DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM

Transcription

1 DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM by A.K. Ghosh & K.S. Rao Reactor Safety Division BARC/2009/E/025 BARC/2009/E/

2 BARC/2009/E/025 GOVERNMENT OF INDIA ATOMIC ENERGY COMMISSION BARC/2009/E/025 DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM by A.K. Ghosh & K.S. Rao Reactor Safety Division BHABHA ATOMIC RESEARCH CENTRE MUMBAI, INDIA 2009

3 BARC/2009/E/025 BIBLIOGRAPHIC DESCRIPTION SHEET FOR TECHNICAL REPORT (as per IS : ) 0 Security classification : Unclassified 02 Distribution : External 03 Report status : New 04 Series : BARC External 05 Report type : Technical Report 06 Report No. : BARC/2009/E/ Part No. or Volume No. : 08 Contract No. : 0 Title and subtitle : Development of uniform hazard response spectra for Kalpakkam, Kaiga and Kudankulam Collation : 59 p., 4 figs., 3 tabs. 3 Project No. : 20 Personal author(s) : A.K. Ghosh; K.S. Rao 2 Affiliation of author(s) : Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 22 Corporate author(s) : Bhabha Atomic Research Centre, Mumbai Originating unit : Reactor Safety Division, BARC, Mumbai 24 Sponsor(s) Name : Department of Atomic Energy Type : Government Contd...

4 BARC/2009/E/ Date of submission : October Publication/Issue date : November Publisher/Distributor : Associate Director, Knowledge Management Group and Head, Scientific Information Resource Division, Bhabha Atomic Research Centre, Mumbai 42 Form of distribution : Hard copy 50 Language of text : English 5 Language of summary : English, Hindi 52 No. of references : 20 refs. 53 Gives data on : 60 Abstract : Variation of Peak Ground Acceleration (PGA) with mean recurrence interval (MRI) has also been presented using various well-known correlations. The present work develops uniform hazard response spectra i.e. spectra having the same MRI at all frequencies for Kalpakkam, Kaiga and Kudankulam sites. These results determine the seismic hazard at the given site and the associated uncertainties. Typical examples are given to show the sensitivity of the results to changes in various parameters. The results will be useful in evaluation of seismic risk. 70 Keywords/Descriptors : KUDANKULAM- REACTOR; KUDANKULAM-2 REACTOR; SEISMIC DETECTION; RADIATION HAZARDS; SPATIAL DISTRIBUTION; SPECTRAL RESPONSE; SEISMIC ARRAYS 7 INIS Subject Category : S2 99 Supplementary elements :

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6 DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM A.K.Ghosh & K.S.Rao Reactor Safety Division A B S T R A C T Variation of Peak Ground Acceleration (PGA) with mean recurrence interval (MRI) has also been presented using various well-known correlations. The present work develops uniform hazard response spectra i.e. spectra having the same MRI at all frequencies for Kalpakkam, Kaiga and Kudankulam sites. These results determine the seismic hazard at the given site and the associated uncertainties. Typical examples are given to show the sensitivity of the results to changes in various parameters. The results will be useful in evaluation of seismic risk.

7 DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM SITES A.K.Ghosh & K.S.Rao Reactor Safety Division. INTRODUCTION The objective of aseismic design of power plant components and structures is to ensure safety of the plant and the people around in the event of an earthquake. Safety needs to be ensured against a set of postulated events originating at various locations, as dictated by the local geological and tectonic features and data on past earthquakes. The design basis ground motion is generally specified by normalised response spectra (also known as response spectral shapes or the dynamic amplifications factors, DAFs) for various values of damping and a PGA together with a ground motion time-history. The PGA is evaluated by empirical relations involving earthquake magnitude and the distance between the source and the site. The former is obtained by a statistical analysis of a large number of records having earthquake parameters in the range of interest and selecting a shape with an acceptable value of the probability of exceedence. These data should be drawn from sites having similar geological conditions (rock/soil). The various uncertainties and randomness associated with the occurrence of earthquakes and the consequences of their effects on the NPP components and structures call for a probabilistic seismic risk assessment (PSRA). Seismic hazard at the site is one of the key elements of the PSRA []. The seismic hazard at a given site is generally quantified in terms of the probability of exceedence of the design level PGA [2] and the probability of exceedence of the specified ground motion response spectral shapes [3-7]. In the approach which has traditionally been adopted the probability of exceedence of the spectral shape is with respect to the database from which it has been derived and is not related with the temporal or spatial distribution of earthquakes. The probability of exceedence of the PGA is, however, evaluated considering the spatial and temporal distribution of earthquakes. The new SRP [8] and Regulatory Guide [9] of USNRC recommend development of unnormalised response spectra. USNRC [9] further proposes to carry out a probabilistic safety hazard analysis (PSHA) based on uniform hazard response spectra (UHRS).

