Seismic risk study of a low-seismicity region dominated by large-magnitude and distant earthquakes

Journal of Asian Earth Sciences 64 (2013) 77–85

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Seismic risk study of a low-seismicity region dominated by large-magnitude and distant earthquakes Li-Ping Huang ⇑ School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore, Singapore

a r t i c l e

i n f o

Article history: Received 3 November 2011 Received in revised form 12 November 2012 Accepted 29 November 2012 Available online 8 December 2012 Keywords: Seismic risk analysis Low-seismicity region Large-magnitude and distant earthquake Liquefaction potential

a b s t r a c t There is an urgent need to perform seismic risk studies prior to the construction of vital facilities, such as liquefied natural gas terminals, in low-seismicity regions that are dominated by large-magnitude and distant earthquakes. Existing attenuation models were compared with local earthquake records in Singapore to determine a suitable attenuation relationship for modeling large-magnitude and distant earthquakes. Peak ground motions corresponding to exceedance probabilities of 10% in 50 years and 1% in 50 years can be predicted, such that the modeled ground motion can be simulated based on local earthquake records. The analysis of liquefaction potentials indicated that individual local deposits have liquefaction potentials with an exceedance probability of 1% in 50 years level. This study helps to improve the understanding of seismic risk in low-seismicity regions such as Singapore and Malaysia. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Singapore is located in a low-seismicity region of the Eurasian plate, where the active seismic sources that may affect the city are located more than 300 km away, along and off the western coast of Sumatra. The Sumatra area, which belongs to the Sunda plate, forms a line parallel to subduction zone. The Australian plate is subducted under the Sunda plate and continues to move forward north to north–northeast at a velocity of 60 mm/year at 6° S, 102° E and 52 mm/year at 2° N, 95° E (Sieh and Natawidjaja, 2000). Where the two plate edges interact, tremendous amounts of energy accumulate for long periods of time until a final release of energy as a series of large earthquakes. According to studies of corals (Natawidjaja et al., 2006, 2007; Sieh et al., 2008), a series of large earthquakes took place in the Sumatra area at 200 year intervals within the past 700 years. Moreover, an earthquake that occurs in the surface rupture under the Mentawai islands is predicted to produce substantial damage in neighboring cities and may yield a tsunami. Singapore experiences a tropical climate throughout the year, with annual rainfall ranging from 2000 mm to 2300 mm (Meteorological Service Singapore, 1997); the entire area is subjected to intensive weathering. The Jurong formation is dominant in the west and southwest regions of Singapore and consists of a series of sedimentary rocks, such as sandstone, mudstone, shale, tuff, ⇑ Tel.: +65 6592 7548; fax: +65 6791 0046. E-mail address: [email protected] 1367-9120/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jseaes.2012.11.044

conglomerate, and limestone, that were deposited during late Triassic to early or mid-Jurassic (Agus et al., 2005; Indrawan et al., 2006; Krisdani et al., 2008; Rahardjo et al., 2004, 2008). The sandstones have become weak and friable, and mudrocks are reduced to clay of variable hardness as a result of intensive weathering (Zhao et al., 1999). Soil properties vary according to the regional weathering and topographic conditions, which makes it necessary to independently consider the soil condition in particular regions. The engineering characteristics of soil types from different formations in Singapore have been studied (Sharma et al., 1999; Zhao, 1996) for the purpose of constructing large underground structures, such as tunnels and the basements of multi-story buildings. However, these studies have concentrated mainly on soil profiles. Seismic analysis has been largely neglected because Singapore has not suffered from any major seismic disasters during the past few hundred years. Earthquake ground motions felt in Singapore have mostly been due to distant earthquakes occurring in Sumatra. Jurong Island, an artificial island located in the southwest of the main island of Singapore, holds several large petrochemical industrial facilities, including those of BASF, BP, and Shell. Moreover, the government plans to construct the nation’s liquefied natural gas (LNG) terminal on Jurong Island to increase the security of Singapore’s domestic gas supply. The potential for earthquake damages of these facilities might destroy the entire island. It is necessary to perform seismic risk assessments at this site. Seismic risk analysis involves the disciplines of seismology, geology, strong-motion geophysics and earthquake engineering. The scope of this study includes the following items: (a) historical seismicity; (b)

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earthquake risk analysis; (c) earthquake response analysis; and (d) the evaluation of liquefaction potentials.

