DEVELOPING TIME HISTORIES WITH ACCEPTABLE RECORD PARAMETERS FOR DILLON DAM. Dina Bourliea Hunt, P.E. 1 Justin Beutel, P.E. 2 Christine Weber, P.E.

Transcription

1 DEVELOPING TIME HISTORIES WITH ACCEPTABLE RECORD PARAMETERS FOR DILLON DAM Dina Bourliea Hunt, P.E. 1 Justin Beutel, P.E. 2 Christine Weber, P.E. 3 ABSTRACT Dillon Dam project is located in Summit County, Colorado. Dillon Dam is an earthfill structure constructed on the Blue River in 1962, rising 231 feet above the riverbed. At over 257,000 acre-feet, it contains the largest reservoir in the Denver Water system, diverting water into the South Platte River Basin via the Harold D. Roberts Tunnel. After completing a seismic hazard analysis and calculating a design response spectrum, time histories were developed for use in finite element modeling of Dillon Dam. Several record parameters (i.e. Arias intensity, peak ground velocity, cumulative absolute velocity, and significant duration) were estimated from published articles. Time histories were then preselected from the NGA-West2 Pacific Earthquake Engineering Research Center database using magnitude, distance, and pre-calculated record parameters as part of the search criteria. The overall goal of spectral matching is to achieve a fit as close as possible to the design response spectrum, while not deviating from the Fourier amplitude spectrum over the spectral frequency range of interest, nor changing the non-stationary phasing of the spectrally matched time history. Performing spectral matching using a conventional approach led to unacceptable record parameters, therefore an alternative method of reducing peak ground acceleration scale factors was used to perform the spectral matching. This alternative method resulted in a spectrally matched time history with record parameters closer to the range of design values. This paper presents a summary of the published references used to estimate record parameters, a discussion of the process used to pre-select the time history records, and the trade-offs between achieving a good fit to the design response spectrum and corresponding record parameters. 1 MWH Global, 1340 Poydras Street, Suite 1420, New Orleans, Louisiana 70112, , dina.b.hunt@mwhglobal.com 2 Pacific Gas and Electric Company, 245 Market Street, MC N11D, San Francisco, California 94105, , jv1w@pge.com 3 MWH Global, 1560 Broadway 18th floor Denver, Colorado 80202, christine.t.weber@mwhglobal.com USSD will insert footer text here 1

2 BACKGROUND Located in Summit County, Colorado, Dillon Dam is an earthfill structure constructed on the Blue River in 1962, rising 231 feet above the riverbed. At over 257,000 acre-feet, it contains the largest reservoir in the Denver Water system, diverting water into the South Platte River Basin via the Harold D. Roberts Tunnel. A finite element dynamic deformation analysis was to be performed for the dam, thus requiring a design seismic event to be defined and the time histories to be developed for use in the deformation model. Probabilistic and deterministic seismic hazard analyses were completed to compute a design response spectrum. Given the results of these analyses, it was decided that a deterministic response spectrum would be the basis for development of time histories. The controlling source for Dillon Dam was identified as a M7.0 event occurring on the Gore Range Frontal Fault, located approximately 5.2 km west of the dam. The fault trace for the Gore Range Frontal Fault (USBR, 2014) is shown in red on Figure 1. N Source: Esri, DigitalGlobe, GeoEye, i-cubed, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community Figure 1: Plan View of Dillon Dam and Gore Range Frontal Fault 2 Dams and Extreme Events

3 Deterministic Response Spectrum The development of a deterministic response spectrum included selecting ground motion prediction equations (GMPEs) and associated weighting. Ground Motion Prediction Equations. The Pacific Earthquake Engineering Research (PEER) Next Generation Attenuation (NGA) West2 relationships were used to estimate ground motions at Dillon Dam. The NGA West2 relationships draw upon a larger dataset and are therefore an improvement on than the previous NGA West relationships. The five relationships are as follows: Abrahamson, Silva, and Kamai (2014) ASK14 Boore, Stewart, Sehan, and Atkinson (2014) BSSA14 Campbell and Bozorgnia (2014) CB14 Chiou and Young (2014) CY14 Idriss (2014) I14 The main inputs for the GMPEs are magnitude, distance, and shear wave velocity. The distance parameters required as input for the deterministic analysis are also shown on Figure 1 (plan view) and Figure 2 (profile view). Figure 2: Cross Section sketch of Gore Range Frontal Fault and Dillon Dam (not to scale) Since Dillon Dam is located on the hanging wall of the Gore Range Frontal Fault (Figure 1 and Figure 2), only four of the five relationships are considered applicable for the site: ASK14, BSSA14, CB14, and CY14. The I14 model was not used because it does not consider the effects of the hanging wall in the calculation of ground motions (Idriss, personal communication, September 30, 2014). The BSSA14 GMPE does not specifically include a hanging wall term, but the effect of the hanging wall is implicitly captured by the use of the Joyner-Boore distance term (RJB), which is the closest distance of the site to the surface projection of the rupture. USSD will insert footer text here 3

