Deterministic and Probabilistic Seismic Soil Structure Interaction Analysis of the Mühleberg Nuclear Power Plant SUSAN Building
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1 Deterministic and Probabilistic Seismic Soil Structure Interaction Analysis of the Mühleberg Nuclear Power Plant SUSAN Building David K. Nakaki, Simpson Gumpertz & Heger Philip S. Hashimoto, Simpson Gumpertz & Heger James J. Johnson, James J. Johnson & Associates Yahya Bayraktarli, BKW FMB Energie AG Olivier Zuchuat, BKW FMB Energie AG Soil Structure Interaction Knowledge and Effect on the Seismic Assessment of NPP Structures and Components October 6-8, 2010 Ottawa, ON, Canada
2 Overview of the Presentation Introduction Summary of the deterministic and probabilistic seismic response analysis methodology Application to Mühleberg SUSAN Building 2
3 Introduction Seismic probabilistic safety assessment (PSA) of Mühleberg Nuclear Power Plant (KKM) is currently being updated. New seismic response analyses were performed using current methods to determine median structure responses for seismic fragility evaluation of structures, systems, and components. Deterministic and probabilistic seismic response analyses was performed for the KKM SUSAN Building 3
4 Methodology Establish Free Field Ground Motion Develop Median Earthquake Strain Compatible Site Soil Properties Develop Fixed Base Structure Model Determine natural frequencies and mode shapes Determine SSI Parameters Foundation impedances Scattering matrices Perform SSI Response Analysis 4
5 Seismic SSI Response Analysis Deterministic SSI Response Analysis Single median-centered response analysis using CLASSI Results used to understand the soil-structure system dynamic behavior. Probabilistic SSI Response Analysis Perform statistical sampling and Latin Hypercube Simulation (LHS) experimental design Execute Seismic Methodology Analysis Chain with Statistics (SMACS) methodology documented in NUREG/CR N = 30 simulations using LHS approach Perform SSI analyses for N = 30 simulations Compute median (50%) and 84% in-structure response spectra (ISRS) 5
6 Spectral Acceleration (g) Spectral Acceleration (g) KKM Free Field Ground Motion Time histories match the site 10-4 mean 5% damped Uniform Hazard Spectra (UHS) Control motion is defined at the soil surface 1.0E-04 Mean Horizontal 1.0E-04 Mean Vertical Frequency (Hz) (-)14 m Surface (-)7 m Frequency (Hz) (-)14 m Surface (-)7 m 6
7 Time Histories for Deterministic Analysis Two horizontal components and one vertical component developed in general compliance with requirements of ASCE
8 Time Histories for Probabilistic Analysis Thirty time history sets generated such that the median spectral acceleration of the ensemble matched the 1.0E-04 UHS Ensemble was conditioned such that the spectral acceleration coefficient of variation (COV) was approximately 0.2 over the frequency range of interest (2 to 20 Hz). Additional variability included for horizontal and vertical peak variability in accordance with recommendations of EPRI TR
9 Spectral Acceleration (g) Spectral Acceleration (g) Spectral Acceleration (g) Ensemble of Thirty Time Histories 2.5 H1 2.5 H Frequency (Hz) Frequency (Hz) V Frequency (Hz) 9
10 Median-Centered Soil Properties General site conditions consist of soil overburden on rock substrate Low strain soil properties based on existing available site data. Site response analysis was performed to establish earthquake strain compatible soil properties for the layered site. Shear wave velocity Soil damping Poisson s ratio Density 10
11 Depth (ft) Median-Centered Shear Wave Velocity Profile 0 Shear Wave Velocity (ft/sec) Low Strain Median Centered Strain Compatible 11
12 SUSAN Building Configuration Squat, rectangular, embedded reinforced concrete structure Nominal grade elevation: 0 m Foundation plan dimensions: 19 m (EW) x 27.5 m (NS) Top of foundation located at Elevation (-)11 m Nominal floor elevations at Elevations (-)7.3 m, (-)4 m, 0 m, 3.5 m, and 7.5 m. Very robust structural system Includes an interface structure on the east side which provides access to the Reactor Building. 12
