable Body ◽  
Phase Spectra

The authors discussed the behavior of the resistivity spectra by means of the Cole‐Cole dispersion model. They also discussed the corrections with which the petrophysical resistivity spectrum can be reduced into an apparent resistivity spectrum caused by a polarizable body embedded in an unpolarizable environment. The application of the Cole‐Cole dispersion model is a marked step forward in spectral IP analysis. However, closer attention must be paid to the assumptions and approaches on which the authors base the relations between the petrophysical and apparent spectra. The authors based their relations between the true and apparent spectra on the use of the dilution factor [Formula: see text]. In accordance with the definition by Seigel (1959), they assumed that [Formula: see text] is a real constant (independent of frequency) over the whole frequency range under consideration. First consider the justification for the assumption of the existence of a constant factor [Formula: see text] in the light of an example calculated for phase spectra. Similar considerations could also be made with the aid of amplitude spectra.

An analysis of the spectrum of a gravity anomaly over an inclined dike

Geophysics ◽  
1985 ◽  
Vol 50 (9) ◽  
pp. 1500-1501
Author(s):  
B. N. P. Agarwal ◽  
D. Sita Ramaiah
Keyword(s):  
Fourier Transform ◽  
Gravity Anomaly ◽  
Fourier Spectrum ◽  
Fourier Transforms ◽  
Weighted Average ◽  
Window Function ◽  
Average Spectrum ◽  
Amplitude Spectra ◽  
Distance Data ◽  
The Fourier Transform

Bhimasankaram et al. (1977) used Fourier spectrum analysis for a direct approach to the interpretation of gravity anomaly over a finite inclined dike. They derived several equations from the real and imaginary components and from the amplitude and phase spectra to relate various parameters of the dike. Because the width 2b of the dike (Figure 1) appears only in sin (ωb) term—ω being the angular frequency—they determined its value from the minima/zeroes of the amplitude spectra. The theoretical Fourier spectrum uses gravity field data over an infinite distance (length), whereas field observations are available only for a limited distance. Thus, a set of observational data is viewed as a product of infinite‐distance data with an appropriate window function. Usually, a rectangular window of appropriate distance (width) and of unit magnitude is chosen for this purpose. The Fourier transform of the finite‐distance and discrete data is thus represented by convolution operations between Fourier transforms of the infinite‐distance data, the window function, and the comb function. The combined effect gives a smooth, weighted average spectrum. Thus, the Fourier transform of actual observed data may differ substantially from theoretic data. The differences are apparent for low‐ and high‐frequency ranges. As a result, the minima of the amplitude spectra may change considerably, thereby rendering the estimate of the width of the dike unreliable from the roots of the equation sin (ωb) = 0.

scholarly journals Bifurcations of a Controlled Two-Bar Linkage Motion with Considering Viscous Frictions

2011 ◽  
Vol 18 (1-2) ◽  
pp. 365-375 ◽  
Author(s):  
Qingkai Han ◽  
Xueyan Zhao ◽  
Xingxiu Li ◽  
Bangchun Wen
Keyword(s):  
Phase Space ◽  
Lyapunov Exponents ◽  
Time Domain ◽  
Shooting Method ◽  
Viscous Friction ◽  
Dynamical Model ◽  
Chaotic Motions ◽  
Amplitude Spectra ◽  
Set Up ◽  
Joint Motions

In this paper, we investigate the joint viscous friction effects on the motions of a two-bar linkage under controlling of OPCL. The dynamical model of the two-bar linkage with an OPCL controller is firstly set up with considering the two joints' viscous frictions. Thereafter, the motion bifurcations of the two-bar linkage along the values of joint viscous frictions are obtained using shooting method. Then, single-periodic, multiple-periodic, quasi-periodic and chaotic motions of link rotating angles are simulated with given different viscous friction values, and they are illustrated in time domain waveforms, phase space portraits, amplitude spectra and Poincare mapping graphs, respectively. Additionally, for the chaotic case, Lyapunov exponents and hypothesis possibilities of the two joint motions are also estimated.

scholarly journals Thermal stimulation neurophysiology of pressure phosphenes

2021 ◽  
Author(s):  
Alexander Kholmansky ◽  
Elena Konyukhova ◽  
Andrey Minakhin
Keyword(s):  
Heat Transfer ◽  
Cerebral Cortex ◽  
Cervical Spine ◽  
Water Clusters ◽  
Bioelectrical Activity ◽  
Subjective Assessments ◽  
Amplitude Spectra ◽  
Pain Receptors ◽  
Resonant Mechanism ◽  
Stimulation Of

AbstractSynesthesia of vision and somatosensory is based on physiology of interconnection of neurons in different nuclei of thalamus or areas of cerebral cortex. Work studied effect on the intensity of pressure phosphenes (PP) of various methods of heating eyes and hands, as well as manual influence on cervical spine. Along with subjective assessments of the PP intensity, EEG and ECG were used for chronometry of bioelectrical activity of brain and heart. From analysis of frequency and amplitude spectra of EEG, it was concluded that mechanism of PP generation is dominated by processes of redistribution and recombination of charges in retinal and LGB layers. Stimulation of PP by heating hands was associated with convergence of LGB neurons and neurons of thalamus nuclei, which are responsible for thermoreception and are adjacent to LGB. Enhancement of effect of PP stimulation by heating hands in water and in sauna was explained by resonant mechanism of heat transfer from heated water to water of physiological fluids of epidermis and water associated with proteins of ion channels of thermoreceptor membranes. It was suggested that breakdown of water clusters in physiological fluids of epidermis at temperature above 42 °C promotes to transformation of thermoreceptors into pain receptors.

Calibration of a Semi-Stochastic Procedure for Simulating High-Frequency Ground Motions

2013 ◽  
Vol 29 (4) ◽  
pp. 1495-1519 ◽  
Author(s):  
Emel Seyhan ◽  
Jonathan P. Stewart ◽  
Robert W. Graves
Keyword(s):  
High Frequency ◽  
Ground Motions ◽  
Random Phase ◽  
Low Frequencies ◽  
Intensity Measures ◽  
Amplitude Spectra ◽  
Random Site ◽  
Broadband Ground Motion Simulation ◽  
Broadband Ground Motion ◽  
Attenuation Bias

Broadband ground motion simulation procedures typically utilize physics-based modeling at low frequencies, coupled with semi-stochastic procedures at high frequencies. The high-frequency procedure considered here combines deterministic Fourier amplitude spectra (dependent on source, path, and site models) with random phase. Previous work showed that high-frequency intensity measures from this simulation methodology attenuate faster with distance and have lower intra-event dispersion than in empirical equations. We address these issues by increasing crustal damping (Q) to reduce distance attenuation bias and by introducing random site-to-site variations to Fourier amplitudes using a lognormal standard deviation ranging from 0.45 for Mw < 7 to zero for Mw 8. Ground motions simulated with the updated parameterization exhibit significantly reduced distance attenuation bias and revised dispersion terms are more compatible with those from empirical models but remain lower at large distances (e.g., > 100 km).

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