4 Additional discussion regarding the applicability of the BSSA14 model to hanging wall sites can be found in the PEER Report Hanging-Wall Scaling using Finite-Fault Simulations by Donahue and Abrahamson (2013). Plots comparing all NGA West2 GMPEs for a range of magnitudes were included in the Donahue and Abrahamson (2013) report and are provided in Figure 3. Figure 3: Comparisons of the hanging-wall results for the NGA West2 Models, from Donahue and Abrahamson (2013) Shear Wave Velocity. The NGA West2 relationships require the input of VS30, the average shear-wave velocity (m/s) over a subsurface depth of 30 meters. This parameter can either be measured or inferred, with a decrease in uncertainty if measured. The shear wave velocity at Dillon Dam was measured in-situ by Stokoe et al. (2008), using spectral analysis of surface waves (SASW). The SASW measurements were performed for finite element modeling purposes and not necessarily to obtain data for up to 30 meters of the foundation. The following equation was used to calculate the VS30 starting at an elevation of 8,720 feet. 4 Dams and Extreme Events

5 VV SS30 = 30 dd VV ss where, d = thickness of layer and V S = shear wave velocity (Equation 1) Only those profiles that extended to depths greater than elevation 8,720 feet were used. The shear wave velocity was estimated by extending the last available layer in the profile to depths of 30 meters (98 feet), adding some conservatism into the calculation since shear wave velocity normally increases with depth. Based on the results of the field tests, a Vs30 of 751 m/s was used to characterize the rock. Deterministic Results. The deterministic inputs are summarized in Table 1. The resulting design response spectrum was calculated by taking the equally weighted average of the four GMPEs. The design (target) response spectrum, along with the response spectra calculated from the four GMPEs, are shown in Figure 4. Table 1. Deterministic Inputs Deterministic Input Parameter Definition Value Mw Moment magnitude 7 RRUP (km) Closest distance to coseismic 4.9 rupture RJB (km) Closest distance to surface 0 projection of coseismic rupture RX (km) Horizontal distance from top of 5.2 rupture measured perpendicular to fault strike Ry0 (km) The horizontal distance off the end of the rupture measured parallel to strike 0 VS30 (m/s) The average shear-wave velocity over a subsurface depth of 30 m 751 Fault Mechanism - Normal fault Dip (deg) Average dip of rupture plane 70 ZTOR (km) Depth to top of coseismic rupture 0 ZHYP (km) Hypocentral depth from the earthquake 10.4 Z1.0 (km)* Depth to Vs=1 km/sec Z2.5 (km)* Depth to Vs=2.5 km/sec W (km) Fault rupture width (km) 21 Vs30 Flag - Measured Region - Global *Z1.0 and Z2.5 estimated from VS30 USSD will insert footer text here 5

6 Figure 4: Comparison of NGA West Relationships and Design (Target) Spectrum SELECTION CRITERIA FOR TIME HISTORIES The search criteria were defined based on the design earthquake event, as defined in Table 1. Time histories were selected from the PEER strong motion database. A search of the NGA West2 database was performed on October 16, 2014 using the initial search criteria discussed below. Earthquakes downloaded from the PEER strong motion database are referred to as seed motions. Initial Search Criteria 1. Magnitude Range considered: M Distance (R RUP ) Range considered: 0-15 km 3. Significant Duration (this criterion was used to reduce the number of potential seed motions) Range considered: seconds (5-95% Arias intensity). The 5-95% significant duration for the design earthquake was estimated using a formula developed by Dobry et al. (1978). Using Equation 2, the estimated 5-95% significant duration (5-95% Arias intensity) for a magnitude 7.0 event is approximately 15.6 seconds. DD = 10 (0.432MM 1.83) where, D = significant duration, in seconds and M = magnitude (Equation 2) 6 Dams and Extreme Events

