Digital near source accelerograms recorded by instrumental arrays in Tangshan, China. Part I (1982.7-1984.12)

The ultimate goal of earthquake hazard mitigation research is to gain sufficient understanding of the phenomena involved in an earthquake to minimize the loss of life and property resulting from such an event. In order to design safe, economical structures and facilities in seismic areas, it is necessary to understand the nature of the ground motion generated by an earthquake. This understanding can ultimately come only from the measurement of the strong ground motion resulting from actual damaging earthquakes. In order to facilitate the acquisition of strong ground motion data world-wide, an International Workshop on Strong Motion Earthquake Instrument Arrays was held in 1978 in Hawaii. Participants in the Workshop appealed to the earthquake-threatened countries of the world to undertake a concerted effort to establish strong-motion accelerograph arrays and networks. In response to the appeal of these experts in earthquake hazard mitigation, and in accord with the "China-U.S. Protocol for Scientific and Technical Cooperation in Earthquake Studies," a joint research project on strong ground motion measurement has been established in China. In the first phase of this project, from April 1981 to December 1984, 22 Kinemetrics PDR-1 Digital Event Recorders equipped with FBA-13 Force Balance Accelerometers, and 18 Kinemetrics SMA-1 Analog Accelerographs were deployed in China. Of this total, 13 PDR-1 and 3 SMA1 instruments were deployed in a surface array and a three-dimensional array in the aftershock region of the 1976 Tangshan earthquake. These two arrays recorded a total of 1053 near-source accelerograms from 416 earthquakes with magnitudes ranging from ML = 1.2 to 5.7. The source-station distances ranged from 2 to 45 kilometers. Most of the records contain the complete P- and S-wave motion along with accurate absolute time. Both the volume and quality of the accelerograms are much greater than ever before obtained in China. The largest event recorded was the ML = 5.7 Lulong earthquake of October 19, 1982. Nine instruments were triggered by this event. The epicentral distance from the recording stations ranged from 5 to 41 kilometers, and the corresponding peak horizontal acceleration ranged from 0.217 to 0.008g. Accelerograms were recorded by the three-dimensional array from twenty-eight events. Measurements were made to a depth of 900 meters below the ground surface. The records obtained provide a unique source of data for the study of the propagation of seismic waves near the earth's surface. In order to make these data more useful, they will be published along with site data in a separate volume. In this report, 218 of the most significant accelerograms; are published. The data was obtained from earthquakes with magnitudes ranging from ML = 2.3 to 5.7. All of the data reproduced in this report is available on 9-track computer tape

Introducing Adaptive Incremental Dynamic Analysis: A New Tool for Linking Ground Motion Selection and Structural Response Assessment

Adaptive Incremental Dynamic Analysis (AIDA) is a novel ground motion selection scheme that adaptively changes the ground motion suites at different ground motion intensity levels to match hazardconsistent properties for structural response assessment. Incremental DynamicAnalysis (IDA), a current dynamic response history analysis practice in Performance-Based Earthquake Engineering (PBEE), uses the same suite of ground motions at all Intensity Measure (IM) levels to estimate structural response. Probabilistic Seismic Hazard Analysis (PSHA) deaggregation tells us, however, that the target distributions of important ground motion properties change as the IM levels change. To match hazard-consistent ground motion properties, ground motions can be re-selected at each IM level, but ground motion continuity is lost when using such “stripes” (i.e., individual analysis points at each IM level). Alternatively, the data from the same ground motions in IDA can be re-weighted at various IM levels to match their respective target distributions of properties, but this implies potential omission of data and curse of dimensionality. Adaptive Incremental Dynamic Analysis, in contrast, gradually changes ground motion records to match ground motion properties as the IM level changes, while also partially maintaining ground motion continuity without the omission of useful data. AIDA requires careful record selection across IM levels. Potential record selection criteria include ground motion properties from deaggregation, or target spectrum such as the Conditional Spectrum. Steps to perform AIDA are listed as follows: (1) obtain target ground motion properties for each IM level; (2) determine “bin sizes” (i.e., tolerance for acceptable ground motion properties) and identify all candidate ground motions that fall within target bins; (3) keep ground motions that are usable at multiple IM levels, to maintain continuity; (4) use each ground motion for IDA within its allowable IM range. As a result, if we keep increasing the “bin sizes”, AIDA will approach IDA asymptotically; on the other hand, if we decrease the “bin sizes”, AIDA will approach the other end of “stripes”. This paper addresses the challenges of changing records across various IM levels. Different ground motion selection schemes are compared with AIDA to demonstrate the advantages of using AIDA. Example structural analyses are used to illustrate the impact of AIDA on the estimation of structural response in PBEE. By combining the benefits of IDA and PSHA without the omission of useful data, AIDA is a promising new tool for linking ground motion selection and structural response assessment

Effect of Ground Motion Characteristics on the Seismic Response of Torsionally Coupled Elastic Systems

This study presents a systematic investigation of the effects of ground motion characteristics, especially its multi-directional character, on the response of torsionally coupled elastic structural systems. The ground motion model is probabilistic and is founded on the assumption of the existence of ground motion principal directions. The structural systems considered are single-story and multi-story elastic shear beam models with stiffness eccentricity.National Science Foundation Grants ENV 77-07190 and PFR 80-0258

Ground Motion Modeling Wilayah Sumatera Selatan Berdasarkan Analisis Bahaya Gempa Probabilistik