2. Historical seismicity Earthquake hazard and risk analysis addresses the potential damage and loss from future events. The first step is to analyze historical earthquakes and make projections about future seismicity. Data from two earthquake databases are included: the United States Geological Survey (USGS) from 1973 through 2010 and the International Seismological Centre (ISC) from 1900 through 1972. A homogeneous earthquake catalog is required for the analysis of historical seismicity. As known, moment magnitude (Mw) does not saturate for large earthquakes as it is directly derived from seismic moment which is related to earthquake physics (slip, fault area, and rigidity). To compile a homogeneous earthquake catalog, different magnitudes types, e.g. body wave magnitude (mb) and surface wave magnitude (MS), are converted into Mw using the regression relations derived based on global data (Das et al., 2011) because of the absence of regional regression relations for the specified area. Fig. 1 shows the locations of past earthquakes with Mw P 5:0 within a distance of 1000 km from Jurong Island. The historical earthquake data within the 1000 km radius circle, shown as dots in Fig. 1, were distributed mainly along the Sumatra fault zone. The region covers between 90° E and 110° E in longitude and between 10° S and 10° N in latitude. The earthquake sources closest to the study site consist of the Great Sumatra fault and the Sumatra subduction zone. Huge earthquakes have been scattered sparsely along the 1900 km-long Sumatra fault zone.

Three giant earthquakes with M w P 8:0 have occurred along the Sumatran megathrust since 2000. The 1300 km-long Sumatra– Andaman rupture of the Sunda megathrust that occurred on 26 December 2004 generated a giant earthquake of moment magnitude 9.2. Estimates show that the great Sumatra earthquake and Indian Ocean tsunami of December 26, 2004, resulted in a death toll of over 200,000, more than 141,000 ‘‘missing’’ persons, over 2 million people displaced and billions of dollars in economic damage (EERI, 2005). Rupture of the Simeulue–Nias segment on 28 March 2005 generated an earthquake with a moment magnitude of 8.7 (Hsu et al., 2006; Nalbant et al., 2005). On 12 September 2007, the Mentawai patch ruptured and produced a moment magnitude 8.4 earthquake and several aftershocks (Natawidjaja et al., 2007; Sieh et al., 2008). Among historical earthquakes, the two earthquakes closest to the study site occurred in 1943, at the same location about 400 km from the study site, with moment magnitudes of 7.4 and 7.6. To date, there has been no evidence of local seismic events in Singapore, and all ground tremors felt in this area were generated by distant Sumatran earthquakes (Pan and Sun, 1996). No significant damage has been caused by these earthquakes. Tremors felt in Padang, Indonesia during the 12 September 2007 earthquake near Bengkulu in southern Sumatra had a Modified Mercalli Intensity (MMI) of level VII, according to USGS website. Padang and Singapore are about 190 km and 549 km from the seismic source, respectively. When the seismic wave reached Singapore, the observed MMI had been reduced to level III. Because building regulations in Singapore had no seismic provisions, and there was a lack of consideration of the effects of soil on structures, occupants in more than 300 buildings reported feeling the tremor. Sensitivity

Fig. 1. Historical seismic events with moment magnitudes larger than 5.0 within a 1000 km radius of Singapore; data include United States Geological Survey (USGS) records from 1973 through 2010 and International Seismological Centre (ISC) records from 1900 through 1972.