13 SUSAN Building Fixed Base Model SAP2000 Fixed Base Model Beam and plate elements Median material properties 200 modes extracted Significant Fixed Base Modes 9.40 Hz Fundamental EW (Y) mode Hz Fundamental NS (X) mode Hz Torsional mode Hz Interface Structure Vertical (Z) mode Hz Fundamental Vertical (Z) mode Output Nodal geometry Mass matrix Natural frequencies and mode shapes 13
14 Development of SSI Parameters Hybrid method employed to calculate the embedded foundation impedances and scattering matrices. The embedded foundation is modeled in SASSI2000 with the median soil properties. The unconstrained (flexible) impedances from the SASSI2000 model are generated. The embedded region is idealized as rigid relative to the surrounding soil. Scattering and impedance functions of the rigid embedded foundation are generated by imposing rigid body constraints within the embedded region. 14
15 SUSAN Building Impedance and Scattering Excavated soil volume displaced by the embedded portion of the structure is modeled in SASSI2000 Quarter symmetry model 15
16 Deterministic Median In-Structure Response Spectra X (NS) Direction, centers of floors Y (EW) Direction, centers of floors 16
17 Probabilistic SSI Response Analysis Consider variability of soil/foundation behavior, structure dynamic properties, and input motion Statistical sampling and Latin Hypercube Simulation experiment design SMACS analysis SSI response analysis of the N = 30 simulations Compute ISRS and probability distributions 17
18 Statistical Sampling and Latin Hypercube Simulation Model variability of the soil/foundation behavior by modifying soil stiffness (shear modulus) and damping through scale factors in the simulations Model variability in the structure dynamic properties by shifts in fixed-base frequencies (stiffness) and modal damping 18
19 Latin Hypercube Simulation Design Input Lognormal distribution of input parameters Soil shear modulus COV = 0.40 Soil damping COV = 0.40 Structure frequency COV = 0.15 Structure damping COV = 0.35 Analysis Techniques Latin Hypercube Simulation with 30 simulations Output Set of input scale factors for the earthquake simulations Scale factors are applied to parameters above Scale factors have median values of 1.0 and COV s above 19
20 SMACS Analysis Perform response simulations using the ensemble of 30 earthquake acceleration time histories with the 30 combinations of soil stiffness and damping and structure frequency and damping. Output in-structure response spectra and calculate probability distributions 20
21 Spectral Acceleration, g SUSAN Building In-Structure Response Spectra 1.6 SUSAN Building Probabilistic, Elevation 0 m, Center of Floor, Z-Direction Median 84% Frequency, Hz 21
22 Probabilistic Median In-Structure Response Spectra X (NS) Direction, centers of floors Y (EW) Direction, centers of floors 22
23 Probabilistic Median and 84%In-Structure Response Spectra X (NS) Direction, Elevation 0 m Y (EW) Direction, Elevation 0 m 23
24 Comparison of Median Deterministic and Probabilistic In-Structure Response Spectra Y (EW) Direction, Elevation 0 m Z (Vertical) Direction, Elevation 0 m 24
25 Advantages of the SMACS Approach Development of the fixed base structure model and calculation of the modal properties represents most of the engineering effort. Greater effort can be dedicated to developing detailed models. Calculation of the impedance and scattering functions of the embedded foundation represents significant computation time, but is only done once using the hybrid approach. By using SMACS to perform the SSI response analysis, the thirty LHS SSI simulations were completed in minutes. 25
26 Summary and Conclusions Deterministic and probabilistic SSI analysis were performed for the KKM SUSAN Building The deterministic SSI analysis were used to benchmark the probabilistic analysis. Deterministic and probabilistic methods produced consistent results. Sharp spectral acceleration peaks in the deterministic analysis are reduced by the probabilistic analysis. High variability was obtained at resonant frequencies of the structure/soil system in the probabilistic analysis. 26
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