7 The 5-95% significant duration was also estimated using a method developed by Kempton and Steward (2006) that is based on the site-specific Vs30. Kempton and Steward (2006) developed their model to estimate the significant duration and uncertainty, calculations for the median and ±1 standard deviation (16 th and 84 th percentile) are also presented. The 5-95% significant duration calculated using these two models are summarized in the Table 2. Note that these values were used to narrow down the potential seed motions. Table 2. Significant Duration (5-95%) Reference Significant Duration (s) 16 th Percentile Median 84 th Percentile DIN78 (5-95%) KS06 (5-95%) References: DIN: Dobry, Idriss, and Ng (1978); KS06: Kempton and Steward (2006). 4. Scale Factor Less than 4 Reviewed Parameters The four initial search criteria narrowed down the number of potential seed motions to 27 motions. From those 27 motions, record parameters (the Arias intensity, 5-75% significant duration, peak ground velocity (PGV), and cumulative absolute velocity) were reviewed to verify the values fell within the 16 th to 84 th percentiles. These record parameters were reviewed prior to spectral matching. The methods used to estimate the record parameters are summarized below. 1. Arias Intensity The range of Arias intensity for the design event was estimated using three different equations: 1) Campbell & Bozorgnia (2012), 2) Travasarou et al. (2003), and 3) Abrahamson (personal communication, 2014). The sources and results are presented in Table 3. There is some difficulty in estimating the Arias intensity, as can be seen in the difference between the 16 th and 84 th percentile see Table 3. Campbell and Bozorgnia (2012) point out that Arias intensity exhibits significantly greater amplitude scaling and aleatory uncertainty as compared to the cumulative absolute velocity. USSD will insert footer text here 7

8 Table 3. Arias Intensity. Reference Arias Intensity (m/s) 16 th Percentile Median 84 th Percentile C&B TBA A Peak Ground Velocity The peak ground velocity for the design event was estimated using the NGA West2 spreadsheets for the ASK14, BSSA14, CB14, and CY14 models. The calculated average of the median PGV was approximately 36.2 cm/s and the calculated 84 th percentile of the PGV was approximately 66.1 cm/s. The range of PGV values is provided in Table 4. Table 4. Peak Ground Velocity Reference Peak Ground Velocity (cm/s) 16 th Percentile Median 84 th Percentile NGA West Cumulative Absolute Velocity The relationship developed by Campbell and Bozorgnia (2010) was used to calculate the Cumulative Absolute Velocity (CAV) for the design event. The range of CAV values is presented in Table 5. Table 5. Cumulative Absolute Velocity Reference Cumulative Absolute Velocity (g-s) 16 th Percentile Median 84 th Percentile CB Significant Duration (5-75%) The Brookhaven Model (Silva et al. 1996) was used to estimate the 5-75% significant duration for each of the time histories. The rupture distance and magnitude for the Gore Range Frontal Fault was used as input to the Brookhaven Model. The estimated range of 5-75% significant duration is provided in the Table 6. Table 6. Significant Duration (5-75%) Event Gore Range Frontal Fault M7.0, Distance 4.9 Horizontal Duration (5-75%), seconds 16 th percentile Median 84 th percentile Dams and Extreme Events

9 Iterations and Comparisons The record parameters discussed above are summarized in Table 7. A range is given when more than one reference was used. Record Parameter 16 th PGA (g) Table 7. Summary of Record Parameters PGV cm/s Arias Intensity (m/s) CAV (g-sec) Significant Duration (s) 5%-95% 5%-75% Percentile Median th Percentile After the record parameters for the potential seed motions were verified to fall within the range of values summarized in Table 7, the response spectra for both horizontal motions were visually compared to the target spectra, and candidates were selected for spectral matching. During this process, only one station was chosen for each earthquake record. For example, several stations recorded the Loma Prieta event and were included in the acceptable motions, but after one station resulted in a good spectral match, the ground motions from other stations were not reviewed. The purpose of this was to provide variability in the developed time histories. Overall, a total of ten motions were selected for spectral matching. SPECTRAL MATCHING AND INITIAL SCALING FACTORS Time histories were developed using spectral matching techniques. Spectral matching adjusts the time series in the time domain by adding wavelets to the initial time series. A formal optimization procedure for this type of time domain spectral matching was first proposed by Kaul (1978) and was extended to simultaneously match spectra at multiple damping values by Lilhanand and Tseng (1987, 1988). This time domain procedure has good convergence properties and, in most cases, preserves the non-stationary character of the reference time history which is a key goal in the spectral matching process. The program RSPM v99 (Abrahamson, 1993) was used to perform the spectral matching calculations. Of the ten time histories selected for spectral matching, the three time histories that maintained a good fit to the design response spectrum and similar displacement to the original input motion (no extraneous wavelets added) after spectral matching were selected as the final time histories. The three motions chosen: Darfield, New Zealand M7.0 (PEER ID 6927); Loma Prieta, California M6.93 (PEER ID 768); and the Chuetsuoki, Japan M6.8 (PEER ID 4866). Normally, a time history is scaled to the target peak ground acceleration (PGA) prior to spectral matching. However, when the selected time histories were scaled to the peak USSD will insert footer text here 9