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to seismic events makes it necessary for building managers or government officers to better understand the seismic risks to Jurong Island and thus control structural damages that might occur. 3. Earthquake risk analysis 3.1. Attenuation relationships for low-seismicity regions It is well recognized that ground motions due to earthquakes are affected by the earthquake source condition, the source-to-site transmission path, and site conditions. In seismic risk analysis, attenuation modeling is used to provide ground motion intensity as a function of magnitude, site-to-source distance and other descriptive parameters. Douglas (2001) presented a comprehensive worldwide summary of strong-motion attenuation relationships for peak ground acceleration (PGA) and spectral ordinates (1969–2000). Conventional empirical modeling approaches are suitable for near-fault predictions in high-seismicity regions where ground motion data are abundantly available and distances less than 100 km are considered. For the subject region, large magnitude earthquakes are predominantly more distant. The recorded data contain low frequency components because high frequency components disappear with energy dissipation during wave propagation. In such cases, distance attenuation parameters should be an important factor in far-fault attenuation predictions. Table 2 summarizes five existing attenuation models derived from earthquakes in eastern North America, east and southeast Asia and worldwide, which include distant earthquakes verifications. The Jacob90 model (Jacob et al., 1990) presented a composite attenuation relationship with two separate regressions: one was based on six earthquakes with a magnitude range of 4:7 6 M 6 6:4 and epicenter distances ranging from 40 to 820 km, and the other was based on two earthquakes of magnitude 1.8 and 3.2 with distances less than 20 km. Model Dahle90 (Dahle et al., 1990) used records from eastern North America, China, Australia, and Europe with source-to-site ranges between 6 and 1300 km to develop attenuation models for intraplate regions. The Free96 model (Free, 1996; Free et al., 1998) used 865 records of rock sites and 171 records of soil to simulate the attenuation model. The earthquakes considered in the Free96 model had distances to epicenter ranging from 0 to 820 km. Two attenuation models were developed for low and moderate seismicity regions: Lam00 (Lam et al., 2000), developed for East China, and Megawati10 (Megawati and Pan, 2010), developed for the Singapore and Kuala Lumpur area. The F-crust attenuation

model within the component attenuation model (CAM) framework has been developed for PGA predictions in low and moderate seismicity regions. CAM is based on stochastic simulations of the seismological model. The proposed attenuation model considers source effects, long distance attenuation, regional upper crustal effects and soil resonance. The CAM F-crust model has also been verified by PGA records from five earthquakes that were generated at the subduction zone of the Indonesian Arc and the Burmese Arc (Balendra et al., 2002). Megawati and Pan (2002, 2010) and Megawati et al. (2003, 2005) have developed a set of attenuation relationships for the Singapore and Kuala Lumpur area. The attenuation model for subduction earthquakes in Megawati10 considered two dominant factors: large amplitude and long distance. The authors considered source-to-station distances range from 200 to 1500 km. The attenuation relationship was validated using a series of ground motion data recorded by the network of seismic stations in Singapore that were subjected to 12 Sumatran megathrust earthquakes from January 2000 through December 2007. 3.2. Ground motion records The Meteorological Service of Singapore (MSS) established a network of seismic stations in Singapore in 1996. The network consists of two stations equipped with STS-2 very broad band seismic sensors, four stations with WR-1 strong motion sensors and two stations with Smart-24A sensors. Four of the down-hole arrays within the MSS network are located on soft soil or reclaimed land. Ground motion records were collected from sensors subjected to four earthquakes generated in the Sumatra region; three of these events were subduction earthquakes and one was a fault earthquake. The three subduction earthquakes were the 16-August2009 earthquake (Mw = 6.7), 30-September-2009 earthquake (Mw = 7.6) and 12-September-2007 earthquake (Mw = 7.9); the fault earthquake was on 1-October-2009 (Mw = 6.6). The source location, depth, distance and moment of magnitude information is shown in Table 1. Ground motions recorded by the seismic stations include 12 sets of ground motions for the 1-October-2009, 16-August-2009, and 30-September-2009 earthquakes and 5 data sets for the 12-September-2007 earthquake. Left column in Fig. 2 shows the three components of acceleration, denoted E–W, N–S and Z, at the Katong Park (KAPK) seismic stations subjected to the 30-September-2009 earthquake. The horizontal E–W and N–S components had PGAs of 3.02 cm/s2 and 3.08 cm/s2, respectively. Right column in Fig. 2 shows the records obtained at the Beatty Secondary School (BESC) seismic station subjected to the

Table 1 Four Sumatra region earthquakes used for PGAs prediction verification. Earthquake no.