8 The present work aims to develop UHRS i.e. response spectra having the same mean recurrence interval (MRI), or equivalently, the same probability of exceedence in a specified span of time at all frequencies for the Kalpakkam, Kaiga and Kudankulam sites. The present paper develops these spectra considering linear and point sources of earthquakes. It is further recognised that the predicted seismic hazard can vary with various parameters involved. Numerical results have been presented to show this variability. These results will help to determine the seismic hazard at the given site and the associated uncertainties. 2. THEORY Cornell [2] has presented a model for evaluating the MRI or the probability of exceedence, P of a specified value of PGA. Ghosh et al. [0] considering aerial source distribution extended the method for more generalised forms for the correlation for PGA. This work was extended to develop UHRS considering a uniform aerial source and line and point sources of earthquakes [,2]. In this report, a similar methodology is applied to determine a uniform hazard response spectrum. 2. SEISMIC HAZARD ANALYSIS The seismic hazard analysis presented by Cornell [2] is based on the peak ground acceleration (a p ) which is assumed to be of the form b3 a = b exp( b M) R () p 2 where b, b2 and b are constants, M is the earthquake magnitude and R is the 3 hypocentral distance. It has been observed [3] that PGA predicted by relations of the type given by equation () does not agree very well with observations particularly for smaller values of R and a distance correction term (D) has been considered by many workers. Several correlations are available for defining the peak ground acceleration (a) for horizontal motion - each developed from a particular data set, and therefore, best suited for interpolation within a particular range of parameters. Two widely used forms for PGA are: a = b exp(b 2 M) (R+D) -b 3 (2) a = b 0 b 2 M (R+D) -b 3 (3) where M is the magnitude, R is the distance and D is a correction term to account for zero distance. For any application, an equation has to be chosen that is best suited to a given source-site combination and the range of parameters under consideration. 2

9 2.2 ATTENUATION RELATION FOR SPECTRAL ACCELERATION The present regulatory documents [8,9] require the ground motion to be presented as the unnormalised response spectrum itself without scaling it to PGA. Attenuation relation has been developed for the unnormalised response spectrum [,2]. The response spectral acceleration is assumed to be of the same form as given by equation (2) i.e. S = S(M, R, ζ,.t) = b exp(b 2 M) (R+D) -b 3 (4) Where M is the magnitude and R is the hypocentral distance. D is a distance correction factor, ζ is the value of damping and T is the period for which the response spectrum is being evaluated. The constants, b, b 2, b 3 depend on ζ and T. McGuire [4] has used a form similar to equation (3). As has been shown by Ghosh et al. [0] equations (2) and (3) are equivalent. 2.3 Line Source Model Earthquakes occur along faults, which are generally linear features or represented as ones (lineaments). It is assumed that earthquakes are equally likely to occur anywhere along the length of a fault (lineament). The number of earthquake of magnitude greater than or equal to M occurring annually is given by Richter s equation [5] log 0 N a bm M = (5) a and b for a given region are determined from the earthquake occurrence records of that region. Considering the effect of all possible values of the focal distances, the cumulative probability P S S ] is obtained. f R [ d P ( S S d = ) = C r 0 d P [ S S b d β 2 G S d R = r ] f ( r ) dr ( r ) - the probability density function of finding an earthquake at a radius r, and G for various types of fault orientation have been presented in [2]. (6) C = e β M 0 b β b 2 3

10 and β = b ln 0. Equation (6) yields the probability that the spectral acceleration (for given values of damping and period) at site, S will exceed a certain value, S d, given that an event of interest ( M M 0 ) occurs anywhere on the fault. Next, we consider the random number of occurrences in any time period. It is assumed that the occurrences of earthquake follow a Poisson arrival process with average occurrence rate of ν per year [2]. Then the number of events, N, of interest occurring in the area in a time interval of length t years is distributed as : ν t n e ( ν t ) P ( n) = P( N= n) = ; n = 0,, 2,... (7) N n! If certain events are Poisson arrivals with average arrival rate ν and if each of these events is independently, with probability p, a special event, then these special events are Poisson arrivals with average annual arrival rate p ν. The probability, pi, that any event of interest M M 0 will be a special event is given by equation (6). Thus the number of times, N, that the spectral acceleration (for given values of damping and period) at the site will exceed S d in an interval of time t has the probability: p iν t n e ( p iν t ) PN ( n) = P ( N = n S Sd ) = ; n= 0,,2,... (8) n! Of particular interest is the probability distribution of S max, the maximum spectral acceleration (at given damping and period) over an interval of time t. Lettiing t = year, p[ S max = e S ] = p[ N = 0 S S ]] p ν t i d d (9) p[ S max S ] = F d a p = e Pi ν = exp( ν C G S β / b 2 ) (0) The annual probability of exceedence of S max > S d is then F a p = exp( Cν G S d β / b 2 ) [ Cν G S β / b 2 d ] β / b 2 d = Cν G S () 4

11 The mean recurrence interval ( T y ) of the spectral acceleration S d is then the reciprocal of ( - F ap ) i.e., T y β b 2 S d = (2) Cν G Then equations (9) and (2) may be used to obtain the probability of exceedence of S d in a given span of t years as P= exp( t/ T ) (3) y The seismic hazard at a site is quantified by the probability (P/S >S d ) and T y and the uncertainties in these quantities due to variations in the correlations for spectral acceleration and uncertainties in the seismic source and occurrence models i.e. a and b, depth of focus, h. 2.4 Point Source Model When there are clusters of earthquakes away from the site, each cluster could be modelled as a point source of earthquakes. In case of a single point source there is no randomness with respect to the location of the earthquake, hence for a specified value of spectral acceleration the magnitude is also fixed by the chosen correlation for spectral acceleration. The probability of exceedence of the specified value of spectral acceleration is therefore decided by the temporal distribution of earthquakes. b 2 P[ S S ) d = r] = C S G (4) d β d where G b 3 b 2 β = ( r + D) (5) 2.5 Multiple Line and Point Sources When there are a number of line or point sources the probability of non-exceedence of a specified value of spectral acceleration is obtained by multiplying the probability of non-exceedence of the specified value of spectral acceleration from each of the sources i.e., 5