10 ground acceleration, the results after spectral matching resulted in Arias intensity, cumulative absolute velocity, and peak ground velocity that were generally in excess of the 84 th percentile values calculated for the design event. To reduce these parameters, the time histories were scaled to a factor of the target PGA. By modifying the initial scaling factor prior to spectral matching, a decrease in the Arias intensity and CAV is normally observed (personal communication Richard Armstrong, October 17, 2014). The scale factors and resulting PGA are summarized in Table 8. Each of these factors was evaluated and the resulting motion that maintained an acceptable significant duration was selected as the final spectrally matched motion. Table 8. Scale Factor for Peak Ground Acceleration Factor Starting PGA of SEED Record * 0.75* Note: *Corresponds to target PGA As shown in Figure 5, the CAV and Arias intensity show a decrease when reducing the initial motion PGA prior to spectral matching; however, the significant duration also decreases. The black line in Figure 5 is plotted at the lowest acceptable significant duration (5-95%) of 13 seconds. 10 Dams and Extreme Events

11 Figure 5. Record parameters after spectral matching for 4 scale factors after scaling to PGA (0.7, 0.8, 0.9, and 1.0) USSD will insert footer text here 11

12 Final Selections and Plots The final selected motions had a magnitude range from 6.8 to 7.0, distance range (RRUP) km, significant duration (5-95%) range of 12.9 to 13.9 seconds, and initial scale factor of 1.7 to 2.4 (see Table 9). The other record parameters (Arias intensity, peak ground velocity, and cumulative absolute velocity) were also calculated before and after spectral matching for comparison purposes and summarized in Table 9. Modifications to the initial scale factor of the SEED record were successfully implemented on the three final records. The final selected scale factors including a comparison to the default scale to the PGA are illustrated for each motion in Figure 6 through Figure 8. The top plot is the match to the target design response spectrum and the bottom plot is the normalized displacement time history. As shown in Figure 6, the match to the 0.7 x PGA (green line) matches closely with the scaled to the PGA (red line), for both the response spectrum plot and normalized displacement time history plot. For the Darfield event, presented in Figure 7, the adjustment to the PGA prior to spectral matching had very little effect on the end spectrum and normalized displacement time history. Of the three final time histories, the Chuetsu-oki event (Figure 8) probably had the worst fit to the displacement time history after changing the initial scale factor, but overall the fit is still acceptable. 12 Dams and Extreme Events

13 Figure 6. Loma Prieta Response Spectrum and Normalized Displacement Time History Comparison of seed and spectrally matched motions with different initial scaling factors USSD will insert footer text here 13

14 Figure 7. Darfield, New Zealand Response Spectrum and Normalized Displacement Time History Comparison of seed and spectrally matched motions with different initial scaling factors 14 Dams and Extreme Events

15 Figure 8. Chuetsu-oki, Japan Response Spectrum and Normalized Displacement Time History Comparison of seed and spectrally matched motions with different initial scaling factors USSD will insert footer text here 15

16 In summary, there are tradeoffs between achieving a good spectral fit and displacement time history while maintaining acceptable record parameters. However, by choosing a different initial scale factor and not the standard practice of scale to the PGA prior to spectral matching, the engineer can control the resulting record parameters, such as Arias intensity and CAV. As more time history records become available (e.g. PEER NGA West2 database), the input record parameters should be considered when developing time histories for both scaled and spectrally matched motions. 16 Dams and Extreme Events

