STRONG MOTION DATA PROCESSING IN TAIWAN AND ITS ENGINEERING APPLICATION

Transcription

1 STRONG MOTION DATA PROCESSING IN TAIWAN AND ITS ENGINEERING APPLICATION CHIN-HSIUNG LOH Professor Department of Civil Engineering, National Taiwan University Taipei, Taiwan ABSTRACT This paper presents the strong motion data processing and its engineering application from TSMIP and TREIRS strong motion array in Taiwan. The TREIRS system provides almost real time earthquake intensity distribution and the TSMIP data provides useful ground motion data for both earth science and engineering study. Since the sampling rate of these 7 seismographs of TSMIP array is / per second with resolution 1/ bits, then the baseline correction is not necessary applied to these data. Three different approaches to calculate ground velocity and displacement from acceleration data are proposed. Engineering application of these free field ground motion data covers: (i) Develop seismic design spectrum for Sa-value at short period and long period, (ii) Generate spatial ground motion for Earthquake Emergency Responses, (iii) Develop regional phase spectrum for simulation of ground motion, (iv) Study probabilistic dynamic response analysis of non-stationary excitation. INTRODUCTION Taiwan is located at the active arc-continent collision region between the Luzon arc of the Philippine Sea plate and the Eurasin plate. The Philippine Sea plate is colliding onto the Eurasian continent at a rate of 7-8 cm/yr, resulting high seismicity in this region. Seismic disaster in Taiwan over the last twenty years, particularly the 1999 Chi-Chi earthquake, had caused a significant number of victims and direct physical damages. Figure 1 shows the distribution of earthquake hypocenter and the active fault in Taiwan are shown. At present time there are over active faults were identified in Taiwan. Therefore, it is important to establish seismic monitoring system in this area for earthquake hazard mitigation. Due to high seismic activities in Taiwan the Central Weather Bureau (CWB) launched a Taiwan Strong Motion Instrumentation Program (TSMIP/CWB) program in 199, so as to increase the precision of earthquake information determination. In the beginning of 199, CWB began to install a seismic network that includes 7 stations around Taiwan area, the Taiwan Rapid Earthquake Information

2 Figure 1: (a) -D distribution of earthquake hypocenter in Taiwan area; (b) Identified active faults in Taiwan. 7 TREIRS Stations Free-Field Stations Latitude (N) Longitude (E) Figure : Distribution of free-field strong motion instrumentation (over 7 instruments) and 7 real-time system under TSMIP/CWB program in Taiwan.

3 Release System, TREIRS (Lee and Shin, 1997). Digital telemetry and digital recording of three-component high-quality force balanced accelerometers were used in this system for seismic monitoring operations. This system can routinely release the location and magnitude of a strong earthquake as well as the distribution of intensity about 1 seconds (or less) after the occurrence of an inland earthquake. In addition, there are more than 7 free-field strong motion observation stations island-wide distributed, as shown in Figure. The sampling rate of these 7 seismographs is / per second with resolution 1/ bits. Site investigation at each observation station was also launched since. Using suspension PS-logger the bole hole data was collected at each site of seismograph. The N-value, P-wave and S-wave velocities along the depth are estimated. This paper presents the data processing technique and engineering application of the strong motion array data collected from TSMIP and TREIRS array in Taiwan. ROUTINE PROCESSING AND INTEGRATION OF RECORDS There are over different series of seismograph in TSMIP strong motion array, such as: A8, A9, etc. These seismographs provide accurate signal with frequency band up to Hz. Ground motion data collected by CWB did not do any correction at all except the DC correction. For engineering application three different approaches have been used to estimate ground velocity and displacement from the acceleration record. A brief description of these methods is made: Method 1: Since the sampling rate of free-field seismograph is / per second with resolution 1/ bits, the recorded acceleration with frequency smaller than Hz represents almost the true ground acceleration, and there is no need to conduct any baseline correction and only DC correction is needed. To evaluate the velocity and displacement from the acceleration record only a least square fit and/or low pass filter of the direct integrated velocity was used, as shown in Figure. Two sets of ground acceleration data were selected to evaluate the method: Chi-Chi earthquake data form station: TCU8 (near-fault ground motion data) and CHY88. Figure a shows the result from direct integration of acceleration from station TCU8 and Figure b shows the direct integration with least square fit on the velocity data. Comparison on the calculated ground displacement using the result from Figure b provides more realistic displacement because a permanent ground deformation was observed at station TCU8. Similar procedure was also applied to data from station CHY88. Because data collected from station CHY88 did not contain the characteristics of near-fault ground motion. To obtain velocity or displacement either direct integration from acceleration or employ least square fitting the result is almost the same, as shown in Figure. This method has been used in all the