12 p[ S NS max Sd ] = p[ Smax S d ] fromtheith source i= = exp[ NS i= C i S β i b 2i d G i ν ] i (6) The above equation is the most general equation for any number of sources. Assuming C, b 2 and β are constants, the above equation simplifies to the following. p[ Smax S ] = exp[ ( C S ) d β NS b 2 d Gi ν i i= (7) The implication of the above assumption is that 'a' can vary with the source thus allowing different earthquake potential for each source, but 'b' and the constants b, b 2, b 3 remain unchanged for the entire region under consideration. When there are NS sources associated with the parameters (a i and b) for the Richter's equation and the parameters are (a,b) for the region as a whole, then in order to have the same number of earthquakes considering either the ensemble of the sources or the region as a whole, the following equality holds. a 0 = a 0 i i i.e. if all the sources have the same value of a i then a i = a log 0 ( NS) (8) 2.6 Aerial Source Model When the size of the cluster of earthquakes is rather large or for diffused seismicity use of an aerial source model will be appropriate []. 3. PRESENT STUDY The present study uses 44 horizontal acceleration records from rock sites to develop attenuation relation for response spectral acceleration [,2]. The range of magnitude is generally from 4. to 8. and there are few records of magnitude lower than 4.. The distance from the fault varied generally about from about 6 km to 25 km. The salient features of the accelerograms are given in [2]. The digitised accelerograms were obtained on magnetic tapes from the World Data Center [6]. In these data, the original accelerograms have been band-pass filtered between 0.07 Hz and 25 Hz and base line corrections have been made. Analysis has been carried out with the recorded accelerograms representing the free-field conditions. The geological conditions of the recording sites, identified by the name and number of the recording station, are verified from published sources. 6

13 It has been observed that the response spectra of the two horizontal components recorded at the same location are often significantly different. This may be attributed to the orientation of the instrument with respect to the fault. To ensure conservatism, the attenuation for spectral acceleration (equation (4)) at any frequency was developed by selecting only the higher of the two horizontal spectral values of the records at a particular site. The attenuation relations thus developed were used for the development of uniform hazard response spectra. 3. Kalpakkam site A detailed lineament map around the Kalpakkam site is presented in Fig Each of these lineaments shown in the 300 Km. radius circles around the site has been considered as a line source. The length of the lineaments and their distance from the site has been obtained from this map. Fig. also shows some of the epicenters of earthquakes. An earlier study [0] has shown that the influence of earthquake sources beyond 50km has insignificant effect on the seismic hazard. Earthquake data for the period AD has been obtained from various catalogues [[7], for example] available as published literature (global sources). Data have also been obtained from the Gauribidanur Seismic array (GBA) of Bhabha Atomic Research Centre period for the period AD [9]. A summary of these data is presented in Table-3... The magnitude frequency relationships for these earthquakes are presented in Figs. 3..2a and 3..2b. The figures include the observed data and results of an earlier study by Ravi Kumar et al. [9]. A least square fit of the data was carried out (see equation 5) and the constant of the equation ( a value) was increased to obtain a modified fit to envelope the observed data which is also included in the figures. 3.2 KAIGA SITE A detailed lineament map around the Kaiga site is presented in Fig Earthquake data for the period AD has been obtained from various catalogues [7], for example available as published literature (global sources). Data have also been obtained from the Gauribidanur Seismic array (GBA) of Bhabha Atomic Research Centre period for the period AD [8]. A summary of these data is presented in Table The magnitude frequency relationships for these earthquakes are presented in Figs a and 3.2.2b. The figures include the observed data and results of an earlier study by Ravi Kumar et al. [9]. A least square fit of the data was carried out (see equation 5) and the constant of the equation ( a value) was increased to obtain a modified fit to envelope the observed data which is also included in the figures. 3.3 Kudankulam site A detailed lineament map around the Kudankulam site is presented in Fig Earthquake data for the period AD has been obtained from various catalogues [7], for example available as published literature (global sources). Data 7

14 have also been obtained from the Gauribidanur Seismic array (GBA) of Bhabha Atomic Research Centre period for the period AD [8]. A summary of these data is presented in Table The magnitude frequency relationships for these earthquakes are presented in Figs a and 3.3.2b. The figures include the observed data and results of an earlier study by Ravi Kumar et al. [9]. A least square fit of the data was carried out (see equation 5) and the constant of the equation ( a value) was increased to obtain a modified fit to envelope the observed data which is also included in the figures. 4. NUMERICAL RESULTS Usually, the value of T y for PGA is required to be of the order of hundred years for the operating basis earthquake (OBE or S ) and ten thousand years for the safe shutdown earthquake (SSE or S 2 ) [20]. 4. Kalpakkam Site Fig. 4..a shows the variation of MRI and the probability of exceedence in 50 years as a function of PGA for the base case. The a and b values for various sources are the reference values given in Table-3... A sensitivity study was carried out to see the variation of MRI with PGA for various values of a and b (Fig.4.. b & c). The effect of M on PGA is shown in Fig.4..d. The sensitivity to other parameters df, shd, al, z2fac is shown in figs.4..e to 4.4.h. Fig.4..j shows the results obtained by various correlations. Figures 4..2a and 4..3a present the UHRS for the base values of a and b for various values of MRI and the probability of exceedence. Figures 4..2b to 4..2m shows the UHRS obtained by varying the parameters for different values of MRI. Fig.4..3a to 4..3m shows the UHRS obtained by varying the parameters for different values of the probability of exceedence. The spectral acceleration at any frequency is higher as the probability of exceedence reduces. 4.2 Kaiga site Fig. 4.2.a shows the variation of MRI and the probability of exceedence in 50 years as a function of PGA for the base case. The a and b values for various sources are the reference values given in Table A sensitivity study was carried out to see the variation of MRI with PGA for various values of a and b (Fig.4.2.b and 4.2.c). The effect of M on PGA is shown in Fig.4.2.d. The sensitivity to other parameters df, shd, al, z2fac is shown in figs.4.2.e to 4.2.h. Fig.4.2.j shows the results obtained by various correlations. Figures 4.2.2a and 4.2.3a present the UHRS for the base values of a and b for various values of MRI and the probability of exceedence. Figures 4.2.2b to 4.2.2m shows the UHRS obtained by varying the parameters for different values of MRI. Fig.4.2.3a to 4.2.3m shows the UHRS obtained by varying the parameters for different values of the probability of exceedence. The spectral acceleration at any frequency is higher as the probability of exceedence reduces. 8