1 2 3 4

Date

12-September-2007 16-August-2009 30-September-2009 1-October-2009

Time (GMT)

23:49:04 7:38:22 10:16:09 1:52:27

Source Latitude

Longitude

2.62° 1.48° 0.72° 2.48°

100.84° E 99.49° E 99.87° E 101.52° E

S S S S

Depth (km)

Moment of magnitude

R (km)

Earthquake type

35 20 81 9

7.9 6.7 7.6 6.6

549 576 499 492

Subduction Subduction Subduction Fault

Table 2 Five existing attenuation relationships for long-distance earthquakes. Reference

Model notation

Magnitude range

Distance to epicenter (km)

Jacob et al. (1990) Dahle et al. (1990) Free (1996) Lam et al. (2000) Megawati and Pan (2010)

Jacob90 Dahle90 Free96 Lam00 Megawati10

1.8–6.4 2.9–7.8 1.5–6.8 P6 5.4–9.1

40–820 6–1300 0–820 10–1000 200–1500

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Fig. 2. Ground motion data recorded at the KAPK seismic station subjected to the 30-September-09 earthquake in left column, and at the BESC seismic station subjected to the 12-September-07 earthquake in right column.

Fig. 3. Comparison of the horizontal PGAs calculated using the Jacob90, Dahle90, Free96, Lam00 and Megawati10 models for Mw values of 6.6, 6.7, 7.6 and 7.9 and data recorded during the 1-October-09 (Mw = 6.6), 16-August-09 (Mw = 6.7), 30-September-2009 (Mw = 7.6) and 12-September-2007 (Mw = 7.9) earthquakes by digital seismic stations in Singapore.

12-September-2007 earthquake, with PGAs of 3.43 cm/s2 and 3.25 cm/s2 in E–W and N–S directions, respectively. The KAPK and BESC seismic stations, both equipped with WR-1 strong motion sensors, are part of the seismic station network. In contrast to typical short distance earthquake records of 10–30 s, the long distance earthquake records lasted for more than 4 min. However, the high frequency components tend to be attenuated significantly in long distance records.

3.3. Comparison between attenuation relationships and records The five attenuation relationships listed in Table 2 were intended to predict the PGAs for distant earthquakes ranging from 300 km to 1000 km to the epicenter. Thus, the seismic sources could be modeled as single point sources. All of the attenuation relationships summarized here give predictions for the horizontal components only. Fig. 3 shows the comparison of horizontal PGAs

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predicted by Jacob90, Dahle90, Free96, Lam00 and Megawati10, for earthquakes with moment magnitudes of 6.6, 6.7, 7.6 and 7.9. In the log–log plots of Fig. 3, it can be seen that the PGAs calculated based on Jacob90, Dahle90, Free96 and Lam00 had trends that descended faster with distance than the trend predicted by Megawati10. Jacob90, Dahle90, Free96 and Lam00 overestimated the PGAs relative to the recorded data for all four events. Results of the Megawati10 estimate were lower than the recorded data, especially for the 1-October-2009 earthquake and 16-August-2009 earthquakes. Among the five attenuation relationships shown here, the PGAs predicted by Jacob90 and Lam00 gave the closest regressions to the recorded data for the 1-October-2009 and 16-August2009 earthquake cases. The attenuation relationship from Jacob90 also gave good predictions for the 30-September-2009 and 12-September-2007 earthquake, whereas Lam00 provided the largest values for the two events. Lam00 PGA prediction for these two earthquakes did not match the actual ground motion records. The results showed that the attenuation relationship of Jacob90 was the best choice among the five published attenuation relationships to predict PGAs for use in low-seismicity region risk studies.

