TSUNAMI EVALUATION OF COASTAL NUCLEAR POWER PLANTS … Documents... · TSUNAMI EVALUATION OF COASTAL NUCLEAR POWER PLANTS IN INDIA Ram Kumar Singh Reactor Safety Division Bhabha Atomic

Dr R K Singh BARC Trombay INDIA

1

TSUNAMI EVALUATION OF COASTAL NUCLEAR POWER PLANTS IN INDIA

Ram Kumar Singh

Reactor Safety DivisionBhabha Atomic Research Centre, Trombay

MUMBAI 400085, INDIA

e-mail [email protected] , [email protected]

Presented in “IAEA International Experts’ Meeting on Protection against Extreme Earthquakes and Tsunamis in the Lig ht of the

Accident at the Fukushima Daichi Nuclear Power Plant ”

Vienna, Sep 04-07, 2012

The progression of two severe accidents at Three Mile Island-1979 (USA)and Chernobyl-1986 (former USSR) nuclear reactors - importance of internalevents-widely studied and analyzed.

The recent severe accident at Fukushima-2011 (Japan) multiple nuclearplants originated from extreme sequential external events of tsunami andearthquake followed by further induced internal events.

Experience of three accidents demands evolution of a comprehensiveapproach for severe accident management - a number of large scaleexperimental and numerical simulations for a robust reactor system design.

Improved public perception about the nuclear reactors - a step forward toinclude the risk due to nuclear reactor internal events and other externalevents earthquakes, tsunamis, fire and dam break- common to all theindustries.

Multi-disciplinary R&D approach for the safety assessment experimentaland numerical simulations for both the internal and external events - largescale experimental programs & computer simulation, round robin exercises,benchmarks and standard problem exercises – the final goal – robustsystem evaluation with sound engineering practice

3

TSUNAMI EVALUATION OF INDIAN COASTAL NPPS AND LESSONS LEARNT FROM EXTREME EVENTS

•Thermal Hydraulics - important for extreme events in additi on toconventional requirements of core cooling in Reactor Safet y.•Decay heat removal and effective hydrogen management - to beensured in all situations including large earthquakes, tsu nami, floodand fire resulting in station black out.•Identified by MIT report (MIT –NSP-TR-025 May 2011) the tech nicallessons as summarized below: (These are only some thoughtprocesses and need to be looked collectively by designers, p lantoperators, regulators and backed up by R&D experts).1.Emergency Power following Beyond Design Basis Exter nal Events 2.Emergency Response to Beyond Design Basis External Events3.Containment4.Hydrogen Management5.Spent Fuel Pools6.Plant Siting and Site Layout

Multi-disciplinary approach in R&D as compared to conventi onalthermal hydraulics- all the above thrust areas addressed at BARC .Thermal hydraulics, structural mechanics with strong link to seismicand geological engineering, combustion and fire engineeri ng andbesides all - sound engineering practices

4

Progressive R&D and information exchange activities in INDIA

IAEA 2005 KalpakkamIAEA EBPPlant Specific data collection for tsunami round ro bin (3 sites)IAEA 2010 KalpakkamTask Force after Fukushima/External Events

SMiRT-21 (Nov 06-11, 2011)

Extreme Events – Thomas Jaeger Lecture – interventio n level- public trauma- specific to a country & its culture – determi nistic & probabilistic approaches . SMiRT -21 workshops ( majority focused around Fukushima event and extreme / BDBA events)

WS-1, WS-2, WS-10 Japanese recommendations on common technical issues ; WS-3 BDB Event (450 plants) Could Fukushima be avoided

WS-11 BARCOM – ultimate load capacity evaluation round robin

Keynote on stress test, extreme events, tsunami / s eismic modeling

CNS Report – Last week

In all above requisite R&D support was given by BAR C Trombay

5

Background

The tsunami event of 26th December 2004 due to Sumatra earthquake and the resulting inundation in the nuclear facilities at Kalpakkam efficiently managed by Department of Atomic Energy (DAE) for the MAPS, the upcoming Fast Breeder Reactor at Bhavini site and the township areas.

SRI and IGCAR, Kalpakkam initiated onsite data collection and numerical tsunami modeling activities.

BARC Trombay participated in the National Warning System since 2005 with the backup of in-house code development & associated numerical modeling activities.

BARC coordinated a systematic National Round Robin Analysis for present and future prospective Indian coastal sites .

Intensive code benchmarking exercises resulted in v alidation of procedures for tsunami hazard evaluation, generatio n of global run up data and local inundation data for Kalpakkam , Tarapur and Vizag. Sites as specific example on eastern and western co asts besides global wave run-up for new prospective sites.

6

SUMATRA TSUNAMITSUSOL Prediction as Compared to Jason-1 Track 109 Satellite observations at 120 minutes

JASON-1 Track 109 Satellite (altidude 1300 km) Recor d http://walrus.wr.usgs.gov/tsunami/sumatraEQ/jason.h tmlJason-1 Trackline ascending orbit 2 hours after the 2004 Sumatra-Andaman eathquake. Blue arc modeled wavefront (direct arrival) of the o utbound tsunami from seafloor displacement caused by the earthquake . Green arc tsunami reflections. View to the north .

Tsunami In-house Finite Element Code TSUSOL

• In-house finite element code Tsunami Solution (TSUSOL) written after Sumatra 2004 event • Compressible wave propagation code with due consideration to free surface shallow water theory and acoustic wave propagation below the free surface.

