Allowing for Uncertainty in Site Response Analysis

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Presentation transcript:

Allowing for Uncertainty in Site Response Analysis The 5th Tongji-UBC Symposium on Earthquake Engineering “Facing Earthquake Challenges Together” May 4-8 2015, Tongji University Shanghai, China Allowing for Uncertainty in Site Response Analysis Dr Jason Dowling Dept of Civil Engineering The University of British Columbia

Overview Site Information & Motivation for the Study Geotechnical Data May 4th, 2015 Overview Site Information & Motivation for the Study Geotechnical Data Variation of Input Properties Site Response Analysis Allowing For Uncertainty Analysis Results

Site Response Analysis May 4th, 2015 Site Response Analysis The propagation of seismic waves as they travel through the local soil stratigraphy to the surface The key components: Input Motions and Soil Properties

Site Information Three schools sites in Richmond, BC British Columbia May 4th, 2015 Site Information Three schools sites in Richmond, BC British Columbia

May 4th, 2015 Site Information Three schools sites in Richmond, BC

Site Information The geological formation of the Fraser Delta May 4th, 2015 Site Information The geological formation of the Fraser Delta As a result, there can be a considerable depth to bedrock in areas of the delta Source: Clague et al. (1998)

May 4th, 2015 Site Information Geological cross-section from Burrard Inlet, BC to Bellingham, WN

May 4th, 2015 Site Information Geological cross-section from Burrard Inlet, BC to Bellingham, WN

May 4th, 2015 Site Information Geological cross-section from Burrard Inlet, BC to Bellingham, WN Source: Clague et al. (1998)

Geotechnical Data Example of data available >300m Borehole May 4th, 2015 Geotechnical Data Example of data available >300m Borehole from Richmond Source: Clague et al. (1998)

May 4th, 2015 Geotechnical Data Vs data, 300m Borehole from Richmond

Geotechnical Data Richmond Vs data Vs (to depths of 3.5km) May 4th, 2015 Geotechnical Data Richmond Vs data Vs (to depths of 3.5km) derived from seismic reflection data Source: Clague et al. (1998)

Geotechnical Data Richmond Vs data Empirical relationship May 4th, 2015 Geotechnical Data Richmond Vs data Empirical relationship Source: Clague et al. (1998)

May 4th, 2015 Geotechnical Data Borings were performed at the three school sites, giving Vs profiles (top 30m only)

May 4th, 2015 Geotechnical Data Combining the Measured Vs profiles and Empirical Vs-depth relationship

Variation of Input Properties May 4th, 2015 Variation of Input Properties Monte Carlo Distributions

Site Response Analysis Allowing For Uncertainty May 4th, 2015 Site Response Analysis Allowing For Uncertainty 1,000’s of randomly simulated sets of soil properties are analysed subject to the same input motions

May 4th, 2015 Analysis Results Example 1: to demonstrate the influence of the uncertainty in a critical parameter, Vs Input Variables to Monte Carlo Material property Mean value Standard Deviation Vs (above 30m) Varies (from SCPT data) 25m/s or 75m/s Vs (below 30m) Varies (Empirical equation) Nkt 14 2 φ 38° 2° γ 19kN/m3 0.5kN/m3

May 4th, 2015 Analysis Results Example 1: to demonstrate the influence of the uncertainty in a critical parameter, Vs The standard deviation used in the input in 25m/s here

May 4th, 2015 Analysis Results Example 1: to demonstrate the influence of the uncertainty in a critical parameter, Vs Spread of Input parameters, Vs (standard deviation = 25m/s)

May 4th, 2015 Analysis Results Example 1: to demonstrate the influence of the uncertainty in a critical parameter, Vs The standard deviation is increased to 75m/s here

May 4th, 2015 Analysis Results Example 1: to demonstrate the influence of the uncertainty in a critical parameter, Vs Comparing the 25m/s and 75m/s standard deviation results

May 4th, 2015 Analysis Results Full Stochastic Analysis: 30 input motions, 150 variations of soil properties for each motion, 4,500 simulations in total

May 4th, 2015 Analysis Results Full Stochastic Analysis: 30 input motions, 150 variations of soil properties for each motion, 4,500 simulations in total

May 4th, 2015 Analysis Results Full Stochastic Analysis: 30 input motions, 150 variations of soil properties for each motion, 4,500 simulations in total

May 4th, 2015 Conclusions Stochastic Monte Carlo simulation was used in the site response analyses of three deep (300m) school sites located in Richmond, BC to estimate amplification factors for seismic retrofit designs It was found to be an effective method of coping with the effects of uncertainty in the soil properties used in nonlinear 1D site response analyses The simulations resulted in stable mean values of spectral accelerations The mean spectral response in the period range of interest for retrofit design of 1-2seconds, increased by 15% as the standard deviation in Vs went from 25m/s to 75m/s

We would like to express our gratitude to some organisations and industry partners who contributed to our travel expenses