4 engineering application of recorded ground acceleration. Correct Accelerogram a (t) Integrate a (t) for v (t) Least square fit () t = v () t v a () t v Low-pass filter to get v (t) Correct velocity () t = v () t v () t v 7 Correct displacement t = d t d t () () () d 1 Low-pass filter to get d (t) Integrate for displacement d 1 (t) Figure : Integration of strong motion acceleration to obtain velocity and displacement through least square fit or/and low-pass filter modification. Accel.(gal) Vel.(c m /s e c ) Displ.(c m ) 1 TCU Tim e (sec) A ccel.(gal) Vel.(cm /sec) Displ.(c m ) 1 TC U Tim e (sec) (a) (b) Figure : (a) Direct integration of acceleration to obtain the velocity and displacement, (b) Direct integration of acceleration record to obtain the velocity and then linear regression the velocity record, for record from TCU8.

5 A ccel.(gal) Vel.(cm /sec) Displ.(c m ) CHY Tim e (sec) - 1 (a) (b) Figure : (a) Direct integration of acceleration to obtain the velocity and displacement, (b) Direct integration of acceleration record to obtain the velocity and then linear regression the velocity record, for record from CHY88. A ccel.(gal) Vel.(cm /sec) Displ.(c m ) CHY Tim e (sec) Input Acceleration a (t (t) Estimate Noise Level From Pre-event Record a 1 (t) = a (t) - (noise level) Fourier transform F {a 1 (t)} Trend removal (using least square method) Error correction on measurement system: Low-pass filter: < Hz 1% High-pass filter: >. Hz 1% A 1 (ω) V 1 (ω)=a 1 (ω)? (1/i ω) D 1 (ω)=v 1 (ω)? (1/i ω) Inverse Fourier Transform Output: a(t) =F -1 {A 1 (ω)} Inverse Fourier Transform Output: v(t) = F -1 {V 1 (ω)} Inverse Fourier Transform Output: d(t) = F -1 {D 1 (ω)} Figure : Estimation of ground velocity and displacement through filtering analysis in frequency domain. Method : Frequency domain approach was used in this method. After trend removal (DC effect) on the acceleration data, data was transform to frequency domain. Both low-pass filter (< Hz) and high pass filter (>.1 Hz) are applied to the acceleration data. Inverse Fourier 1 transform is then used to obtain the correct acceleration data, a1() t F { A1 ( ω) } is obtained from the inverse Fourier transform of 1( ω) = A1 ( ω) (1 ω) obtained from the inverse of Fourier transform of ( ω) = V ( ω) ( 1 ω) =. The velocity V and the displacement is D, as shown in Figure. 1 1

6 Method : Empirical mode decomposition method was applied to the recorded acceleration. Separate the decomposed acceleration into two parts: high frequency part and low frequency part. Integrate the separated signals, a H (t) and a L (t), so as to obtain the fling effect. Figure 7 show the flow chart of the procedure of the method. The result of this analysis using data from TCU8 (Chi-Chi earthquake) is shown in Figure 8. Ground acceleration Empirical Mode Decomposition or Wavelet analysis Remove lowest frequency signal From the original signal Separate high frequency signal a H (t) and low frequency signals a L (t) Identify fling effect from the decomposed waves Figure 7: Application of EMD method to estimate fling effect of ground motion. A ccel. (g a l) Vel. (cm /sec) 1 TC U 8 (s1-s1): filte re d A ccel. (g a l) Vel. (cm /sec) TC U 8 (s11-s1): filte re d Displ. (c m ) Tim e (s e c ) Displ. (c m ) Tim e (sec) (a) (b) Figure 8: (a) Summation of decomposed acceleration (from No.1 to 1) and the velocity and displacement from direct integration, (b) Summation of decomposed acceleration (from No.11 to 1) and the velocity and displacement from direct integration,