Continuity and momentum equations with velocity components vi are ∂ρ∂ρ∂ρ∂ρ/∂∂∂∂t + ∇∇∇∇(ρρρρv i) = 0 (1)ρρρρ Dv i / Dt = σσσσ ij,j - ρρρρ g i (2)

Normal surface tractions gradient with surface normal n as∂∂∂∂p/∂∂∂∂n = -1/g ∂∂∂∂2p/∂∂∂∂t2 (3)

The Sommerfeld radiation boundary condition at the non-reflecting boundary is∂∂∂∂p/∂∂∂∂n = -1/c ∂∂∂∂p/∂∂∂∂t (4)

For computation of fluid continuum up to the seabed coupled with the ground structure the boundary condition at the seabed is

∂∂∂∂p/∂∂∂∂n = - ρρρρ ∂∂∂∂vn/∂∂∂∂t, (5)

vn is the normal velocity at the seabed due to the earthquake/subduction motion

Dr R K Singh BARC INDIA 8

Finite element code TSUSOL Prediction for Srilankan coast

150 minute typical height 4.842 m 168.75 minutes typical heights 10.726 m and 10.497 m

TSUSOL-2005


Tsunami arrival near South Indian coast at 206.25 minute wave height 3.325 m

Finite element code TSUSOL Prediction for Indian coast

225 minute typical wave height 5.0 m

TSUSOL-2005


TSUSOL-2005

Typical wave heights at 150 minutes 6.374 m (south-east Little Nicobar), 4.365 m (north Great Nicobar), 3.691 m (east Great Nicobar) and 3.514 m (west Great Nicobar)

Finite element code TSUSOL Prediction for Nicobar Andaman Island coasts

231.25 minutes max height 8.831m (south-west Great Nicobar

243.75 minutes typical heights 4.867 m, 3.94 m and 3.7m (south Andaman)

218.75 minutes typical heights 2.147 m and 4.28m (south Andaman)


TSUSOL-2005 predictions

0 5000 10000 15000 20000 25000-6

-4

-2

0

2

4

6

Wav

e H

eigh

t (m

)

Time (sec)

70386

Typical Time Signal at South Indian Coast Multiple Wave Periods due to Wave Scattering and Reflections from Sri LankaSumatra event was a far field event and hence decou pled analysis justified with static boottom displacement model as evident here

Peak Wave Height ~ 4.4 mAt 14655 sec

Wave Periods(sec) 1 - 10240 2 – 4096 (Sri Lamka) 3- 2560 (Nicobar) 4- 17075-1280 (Sri Lamka) 6- 1024�Coupled system needed for long periods (> 2500 sec)

1 2

3

4

5 6

Spectral periods (sec)

4380, 2580 &

1320 (NIO de-tided gauge data Rabinovich (2007)


0 5000 10000 15000 20000 25000-12

-10

-8

-6

-4

-2

0

2

4

6

8

10

Wav

e H

eigh

t (m

)

Time (sec)

161130

Typical Time Signal at Nicobar Island Coast Single Predominant Wave Period- Small Land Mass

Peak Wave Height ~ 9.0 m

At 16380 sec

Wave Period (sec)

1 – 2560 (Nicobar)1


4380, 2580 &


TSUSOL-2005 predictions Proximity to sourceResults in just adequacy ofstatic bottom displacement model


Wave Periods(sec)

1 – 4096 (South India)

2 – 2926

3- 2276

4- 1862

5-1575

6- 1280 (South India)

7-1078

0 5000 10000 15000 20000 25000

-15

-10

-5

0

5

10

15

Wav

e H

eigh

t (m

)

Time(sec)

78606

Time Signal at Sri Lankan Coast- Influence of Wave S cattering andReflections from South Indian Coast major energies below 2500 sec wave

periods – manifestation of remote fault

Peak Wave Height ~10.0m

12

3

4

5 6

7


4380, 2580 &


TSUSOL-2005 predictions

Confirmation of the reflections from Sri Lanka and various other Indian islands with time signal analysis of the wav e time history from TSUSOL code. The reflected wave periods from S ri Lanka computed as 4096 sec, 2560 sec and 1280 sec compara ble with the spectral periods of 4380 sec, 2580 sec and 1320 sec respectively from the de-tided data of NIO tide gau ge records reported by Rabinovich et. al. (2007).The strong reflections of tsunami waves from Sri La nka and Maldives also recorded at remote stations in Atlant ic and Pacific Oceans and its attributes confirmed through global models by Kowalik et. al.(2007). Our evaluations of Sumatra-2004 tsunami event repor ted in 2005 have been lately confirmed by all these studies and it provided the requisite support to the National Warning System .Notable- large periods (>2500 sec) need attention to include compressibility effects in particular for near sour ce events such as March 2011 of the Pacific Tohoku Earthquake that affected Fukushima Plants. For remote faults this is not concerns for Indian NPPPs.


Tunami-N2 and TSUSOL Comparison Case 3

Parametric study for conclusive evidence of fault parameters importance

Improved studies based on the past events in Makran [1483(West?)], [1765, 1851 & 1945(East)] and Sumatra-Andman [1881-Mw 8.0, 1941-Mw-7.9] regions

10 minutes

30 minutes

56 58 60 62 64 66 68 70 72 74 76 78

12

14

16

18

20

22

24

26

-10

-8

-6

-4

-0.5

0

1

2

3

4

12

15

56 58 60 62 64 66 68 70 72 74 76 78

12

14

16

18

20

22

24

26

-10

-8

-6

-4

-0.5

0

1

2

3

4

12

15

Important steps for the qualification of a tsunami mathematical model

The tsunami source term identification with the det ails of fault parameters, propagation analysis to obtain the tsunami wave height and wave arrival time- global modelling

The local inundation modelling on a refined bathyme try and land morphology with a suitable inundation model and the numerical code va lidation with post tsunami survey data, tide gauge records and historical tsunami dat a

Possible using the data of an instrumented tsunami event to generate improved data of the fault parameters.

