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PREDICTION OF RESPONSE SPECTRAL PARAMETERS FOR BHUJ EARTHQUAKE (26TH JANUARY 2001) USING COMPONENT ATTENUATION MODELLING TECHNIQUE By DR. SAROSH.H. LODI.

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Presentation on theme: "PREDICTION OF RESPONSE SPECTRAL PARAMETERS FOR BHUJ EARTHQUAKE (26TH JANUARY 2001) USING COMPONENT ATTENUATION MODELLING TECHNIQUE By DR. SAROSH.H. LODI."— Presentation transcript:

1 PREDICTION OF RESPONSE SPECTRAL PARAMETERS FOR BHUJ EARTHQUAKE (26TH JANUARY 2001) USING COMPONENT ATTENUATION MODELLING TECHNIQUE By DR. SAROSH.H. LODI Professor, Department of Civil Engineering NED UNIVERSITY OF ENGINEERING AND TECHNOLOGY KARACHI, PAKISTAN & MUKESH KUMAR Research Assistant, Department of Civil Engineering NED UNIVERSITY OF ENGINEERING AND TECHNOLOGY KARACHI, PAKISTAN PRESENTED BY: MUKESH KUMAR

2 PRESENTATION LAYOUT  Research Background  Available Data  Component Attenuation Modeling  Methodology  Input Parameters & Comparative Analysis  Conclusions and Future Research Direction  Discussion Session

3 BHUJ EARTHQUAKE  It was one of the most devastating earthquake in the history of Indian sub-continent.  Mw=7.7 earthquake, hypocentral depth of 23.6 km, epicenter located near Bhachau city.  There exists a debate whether the earthquake was interplate or intraplate.  Li et al., developed a viscoelastic finite element model and concluded that the cause of plate-interior earthquake was intracontinental thrusting and shearing along the northwestern Indian plate boundary. RESEARCH BACKGROUND

4 RESEARCH OBJECTIVES  The objective of the research endeavor is to pave way towards the development of Design Response Spectra for Southern Coastal Region (SCRS) for future design of engineering structures and seismic evaluation of existing structures, in the most data scarce environment.  It also aims at assessing the applicability of Component Attenuation Modeling Technique, and future improvements in the technique. RESEARCH BACKGROUND

5 AVAILABLE DATA  The event remained least recorded in the near vicinity of the source.  Digital Strong-motion Accelerographs located at a distance of 238 km provide the Ground Acceleration Records, but the recordings have been infected due to the location of accelerograph in a high rise building.  Only usable recordings are Structural Response Recorders (SRR) data. AVAILABLE DATA

6 STRUCTURAL RESPONSE RECORDER DATA  Thirteen SRR located within a periphery of 300 km from the epicenter recorded spectral acceleration for varying natural time period of 0.4 sec, 0.75 sec and 1.25 sec with a fixed damping ration of 5%.  SRR stations have been divided into three categories based on site soil conditions. The sites have been categorized into Rock, Quaternary, and Tertiary; using NEHRP site classification scheme.  The sites are categorized into three schemes using Geologic Map of India (1962), at a scale of 1:2,000,000, which may be cause of uncertainty. AVAILABLE DATA

7 TABLE SHOWING SRR VALUES Epicentral Distance (Km) Sa-5% Damped Site Condition 0.4 sec0.75 sec1.25 sec T T Q T R R Q Q R R Q Q Q AVAILABLE DATA

8  CAM is the modified version of stochastic simulation method using wave attenuation model, developed by Boore (1983).  It is a technique proposed by Lam et al., to predict response spectral parameters of an earthquake for regions with scarcity of earthquake ground motion data.  The idea is based on the finding of Atkinson and Boore, that the source models for interplate and intraplate regions exhibit similar frequency content properties. COMPONENT ATTENUATION MODELING (CAM) COMPONENT ATTENUATION MODELING

9 Component Attenuation Modeling Technique Response spectral parameter of interest (SDmax, SVmax and SAmax) Constant pertaining to spectral parameter of interest Source factor Geometric factor Anelastic attenuation factor Upper crust factor, product of Cm and Cu for mid-crust amplification and combined upper crust amplification and attenuation COMPONENT ATTENUATION MODELING

10 METHODOLOGY  The SRR values have been divided into two sections.  Data recorded on Rock sites.  Data recorded on Quaternary and Tertiary sites.  Recorded is compared with prediction of CAM and orthodox stochastic simulation. METHODOLOGY

11 PARAMETERS USED FOR CAM  Mw=7.7  Mid-crust exhibits Pre-Cambrian Crystalline basement and upper crust consists of Phanerozoic sedimentary sequence Lozios et al.  The thickness of the crust is taken to be 40 km, so the Geometric Attenuation characteristics are similar to ENA. INPUT PARAMETERS

12 Predicted V/s Recorded Distance (km) Sa/g ValuesCorner Periods Peak Spectral Parameters T1T1 T2T2 SdSd SvSv SaSa * COMPARATIVE ANALYSIS

13 Graph Illustrates the predicted DRS V/S SRR values at the distance of 150 km COMPARATIVE ANALYSIS

14 Graph Illustrates the predicted DRS V/S SRR values at the distance of 166 km COMPARATIVE ANALYSIS

15 PREDICTION ON TERTIARY SEDIMENTS Distance (km) Sa (g) Values Observed Sa (g) Values Predicted Ratio Observed/Predicted N.A N.A N.A N.A. COMPARATIVE ANALYSIS

16 PREDICTION ON QUATERNARY SEDIMENTS Distance (km) Sa (g) Values Observed Sa (g) Values Predicted Ratio Observed/Predicted N.A N.A N.A N.A COMPARATIVE ANALYSIS

17 USING STOCHASTIC SIMULATION METHOD Distance (km) Recorded valuesPredicted with CAM Predicted With (AB95) Model COMPARATIVE ANALYSIS

18 CONCLUSION  The observed data seem to be in overall agreement with that predicted by CAM and stochastic simulation of AB95 model.  The sites classified as sediments are under predicted by the applied technique, due to soil amplification.  The maximum value of amplification due to sedimentary site condition is observed at a distance of 238 km, shows that SRR was stationed in Ahmedabad City; which was the worst affected in the earthquake. CONCLUSION

19 CONCLUSION (Contd)  CAM successfully predicts Response Spectral Parameters in the available period range i.e. in velocity controlled regime.  Due to unavailability of ground acceleration data, in near- source region, restricts to assess its applicability in all period ranges.  Yet, It may be concluded that an ad-hoc design response spectra may be developed using CAM, for region with scarcity of data. CONCLUSION


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