Seismic Time History Data Precision and Time Interval Requirement

2021 ◽  
Author(s):  
Dali Li
Keyword(s):  
Time History ◽  
Time Interval ◽  
History Data

Seismic Time History Data Precision and Time Interval Requirement

2020 ◽  
Author(s):  
Dali Li
Keyword(s):  
Response Spectrum ◽  
Total Duration ◽  
Time History ◽  
Response Spectra ◽  
Design Parameters ◽  
Time Interval ◽  
Nyquist Frequency ◽  
Frequency Range ◽  
History Data ◽  
Data Points

Abstract This paper provides the seismic time history data precision and time interval requirement for seismic dynamic analysis. U.S.NRC SRP 3.7.1 “Seismic Design Parameters” Acceptance Criteria for Design Time Histories specifies the power spectral density Nyquist Frequency, time interval, and total duration; however, it does not have the requirement for Response Spectra. The response spectrum bandwidth is inverse-proportional to time interval of the time history. For the time interval of 0.005 seconds, the bandwidth for the response spectrum is between 0.194 Hz and 80.5 Hz; the PSD Nyquist frequency is 100 Hz. For 20.48 seconds time history, 4096 data points are required. The response spectrum between 1.28 Hz and 13.6 Hz has the peak flat magnitude value; the magnitude drops to 0.707 of the peak value from 1.28 Hz to 0.194 Hz and from 13.6 Hz to 80.5 Hz. This paper also provides the time interval requirement for various response spectrum peak flat magnitude value; i.e., the response spectrum highest flat magnitude of 27.2 Hz requires a time interval of 0.0025 seconds time history. For 20.48 seconds time history, 8192 data points are required. For CSDRS, the time interval of 0.005 seconds is adequate for the frequency range of interest between 0.36 Hz and 57.2 Hz. For HRHF, the time interval of 0.0025 seconds is required to analyze the frequency range of interest between 0.36 Hz and 114.4 Hz.

scholarly journals Solar, ionospheric and geomagnetic indices

1998 ◽  
Vol 41 (5-6) ◽  
Author(s):  
L. Perrone ◽  
G. De Franceschi
Keyword(s):  
Time History ◽  
The Internet ◽  
Time Interval ◽  
Geomagnetic Indices

The most common solar, ionospheric and geomagnetic indices are here presented with particular reference to their application for radiocommunication prediction purposes. Summary tables of practical use are also included concerning the method of derivation of the indices, their time interval, their drawbacks, their time-history and the INTERNET node addresses where they are available.

Energies of precipitating electrons during pulsating aurora events derived from ionosonde observations

1981 ◽  
Vol 59 (8) ◽  
pp. 1070-1076 ◽  
Author(s):  
J. W. MacDougall ◽  
J. Hofstee ◽  
J. A. Koehler
Keyword(s):  
Energy Flux ◽  
Time History ◽  
Time Interval ◽  
Characteristic Energy ◽  
Morning Sector ◽  
History Of

The time-history of particle energies and fluxes associated with pulsating auroras in the morning sector is derived from ionosonde measurements. All the pulsating auroras studied showed a similar history with the pulsations occurring during a time interval of the order of an hour during which the average auroral Maxwellian characteristic energy stays relatively constant but the energy flux decreases progressively during the event. A possible explanation for this behaviour in terms of an injection of particles into a magnetospheric "bottle" near the midnight meridian and the progressive precipitation out of the bottle during the pulsating event is suggested.

Use of falling weight deflectometer time history data for the analysis of seasonal variation in pavement response

2010 ◽  
Vol 37 (9) ◽  
pp. 1224-1231 ◽  
Author(s):  
Kate Deblois ◽  
Jean-Pascal Bilodeau ◽  
Guy Doré
Keyword(s):  
Phase Angle ◽  
Time History ◽  
Test Site ◽  
Flexible Pavement ◽  
Dissipated Energy ◽  
Falling Weight Deflectometer ◽  
History Data ◽  
The Road ◽  
Pavement Structures ◽  
Falling Weight

This paper presents the results of an exploratory analysis of falling weight deflectometer (FWD) data collected on a large project about the spring thaw behaviour of pavements. The test site includes four test sections, two of which are conventional flexible pavement structures, whereas the other two are built with a cement-treated base. The aim of this study is to verify the applicability of using FWD time history data to evaluate damage to a road during the thawing period. The applicability of the analysis techniques is verified through the phase angle and dissipated energy. The data analyzed were obtained from tests conducted with an FWD on one flexible pavement test section. The results obtained showed a clear difference between the winter, thawing, and summer periods. It was found that the phase angle and dissipated energy can be used to evaluate the road damage during the thawing period through quantification of the phase angle and dissipated energy. These factors can also be used to describe the pavement behaviour in terms of elasticity and viscoelasticity.

scholarly journals An Accuracy Problem of the Fwd Time History with Regard to the Application of the Sasw Method

2017 ◽  
Vol 13 (2) ◽  
pp. 120-124
Author(s):  
Jozef Komačka
Keyword(s):  
Shear Modulus ◽  
Bearing Capacity ◽  
Evaluation Method ◽  
Time History ◽  
Evaluation Process ◽  
History Data ◽  
Consecutive Time ◽  
Equivalent Modulus ◽  
Propagation Of Waves ◽  
Falling Weight

Abstract A Falling Weight Deflectometer (FWD) represents one group of the devices used for diagnostics of pavement bearing capacity. Usually, the FWD dynamic load is substituted by a static load in the evaluation process to determine the equivalent modulus of a pavement structure or modulus of pavement layers. However, the data recorded during a bearing capacity test by FWD can be used to reveal the propagation of a dynamic impulse generated by FWD. It gives a possibility to use them in an evaluation method based on the propagation of waves generated by dynamic impulse. Therefore, the FWD time history data was assessed with regard to possible using in the method of the Spectral Analysis of Surface Waves. Basically, the possibility to determine the velocity of a generated surface wave was evaluated. It was found out the same deflection values exist at consecutive time intervals in the relevant part of the time history data (the arrival of the front of the wave or the area of maximum deflection value). Two methods were used to determine the exact time of the wave occurrence at receivers. It was concluded the differences between the used methods exist. It means the calculated velocities of a wave and shear modulus are also different. Importance of the shear modulus differences were estimated using the Slovak bearing capacity classification based on elastic modulus values. Taking into account the range of modulus in one classification class it can be stated the differences in the shear modulus determined according to used two methods could be very significant if the values calculated for short distance of the receiver are used. In the case of longer distance of the receivers the differences are not so high and significant.

Validation of Pyroshock Data

2012 ◽  
Vol 55 (1) ◽  
pp. 40-56 ◽  
Author(s):  
Vesta Bateman ◽  
Ronald Merritt
Keyword(s):  
Data Acquisition ◽  
Proper Time ◽  
Time History ◽  
Government Agencies ◽  
Comprehensive Description ◽  
Private Companies ◽  
History Data ◽  
Data Acquisition Systems ◽  
Data Analyses ◽  
Test Specification

This paper presents a comprehensive description of pyroshock, the interpretation of pyroshock data, and the validation of pyroshock data. Recent events in the pyroshock testing community show that corrupted pyroshock data are still being acquired at government agencies and private companies. A large part of this paper is devoted to acquisition and analysis of pyroshock data because proper time-history data acquisition and, consequently, test specification development are common industry problems. To avoid corrupted pyroshock data and thus corrupted pyroshock specifications, recommended practices for instrumentation and data acquisition systems as well as data analyses are provided. Causes of corrupted pyroshock data are explored and recommendations for avoiding corrupted pyroshock data are presented.

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