Fig. 4. Standard deviation of the estimate of the mean of the annual number of events as a function of sample length and magnitude.

3.4. Local ground motion development Site-specific response spectra can be generated by deterministic seismic hazard analysis (DSHA) or a probabilistic seismic hazard analysis (PSHA) (Reiter, 1990). Because Singapore is in a low-seismicity region of Southeast Asia, there are not enough actual and reliable earthquake records to derive the response spectrum for the study site. The PSHA approach was used because it considers potential earthquake sources that may be significant to the site, the frequency of occurrence and the distance to source. The evaluate the LNG terminal design for the subject area, two probability of exceedance levels, Operating Basis Earthquake (Robertson and Wride) and Safe Shutdown Earthquake (Rosset and Whitman), were considered, as recommended by the USA National Fire Protection Association standard NFPA 59A-2001 (National Fire Protection Association, 2001). OBE and SSE correspond to probabilities of exceedance of 10% in 50 years (recurrence period of 475 years) and 1% in 50 years (recurrence period of 4975 years), respectively. In the earthquake catalog for calculating seismic moment rates, dependent events (i.e., aftershocks and foreshocks) are removed using the window technique with a scan within distance and time (Gardner and Knopoff, 1974). For large events like the Sumatra earthquake of December 26, 2004, dependent events are manually removed from the catalog because of the relatively long period of aftershock activities. The frequency of earthquake occurrences can be roughly estimated by calculating rates of seismic moment accumulation of each segment for given periods. A Gumbel distribution is typically used to fit the PGAs for various return periods:

F ¼ c expð expðaðx  bÞÞÞ

ð1Þ

where F is the non-exceeding probability, x is the PGA and a, b and c are constants. Once the relationship between the PGA and recurrence period is built, PGAs corresponding to the OBE and the SSE exceedance levels can be obtained. A complete earthquake catalog is of basic importance for the studies related to seismic moment rates. The completeness analysis method described by Stepp (1972) is applied in this study. For each magnitude interval in Fig. 4, the points are supposed to give a linear relation if the catalog is complete. It can be seen from the figure that the data for 5:0 6 M W 6 5:4 and 5:5 6 M W 6 5:9 appear complete for the past 50 years, from 1961 through 2010. For the set 6:0 6 MW 6 6:4 the data appear complete for the past 80 years, that is, from 1931 through 2010. For any earthquakes with the moment magnitude larger than or equal to 6.5, they were

Fig. 5. The relationship between recurrence period and peak ground acceleration determined using the Jacob90 attenuation model.

supposed to have been reported. It is reasonable to assume that the earthquake complete catalog includes seismic events recorded from 1931 through 2010 with a cut-off moment magnitude of 6.0. The attenuation relationship according to Jacob90 has been applied to the earthquake records for estimation of the relationship between peak ground acceleration and recurrence period. Fig. 5 shows the recurrence period versus Gumbel distribution plot superimposed over the recurrence period versus horizontal peak ground acceleration plot. Thus, the PGAs corresponding to the OBE and SSE levels predicted by Jacob90 can be read from the recurrence period versus Gumbel distribution plot. Values of 30.0 cm/s2 for the OBE level and 53.2 cm/s2 for the SSE level were adopted for modeling base acceleration in the horizontal direction. The designed acceleration response spectra recommended in the IBC 2006 code (International Code Council, 2006) was adopted, and an adjustment of the level of the acceleration spectra has been applied such that the designed input waveforms can be obtained. The response spectrum of the recorded accelerogram was matched with the target design spectrum by scaling up (or down) the timehistory based on the amplification (or reduction) (Mukherjee and Gupta, 2002). The key technique is an iterative scheme to lead the time history to the average value of the target spectrum over ðiþ1Þ the corresponding period-band. In the i + 1 th iteration, fj ðtÞ ðiÞ changes based on fj ðtÞ according to following formula:

