Actual Earthquake Data Research Articles

The MASLIS: A five-year review of Costa Rica's near real-time seismic intensity processing system

The MASLIS is an online system that displays the earthquake’s seismic intensity in near-real time. The system analyzes the data from Costa Rica’s strong motion network. When the intensity exceeds a specified intensity threshold at a number of sites, the system sends several warning messages. When it was first developed in 2019, the system was tested using scenario earthquakes. After five years of operation, this article briefly discusses its performance using actual earthquake data.

Design and Simulation of a Model Predictive Controller (MPC) for a Seismic Uniaxial Shake Table

Shake table is one of the apparatus that aids in researches to generate techniques, structural developments, and strategies to prevent, prepare, and minimize an earthquake’s devastating effects. One important factor that should be considered in a shake table is the system dynamics due to control-structural interactions, which could either be linear or non-linear. To accurately model both has always been the challenge but becomes more plausible with the availability of faster hardware and computers and the continuous decrease in latency. Model Predictive Controller (MPC) is a type of controller extensively used in the industry that can be used on linear and non-linear systems. This study presents the design and simulation of an MPC for a uniaxial shake table intending to analyze the system’s behavior and accuracy. MATLAB Simulink was utilized to handle the simulation analysis of the controller. Different MPC parameters such as sample time, prediction horizon, control horizon, and closed-loop performance were manipulated and adjusted to observe their effects on the output of the system. A signal that mimics the actual earthquake data was inputted into the controller, and the system's behavior and outputs were measured and presented through graphical representations. To determine the accuracy of the system’s output, its relationship with the reference signal was compared. From the simulation produced, the system demonstrated high accuracy levels and could be adjusted depending on the set performance aggressiveness of the system.

Seismic microzonation and building vulnerability assessment based on site characteristic and geotechnical parameters by use of Fuzzy-AHP model (a case study for Kermanshah city)

ABSTRACT On 12th November 2017, an earthquake with a magnitude of 7.3 Richter scale in the town of Sarpol-e Zahab took place that caused lots of human casualties and devastation. After the incident, issues related to the probability of an earthquake with equal intensity and extents of similar building destruction were raised in Kermanshah city. Therefore, a seismic microzonation map of Kermanshah city has been prepared based on the geotechnical, geological, and geophysical data, and the data were analysed using Fuzzy analytic hierarchy process (AHP). In the next step, the vulnerability analysis of city buildings was carried out based on the ground-shaking map, vulnerability curves, and statistical data regarding the buildings. The results of the vulnerability rate of residential buildings indicate that 80% of residential buildings would be exposed to vulnerability from low to moderate. However, other buildings would suffer 2% fully destruction (D1), 7% very high destruction (D2) and 11% high destruction (D3), respectively. Finally, according to the obtained results, the proposed model is verified with the help of the data and observations from the Sarpol-e Zahab earthquake, which reveals that the model is in good agreement with the actual earthquake data.

Effects of 2D small-scale sedimentary basins on strong ground motion characteristics

A lot of research on the 2D or 3D effects of large-scale basins (within several kilometers depth) have been conducted in the past. However, different 2D aspects of small-scale sedimentary basins (within tens of meters depth) remain in the developing stage. Here, an attempt is made to analyze different aspects of small-scale basins using both numerical and empirical investigations. In the first step, the 2D effects of small-scale basins on strong motion characteristics are numerically examined both in the time and frequency domains. In addition, the effects of input motion are also explained by the results of model excitation in different orthogonal directions. Then, the numerical outcomes are verified by the analysis of actual earthquake data recorded at a downhole array in the Fujisawa small basin, Japan. In the second step, since available recorded earthquake data in small basins with a clear understanding of subsurface geology are very limited, different 2D aspects of the small basin are parametrically investigated. For this purpose, extensive parametrical studies are carried out on the main features of a small basin such as slope angle, shape, infill soil properties, and basin thickness by using the finite difference numerical method. The horizontal and vertical peak ground accelerations of 2D with respect to 1D ones are defined as the horizontal and vertical aggravation factors (AGH and AGV). The AGH and AGV factors show large sensitivity to infill soil properties, shape and thickness, and small sensitivity to slope angle. The values of AGH and AGV factors vary in the range of 0.5?2 with large variations around small basin edges due to wave coupling, conversion, scattering and focusing in the vicinity of small basin edges. These cause a complicated pattern of 2D de-amplification and amplification, which mostly affect the motion in the high frequency range (>1?Hz). Finally, the outcomes provide numerical and field evidence on the 2D effects of small basins, and give some recommendations for design codes.