15 4.3 Kudankulam site Fig. 4.3.a shows the variation of MRI and the probability of exceedence in 50 years as a function of PGA. The a and b values for various sources are the reference values given in Table A sensitivity study was carried out to see the variation of MRI with PGA for various values of a and b (Fig.4.3.b and 4.3.c). The effect of M on PGA is shown in Fig.4.3.d. The sensitivity to other parameters df, shd, al, z2fac is shown in figs.4.3.e to 4.3.h. Fig.4.3.j shows the results obtained by various correlations. Figures 4.3.2a and 4.3.3a present the UHRS for the base values of a and b for various values of MRI and the probability of exceedence. Figures 4.3.2b to 4.3.2m shows the UHRS obtained by varying the parameters for different values of MRI. Fig.4.3.3a to 4.3.3m shows the UHRS obtained by varying the parameters for different values of the probability of exceedence. The spectral acceleration at any frequency is higher as the probability of exceedence reduces 5. Discussion From the earlier studies [,2] it has been observed that for a single source, as the distance from the fault, Δ increases the value of the spectral acceleration for a fixed MRI reduces. Similarly, for a fixed MRI, the spectral acceleration reduces with increasing value of l, the length of the fault. At smaller values of l, all the earthquakes are concentrated in a small zone around the site. So for a given value of MRI, the spectral acceleration will be more than that when earthquakes are likely to occur over a wider range of distance. As l increases, the results tend to become asymptotic. Distant earthquakes affect motion in the long period (range 0.5s - 2s). As one moves away from the site, the same spectral acceleration at the site would be required to be generated by an earthquake of a higher magnitude. Thus the value of MRI for the specified spectral acceleration will be higher. A higher value of 'a' or a lower value of 'b' while the other remains unchanged would imply a higher value of M, leading to a higher value of spectral acceleration. It is seen that generally the spectral acceleration for the point source is higher since the earthquakes occur at the same distance, Δ whereas the earthquake source distance is greater than or equal to Δ for a line source. However, for longer periods the two spectra appear to be closer. This is due to contribution of the distant earthquakes to the long period region of the response spectra. 9

16 REFERENCES. Kennedy RP and Ravindra MP. Seismic Fragilities for Nuclear Power Plant Hazard Studies, Nuclear Engineering and Design, 984; 79, Cornell, C.A. Engineering Seismic Hazard Analysis, Bulletin of the Seismological Society of America, 968; 59, 5, U.S.A.E.C.. Design Response Spectra for Seismic Design of Nuclear Power Plants, Regulatory Guide.60, U.S. Atomic Energy Commission, Directorate of Regulatory Standards, Seed HB, Ugas C and Lysmer J. Site Dependent Spectra for Earthquake Resistant Design, Bull. Seism. Soc. Am., 976; 66, Ghosh AK, Muralidharan, N and Sharma RD. Spectral Shapes for Accelerograms Recoded at Rock Sites, Report B.A.R.C.-34, Bhabha Atomic Research Centre, Government of India, Mumbai, Ghosh AK and Sharma RD. Spectral Shapes for Accelerograms Recorded at Soil Sites, Report B.A.R.C.-365, Bhabha Atomic Research Centre, Government of India, Mumbai, Ghosh AK, Rao KS and Kushwaha HS. Development of Response Spectral Shapes and Attenuation Relations from Accelerograms Recorded on Rock and Soil Sites, Report BARC/998/06, Bhabha Atomic Research Centre, Government of India, U.S.N.R.C. Vibratory Ground Motion, Standard Review Plan 2.5.2, NUREG- 800, Rev.3., U.S.N.R.C. Identification and Characterisation of Seismic Sources and Determination of Safe Shutdown Earthquake Ground Motion, Regulatory Guide.65., Ghosh AK and Kushwaha HS. Sensitivity of Seismic Hazard to Various Parameters and Correlations for Peak Ground Acceleration, Report BARC/998/025, Bhabha Atomic Research Centre, Government of India, Ghosh AK and Kushwaha HS. Development of Uniform Hazard Response Spectra from Accelerograms Recorded on Rock Sites, Report BARC/2000/E/04, Bhabha Atomic Research Centre, Government of India, Ghosh AK and Kushwaha HS. Development of Uniform Hazard Response Spectra for Rock Sites Considering Line and Point Sources of Earthquakes, Report BARC/200/E/03, Bhabha Atomic Research Centre, Government of India, Campbell KW. Strong Motion Attenuation Relations: A Ten-Year Perspective, Earthquake Spectra, 985; (4),

17 4. McGuire RK. Seismic Design Spectra and Mapping Procedure using Hazard Analysis based Directly on Oscillator Response, Earthquake Engineering and Structural Dynamics, 977; 5, Richter CF. Seismic Regionalisation, Bulletin of the Seismological Society of America, 959; 49, World Data Centre. Catalogue of Seismographs and Strong Motion Records, Report SE-6, Solid Earth Geophysics Division, Environmental Data Service, Boulder, Colorado, U.S.A, Chandra U. Earthquakes of Peninsular India, Seismotectonic Study. Bulletin of the Seismological Society of America, 977, 67(5), Gangrade, BK et al. Earthquakes from Peninsular India: Data from Gauribidanur Seismic Array Reports BARC 347, 987; BARC 385, 987; BARC 454, 989; BARC/992/E/024, 992; BARC/994/E/040, 994; BARC/996/E/024, 996. Bhabha Atomic Research Centre, Government of India. 9. Ravi Kumar, M. and Bhatia, S.C. A New Seismic Hazard Map for the Indian Plate Region Under the Global Seismic Hazard Assessment Program, Current Science, 999, 77(3), IAEA. Earthquakes and Associated Topics in Relation to Nuclear Power Plant Siting: A Safety Guide, Safety Guide 50-SG-S, International Atomic Energy Agency, and Vienna, 979.