R 2aj ðiþ1Þ

fj

ðiÞ

2a =r ½PSAðTÞt arg et dT

ðtÞ ¼ fj ðtÞ R 2a j j

i 2aj =r ½PSA ðTÞcalculated dT

j ¼ 1; 2; . . . ; N

ð2Þ

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where [PSA(T)]target is the target pseudo-spectral acceleration at period T and [PSAi(T)]calculated is the calculated PSA determined by integrating the equation of motion for the oscillator of period T. In each step, the error at time-period T is calculated as

errori ðTÞ ¼

j½PSAðTÞt arg et  ½PSAi ðTÞcalculated j ½PSAðTÞt arg et

ð3Þ

This error is averaged over each iteration, and the calculation is continued until the average error fell below a tolerance limit. Historical earthquake data recorded at sites with the same soil formation as the project site in Singapore, NTU-E, NTU-N and NTUZ, were adopted to develop the base ground motion corresponding to 10% in 50 years and 1% in 50 year cases. These reference data were collected from one of the seismic stations located on a rock outcrop site at the Nanyang Technological University, west of Singapore, which was subjected to the 30-September-2009 earthquake. This rock outcrop site is one component of the network of seismic stations in Singapore. Fig. 6 shows the developed horizontal ground motion at bedrock corresponding to the OBE and SSE levels. 4. Earthquake response analysis A site response study was used to determine the free-field ground motion at various locations within the site soil profile. Shear wave velocity is an index property used to evaluate the soil amplifications. The EERA (Equivalent-linear Earthquake Response Analysis) program, developed in 1998 using FORTRAN 90 according to the same basic concepts as SHAKE program, was applied to compute the response in a horizontally layered soil model subjected to shear waves. EERA assumes that the soil behaves as an equivalent linear model and adopts the wave propagation solutions proposed by Kanai (1951), Rosset and Whitman (1969) and Tsai and Housner (1970). The near surface geophysical investigations, the standard penetration test (SPT), cone penetration test (CPT) and shear wave velocity test were conducted to understand the soil properties. The project area is at 1.24 °S, 103.67 °E on Jurong Island, Singapore. Three typical sites, denoted site S-01, S-16 and S-12, were distributed at the vertices of the triangle. Site S-16 is approximately 238 m south and 124 m west of site S-01, and site S-12 is about 288 m south and 28 m west of site S-01. The CPTs were conducted for every 0.1 m of depth up to 26.6 m, 23.4 m and 23.3 m near sites S-01, S-16 and S-12, respectively. As shown in Fig. 7, the average cone penetration resistance from 7.4 to 9.0 m depth at site S-01 was about 0.95 MPa. The average cone penetration resistance from

0.2 to 1.9 m depth at site S-12 was about 0.15 MPa. The cone penetration area for site S-16 was generally low, from 9.1 to 10.5 m depth. SPTs have been conducted for every 1 m of depth up to 34.6 m, 40.7 m and 36.4 m in boreholes near site S-01, S-16 and S-13, respectively. The upper portion of the soils, from 0 to about 9 m depth at S-01, 0–23 m depth at S-16 and 0–17 m at S-12, was filled with loose and medium dense grayish-brown silky sand and light olive brown silky sand. The lower zones below the sandfilled layer were typical of the Jurong formation soil profile. The sands in these layers ranged from medium dense, brownish grey, fine to coarse sand with seashell fragments to very stiff, dark grey silt. The silt became hard and dark grey with light grey silt containing traces of fine-grained sand and rock fragments. The Jurong formation soil properties were the most cohesive and consistently ranged from stiff to hard. The entire layers were affected by weathering until they reached the rock base. The shear wave velocity profiles near sites S-01, S-16 and S-12, as shown in Fig. 7, are obtained from in situ measurements. The average measured shear wave velocity values for site S-01, S-16 and S-12 were 189 m/s, 218 m/s and 263 m/s, respectively. According to site class definitions in the IBC 2006 codes (International Code Council, 2006), the project site was classified as Class D. The results of the site response analysis with exceedance probabilities of 10% in 50 years and 1% in 50 years are shown in Table 3. At site S-01, S-16 and S12, the peak surface ground motions to the OBE level are 47.9, 43.3 and 39.3 cm/s2, respectively. The corresponding peak surface ground motions to the SSE level are 82.3, 82.6 and 68.3 cm/s2.