A number of analyses with various fault parameters to deduce the refined multi-segment fault model, consistent with the tide gauge measure ments at a number of stations.

Desirable to account for all the past historical an d the possible future tsunami events to arrive at the design tsunami - the uncertainties for tsunami hazard assessment.

In Indian Ocean the tsunami historical data limited . However, the mega tsunami event of December 26, 2004 (M 9.3) well studied, recorded a nd instrumented. Further, the events of submarine earthquakes of 28 March 2005 (M 8.6) , Jul y 17, 2006 (M7.7) and September 12/13, 2007 (M 8.5/7.9) analyzed by seismologists a nd oceanographers.

The National Warning System in place - the earthquake events and the tide gauge data being continuously recorded and analyzed in a regul ar manner.

The detail evaluation of the present and future coa stal nuclear sites for calibration of tsunami models & source model verif ication -continuing activity – Japanese experience – inversion models /


Various Steps for Evaluation for Indian Present an d Future NPP Sites – A Detail Case Study for Kalpakkam Site

1 Source Modeling - Fault parameters, segments, orientation, whether e vent is tsunamigenic ? Static vs. Dynamic Models, Inverse M odels, Coupled / Decoupled models for sea bed and water column

2 Wave propagation TUNAMI-N2, TSUSOL, SWAN, COMCOT, ANUGA,TIDAL Codes with BARC, IGCAR, IIT Madras, ICMAM, NGRI & A CRI

3 Local Run up height and inundation reach evaluation

4 Identify the inputs – geomorphology, bathymetry (~50-90 m grid)data collected using Airborne Lidar Terrain Mapper (ALTM) with an accuracy

of 0.35m – Data security issues NRSA & ICMAM5 Code qualification and comparison with NPP site observations

6 Uncertainty Estimation - inputs, assumptions in codes boundary conditions, influence of storm, friction, Coriolis forces and pr esence of estuary, creek, jetty – Sensitivity analysis


Some Reported Observations on Tsunami Source Modeli ng

All tsunami modellers classically use Okada (1985, 1982) model (static bottom displacement) – Initial condition

Built in assumptions- fast and rapid coseismic deform ation (~ duration a few minutes) compared to characteristic time of wav e propagation & length of sea floor deformation >> water depth, ini tial sea surface deformation = coseismic vertical displacement – attri butes of elastic dislocation theory

Dynamic displacement and compressibility of water i gnored, which are important particularly for near field tsunami – Japa nese studies for 1993 Hokkaido-nansei-oki earthquake & more recently for March-2011 Tohoku Earthquake (significance for Nicobar and Andaman regions in pa rticular and some potential sources in Indian Ocean)

Acoustic waves in water & Rayleigh waves in sea bed are important for source modelling within dynamic framework (Rayleigh waves modify the free surface wave height) – Significant for near fil ed and even for far field the arrival time get affected ( Japanese Experience )

19

Refined bathymetry and land morphology data collect ed with support from NRSA and ICMAM - specific to Kalpakkam, Tarapur site s & recently for Vizag.

Benchmark Examples Analyzed by the National Round Ro bin Participants

Numerical code capabilities evaluated and analysis methodologies evolved

Additional benchmarking issues addressed along with benchmark examples

100% reflecting boundary for coarser propagation gl obal models at shore

Inundation mapping with local refined models – bound ary conditions as per the code features with regard to the different global/local grid schemes-nested, moving stencil

NPP tsunami hazard evaluation- complex - 100 m ocean depth identified for local/global interface (common point) for comparison and global propagation model and local runup model validation

Minimize numerical dispersion and diffusion in the multi-grid models to capture natural physically consistent amplitude dispersion and pha se dispersion for accurate inundation and run-up modeling

POINT AT 100 M DEPTH FOR COMPARISON BETWEEN TWO M ODELS WITH GLOBAL AND LOCAL GRIDS- To minimize numerical diffusion and dispersion to the extent possible to arrive an engi neering accurate solution

Benchmark Problem-2 Comparison with Gauge Data – Prof YalcinerOkushiri benchmark problem

July 12, 1993, strong earthquake west of Hokkaido in the Seaof Japan resulted in a tsunami causing severe damage nearbyOkushiri island. The maximum runup ~32 meters observed atMonai village due to presence of a narrow gulley near a smallcove.

A 1/400 scale laboratory experiment of the Monai runup, using alarge-scale tank (205 m long, 6 m deep, 3.4 m wide) at CentralResearch Institute for Electric Power Industry (CRIEPI) in Abiko,Japan was conducted. This water tank experiment became oneof the standard benchmark problems for tsunami simulationcodes.

Okushiri benchmark problem (Contd..)

The problem summary

BathymetryNumerical simulation area: 5.448m X 3.402mMinimum depth: -0.125m (land)Maximum depth: 0.13535mGrid size 0.014m

Boundary Conditions Input Wave West: input wave Time domain: 0-22.5secNorth: solid wall Time step: 0.05secEast: solid wallSouth: solid wall

Output

Temporal water-surface variations at (x, y) = (4.521, 1.196), (4.521, 1.696), and (4.521, 2.196) in meters for comparison with observed experimental data.

Benchmark Problem B.C. & I.C.