18 TABLE 3.. Distribution of Earthquakes Around Kalpakkam SITE Data from Global Sources Sr.no. (M 0 M i ) Magnitude Range No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Data from GBA Sr.no. (M 0 M i ) Magnitude Range No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Table 3..2 Magnitude Frequency Relationships Data a b Remarks Global Least square fit data modified to envelope the observed values GBA Least square fit data modified to envelope the observed values 2

19 Table3.2. Distribution Of earthquakes around Kaiga Site and Magnitude frequency relationship Data from Global Sources Sr.no. (M 0 M i ) Magnitude Range No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Data From GBA Sr.no. (M 0 M i ) Magnitude Range No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Table Magnitude Frequency Relationships Data a b Remarks Global Least square fit data modified to envelope the observed values GBA Least square fit data 3

20 TABLE 3.3. Sr.no. (M 0 M i ) Magnitude Range Distribution of Earthquakes Around Kudankulam Site Data from Global Sources No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Data from GBA Sr.no. (M 0 M i ) Magnitude Range No. of Earthquakes in this range No. of Earthquakes M > M 0 No. of Earthquakes occurring annually (N) Log 0 N Table Magnitude Frequency Relationships Data a b Remarks Global Least square fit data modified to envelope the observed values 4

21 Fig.3.. : Seismotectonic and Lineament map Kalpakkam site 5

22 observed a=0.77,b= a=.69,b= a=.265,b= a=2.35,b= log 0 N Magnitude Fig.3..2a: Magnitude Frequency Relationship Kalpakkam Site Global data.5 Obs Linear fit log 0 N Magnitude Fig.3..2b: Magnitude Frequency Relationship Kalpakkam Site gba data 6

23 Fig.3.2. SEISMOTECTONIC AND LINEAMENT MAP KAIGA SITE 7

24 2.0.5 obs. linear fit a=.0, b= a=2.0,b= a=3.0,b= log 0 N Magnitude Fig.3.2.2a: Magnitude Frequency relationship Kaiga site global data obs. linear fir a=.,b= a=2.,b= a=3.,b= log 0 N Magnitude Fig.3.2.2b: Magnitude Frequency relationship Kaiga site GBA data 8

25 Fig. 3.3.: Seismotectonic and Lineament Map Kudankulam site 9

26 2.0.5 logn abfit ab5989 a2b5989 a3b log 0 N magnitude Fig.3.3.3a: Magnitude Frequency Relationship Kudankulam site global data Log 0 N AB-fit A= A=2 A=3 lin fit Log 0 N Magnitude Fig.3.3.3b: Magnitude Frequency Relationship Kudankulam site GBA data 20

27 00000 Return Priod Ty Ty base case P base case E-3 Probability of exceedence P Return Period Ty ty.a ty basecase ty 0.9a P.a P basecase P 0.9a E-3 Probability of exceedence P PGA Fig.4..a: MRI/Probability Vs PGA;Basecase; Kalpakkam site E E PGA Fig.4..b: MRI/Probability Vs PGA; Comparison of basecase.a and 0.9a; Kalpakkam site Return Period Ty Ty.b Ty 0.9b Ty basecase P.b P 0.9b P basecase E-3 Probability of exceedence P Return period Ty Ty mmax dec Ty mmax inc Ty base case P mmax dec P mmax inc P base case E-3 Probability of exceedence P PGA Fig.4..c: MRI/Probability Vs PGA; Comparison of basecase.b and 0.9b; Kalpakkam site E-4 E PGA Fig.4..d: MRI/Probability Vs PGA; Comparison of basecase MMax +/- 0.5; Kalpakkam site 2

28 Return Period Ty Ty.al Ty 0.9al Ty basecase P.al P 0.9al P basecase E-3 Probability of Exceedenca P Return Period Ty.df Ty 0.9df Ty basecase P.df P 0.9df P basecase E-3 probability of exceedence P PGA E-4 Fig.4..e: MRI/Probability Vs PGA; Comparison.al,0.9al and base case; Kalpakkam site E PGA Fig.4..f: MRI/Probability Vs PGA; Comparison.df,0.9df & base case; Kalpakkam site Return Period Ty Ty.shd Ty 0.9shd Ty base case P.shd P 0.9shd P base case E-3 Probability of exceedence P Return Period Ty 00 0 ty z2fac-0.5 ty z2facc+0.5 ty AKG basecase P z2fac-0.5 P z2fac+0.5 P akg basecase E-3 Probability of exceedence P E PGA Fig.4..g: MRI/Probability Vs PGA; Comparison.shd,0.9shd & base case; Kalpakkam site E PGA Fig.4..h: MRI/Probability Vs PGA Kalpakkam site Comparison Z2fac.+/- 0.5 with base case 22

29 ty=. ty=0. ty=00. ty=000. ty=0000. ty=5920 Spectral Acc Per. Fig.4..2a: UHRS for various values of MRI; Base case; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. spectral acc per. Fig.4..2b: UHRS for Various values of MRI; 0.9a; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000 Spectral acc per. Fig.4..2c: UHRS for Diff vals. of MRI;.a ; Kalpakkam site 23