5. Evaluation of liquefaction potentials 5.1. Liquefaction potential safety factor evaluation procedure A construction site should normally be free from risks of liquefaction in the event of an earthquake. Simplified methods have been presented for evaluating liquefaction potentials under earthquake loading (Ishihara, 1977; Iwasaki et al., 1984; Seed and Idriss, 1971; Seed et al., 1983, 1985). These evaluation procedures were the standard practice throughout the world until Youd et al. (2001) incorporated several updates and arguments to derive a set of simplified procedures in 1996–1998. The liquefaction potential safety factor evaluation procedure applied in this study is described as below. Liquefaction of soil will potentially occur if the factor of safety (FS), which is the ratio of the cyclic resistance ratio (CRR) to the cyclic stress ratio (CSR), is less than or equal to one. Seed and Idriss (1971) devised a formula for the cyclic shear stress ratio:

Fig. 6. Developed horizontal ground motion at bedrock corresponding to OBE and SSE levels.

L.-P. Huang / Journal of Asian Earth Sciences 64 (2013) 77–85

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Fig. 7. Cone penetration resistances and shear wave velocity profiles for site S-01, S-16 and S-12.

Table 3 Peak surface ground accelerations for different borehole sites (units: cm/s2). Reference base acceleration

NTU-E NTU-N NTU-Z

S-01

S-16

S-12

OBE

SSE

OBE

SSE

OBE

SSE

47.0 42.0 47.9

81.4 71.9 82.3

41.0 42.8 43.3

82.4 71.1 82.6

39.3 32.3 34.9

68.3 61.3 62.4

CSR ¼ sd =r0v ¼ 0:65ðamax =gÞðrv =r0v Þrd

ð4Þ

where sd is a constant equivalent to the repeating shear stress amplitude; amax is peak horizontal ground acceleration; g is the acceleration due to gravity; and rv and r0v are total and effective overburden pressure at the depth under consideration. The stress reduction factor rd can be approximated by the following equation (Youd et al., 2001):

rd ¼

1:000  0:4113z0:5 þ 0:04052z þ 0:001753z1:5 1:000  0:4177z0:5 þ 0:05729z  0:006205z1:5 þ 0:001210z2 ð5Þ

where z is the depth below ground surface in meters. Among the in situ tests for evaluating liquefaction, CPT, which uses continuous soil profiles, has the advantages of high accuracy and repeatability (Ishihara, 1993; Lee et al., 2003). CPT exploration and the liquefaction potentials of the sites S-01, S-16 and S-12 were investigated. The clean-sand base curve for evaluating liquefaction resistance proposed by Robertson and Wride (1998) can be approximated by:

If 50 6 ðqc1N Þcs < 160; CRR7:5 ¼ 93½ðqc1N Þcs =10003 þ 0:08

ð6aÞ

If ðqc1N Þcs < 50; CRR7:5 ¼ 0:833½ðqc1N Þcs =1000 þ 0:05

ð6bÞ

where CRR7.5 is the cyclic resistance ratio for a moment magnitude of 7.5 earthquake, and (qc1N)cs is the clean-sand cone penetration resistance in atm (1 atm is approximately equal to 100 kPa). Thus, the safety factor can be calculated as follows:

FS ¼ ðCRR7:5 =CSRÞMSF

ð7Þ

where MSF is the magnitude scaling factor of moment magnitude Mw, as recommended by Youd et al. (2001):