0 5 10 15 20-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

wat

er le

vel (

m)

t ime (s)

BFC Area

Reflective

2D Shallow Water Area

Runup on land

Reflective

Benchmark Comparison with Gauge Data

Height for 200 sec simulation

12 Bottom Pressure Recorders (BPRs) and 11 Coastal Stations identified for Global Comparison of Tsunami Run up

Predicted Run-Up for Bottom Pressure Recorders (BPR s)

Name of theLocations

Bottom Pressure

Recorders (BPR)

Average run-up

(m)

Std.Dev(m)

Predicted Run-up (m)

IGCAR-SWAN

IGCAR-COMCOT

IIT-M ICMAM NGRI ACRi

Remark

BPR1 1.13 ±±±±0.35 1.36 1.41 (H) 1.30 0.70 0.67(L) 1.35 Good agreement with reasonably low range of values with small sigma. However, ICMAM and NGRI values are consistently lower for all BPRs.

BPR2 0.32 ±±±±0.16 0.17 0.29 0.56 (H)

0.12 (L) 0.37 0.42

BPR3 1.55 ±±±±0.49 1.83 1.84 1.93 (H)

0.90 (L) 0.95 1.86

BPR4 1.19 ±±±±0.37 1.43 1.45 (H) 1.40 0.70 (L) 0.74 1.43

BPR5 1.24 ±±±±0.25 1.31 1.36 (H) 1.40 0.80 0.71(L) 1.33

BPR6 0.39 ±±±±0.11 0.45 0.45 0.50 (H)

0.25 (L) 0.24(L) 0.43

BPR7 1.00 ±±±±0.30 1.21 1.23 (H) 1.14 0.60 (L) 0.61(L) 1.19

BPR8 0.98 ±±±±0.30 1.16 1.17 1.20 (H)

0.60 (L) 0.60 (L) 1.16

BPR9 0.46 ±±±±0.13 0.54 0.54 0.56 0.30 0.29(L) 0.51

BPR10 1.12 ±±±±0.33 1.35 1.35 1.26 0.70 (L) 0.70(L) 1.38 (H)

BPR11 (west) 0.09 ±±±±0.07 0.08 0.07 0.2 (H)

0 N.D. 0.08

BPR12 (west) 0.09 ±±±±0.07 0.09 0.07 0.2 0 N.D. 0.08

Indian Costal Sites

Mean tsunami height(m)

Std.Dev(m)

Predicted tsunami height (m)

IGCAR-SWAN

IGCAR-COMCOT

IIT-M

ICMAM

NGRIACRi

Remarks(sigma to mean

ratio %)

Mumbai 0.29 ±±±± 0.05 0.32 0.25 0.37(H)

0.25 0.30 0.23(L)

Good Agreement. Results varied over a small range of 14 cm. (17%)

Trombay(BARC)

0.310.261

±±±± 0.11±±±±0.041

0.26 0.28 0.53(H)

0.30 0.20(L)

0.27 Reasonably Good Agreement. Results varied over a range of 33 cm. Sigma is twice the Mumbai site for nearly same mean. IIT-M appears to be an outlier. (14%)1

Tarapur 0.29 ±±±± 0.05 --- 0.33(H) 0.28 0.20(L) 0.30 0.32 Good Agreement. Results varied over a small range of 13 cm. (17%)1

Jaitapur(Ratnagiri)

0.380.411

±±±± 0.13±±±±0.101

0.54(H) 0.35 0.33 0.50 0.20(L)

0.33 Reasonably Good Agreement. Results varied over a range of 34 cm. Sigma is nearly same as that of Trombay site for higher mean. NGRI appears to be an outlier. (25%)1

Visakhapatnam 1.571.721

±±±±0.39±±±±0.111

1.75 1.85(H) 0.80(L)

1.60 1.80 1.61 Large Range and sigma of 0.39 m. IIT-M appears to be an outlier.(6%)1

Predicted Tsunami Wave Height Indian Coastal Nuclea r Sites - Global Analysis

Kalpakkam 3.974.091

±±±±1.20±±±±0.611

4.05 4.89 4.00 2.00(L) 3.40 5.45(H)

Large Range and higher sigma of 1.2m. ACRi and ICMAM appear to be outliers. (15%)1

Kudankulam 1.531.351

±±±±0.44±±±±0.111

1.51 1.41 1.30 1.25(L) 2.40(H)

1.28 Reasonably Good Agreement. NGRI appears to be an outlier.(8%)1

Haripur (WB) 0.80 ±±±± 0.11 0.87 0.83 0.68(L)

0.75 0.97(H)

0.71 Good Agreement.(14%)1

Patisonapur (Orissa)

1.78 ±±±±0.38 1.96 1.8 1.24 --- --- 2.1(H) Reasonably Good Agreement (21%)1

Mithirvirdi (Gujarat)

0.150.291

±±±±0.14--

--- --- 0.01(L)

0.15 --- 0.29(H)

Not so good agreement. IIT-M appears to be an outlier. Should be closer to Trombay&Tarapur sites

Kovvada (A.P.)

1.462.11

±±±±0.73±±±±0.051

--- 2.12(H) 0.68(L)

1.00 --- 2.03 Reasonably Good Agreement. . IIT-M appears to be an outlier.(2%)1

Indian Costal Sites

Mean tsunami height(m)

Std.Dev(m)

Predicted tsunami height (m)

IGCAR-SWAN

IGCAR-COMCOT

IIT-M ICMAM NGRI ACRiRemarks

(sigma to mean ratio %)

1The mean and standard deviations calculated for ori ginal data and after removing the outlier.