30 ty=. ty=0. ty=00. ty=000. ty=0000. ty=25830 Spectral acc per. Fig.4..2d: UHRS for Diff vals. of MRI; 0.9b ; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. ty= spectral acc per. Fig.4..2e: UHRS for Diff vals. of MRI;.b ; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. ty= Spectral Acc Per.(sec) Fig.4..2.f: UHRS for Diff vals. of MRI; 0.9 df; Kalpakkam site 24

31 Spectral Acc. 0.5 ty=. ty=0. ty=00. ty=000. ty=0000 ty= Per Fig.4..2g: UHRS at Diff vals. of MRI;. df; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. ty=29670 spectral Acc per. Fig.4..2h: UHRS at Diff vals.of MRI; mmax-0.5; Kalpakkam site spectral acc. 0.5 ty=. ty=0. ty=00. ty=000. ty=0000. ty= per. Fig.4..2i: UHRS at Diff vals.of MRI; mmax+0.5; Kalpakkam site 25

32 ty=. ty=0. ty=00. ty=000. ty=0000. ty= Spectral Acc Per Fig.4..2j: UHRS at Diff vals. of MRI; 0.9 shd; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. ty= Spectral Acc Per. Fig.4..2k: UHRS at Diff vals. of MRI;. shd; Kalpakkam site ty=. ty=0. ty=00. ty=000. ty=0000. spectral acc Per. Fig.4..2l: UHRS at Diff vals. of MRI; z2fac-0.5; Kalpakkam site 26

33 ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= PGA Per Fig.4..2m: UHRS at Diff vals. of MRI; z2fac+0.5; Kalpakkam site pe=0. pe= pe=0.0 pe=5 pe=8.454e-4 Spectral acc Per. Fig.4..3a:UHRS for various values of Probability; Basecase; Kalpakkam site pe=0. pe= pe=0.0 pe=5 pe= spectral acceleration per. Fig.4..3b: UHRS for Diff vals. of probability; 0.9a; Kalpakkam site 27

34 0.40 pe=0. pe= pe=0.0 pe=5 pe= spectral acc per. Fig.4..3c: UHRS at Diff vals. of probability;.a ; Kalpakkam site pe=0. pe= pe=0.0 pe=5 spectral acc per. Fig.4..3d: UHRS for Diff vals. of probability; 0.9b ; Kalpakkam site pe=0. pe= pe=0.0 pe=5 pe= Spectral Acc Per. Fig.4..3e: UHRS for Diff vals. of Probability;.b ; Kalpakkam site 28

35 pe=0. pe= pe=0.0 pe=5 pe= pe=8.05e-4 Spectral Acc Per. Fig.4..3f: UHRS at Diff vals. of probability; 0.9 df; Kalpakkam site pe=0. pe= pe=0.0 pe=5 pe= pe=8.404e-4 Spectral Acc per. Fig4..3g: UHRS at Diff vals. of probability;. Df ; Kalpakkam site pe=0. pe= pe=0.0 pe=5 spectral acc per. Fig.4..3h: UHRS at Diff vals. of probability; mmax-0.5; Kalpakkam site 29

36 pe=0. pe= pe=0.0 pe=5 pe=4.98e-4 Spectral acc per. Fig.4..3l:UHRS at Diff vals. of Probability; mmax+0.5; Kalpakkam site Spectral Acc. 0.5 pe=0. pe= pe=0.0 pe=5 pe=8.5433e Per. Fig.4..3j: UHRS at Diff vals. of Probability; 0.9 shd; Kalpakkam site pe=0. pe=0.0 pe= speactral acc per. Fig.4..3k: UHRS at Diff vals. of Probability;. shd; Kalpakkam site 30

37 Spectral acc pe=0. pe= pe=0.0 pe=5 pe= Per. Fig.4..3l: UHRS at Diff vals. of Probability; z2fac-0.5; Kalpakkam site 0.50 spectral acc pe=0. pe= pe=0.0 pe=5 pe= pe= per. Fig.4..3m: UHRS at Diff vals. of Probability; z2fac+0.5; Kalpakkam site 3

38 Return Period Ty Ty basecase P basecase E-3 Probability of Exceedence Return Period Ty Ty 0.9a Ty.a Ty basecase P 0.9a p.a p basecase E-3 Probability of exceedence P E PGA Fig.4.2.a: MRI/Probability Vs PGA Base Case; Kaiga site 0.0 E PGA Fig.4.2.b:MRI/Probability Vs PGA; Comparison of basecase with 0.9a and.a; Kaiga site Return period Ty Ty.b Ty basecase Ty 0.9b P.b p basecase P 0.9b E-3 Probability fo exceedence P Return period Ty Ty MMax+0.5 Ty mmax-0.5 ty basecase P mmax+0.5 p mmax-0.5 P basecase E-3 Probability of Exceedence P PGA Fig.4.2.c:MRI/Probability Vs PGA; comparison of base case with 0.9b and.b; Kaiga site E-4 0. E PGA Fig.4.2.d:MRI/Probability Vs PGA; comparison of base case with mmax +/- 0.5; Kaiga site 32

39 Return Period Ty Ty.al Ty 0.9al Ty basecase P.al P 0.9al P basecase E-3 Probability fo exceedence P return period Ty ty.df ty 0.9df ty basecase P 0.9df P.df p Base case E-3 Probability of exceedence P 0. E PGA Fig.4.2.e:MRI/Probability Vs PGA; comparison of base case with 0.9al and.al; Kaiga site PGA Fig.4.2.f:MRI/Probability Vs PGA; comparison of base case with 0.9df and.df; Kaiga site E Return period Ty Ty. SHD Ty 0.9 SHD Ty basecase P. SHD P 0.9 SHD P base case E-3 Probability of exceedence P Return Period ty Ty z2fac-0.5 Ty base case TY z2fac+0.5 P z2fac-0.5 P basecase P z2fac E-3 Probability of exceedence P pga E-4 Fig.4.2.g:MRI/Probability Vs PGA; comparison of base case with 0.9shd and.shd; Kaiga site 0. E PGA Fig.4.2.h:MRI/Probability Vs PGA; comparison of base case with z2fac +/- 0.5; Kaiga site 33