7 1 TC U 8 (s1-s1): filte re d A ccel. (g a l) Vel. (cm /sec) Displ. (c m ) Tim e (sec) (c) Figure 8: (c) Combine (a) and (b) to obtain the velocity and displacement. ENGINEERING APPLICATION OF STRONG MOTION DATA Ground motion data collected from the strong motion array in Taiwan have been applied to earthquake engineering researches and hazard mitigation. In this section the application of strong motion data will be introduced which covers the topics on: (i) Development of seismic design spectrum for Sa-value at short period and long period, (ii) Spatial ground motion estimation for earthquake emergency responses, (iii) Simulation of ground motion using phase spectrum, (iv) Probabilistic dynamic response analysis of non-stationary excitation, Development of seismic design spectrum For the current development of seismic design code in Taiwan, the elastic seismic demand is represented by the design spectral response acceleration S ad corresponding to a uniform seismic hazard level of 1% probability of exceedance within years (return period of 7 years). The TSMIP strong motion array and TREIRS real time strong motion array provide accurately observing ground motions from seismic events. Based on the free field strong motion data collected by the Seismology Center of the Central Weather Bureau during the past, the scenario earthquake induced intensity measure (such as PGA or spectral intensity) around the island is calculated. The empirical attenuation form can be expressed as: b M b IM = Y = f (M,R) = b e [R + b exp(b M)] (1) r 1 where IM is the intensity measure of seismic demand (it can be expressed as peak ground acceleration, or spectral acceleration at any specified period); M and R are the earthquake magnitude and the site-to-source distance, respectively; b 1 through b are constants given

8 earthquake magnitude, focal depth, epicenter and/or surface fault rupture. The seismic demands in terms of peak ground acceleration and response spectrum are calculated for user-specified scenario earthquake. Table 1 shows the estimated model parameters from Taiwan earthquake data. Table 1: Model parameters of attenuation model shown in Eq.(1) Case b 1 b B b b σ ln( Err) PGA S as S al Figure 9 shows the PGA attenuation equation for M=.,. and 7., and the PGA data is also shown in this figure. Data collected from TSMIP array since 1991 is also plot in this figure for comparison. Normally the attenuation relationships of ground motion parameter predict the ground intensity in rock site condition. Based on the uniform hazard analysis, the mapped D D design % damped spectral response acceleration at short periods ( S ) and at 1 second ( S S 1 ) are determined and prepared for each administration unit of village, town or city level. Peak Ground Acceleration, [g] 1E E E E PGA-Attenuation Curve, GeoMean[EW,NS) Data : M = ; Depth = - km, Sall Ca, M=7 Ca, M= Ca, M= Data, M=7.-7. Data, M=.-7. Data, M=.-. Data, M=.-. 1E-1 1E+ 1E+1 1E+ Distance, km Peak Groung Acceleration, (g) 1E E E Comparison For Taiwan Campbell Form, Norman Form and 91 Chi-Chi WQ. data PGA, Taiwan Campbell Form PGA, Norman Form, S/S PGA, Norman Form, R/S PGA, Norman Form, RHW 91 Chi-Chi EQ. Data 91 Chi-Chi EQ. Data, HW 91 Chi-Chi EQ. Data, FW PGA, Taiwan, For FW, Ratio =.7 ML=7., MW=7., Geo-Mean 1E- 1E E E E+ Surface Rupture Distance, (km) Figure 9: (a) PGA attenuation for M=,, and 7. The recorded PGA is also shown in the figure. (b) Chi-Chi earthquake PGA data is plotted w.r.t. Taiwan PGA attenuation equation.

9 Ground Motion Estimation for Earthquake Emergency Responses The TSMIP and TREIRS systems provide accurately observing ground motions from seismic events. In cooperate with these data the Earthquake Hazard Assessment Methodology (HAZ-Taiwan) was developed. This system can estimate the ground motion immediately after the earthquake. This system is aimed to support the central government and local governments to optimize its post disaster management such as rescue, recovery and reconstruction. It aims at enabling the disaster responders to take more effective measures. Under such a goal a simulation system of earthquake disaster processes is being constructed. For a given earthquake information (i.e. magnitude and hypocenter distance), the peak intensity of ground motion can be evaluated using the attenuation model for hard site condition. For other site conditions, the estimation of ground motion intensity should be modified by site amplification factor. This site amplification factor can be developed in advance by using ground motion data collected from the strong motion array data (from Taiwan Strong Motion Instrumentation Program) with different soil conditions. For each specific site the revised intensity measure Y s can be evaluated using the following equation (Chang et al. ): Y s = (C +y s C 1 ) () where C and C 1 are the coefficients of the linear regression form between recorded and estimated intensity measure, as shown in Figure 1. The real-time free-field strong motion data (from Taiwan rapid Information Release System, TREIRS) may also be used to upgrade the ground motion estimation. Figure 11 shows the flowchart of the estimation of spatial ground motion for a given earthquake magnitude and hypocenter. Not only the PGA attenuation equation was used but also the site amplification factored the real-time TREIRS data are implemented in this model. This system can also generate the shake map accurately immediately after an earthquake (within min.). Besides, this system can also be used to perform scenario earthquake for hazard mitigation. To be more realistic, the scenario earthquake should be selected based on probabilistic analysis in order to identify the important source areas that have large contribution factor to each specific site for a prescribed probability. Under the TSMIP a site investigation project was also launched. By using suspension PS-logger the bole hole data was collected. This information provides researchers to identify the site condition at each location of seismograph. One of the important application of these bole hole data is to develop the relationship between S-wave velocity and SPT N-value in any particular region, as shown in Figure 1. borehole data were investigated in YunLin, ChiaYi and TaiNan counties, as shown in Figure 1a. The reported data including soil profiles, SPT-N values and wave velocities measured by Suspension PS Logger were used to develop an empirical equation of shear wave velocities especially for alluvium deposits. It is found that there is a linear relationship between shear wave velocity and depth. After corrected by standard overburden pressure, the standard penetration test value was added into the linear empirical