MSF ¼ 102:24 =M 2:56 w

ð8Þ

5.2. Site liquefaction evaluation results As recommended by Iwasaki et al. (1984), the liquefaction potential index IL at a given site is

IL ¼

20 X F L WðzÞdz

ð9Þ

0

where FL = 1  FS for FS 6 1:0 and FL = 0 for FS > 1.0. W(z) is a function of the depth z defined as W(z) = 10  0.5z. The preliminary proposed guidelines based on the soil liquefaction index IL are as follows: (a) IL ¼ 0, the liquefaction potential is very low; (b) 0 < IL 6 5, the liquefaction potential is low; (c) 5 < IL 6 15; the liquefaction potential is high; and (d) IL > 15, the liquefaction potential

Fig. 8. Liquefaction potential assessment using methodologies updated by Youd et al. (2001).

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is very high. The liquefaction resistance factor and liquefaction potential index have proven to be effective at 64 liquefied sites and 23 non-liquefied sites during six historical earthquakes (Iwasaki et al., 1984). The liquefaction potential estimation results at site S-01, S-16 and S-12 to the OBE and SSE levels are shown in Fig. 8. The calculated factors of safety FS along the depth are, for the most part, larger than 1.0 for the three sites. Whereas the values to the SSE levels were less than 1.0 in few parts in site S-01 and site S-16. For example, the factor of safety are less than the layer of 6.4–9 m at site S-01 and the layer of 5.6–10.5 m at site S-16 are. It is easy to convert FS to IL, and the liquefaction failure potential defined in the Iwasaki risk criteria can be obtained. For S-12, the liquefaction failure potential was extremely low. For S-01 and S-16, the liquefaction failure potential was low. However, there was potential for liquefaction at site S-01 and S-16 with a probability of exceedance of 1% in 50 years. 6. Conclusions and discussions Mentawai Island, one of the nearest Sumatra megathrust fault part to Singapore, will suffer a large energy relief in the near future, according to the supercircle of earthquakes derived by Sieh et al. after an investigation of epicenter local corals (Sieh et al., 2008). The Singapore LNG terminal construction site is located on the artificial Jurong Island adjacent to the existing petrochemical facilities of BASF, BP and Shell. The island soil is divided into two layers: upper sands of different thickness and the lower Jurong formation. The Jurong formation features medium dense, brownish grey sand and recently deposited stiff and dark grey silt. The sandstones in the Jurong formation have been reduced to clay of variable hardness due to tropical rainfall that occurs throughout the year. Because of these special geographic factors, a seismic risk study has been conducted at the LNG terminal site using a comprehensive understanding of geophysical and geotechnical data to minimize seismic risk and prevent damage to important structures. Conventional attenuation relationships are suitable for nearfault predictions, but are insufficient for the consideration of large-magnitude and long distance earthquakes. The model comparison among a set of attenuation relationships that considered distant earthquakes showed that the one by Jacob90 provided the best choice for seismic hazard assessment in low-seismicity regions such as Singapore. The evaluation of liquefaction potential response output based on local soil characteristics proved that the Jurong formation in Singapore had good soil characteristics at the OBE level. However, for certain depths there was a potential for liquefaction damage at the SSE level; this liquefaction might be induced by tropical rainfall and weathering of individual local deposits. This study helps to improve the understanding of seismic risk in low-seismicity regions, such as Singapore and Malaysia, that are subjected to large-magnitude and distant earthquakes. For structures that function as liquid or gas factories, an SSE level should also be considered due to the potential for earthquake damages that might destroy the entire island. For those layers of soil with a tendency for liquefaction, mitigation of potential liquefaction should be stipulated according to the importance of the type of structure. Acknowledgments The author is grateful to Rybio G Pte Ltd (Meteorological Service Singapore) for providing the standard penetration test, cone penetration test and shear wave velocity test data. The author would also like to thank Meteorological Service Singapore for the use of the earthquake recordings at NTU station.

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