Ground motion modeling dapat dipergunakan untuk menentukan besarnya bahaya gempa pada batuan dasar di suatu site dan untuk menentukan sumber gempa yang memberikan dampak paling dominan pada suatu site. Dengan menggunakan prinsip Probabilistic Seismic Hazard Analysis (PSHA) dan dengan menggunakan software USGS akan didapatkan nilai peak ground acceleration (PGA) pada batuan dasar, yang kemudian dengan menggunakan Nonlinear Earthquake site Response Analyses (NERA) akan didapatkan ground motion modeling pada permukaan. Dengan melakukan metode tersebut pada suatu site di wilayah Sumatera Selatan, BH-01 dan BH-08 didapatkan hasil nilai PGA pada site BH-01 sebesar 0.248g dan pada BH-08 sebesar 0.2711g dengan masing masing memiliki maksimum kekuatan gempa sebesar 7.2 SR dan 7 SR serta sumber gempa yang memberikan dampak bahaya paling dominan adalah sumber gempa background. Dan untuk ground motion modeling pada permukaan untuk site BH-01 sebesar 0.41g dan pada site BH-08 sebesar 0.49g

Effects of Topography on Seismic-Wave Propagation: An Example from Northern Taiwan

Topography influences ground motion and, in general, increases the amplitude of shaking at mountain tops and ridges, whereas valleys have reduced ground motions, as is observed from data recorded during and after real earthquakes and from numerical simulations. However, recent publications have focused mainly on the implications for ground motion in the mountainous regions themselves, whereas the impact on surrounding low-lying areas has received less attention. Here, we develop a new spectral-element mesh implementation to accommodate realistic topography as well as the complex shape of the Taipei sedimentary basin, which is located close to the Central Mountain Range in northern Taiwan. Spectral-element numerical simulations indicate that high-resolution topography can change peak ground velocity (PGV) values in mountainous areas by ±50% compared to a half-space response. We further demonstrate that large-scale topography can affect the propagation of seismic waves in nearby areas. For example, if a shallow earthquake occurs in the I-Lan region of Taiwan, the Central Mountain Range will significantly scatter the surface waves and will in turn reduce the amplitude of ground motion in the Taipei basin. However, as the hypocenter moves deeper, topography scatters body waves, which subsequently propagate as surface waves into the basin. These waves continue to interact with the basin and the surrounding mountains, finally resulting in complex amplification patterns in Taipei City, with an overall PGV increase of more than 50%. For realistic subduction zone earthquake scenarios off the northeast coast of Taiwan, the effects of topography on ground motion in both the mountains and the Taipei basin vary and depend on the rupture process. The complex interactions that can occur between mountains and surrounding areas, especially sedimentary basins, illustrate the fact that topography should be taken into account when assessing seismic hazard

Extending displacement-based earthquake loss assessment (DBELA) for the computation of fragility curves

This paper presents a new procedure to derive fragility functions for populations of buildings that relies on the displacement-based earthquake loss assessment (DBELA) methodology. In the method proposed herein, thousands of synthetic buildings have been produced considering the probabilistic distribution describing the variability in geometrical and material properties. Then, their nonlinear capacity has been estimated using the DBELA method and their response against a large set of ground motion records has been estimated. Global limit states are used to estimate the distribution of buildings in each damage state for different levels of ground motion, and a regression algorithm is applied to derive fragility functions for each limit state. The proposed methodology is demonstrated for the case of ductile and non-ductile Turkish reinforced concrete frames with masonry infills

Statistical modeling of ground motion relations for seismic hazard analysis

We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function. We derive mathematically the principle of area-equivalence; wherein two alternative GMRs have an equivalent influence on the hazard if these GMRs have equivalent area functions. This includes local biases. An interpretation of the difference between these GMRs (an actual and a modeled one) as a random component leads to a general overestimation of residual variance and hazard. Beside this, we discuss important aspects of classical approaches and discover discrepancies with the state of the art of stochastics and statistics (model selection and significance, test of distribution assumptions, extreme value statistics). We criticize especially the assumption of logarithmic normally distributed residuals of maxima like the peak ground acceleration (PGA). The natural distribution of its individual random component (equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized extreme value. We show by numerical researches that the actual distribution can be hidden and a wrong distribution assumption can influence the PSHA negatively as the negligence of area equivalence does. Finally, we suggest an estimation concept for GMRs of PSHA with a regression-free variance estimation of the individual random component. We demonstrate the advantages of event-specific GMRs by analyzing data sets from the PEER strong motion database and estimate event-specific GMRs. Therein, the majority of the best models base on an anisotropic point source approach. The residual variance of logarithmized PGA is significantly smaller than in previous models. We validate the estimations for the event with the largest sample by empirical area functions. etc

Nonstationary Stochastic Simulation of Strong Ground-Motion Time Histories : Application to the Japanese Database

For earthquake-resistant design, engineering seismologists employ time-history analysis for nonlinear simulations. The nonstationary stochastic method previously developed by Pousse et al. (2006) has been updated. This method has the advantage of being both simple, fast and taking into account the basic concepts of seismology (Brune's source, realistic time envelope function, nonstationarity and ground-motion variability). Time-domain simulations are derived from the signal spectrogram and depend on few ground-motion parameters: Arias intensity, significant relative duration and central frequency. These indicators are obtained from empirical attenuation equations that relate them to the magnitude of the event, the source-receiver distance, and the site conditions. We improve the nonstationary stochastic method by using new functional forms (new surface rock dataset, analysis of both intra-event and inter-event residuals, consideration of the scaling relations and VS30), by assessing the central frequency with S-transform and by better considering the stress drop variability.Comment: 10 pages; 15th World Conference on Earthquake Engineering, Lisbon : Portugal (2012