Tide Gauge Station

Mean tsunami height

(m)

Std.Dev(m)

Reported de-tided gauge

(m)

Predicted tsunami height (m) and (sigma to mean ra tio %)

IGCAR-

SWAN

IGCAR-COMCOT

IIT-M

ICMAM

NGRI ACRi

Remarks

Paradeep 1.741.58

±±±±1.45±±±±0.31

3.18 1.23 1.82 (H) 0.51(L)

0.70(L)

1.7 4.5(H)

Large range ofvalues and highsigma of 1.4 m.Possible outliers:IIT-M ACRi andICMAM(20%1)

Visakhapatnam

1.961.84

±±±±1.05±±±±0.55

2.91 2.55 3.68 (H) 0.71(L)

1.20 1.78 1.84 Large range ofvalues and highsigma of 1.05 m.Possible outliers:IIT-M & IGCAR-COMCOT.(30%)

Chennai 3.323.35

±±±±1.09±±±±0.77

3.24 3.43 3.72 4.00 1.80(L)

4.7(H)

2.25 Large range ofvalues and highsigma of 1.09 m.Possible outliers:IIT-M and NGRI(23%1).

NIO tide gauge analysis from de-tided data Rabinovi ch et. al. (2007). Good comparison for Chennai due to local refined grid co mpared to other stations

Evaluation of Global Propagation Models with Tide G auge Data and Prediction for Coastal Nuclear Facilities

Indian Coastal Locations

Global Tsunami wave height in reasonably good agree ment with standard deviation to mean height ratio ~2% to 25% (Larger d ifferences only for sites that see secondary insignificant effects and tsunam i heights are very negligible)

Tide gauge stations Paradeep, Visakhapatnam and Che nnai

The global predictions of tsunami heights in reason ably good agreement among the participants for these tide gauge locatio ns (within a range of 20%-30%).

Only for Chennai tide gauge, the mean prediction of 3.35 m tsunami wave height has very good comparison with the de-tided m easured data of 3.24 m (within ~3.4%) while at other two locations the dif ferences are large. This is due to refined bathymetry used by the participants around Chennai with an objective to carry out inundation modelling for Kal pakkam nuclear site.

IdentifiedLocations(100m depth)

Mean tsunami height

(m)

Std.Dev(m)

Predicted run up (m)

IGCAR-

SWAN

IGCAR-COMCOT

IIT-M(Global Model)

IIT-M(Local Model

)

ICMAM

NGRI

ACRi

Remark

X - North 2.301.911

±±±±1.06±±±±0.371

2.07 2.15 3.86 (H)

3.58(H)

1.00(L)

1.36 (L)

2.07 Large range of values and high sigma of 1.06 m.Possible outliers: IIT-M ICMAM(19%1)

Y - Middle 1.972.021

±±±±0.59±±±±0.381

2.12 2.17 2.73 (H)

2.35 1.00(L)

1.37 (L)

2.08 Moderate range of values with sigma of 0.59 m. Possible outliers: IIT-M ICMAM (19%1)

Z – South 1.661.921

±±±±0.49±±±±0.211

2.1 2.12 (H)

1.9 1.61 1.00(L)

0.98 (L)

1.89 Moderate range of values with sigma of 0.49 m. Possible outliers: ICMAM NGRI.(11%1)

1The mean and standard deviations are calculated for original data and after removing the outlier.

Validation of Global and Local Numerical Models at 100m depth

Inundation Prediction Locations (I-1 to I-5)

I-1I-2

I-3

I-4

I-5

I-1 outside Kokkilimedu Security GateI-2 outside Kokkilimedu Security GateI-3 back side of the Fire StationI-4 Behind Swimming PoolI-5 Behind Central Avenue

I1 Kokkilimedu Security Gate I3 Back side of Fire Station

I4 Behind Swimming Pool I5 Behind Central Avenue

I-1 outside Kokkilimedu Security Gate

330

156212 212

362

113

-61

-5 -5

125

217

-100

0

100

200

300

400

Prediciton 217 330 156 212 212 362

Deviation 113 -61 -5 -5 125

SRI IGCAR IIT-M ICMAM NGRI ACRi

615 662

185

601

458391

438

-39

377

234224

-100

0

100

200

300

400

500

600

700

Prediction 224 615 662 185 601 458

Deviation 391 438 -39 377 234


335385

299350

458

99149

63114

222236

0

100

200

300

400

500

Prediction 236 335 385 299 350 458

Deviation 99 149 63 114 222


615350

845

1350 1310

303

38

533

1038 998

312

0200400600800

1000120014001600

Prediction 312 615 350 845 1350 1310Deviation 303 38 533 1038 998


I-2 outside Kokkilimedu Security Gate I-3 back side of the Fire Station

I-4 Behind Swimming Pool I-5 Behind Central Avenue

Comparison of Predicted Inundation Reach for Kalpak kam site

IdentifiedLocation

SRI-Inundation

Measurement(m)

Inundation (m) PredictionsMean

Inundation (m)

Std. Dev(m)

