Analysis of borehole data Luis Fabian Bonilla Universite Paris-Est, - - PowerPoint PPT Presentation

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Analysis of borehole data Luis Fabian Bonilla Universite Paris-Est, IFSTTAR, France 1 Outline Advantages of borehole data Difficulties of working with these data Understanding linear and nonlinear modeling Working

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Analysis of borehole data

Luis Fabian Bonilla

Universite Paris-Est, IFSTTAR, France

1

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Outline

  • Advantages of borehole data
  • Difficulties of working with these data
  • Understanding linear and nonlinear

modeling

  • Working proposition?

2

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SLIDE 3
  • 1. Advantages of borehole data

Garner Valley - USA (Borehole Obs.)

Wave propagation from bedrock to surface

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PGA distribution (KiK-net)

Field data observation of soil nonlinearity onset? Statistical analysis with respect to magnitude and Vs30

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SLIDE 5

Calibration of soil models

Stress computation from deformation data Waveform modeling

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Revealing nonlinear response

after Bonilla et al. (2011)

  • 2011 Tohoku earthquake data
  • Predominant frequency more affected than fundamental
  • Affected frequency increases as Vs30 increases

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SLIDE 7

Loose sand => liquefaction

  • Lowpass filtering
  • Deamplification

Dense sand => cyclic mobility

  • High frequency peaks
  • Amplification

Port Island, Kobe / Kushiro Port

Velocity model is not always enough!

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SLIDE 8
  • 2. Difficulties of borehole data

Downgoing wavefield Site response (outcrop response) is not the same as borehole response

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Vs30 uncertainty (lack of knowledge of the medium)

  • Variability within each

soil class is important

  • This variability is even

larger at depths greater than 30 m

  • Is Vs30 enough?
  • Not always core

sampling, thus no dynamic soil parameters

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SLIDE 10

Analysis of KiK-net boreholes

After Regnier et al. (2010)

  • Similar Vs30

(between 350 and 450 m/s)

  • Different velocity

distribution at depth

  • Different site

response

  • Is Vs30 enough?

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SLIDE 11

Vs30 = 400 +/- 5 m/s

After Regnier et al. (2010)

No comments! The data speak alone

20 40 60 80 100 120 140 160 500 1000 1500 2000 2500 3000 Depth(m) Vs (m/s)

"+>&'+"(

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  • 3. We need to know well the linear response

(example of the CORSSA array, Greece)

1. H/V spectral ratio (noise data) 2. H/V spectral ratio (earthquake data) 3. Standard spectral ratio (borehole response) 4. Borehole response inversion (velocity, thickness, and Q profiles)

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Inverting for nonlinear soil properties

1832

  • T. Satoh, T. Sate, and H. Kawase

Table 3 Soil Properties Obtained from the Identification Method for S-Wave Velocities and Damping Factors

No. S-Wave Velocity (m/see) Damping-Factor (%) Thickness Kanagawa Kanagawa (m) Mainshock Foreshock Aftershock Earthquake Mainshock Foreshock Aftershock Earthquake

1 7.0 53.8(63.8) 60.7 59.1 64.4 7.0(6.3) 3.4 3.9 5.0 2 5.0 158.8(168.8) 165.7 165.8 169.4 3 16.0 690.0* 4 48.0 340.0

5 6.0 750.0* 2.8 6 12.0 340.0 7 3.6 700.0* 8

  • 800.0*

In the first and second layers, the values in parentheses are identified from the part just after the main parts of the mainshock records, and the values without parentheses are identified from the main parts. Asterisks indicate S-wave velocities based on the logging results, i.e., not identified here.

Identified

~t

Equivalent linear the main part of the foreshock record A the main part of the mainshock record O just after the main part of the mainshock record m

..q

  • <

1.0 0.8 0.6 0.4 0.2 0.0 10-4 1.0 0.8 0,6

I lllllll IIIIIIII IIIlllll IIIitll

IIIIIIll I LtlI_'. -

'--FI-fl-flff- I IIIIIll

10- 3 10- 2 10- 1 (a) First layer

t ll,,Jl,,I ,,,lll,Jt I

041j r

02

I IIIIIJl lJ l-- llrllll I

  • .of-FFIll-Itff-Tlflllltl

I IIIIIIII I IIIIIIII

10

  • 4

10-3 10- 2 10-1 100 SHEAR STRAIN (%) (b) Second layer 20 16 12 8 4 100 0 20 16 12 8 4 ~7 >

'-n >. ,q

  • Figure 15.

Relationships between the effective shear strain and the shear modulus reduction ratio or the damping factor for (a) the first layer and (b) the second layer are estimated by two methods. Solid symbols shows the values based on linear 1D theory with the S-wave velocities and the damping factors estimated by the identification method. Open symbols show the values based on the equivalent linear 1D theory in which the S-wave velocities and the damp- ing factor for the main part of the foreshock are used as initial values for iteration. The shear modulus re- duction ratio for the foreshock are assumed to be unity and the damping factor to be 3.4% at the effective shear strain of 10-4%. Solid and dashed curves rep- resent the shear modulus reduction ratios and the damping factors as a function of the effective shear strain given by JESG (1991) from laboratory tests. in the main part and the part just after the main part of the strong motion, vertically propagating S waves are dominant in the period range from 0.1 to 2.0 sec, while in the later part, horizontally propagating waves are dominant in the pe- riod range longer than 0.7 sec, and vertically propagating S waves are still dominant in the shorter period range. For the weak motion, only the main part can be examined because