10 equation. The empirical equation fits the measured data very well and the result is very useful to site effect analysis and(or) other seismic issues, as shown in Figure 1b. Evaluation of Site Effect Because of the dense strong motion array (TSMIP), the site response can be studied in terms of spectra ratio calculated by dividing of the site spectrum by the reference spectrum estimated for a hypothetical very hard rock site. The developed empirical source scaling and attenuation models can be used for the reference spectra calculation. Due to the ample amount of free field ground motion recorded by TSMIP, this approach allows us to evaluate the variability of spectral ratios due to uncertainties introduced by source and propagation path effects and variability in the site response itself. In Taipei basin, there are about seismograph been installed under TSMIP. It provides the opportunity for this research topic. Figure 1 shows the comparison between theoretical spectral ratios obtained using 1-D model and the empirical ratios for stations characterized by different thickness of Quaternary deposits. Simulation Ground Motion Using Phase Spectrum In order to generate spectrum compatible ground motion both target amplitude response spectrum and phase spectrum need to be presented as a prior. Generally, a primitive method to simulate design ground motions is to use the phase spectrum from a certain observed ground motion. Actually, the importance of phase spectrum is illustrated based on an ensemble of ground motion data. TSMIP data provides this opportunity to develop models for regional phase spectrum. A theoretical derivation on phase spectrum is introduced by Sato (1999) on the basis of group delay time that is defined as the derivative of the phase spectrum with respect to circular frequency: ( ) dφ ω t gr ( ω ) = () dω The mean value and standard deviation of group delay times within a certain frequency range express the central arrival time and duration, respectively, of the earthquake motion with frequency content at such a bandwidth. Therefore, it is much easier to model the group delay time than to model the phase spectrum directly. The procedure to generate the mean value and standard deviation of group delay time for each frequency band is shown in Figure 1. Based on the recorded ground motion from a specific region (same site condition) attenuation equation (as a function of earthquake magnitude and distance) of the mean and standard deviation of group delay time for each specific frequency band can be generated. It can be found that the student t-distribution with a degree of freedom φ= can be recognized as the representative distribution of group delay times within the compact support of Meyer wavelet [Chai et al, ]. Based on this result the phase spectrum can be generated and the simulation of ground motion can incorporate with this phase spectrum.

11 Figure 1: Comparison on the estimated (from PGA or Sa attenuation equation) and recorded PGA, Sa (T=. sec) and Sa(T=1. sec). A regression line on the recorded ground intensity is developed. TSM IP data IM 1 = Y = b e b M r = f (M,R ) [R + b exp (b M )] b E arthquake Param eters (M a g n itu d e, D epth, E p icen ter etc.) U p d a te estim a tio n using Taiwan R apid In fo rm a tio n Release System Site Effect Attenuation M odel M odification a = f ( M, R ) y s S = f S ( y a, C, C 1 ) y S R = ( RTD S ) obs ( RTD S ) y s Spatial D istribution of G rou n d M otion E stim ation PD = y S s S f S ( R, D, D 1 ) Figure 11: Flow chart indicates the procedures for estimation of ground motion intensity (PGA, Sa -value) immediately after the catastrophic earthquake.