% Variation among various codes

% Variation

with measurem

ent

IGCAR IIT- M ICMAM NGRI ACRi

Original/after

outlier correction

Original /after outlier correction

Original/ after outlier correction

Original/after outlier correction

I-1 241 560 430 322 600 547 491.8/512 114/71.6 23.2/13.97 104/112.6

I-2 224 615 662 185 601 458 504/558 194/86.9 38.5/15.6 125/149

I-3 217 330 156 212 212 362 254.4/251 87.4/68.1 34.4/27.1 17.2/15.8

I-4 312 615 350 845 1350 1310 894/923 435/354 48.7/38.3 186.5/196

I-5 236 335 385 299 350 458 365/357 60.3/25.66

16.5/7.2 54.8/14.3

Prediction Locations of Run-up Height reach at Kalpakkam site

R-1

R-2

R-4

R-3

R-5

R-6

R-7R-8

Edaiyur Bridge

Water intake - MAPS

BHAVINI soil sample storage building

GAMMON Quarters

Sadras Fort

Township, Sadras East

21st Street

23rd Street CISF Barracks

R1 Edaiyur Bridge R2 Water Intake MAPS

R5 Sadras Fort R6 Township, Sadras East

3.99

6.00

2.833.46 3.5

-0.61

1.40

-1.77-1.14 -1.1

4.6

-3-2

-10

12

34

56

7

Prediction 4.6 3.99 6.00 2.83 3.46 3.5

Deviation -0.61 1.40 -1.77 -1.14 -1.1


5.155.72

3.88 4.00

5.74

0.651.22

-0.62 -0.50

1.24

4.5

-1

0

1

2

3

4

5

6

7

Prediction 4.5 5.15 5.72 3.88 4.00 5.74

Deviation 0.65 1.22 -0.62 -0.50 1.24


4.905.70

3.75 3.954.49

0.301.10

-0.85 -0.65-0.11

4.6

-2

-1

0

1

2

3

4

5

6

7

Prediciton 4.6 4.90 5.70 3.75 3.95 4.49

Deviation 0.30 1.10 -0.85 -0.65 -0.11


4.575.78

2.95 3.144.27

-0.23

0.98

-1.85 -1.66

-0.11

4.8

-4

-2

0

2

4

6

8

Prediction 4.8 4.57 5.78 2.95 3.14 4.27

Deviation -0.23 0.98 -1.85 -1.66 -0.11


R-1 Edaiyur Bridge R-2 Water intake - MAPS

R-3 BHAVINI soil sample storage building

R-4 GAMMON Quarters

R-5 Sadras Fort R-6 Township, Sadras East

R-7 21st Street R-8 23rd Street CISF Barracks

4.465.80

3.53 3.995.22

-2.14

-0.80

-3.07 -2.61-1.38

6.6

-4

-2

0

2

4

6

8

Prediction 6.6 4.46 5.80 3.53 3.99 5.22

Deviation -2.14 -0.80 -3.07 -2.61 -1.38


3.79

5.77

3.20 3.524.38

-0.96

1.02

-1.55 -1.23-0.37

4.75

-2

0

2

4

6

8

Prediction 4.75 3.79 5.77 3.20 3.52 4.38

Deviation -0.96 1.02 -1.55 -1.23 -0.37


2.73

5.82

2.663.97 4.19

-1.37

1.72

-1.44

-0.13

0.09

4.1

-2

-1

01

2

3

45

6

7

Prediction 4.1 2.73 5.82 2.66 3.97 4.19

Deviation -1.37 1.72 -1.44 -0.13 0.09


2.68

5.83

2.45

3.94 3.79

-1.12

2.03

-1.35

0.14 -0.01

3.8

-2

-1

01

2

3

45

6

7

Prediction 3.8 2.68 5.83 2.45 3.94 3.79

Deviation -1.12 2.03 -1.35 0.14 -0.01


Comparison of Predicted Run-Up for Kalpakkam site

IdentifiedLocation

SRI-Run-up

Measurement

(m)

Run-up (m) Predictions

MeanRun-up (m)

Std. Dev(m)

% Variation

among various

codes

% Variation with measurement

IGCAR IIT-M ICMAM NGRI ACRi





R-1 4.60 3.99 6.00 2.83 3.46 3.5 3.96/3.65 1.21/0.30 30.7/8.0 14.0/20.7

R-2 4.50 5.15 5.72 3.88 4.00 5.74 4.96/4.90 0.88/0.91 17.6/18.5 10.1/8.8

R-3 4.60 4.9 5.70 3.75 3.95 4.49 4.45/4.56 0.48/0.78 10.7/17.2 3.3/0.1

R-4 4.80 4.57 5.78 2.95 3.14 4.27 4.14/3.99 1.15/0.75 27.8/18.9 13.7/16.8

R-5 6.60 4.46 5.80 3.53 3.99 5.22 4.60/4.56 0.92/0.62 19.9/13.6 30.3/30.9

R-6 4.75 3.79 5.77 3.20 3.52 4.38 4.13/3.90 1.01/0.44 24.5/11.3 13.0/18.0

R-7 4.10 2.73 5.82 2.66 3.97 4.19 3.87/3.63 1.29/0.79 33.3/21.7 5.5/11.5

R-8 3.80 2.68 5.83 2.45 3.94 3.79 3.74/3.47 1.34/0.69 35.9/19.8 1.6/8.7

Observations on Inundation and Runup Computations

All the participants have over predicted the inunda tion. This may be due to the simplified models without any str uctures and percolation into the ground. The deviation at I-4 was generally high due to proximity of location to Sadr as backwaters and land morphology grid interpolation e rror.

All the run-up values predicted by various particip ants are in good agreement Also, at location R-5 (near Sadra s fort) the deviation was large for most of the participant s.

The present code capabilities are sufficient for ts unami run up predictions but inundation prediction can only i mprove with additional land / structure data and improved capabilities in the code.

Remarks on Sumatra Tsunami-Eastern Coast The initial studies (2005) of tsunami propagation for Sumatra-2004 and Makran-1945 events with in-house finite element code TSUSOL have been useful for the National Warning System. Spectral signals confirmed by the tide gauge data later published by Rabinovich et. al. (2007).

The various codes in use for the tsunami propagatio n and inundation / run-up prediction in the National Rational Round Ro bin have been evaluated and benchmarked with the measured and rep orted data.