  • f the small signal-to-noise ratios in other parts. In the main

part of the weak motion, vertically propagating S waves are also dominant. Based on these results, we decided to analyze these three S-wave dominant time segments, that is, the main part of the strong motion, the part just after the main part of the strong motion, and the main part of the weak motions, based on 1D wave propagation theory for vertically propagating S waves. The observed spectral ratio between KD2 and KS2 for the main part of the strong motion shows a longer peak period with lower amplitude at the peak around 0.5 sec compared to the corresponding peak for the weak motions. The shift

  • f the peak period can be clearly seen in the Fourier spectra
  • f the KS2 records. To quantify this period and amplitude

shift, the S-wave velocities and the damping factors are iden- tified by minimizing the residual between the observed spec- tral ratio and the theoretical amplification factor calculated from the 1D wave propagation theory. The S-wave velocity and the damping factor in the surface alluvial layer identified for the main part of the strong motion are about 10% smaller and 50% greater, respectively, than those identified for the main part of the weak motions. The relationships between the effective shear strain and the shear modulus reduction ratios or damping factors estimated by the identification method agrees with the laboratory test results. We corrob-

  • rate that the main part of the strong motion, whose maxi-

mum acceleration at the surface station KS2 is 220 cm/sec 2 and whose duration is 3 sec, has the potential of making the surface soil nonlinear at an effective shear strain on the order

  • f 0.1%.

The S-wave velocities in the alluvial layers identified from the part just after the main part of the strong motion

0. 2 0. 4 0. 6 0. 8

1

10-6 10-5 10-4 10-3 10-2 10-6 10-5 10-4 10-3 10-2

G/Gmax G/Gmax γ Sand and gravel

1 2 3, 5, 9 7 11 Inversion - sand Inversion - gravel Seed and Idriss (1970b) 0.2 0.4 0.6 0.8

1

γ Clay

PI = 200% PI = 0% 4 6 8 10 Inversion - clay Vucetic and Dorby (1991)

(a) (b)

Surface Layer Intermediate Layer

0.2 0.4 0.6 0.8 1.0 1.2 1.4

40 50 60 70 80 90 100 120 140

0.2 0.4 0.6 0.8 1.0 1.2 1.4

40 50 60 70 80 140

Strain Strain

10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-8 10-7 10-6 10-5 10-4 10-3 10-2 Fujisawa Sand Disturbed Samples Undisturbed Samples Empirical Relationship

: void ratio

Empirical Relationship

(a) (b)

Pioneering work by T. Satoh since the 90’s De Martin et al. (2010) Mogi et al. (2010)

  • Use of vertical arrays
  • Inversion of G/Gmax only

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Inverting for nonlinear soil properties

Assimaki et al. (2010)

Inverting for G/Gmax and damping ratio

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An insight of nonlinear soil response

1 2 3 ff ts sb

  • ut

P o.C P o.B P o.A a Foundation length a/2 a

10m ρ1 = 1930kg/m3 Vs1 = 220m/s 20m ρ2 = 1980kg/m3 Vs2 = 400m/s 20m ρ3 = 2040kg/m3 Vs3 = 550m/s ρ = 2100kg/m3 Vs = 800m/s

(b) Soil profile (#2)

Soil-structure interaction model

Confining pressure dependency

Gandomzadeh (2011)

200 400 600 800 1000 −50 −45 −40 −35 −30 −25 −20 −15 −10 −5

Shear Modulus (MPa) Depth (m)

Soil profile 1 Soil profile 2 Soil profile 3

(a) Low-strain shear moduli of the profiles 15

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An insight of nonlinear soil response

1 2 3 ff ts sb
  • ut
P o.C P o.B P o.A a Foundation length a/2 a

Isoil = 1 Ω

  • Ω
  • t

σ(x, t) : d(x, t)dV

(a) Dissipated energy (b01 and soil profile #2) (b) Dissipated energy (b02 and soil profile #2) (c) Dissipated energy (b03 and soil profile #2)

0. .5 1. 1.5 2. 2.5 2.5 3. 3.5 4. 4.5 5.

(d) Legend: (J/m3)

0.2 0.4 −50 −45 −40 −35 −30 −25 −20 −15 −10 −5

Isoil (J/m3) Depth

free field Po.A Po.B Po.C

(a) Dissipated energy

2 4 6 x 10

−3

−50 −45 −40 −35 −30 −25 −20 −15 −10 −5

Shear strain (%) Depth

free field Po.A Po.B Po.C

(b) Maximum shear strain

50 100 −50 −45 −40 −35 −30 −25 −20 −15 −10 −5

Isoil (J/m3) Depth

free field Po.A Po.B Po.C

(c) Dissipated energy

0.02 0.04 0.06 −50 −45 −40 −35 −30 −25 −20 −15 −10 −5

Shear strain (%) Depth

free field Po.A Po.B Po.C

(d) Maximum shear strain

Dissipated energy is higher at interfaces and close to the free surface

Gandomzadeh (2011)

0.2g 0.7g

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What do we observe?

  • Energy is strongly dissipated at the bottom of each

layer and close to the free surface

  • Since shear strength increases with depth, the

energy is dissipated in the weaker part (transition between layers)

  • Furthermore, the impedance contrast increases at

each layer interface

  • Thus, nonlinear response has a cumulative effect

(number of cycles) and competition between impedance contrast (linear part) and material strength (nonlinear part)

  • It is therefore necessary to instrument not only the

middle of the layers but near their interfaces

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Conclusions

  • Input ground motion (e.g. near- and far-field)
  • Low strain properties (linear site response)
  • Dynamic soil properties (nonlinear site response)
  • Methods of computing site response

Sources of uncertainty (variability) in site response

What do we need?

  • Understanding linear site response
  • Inverting earthquake data to obtain dynamical soil

properties (up to bedrock?)

  • Core sampling and laboratory tests (material

strength, granulometry, pore pressure effects, etc.)

  • Instrumenting middle of layers and near their

interfaces

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