40 0.50 Spectral Acceleration Ty=. Ty=0. Ty=00. Ty=000. Ty=0000. Ty= Per. Fig.4.2.2a: UHRS for Diff vals. of MRI; Basecase; Kaiga site 0.50 Spectral acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= per. Fig.4.2.2b: UHRS for Diff vals. of MRI; 0.9a; Kaiga site 0.55 spectral Acceleration Ty=.0 ty=0.0 Ty=00.0 Ty=000.0 Ty= Ty= Per. Fig.4.2.2c: UHRS for Diff vals. of MRI;.a; Kaiga site 34

41 0.50 spectral acceleration Ty=.0 Ty=0.0 Ty=00.0 ty=000.0 ty= ty= per Fig.4.2.2d: UHRS for Diff vals. of MRI; 0.9b; Kaiga site Spectral acceleration ty.0 ty0.0 ty00.0 ty000.0 ty ty ty2.7e Per. Fig.4.2.2e: UHRS for Diff vals. of MRI;.b; Kaiga site Spectral Acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= Per. Fig.4.2.2f: UHRS for various values of MRI; 0.9df; Kaiga site 35

42 Spectral Acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= per. Fig.4.2.2g: UHRS for various values of MRI;.df; Kaiga site Spectral Acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= Per, Fig.4.2.2h: UHRS for various values of MRI; 0.9 shd; Kaiga site Spectral acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= PER. Fig.4.2.2i: UHRS for various values of MRI;. shd; Kaiga site 36

43 Spectral acceleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= Per. Fig.4.2.2j: UHRS for various values of MRI; mmax-0.5; Kaiga site Spectral accleration ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty= ty=.76e Per. Fig.4.2.2k: UHRS for various values of MRI; mmax+0.5; Kaiga site ty=.0 ty=0.0 ty=00.0 ty=000.0 ty= ty=8840 spectral acc per. Fig.4.2.2l: UHRS for various values of MRI; z2fac-0.5; Kaiga site 37

44 ty=. Ty=0. Ty=00. Ty=000. ty=0000. Spectral acc PGA Fig.4.2.2m: UHRS for various values of MRI; z2fac+0.5; Kaiga site 0.50 Spectral acceleration pe=0. pe= pe=0.0 pe=5 pe= pe=655e Per. Fig.4.2.3a: UHRS for various values of Probability; basecase; Kaiga site 0.50 Spectral Acceleration pe=0. pe= pe=0.0 pe=5 pe= pe= PER. Fig.4.2.3b: UHRS for various values of Probability; 0.9a; Kaiga site 38

45 0.55 Spectral acceleration pe=0. pe= pe=0.0 pe= Per. Fig.4.2.3c: UHRS for various values of Probability;.a; Kaiga site 0.50 Spectral Acceleration pe=0. pe= pe=0.0 pe= Per. Fig.4.2.3d: UHRS for various values of Probability; 0.9b; Kaiga site Spectral acceleration pe0. pe pe0.0 pe5 pe2.30e Per. Fig.4.2.3e: UHRS for various values of Probability;.b; Kaiga site 39

46 0.55 Spectral acceleration Pe=0. pe= pe=0.0 pe=5 pe= per Fig.4.2.3f: UHRS for various values of Probability; 0.9df; Kaiga site 0.50 Spectral Acceleration Pe=0. pe= pe=0.0 pe=5 pe= per. Fig.4.2.3g: UHRS for various values of Probability;. df; Kaiga site pe=0. pe= pe=0.0 pe=5 pe= Spectral Accleration Per. Fig.4.2.3h: UHRS for various values of Probability; 0.9shd; Kaiga site 40

47 Spectral Acceleration pe=0. pe= pe=0.0 pe=5 pe= Per. Fig.4.2.3i: UHRS for various values of Probability;. shd; Kaiga site 0.40 Spectral Acceleration pe=0. pe= pe= Per. Fig.4.2.3j: UHRS for various values of Probability; mmax-0.5; Kaiga site Spectral acceleration pe=0. pe= pe=0.0 pe=5 pe= per Fig.4.2.3k: UHRS for various values of Probability; mmax+0.5; Kaiga site 4

48 Spectral Acceleration pe=0. pe= pe=0.0 pe=5 pe= pe= Per. Fig.4.2.3l: UHRS for various values of Probability; z2fac-0.5; Kaiga site pe=0. pe= pe=0.0 pe=5 pe= Spectral acc Per. Fig.4.2.3m: UHRS for various values of Probability; z2fac+0.5; Kaiga site 42

49 RETURN Period Ty Basecase P basecase probability of exceednece Return Period Ty Ty.a Ty Basecase Ty 0.9a P.a P basecase P 0.9a Probability of exceedence P E pga Fig.4.3.a:MRI/Probability Vs PGA; Basecase; Kudankulam site 0.0 E PGA Fig.4.3.b:MRI/Probaility Vs PGA; Comparing.a,0.9a with the base case; Kudankulam site Return Period Ty tybinc Tybc Tybdec Pbinc Pbc Pbdec E-3 Probability of exceedence P Return Period Ty mmax+0.5 Ty basecase Ty mmax-0.5 P mmax+0.5 P basecase P mmax Probability of exceedence 0. E PGA Fig.4.3.c:MRI/Probaility Vs PGA; Comparing.b,0.9b with the base case; Kudankulam site PGA Fig.4.3.d:MRI/Probaility Vs PGA; Comparing mmax+/-0.5 with basecase; Kudankulam site E-3 43