Tsunami height data has been generated for the pres ent and future prospective coastal stations.

Design tsunami wave runup can be predicted by the p resent codes in case refined bathymetry and land morphology data is collected for a specific site as is shown for Kalpakkam site as a c ase study.

Our future efforts are directed towards generating improved source models backed up with data from warning system for s ubsequent earthquake events and carry out the detail tsunami studies for the present and future coastal nuclear facilities.

Work for Western Coast NPPs – Tarapur SiteWith the benchmarking of various numerical codes available with theNational Tsunami Round Robin Participants, the tsunami haz ardevaluation for Indian West Coast carried with detail inunda tion andrun-up estimation of the existing plants at Tarapur site for Makran-1945 event.

Makran subduction zone ~ 1000 km of Eurasian-Arabian plateboundary – poor historical record and the only single record of 1945Mw 8.1 event insufficient as per the present day standards.

Eastern & western halves of Makran subduction zones have dif ferentseismicity patterns

Western coast regions with shallow depths pose difficultie s toseparate global/local models as experienced in Sumatra-20 04simulation

Possible focusing effects due to above complexities needs t o bestudied.

Name of theLocations

AverageRun up

(m)

Std.Dev

Range Predicted Run-up (m) Remarks

AERB IGCAR ACRi NPCIL ICMAM

Mumbai 0.97 ±±±±0.15 0.75-1.03 0.94 0.85 1.03(H) 1.23 0.75(L)

Trombay (BARC) 0.59 ±±±±0.43 0.02-1.05 N.D. N.D. 0.02(L) N.D. 1.05(H)

Tarapur 0.52 ±±±±0.33 0.14-1.06 0.43 N.D. 1.06(H) 0.46 0.14(L)

Jaitapur (Ratnagiri) 0.89 ±±±±0.14 0.69-1.10 0.83 0.87 0.96 1.10(H) 0.69(L)

Visakhapatnam 0.01 ±±±±0.01 0-0.020.01 N.D. 0.02(H) 0.00(L) N.D.

Kalpakkam 0.01 ±±±±0.01 0-0.020.02 N.D. 0.02(H) 0.00(L) N.D.

Kudankulam 0.54 ±±±±0.20 0.29-0.81 0.44 N.D. 0.29(L) 0.81(H) 0.62

Patisonapur(Orissa) 0.02 ±±±±0.01 0.01-0.02 0.02 N.D. 0.02(H) N.D. 0.01(L)

Mithirvirdi (Gujarat) 0.22 ±±±±0.05 0.24-0.26 0.24(L) N.D. 0.26(H) N.D. 0.26

Kovvada (Andhra Pradesh)

0.02 ±±±±0.01 0.01-0.03 0.01(L) N.D. 0.03(H) N.D. N.D.

Haripur (West Bengal)0.02 ±±±±0.00 0-0.02

0.02(H) N.D. N.D. N.D. N.D.

Prediction of Sea Wave Height at Coastal Locations from Global Analysis

CS1 Mumbai

Run

up

(m

)

Mean 0.97SD ±0.15

Series1, AERB,

0.94

Series1, IGCAR_G,

0.85

Series1, IGCAR_L,

1.04

Series1, ACRi, 1.03

Series1, NPCIL,

1.23 Series1, ICMAM,

0.75

CS4 Jaitapur (Ratnag

iri), AERB…


iri), IGCA…


iri), ACRi, …


iri), NPCI…


iri), ICMA…

Mean 0.89SD ±0.14

CS4 Jaitapur (Ratnagiri)

CS7 Kudanku

lam, AERB,

0.44

CS7 Kudanku

lam, ACRi, 0.29

CS7 Kudanku

lam, NPCIL,

0.81

CS7 Kudanku

lam, ICMAM,

0.62

CS7 Kudankulam

Mean 0.539SD ±0.195

Comparison of Tsunami Wave Heights at Important Coa stal Stations

CS9 Mithirvir

di (Gujarat)

, …

CS9 Mithirvir

di (Gujarat)

, …

CS9 Mithirvir

di (Gujarat), ACRi, …

CS9 Mithirvir

di (Gujarat)

, …

CS9 Mithirvirdi (Gujarat)

ID Validation Locations AERB IGCAR_G ACRi NPCIL ICMAMNTS1 PORBANDAR 0.71 1.33 1.06 1.16 0.75NTS2 JAFARABAD 0.53 0.61 1.20 0.57NTS3 BOMBAY APOLLO BANDAR 1.02 0.99 1.51 1.31 0.68NTS4 RATNAGIRI BAY 1.13 0.99 1.66 1.63 1.10NTS5 MORMUGAO 0.86 0.80 0.75 1.18 0.30NTS6 MANGALORE 0.66 0.75 1.01 0.78 0.61NTS7 COCHIN 0.92 0.57 0.78 0.75 0.45NTS8 KAVARATTI 0.22 0.39 0.31 0.28 0.20NTS9 MINICOY 0.28 0.42 0.46 0.24 0.32

� Good agreement forMumbai Jaitapur andMithirvirdi.� For Tarapur 4 participantsprovided predictions andthere is a scatter of about ±±±±0.3m. Range: 0.14-1.06m�The run up at Kudankulam(0.54 ±±±± 0.2 m) for Makranevent & 1.35 ±±±± 0.11m forSumatra Case.