12 A rm ored 7-C onductor cable CHY1 N v s CHY N v s CHY N v s C able H ead OYO PS-17 Logger/R ecorder 1 H ead R educer W inch Diskette with D a ta Depth (m) U pper (R ) Receiver D epth reference location. m for R 1-R analysis: m id-point of R eceivers. m Low er (R 1) Receiver m 1.7 m Joint 1. m flexible Is o lation C ylinder 1.7 m D epth reference location fo r S -R 1 a n a lysis : m id point of.1 m S -R 1 spacing CHY N v s CHY1 N v s CHY N v s Joint Com bined S h and P -w ave S ource (S ).1 m.7 m 1 Source Driver W eight Tip 1. m Depth (m) O veralllength ~.8 m N o t to S cale Figure 1: Plot of estimated S-wave velocity and SPT-n value along the soil depth using suspension PS-logger (shown on the left figure) at location of seismograph: Stations CHY1, CHY, CHY, CHY, CHY1, and CHY. v' s (after depth corrected)(m/sec) 1 1 v' s= N 1 Vs= N1 1 N 1 (after corrected by overburden pressure) Figure 1: Forty-five bole hole data were collected from YunLin, ChiaYi and TaiNan counties (left ) to estimate the relationship between S-wave velocity and N 1 -value (right).

13 1. A m p lific a tio n. TAP 1. A m p lifica tio n. TAP7 Am plification. 1. TAP Frequency, Hz Frequency, Hz Frequency, Hz Figure 1: Theoretical and empirical spectral ratios (solid lines: mean and ±1 σ limits) of Taipei basin calculated using 1-D models and TSMIP Data (Sokolov, Loh, Wen ). Fourier Transformation x(t) x j (t) X J (ω) t j gr(ω)= Φ J (ω)/ ω Φ J (ω) t j gr(ω) A J (ω) µ j tgr σ j tgr Meyer Wavelet Transformation Mean Value µ j tgr G Central arrival time Standard Deviation σ j tgr Duration Figure 1: Flowchart for generating the mean value and standard deviation of group delay time. CONCLUSIONS Two strong motion recording systems, TSMIP and TREIRS, which include over 7 free field strong motion instrumentations all over the island, provide valuable data for engineering application. The sampling rate of these 7 seismographs is / per second with resolution 1/ bits. A very simple processing technique to evaluate the ground velocity and displacement is proposed. Because of the high resolution data recorded from these array system there is almost no need to do baseline correction on the acceleration data except the trend removal on constant DC shift. To calculate the ground velocity direct integration of the acceleration data with the implementation of low pass filter or a linear trend removal on the original velocity data. With these high quality ground motion data several application were developed, which include:

14 1. Develop seismic design spectrum for Sa-value at short period and long period,. Generate spatial ground motion for Earthquake Emergency Responses,. Study the site effect, particularly on the basin effect,. Develop regional phase spectrum for simulation of ground motion. REFERECES Chen, M.H., K. L. Wen, and C. H. Loh, A Study of Shallow Shear Wave Velocities for Alluvium Deposits in Southwestern Taiwan, J. of the Chinese Institute of Civil & Hydraulic Engineering,. Loh, C. H., C. H. Yeh, L. C. Chen, H. C. Hung, W. Y. Jean and W. I. Liao, Damage Assessment System HAZ-Taiwan for Seismic Loss Estimation in Taiwan, NTU Journal, Sokolove, V. Yu., C. H. Loh, and K. L. Wen, Empirical model for estimating Fourier amplitude spectra of ground acceleration in Taiwan region, J. of Earthquake Engineering and Structural Dynamics, 9, 9-7,. Sokolov, V., C.H. Loh and K.L. Wen, Site-dependent design input ground motion estimation for the Taipei area: A probabilistic approach, Probabilistic Engineering Mechanics, 1, 1, Wu, Y. M., W. H. K. Lee, C. C. Chen, T. C. Shin, T. L. Teng, and Y. B. Tsai,, Performance of the Taiwan Rapid Earthquake Information Release System (RTD) during the 1999 Chi-Chi (Taiwan) Earthquake, Seismo. Res. Let., 71, pp. 8-. Chai, J.-F., Loh, C.-H. and Sato, T. (), Modeling of Phase Spectrum to Simulate Design Ground Motions, Journal of the Chinese Institute of Engineers, Vol., No., pp Sato, T., Murono, Y., and Nishimura, A., 1999, Modeling of Phase Spectrum to Simulate Design Earthquake Motion, Optimizing Post-Earthquake Lifeline System Reliability, Edited By W.M. Elliot and P. McDonough, Technical Council on Lifeline Earthquake Eng., ASCE, Monograph No.1, pp Sato, T. and Imabayashi, H,. 1999, Real Time Conditional Simulation of Earthquake Ground Motion, Earthquake Engineering and Engineering Seismology, 1(1), 7-8.