Assessment of the Contribution of Crowd Sourced Data to Post-Earthquake Building Damage Detection

This paper compares the results of building damage detection based on Crowd Sourced (CS) data, image processing of remotely sensed (RS) data and predictive modelling with institutional spatial data (Spatial Data Infrastructure - SDI). In particular, it focuses on the contribution of Crowd Sourcing to detecting post-earthquake building damages, while also considering the integration of Crowd Sourced with two other data sources (RS and modelling). To simulate CS data submission following the 2003 earthquake in Bam City (Iran) a survey was administered to the population which experienced the earthquake. The results obtained from this and two other sources are compared with the Actual Earthquake (AE) data by cross-tabulation analysis and McNemar's Chi Square Test. When assessed against AE data, the average accuracy levels of assessments based on the use of RS data and CS data integrated with each RS data and predictive modelling and with both, show a statistically significant increase relative to the predictive modelling. While this research does not provide for a full assessment of the value of CS data alone and in fact finds it slightly inferior to predictive modelling, it suggests that Crowd Sourcing could be a useful source of information, especially if combined with other sources.

Ground Motion Parameters Influences on Input Seismic Energy

Based on the energy analysis of a multi-degree-of-freedom (MDOF) system, a mode decomposition method for the input seismic energy is proposed, which substitutes a MDOF system with equivalent single-degree-of-freedom (SDOF) systems. The input seismic energy is obtained, using the actual earthquake data. The influence of ground motion parameters is analyzed. The results show that the seismic input energy increases proportionally with the square of ground motion acceleration peak. The bigger the predominant period is, the more the input seismic energy is.

Spatial variability of strong ground motion: novel system-based technique applying parametric time series modelling

Spatial variability of strong ground motion within the dimensions of a horizontally extended structure is often described in terms of spectral parameters, such as autospectral densities and cross-spectral densities of motion, recorded at an array of closely spaced sensors. Traditionally, windowed and tapered periodogram techniques have been used in processing strong-motion array data, whereby spectral quantities are estimated. This approach involves large variances in the computed estimates, which can be reduced by decreasing the bandwidth of smoothing windows. A major problem in such applications is the selection of an optimal window, for which, as far as we know, no formal mathematical criteria exist. In this paper we propose a novel technique, based on parametric time series modelling, to replace the periodogram technique for estimating spectral quantities relevant to the description of spatial variability of ground motion. By using actual earthquake data recorded by a strong-motion array, we demonstrate that autoregressive (AR) time series modelling can be used in spectral analysis of strong-motion array data. Such models can easily be calibrated using a variant of least squares techniques, and well-defined statistical criteria are used to identify an optimal model to describe the recorded data. The application of AR modelling eliminates the subjective judgement involved in periodogram techniques and provides stabler estimates of lagged coherencies.

Fragility of underground pipeline under high levels of ground motion

Damage estimation relationships have been proposed based on seismic ground motions and pipeline damage records from past earthquakes as a technique for understanding damage in future seismic hazards. This kind of relationship is formulated by correcting the standard damage relationship shown by the amount of damage from seismic ground motion with coefficients such as pipe materials and ground conditions. However, the existing relationship is based on the actual earthquake data, and has not yet been verified by numerical analysis. In addition, there is little data on pipeline damage by high-level seismic ground motion from the 1995 Kobe earthquake, and we cannot compare those in the other earthquakes. Therefore, this study was conducted to analyse the damage tendency by using the seismic response analysis of a pipeline under high-level ground motion with the aid of the discrete element method (DEM), which can express slipping out and breaking of the pipeline joint. The damage tendency to the pipeline was evaluated relatively by giving the characteristic of the pipe material and joint.

An evolutionary ground motion model for earthquake analysis of structures in zones with little history

Time history methods to perform structural dynamic analysis for vulnerability, seismic risk and structural performance studies are frequent in all kinds of projects. To apply these methods it is necessary to have earthquake acceleration records consistent with the seismic characteristics of the zone where the structure or facilities will be constructed. In regions where seismic activity is important but recorded history is scarce, the simulation of acceleration records becomes necessary.In the present work, a methodology to simulate artificial acceleration records is presented. This methodology is based on the theory of non-stationary random processes with evolutive power spectral density function. The random process model proposed uses the definition of the Boore power spectral density function, in order to take into account the seismic mechanism of the zone. The zone of Mendoza, in the province of Cuyo in Argentina close to the border with Chile, was selected to make applications of the theory. This zone was selected because it has important seismic activity but the information about this activity is scarce. To evaluate the performance of the method some response and seismic variables such as response spectra, Arias evolutionary intensity, and power spectra were computed. The results were compared with actual earthquake data obtained in the region.

Identification method of seismic phase in three-component seismograms on the basis of wavelet transform

This paper puts forward wavelet transform method to identify P and S phases in three component seismograms using polarization information contained in the wavelet transform coefficients of signal. The P and S wave locator functions are constructed by using eigenvalue analysis method to wavelet transform coefficient across several scales. Locator functions formed by wavelet transform have stated noise resistance capability, and is proved to be very effective in identifying the P and S arrivals of the test data and actual earthquake data.

Nonlinear system identification based on modelling of restoring force behaviour

This paper introduces a system identification algorithm based upon modelling of the restoring force behaviour of the structure. This algorithm is more efficient than traditional algorithms based upon matching the time history of response of the structure, since error evaluation does not require the solution of any differential equations. The effectiveness of this system identification approach, in coordination with a model for deteriorating structures is demonstrated by an example using actual earthquake data from the Bank of California building which was damaged during the 1971 San Fernando earthquake.