Comparison of Results Near Shore Tidal Stations (NTS)

Good agreement for all near shore tidal stations (NTS) scatt erbetween: ±±±± 0.07 to ±±±± 0.29m

I4, ACRi, 100

I4, ICMAM, 92

I5, ACRi, 200

I5, NPCIL, 202

I5, ICMA

M, 184

Inundation Reach (m) around Tarapur siteID AERB NPCIL ICMAMI1-A 0.88 0.91I1-BI2-C 0.88 0.88 1.42I2-D 0.79 0.89I3-E 0.90 0.88 1.70I3-F 0.88I4-G 0.83 0.80 1.50I4-HI5-I 0.67 0.98 1.15I5-J 0.70 1.01 1.25I6-K 0.74 1.12 1.48I6-L 1.15 1.60I7-M 0.83 0.98 2.55I7-N 0.80 1.01 2.42I8-O 0.79 1.24 1.49I8-P 0.90 2.20

Inundation Run-up (m) around Tarapur site

I-4 I-5

NUCLEAR POWER PLANTS INUNDATION MODELING

FAULT PARAMETERS FOR THE 1945 EARTHQUAKE IN MAKRAN REGION (Actual Magnitude of the Earthquake i s

8.1Mw in this worst scenario we consider 9.0Mw like Fukushima)

S.NO PARAMETERS VALUES

1 ORIGIN TIME(IO,JO) (134,1133)

2 SLIP MAGNITUDE 15m

3 LENTH&WIDTH OF THE FAULT 200 km,100 km

4 STRIKE ANGLE 270˚

5 DIP ANGLE 14˚

6 SLIP ANGLE 90˚

7 FOCAL DEPTH 10 km

Computatinal Grids used for Inundation model

GRID-A;Resolution:81 Arc Seconds

Directivity Map

Location Map

S.NO

LOCATIONS LONGITUDE (DD)

LATITUDE (DD)

ARRIVALTIME (min)

RUN-UP HEIGHT

(m)

1 R-1 77.6854 8.1545 336.75 1.765

2 R-2 77.7021 8.1574 338.25 1.518

3 R-3 77.7139 8.1613 339.00 1.468

4 R-4 77.7274 8.1657 341.75 1.434

5 R-5 77.7393 8.1692 342.25 1.204

1945 Makran Results

INUNDATION EXTENT

SEA

LAND

Directivity map showing Tsunami Wave Propagation of 26th Dec 2004 Sumatra Tsunami

S.NO

LOCATIONS LONGITUDE (DD)

LATITUDE (DD)

ARRIVALTIME (min)

RUN-UP HEIGHT (m)

1 R-1 77.6854 8.1545 223.25 4.07

2 R-2 77.7021 8.1574 222.75 3.34

3 R-3 77.7139 8.1613 222.00 2.76

4 R-4 77.7274 8.1657 221.25 2.48

5 R-5 77.7393 8.1692 218.75 2.26

2004 SUMATRA RESULTS

INUNDATION EXTENT

LONGITUDE(DD)

LATITUDE(DD)

m

JAITAPUR RESULTS

Computatinal Grids used for Jaitapur Inundation model

GRID-D;Resolution:3 Arc Seconds

JAITAPUR RUN-UP HEIGHT AND INUNDATION EXTENT

S.NOLONGITUD

E(degree)

LATITUDE(degree)

LOCATIONS RUN-UP HEIGHT

(m)

INUNDATION EXTENT (m)

1 73.3183 16.6414 I-1 1.436 277.75

2 73.3351 16.6312 I-2 1.790 555.50

3 73.3350 16.6126 I-3 1.696 499.95

4 73.3165 16.6033 I-4 1.390 440.00

5 73.3161 16.5864 I-5 1.621 444.40

6 73.3147 16.5622 I-6 1.395 222.00

0 10000 20000 30000 40000

TIME (m)

-2

-1

0

1

2

WA

VE

AM

PLI

TU

DE

(m

)

Run-upI-1I-2I-3I-4I-5

Jaitapur Run-up Height

Jaitapur Inundation

Longitude.(°)

Latitude.(°)

m

Sea Land

During the recent Sumatra earthquake event of April 11, 2012 , the initialmagnitude of the earthquake estimated ~8.7 on the Richter sc ale. As reportedby Indian National Centre for Ocean Information Services (I NCOIS), the firstbulletin issued within 8 minutes ie.1416 hours IST. This est imate revised to 8.5.An earthquake of this magnitude can generate tsunami. All th e systems for theidentification of location of earthquake, estimation of ts unami arrival time andheight, dissemination of messages through SMS, email, Fax, GTS & Website,as well as bottom pressure recorders and tidal gauges to reco rd sea levelchanges managed under the National Warning System have perf ormed asenvisaged. This event is further being studied.

Chennai 13.10 N 80.30 E 11/04/2012 23:50 0.18mVizag 17.71 N 83.32 E 11/04/2012 17:49 0.10m

Ennore 13.25 N 80.33 E 11/04/2012 17:21 0.09m

Meulaboh 4.317 N 96.217 E 11/04/2012 15:30 1.02m

Conclusions

Tsunami evaluation for Indian NPP sites have been carried ou tin an extensive manner for coastal plants on eastern & wester n coasts

The on site refined data collection with regard to local bath ymetry &land morphology and past historical records is important fo r numericalcode validation

Numerical code comparison is needed to evolve a suitable ana lysisprocedure to obtain acceptable results with due considerat ion tolimit the numerical dispersion & diffusion errors using opt imum gridscheme consistent with local site

Near shore earthquake need special considerations for sour cemodeling including compressibility effects- March 2011 of the PacificTohoku Earthquake experience that affected Fukushima Plan ts .

In our case we need to relook the Andaman Source which is neare r toeastern coast and study the directivity effects.


Thank You