50 Return period Ty.al Ty basecase ty 0.9al P.al P basecase P 0.9 al Probability of exceedence Return Period Ty.df Ty basecase Ty 0.9df P.df P basecase P 0.9df Probability of exceedence 0. E PGA Fig.4.3.e:MRI/Probaility Vs PGA; Comparing 0.9al &.al with base case; Kudankulam site 0. E PGA Fig.4.3.f:MRI/Probaility Vs PGA; Comparing 0.9df &.df with base case; Kudankulam site Return Period Ty.shd Ty basecase Ty 0.9shd P. shd P basecase P 0.9 shd Probability of Exceedence Return period Ty Ty z2fac+0.5 Ty basecase Ty z2fac-0.5 P z2fac+0.5 P basecase P z2fac Probability of exceedence 0. E PGA Fig.4.3.g:MRI/Probaility Vs PGA; Comparing 0.9shd &.shd with base case; Kudankulam site 0. E PGA Fig.4.3.h:MRI/Probaility Vs PGA; Comparing z2fac +/- 0.5 with basecase; Kudankulam site 44

51 spectral Acc ty ty0 ty00 ty000 ty0000 ty Per Fig.4.3.2a: UHRS for various values of MRI; Basecase; Kudankulam site Spectral Acc ty.0 ty0.0 ty00.0 ty000.0 ty ty Per. Fig.4.3.2b: UHRS for various values of MRI; 0.9a; Kudankulam site TY.0 Ty0.0 Ty00.0 TY000.0 TY TY3040 Spectral acc Per. Fig.4.3.2c: UHRS for various values of MRI;.a; Kudankulam site 45

52 Spectral acc Ty.0 ty0.0 Ty00.0 TY000.0 TY TY PER. Fig.4.3.2d: UHRS for various values of MRI; 0.9b; Kudankulam site Spectral Acc TY.0 TY0.0 TY00.0 TY000.0 TY TY PER. Fig.4.3.2e: UHRS for various values of MRI;.b; Kudankulam site spectral acc TY.0 TY0.0 TY00.0 TY000.0 TY TY per Fig.4.3.2f: UHRS for various values of MRI; 0.9df; Kudankulam site 46

53 Spectral acc TY.0 TY0.0 TY00.0 TY000.0 TY TY per Fig.4.3.2g: UHRS for various values of MRI;.df; Kudankulam site SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY TY PER Fig.4.3.2h: UHRS for various values of MRI; 0.9al; Kudankulam site SPECTRAL ACC Ty.0 TY0.0 TY00.0 TY000.0 TY TY PER Fig.4.3.2i: UHRS for various values of MRI;.al; Kudankulam site 47

54 SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY TY PER. Fig.4.3.2j: UHRS for various values of MRI; 0.9shd; Kudankulam site SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY TY PER. Fig.4.3.2k: UHRS for various values of MRI;.shd; Kudankulam site SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY TY PER Fig.4.3.2l: UHRS for various values of MRI; mmax-0.5; Kudankulam site 48

55 SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY TY PER. Fig.4.3.2m: UHRS for various values of MRI; mmax+0.5; Kudankulam site SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY Ty PER. Fig.4.3.2n: UHRS for various values of MRI; z2fac-0.5; Kudankulam site SPECTRAL ACC TY.0 TY0.0 TY00.0 TY000.0 TY PER. Fig.4.3.2o: UHRS for various values of MRI; z2fac+0.5; Kudankulam site 49

56 spectral Acc p0. p p0.0 p5 P per Fig.4.3.2a: UHRS for various value of probability; Basecase; Kudankulam site Spectral Acc P0. P P0.0 P5 P p6.6e Per. Fig.4.3.3b:UHRS for various values of Probability; 0.9a; Kudankulam site Spectral acc P0. P 0.0 P5 P Per. Fig.4.3.3c:UHRS for various values of Probability;.a; Kudankulam site 50

57 Spectral acc P0. P P0.0 P5 P PER. Fig.4.3.3d:UHRS for various values of Probability; 0.9b; Kudankulam site P0. P P0.0 P5 P P046 Spectral Acc PER. Fig.4.3.3e:UHRS for various values of Probability;.b; Kudankulam site spectral acc PE0. PE PE0.0 PE5 PE per. Fig.4.3.3f:UHRS for various values of Probability; 0.9df; Kudankulam site 5

58 PE0. PE PE0.0 PE5 PE05 Spectral acc per Fig.4.3.3g:UHRS for various values of Probability;.df; Kudankulam site SPECTRAL ACC PE0. PE PE0.0 PE5 PE PER Fig.4.3.3h:UHRS for various values of Probability; 0.9al; Kudankulam site PE0. PE PE0.0 PE5 PE03 SPECTRAL ACC PER Fig.4.3.3i:UHRS for various values of Probability;.al; Kudankulam site 52

59 SPECTRAL ACC PE0. PE PE0.0 PE5 PE PER. Fig.4.3.3j:UHRS for various values of Probability; 0.9shd; Kudankulam site PE0. PE PE0.0 PE5 PE06 SPECTRAL ACC PER. Fig.4.3.3k:UHRS for various values of Probability;.shd; Kudankulam site SPECTRAL ACC PE0. PE PE0.0 PE5 PE PER Fig.4.3.3l:UHRS for various values of Probability; mmax-0.5; Kudankulam site 53