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Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire, France

Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

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Page 1: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Nonlinear Site Effects: laboratory and field data

observations and numerical modeling

Luis Fabián Bonilla

Institut de Radioprotection et de Sûreté Nucléaire, France

Page 2: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Presentation Outline

• Empirical evidence of nonlinear site effects

• Some models of nonlinear site response

• Examples

Page 3: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Loose sand => licuefaction

-Lowpass filtering

-Deamplification

Dense sand => cyclic mobility

- High frequency peaks

- Amplification

Port Island, Kobe / Kushiro Port

Page 4: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Nonlinear Effects: TTRH02 Station (Japan)

Site amplification is different for strong ground motion

Page 5: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

PGA distribution (Kik-net)

(M7, 26 Mai 2003)

Page 6: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

EPRI modulus reduction and damping curves

Page 7: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Velacs Project, 1992 (pore pressure effects)

Page 8: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

How is the transfer function affected?

Deamplification: the damping increases (pay

attention)

Increase of the signal duration (long period

waves arrive later)

1. The shear modulus is computed as G=2

2. The fundamental frequency of the soil is f0=/(4H)3. If G changes, so does : if G(-) ---> (-) ---> f0(-)

Page 9: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Numerical solutionsWhy?

There is no analytical solutionFinite differences, spectral elements,

finite elements methods, etc.Boundary conditions:

Surface: free surface effectBedrock: elastic boundary conditions

(transmitted waves) or rigid boundary conditions (complete reflection)

Page 10: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Some models of nonlinear site response

Page 11: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

The equivalent linear model (1972)

G- frequency dependent (Assimaki and Kausel, 2002)

Page 12: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Iwan-Mroz Model (1967) – Plasticity Theory

Gmax G1

G2

Gn

Shear Strain

She

ar M

odul

us (

G)

Gmax

G1

G2

Gn

Shear StrainS

hear

Str

ess

Reconstruction of backbone from the modulus reduction curve

Backbone

Page 13: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Multi-spring Model (1)

2D plane strain model Each spring obeys the

hyperbolic model Hysteresis follows the

generalized Masing rules

Capability to model anisotropic consolidation conditions

Plasticity theory and phenomenological description of hysteresis

Page 14: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Pore pressure excess is correlated to shear work

Model space has five parameters to take into account dilatancy

Plastic parameters are angle of internal friction, and angle of phase transition

Elastic parameters are thickness, Q, density, P and S wave speeds

Multi-spring Model (2)

Page 15: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Examples

Page 16: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

The M7.8 Kushiro-Oki 1993 event

Dense sand deposit, first studied by Iai et al (1995)

Vs30 = 284 m/s

Page 17: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Results

Pore pressure analysis may be needed if soil is saturated

Input

Trad. EqL

Improved EqL

Iwan-Mroz

Multispring

Page 18: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

2D linear and nonlinear response of the Grenoble basin

Linear

Nonlinear

Page 19: Nonlinear Site Effects: laboratory and field data observations and numerical modeling Luis Fabián Bonilla Institut de Radioprotection et de Sûreté Nucléaire,

Perspectives The choice of rheology is important in the modeling of

nonlinear site response. A desirable rheology should have the lower number of

parameters that realistically model observed data. The Iwan-Mroz represents better the nonlinear soil behavior

with the same data as the Eq. Linear method. However, better soil characterization is needed when having

saturated medium (triaxial and centrifuge modeling). Luca Lenti, LPCP-IRSN postdoc, has developed a 3D elasto-

plastic model following Iwan (1967). Only G/Gmax data are needed.

We need to study which numerical integration scheme (FDM, FEM, SEM, etc.) is suitable to handle material nonlinearity.

How are we going to combine all these numerical efforts? SUGGESTIONS?