17 Table 9. Record Parameters before and after Spectrally Matching Event Title Darfield, New Zealand (M7.0) Loma Prieta, Californi a (M6.93) Event ID RRUP VS30 (m/s) Station LINC N67W Gilroy Array #4-090 Arias Significant Duration (s) No. PGA (g) PGV( cm/s) Intensity (m/s) CAV (g-sec) Predominant Period (sec) Predominant Freq. (Hz) 5%-95% 5%- 75% Cycles Seed Spectrally Matched (SF=2.1) 1 Seed Spectrally Matched (SF=2.4) Chuetsuoki, Japan (M6.8) Kawanishi Izumozaki -NS Seed Spectrally Matched (SF=1.7) 1 Source: NGA West2 PEER Database Note: SF = Scale Factor applied prior to spectral matching USSD will insert footer text here 1

18

19 REFERENCES Abrahamson, N.A., W.J. Silva, and R. Kamai (2014) Summary of the ASK14 Ground- Motion Relation for Active Crustal Regions. Earthquake Spectra. Volume 30, Issue3. August. Boore, P.M., J.P. Stewart, E. Seyhan, and G.M. Atkinson (2014). NGA-West2 Equations for Predicting PGA, PGV, and 5%-Damped PSA for Shallow Crustal Earthquakes. Earthquake Spectra. Volume 30, Issue 3. August. Campbell, K. and Bozorgnia, Y. (2010). A Ground Motion Prediction Equation for the Horizontal Component of Cumulative Absolute Velocity (CAV) Based on the PEER-NGA Strong Motion Database, Earthquake Spectra, Volume 26, No. 3, pages , August 2010 Campbell, K. and Bozorgnia, Y. (2012). A comparison of Ground Motion Prediction Equations for Arias Intensity and Cumulative Absolute Velocity Developed Using a Consistent Database and Functional Form, Earthquake Spectra, Vol. 28 No. 3, Campbell, K. W., and Y. Bozorgnia, (2014). NGA-West2 Ground Motion Model for the Average Horizontal Components of PGA, PGV, and 5%-Damped Linear Acceleration Response Spectra. Earthquake Spectra. Volume 30, Issue 3. August Chiou, B. S., and R.R. Youngs, (2014). Update of the Chiou and Youngs NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra. Earthquake Spectra. Volume 30, Issue 3. August. Derouin, S.A., Klinger, R.E. (2014). Revised Fault Characterization for Green Mountain Dam Seismic Hazard Analysis. Technical Memorandum No A, Seismotectonics and Geophysics Group, Bureau of Reclamation, Denver, Colorado, 57pp Dobry, R., Idriss, I. M., & Ng, E. (1978). Duration characteristics of horizontal components of strong-motion earthquake records. Bulletin of the Seismological Society of America, Donahue, J. L., & Abrahamson, N. A. (2013). Pacific Earthquake Engineering Research Center. Retrieved from PEER: Donahue.pdf USSD will insert footer text here 1

20 Idriss I. M., An NGA Empirical Model for Estimating the Horizontal Spectral Values Generated By Shallow Crustal Earthquakes. Earthquake Spectra. Volume 30, Issue 3. August. Kaul, M. K. (1978). Spectrum-consistent time-history generation, Journal. Engineering Mechanical. Div. 104, Kempton, J. J., & Stewart, J. R. (2006). Prediction Equations for Significant Duration of Earthquake Ground Motions Considering Site and Near Source Effects. Earthquake Spectra, Lilhanand, K., & Tseng, W. S. (1987). Generation of synthetic time histories compatiable with multiple-damping response spectra. SMiRT-9, Lausanne, K2/10. Lilhanand, K., & Tseng, W. S. (1988). Development and application of realistic earthquake time histories compatible with multiple damping response spectra. Ninth World Conference Earthquake Engineering Vol. II, (pp ). Tokyo, Japan Pacific Earthquake Engineering Research (PEER). (2014). Pacific Earthquake Engineering Research Center Database. Retrieved October 16, 2014 RSPMATCH (v.99, 1999) Silva, W., Abrahamson, N., Toro, G., & Costantino, C. (1996). Description and Validation of the Stochastic Ground Motion Model. El Cerrito: Pacific Engineering and Analysis. Stokoe, K.H., Yuan, J., Lin, Y-C. and Jung, M.J. (2008). Field Data Summary: SASW Field Testing at Dillon Dam, Colorado. Geotechnical Report No. GR Geotechnical Engineering Center, University of Texas at Austin. Prepared for GEI Consultants, December Travasarou, T., Bray, J. and Abrahamson, N., Empirical Attenuation Relationship for, Earthquake Engineering & Structural Dynamics 32, Dams and Extreme Events