Analysis of borehole data
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1 Analysis of borehole data Luis Fabian Bonilla Universite Paris-Est, IFSTTAR, France
2 Outline Advantages of borehole data Difficulties of working with se data Understanding linear and nonlinear modeling Working proposition?
3 1. Advantages of borehole data Garner Valley - USA (Borehole Obs.) Wave propagation from bedrock to surface
4 PGA distribution (KiK-net) Field data observation of soil nonlinearity onset? Statistical analysis with respect to magnitude and Vs3
5 Calibration of soil models Stress computation from deformation data Waveform modeling
6 Revealing nonlinear response after Bonilla et al. (211) 211 Tohoku earthquake data Predominant frequency more affected than fundamental Affected frequency increases as Vs3 increases
7 Port Island, Kobe / Kushiro Port Loose sand => liquefaction -Lowpass filtering -Deamplification Dense sand => cyclic mobility - High frequency peaks - Amplification Velocity model is not always enough!
8 2. Difficulties of borehole data Downgoing wavefield Site response (outcrop response) is not same as borehole response
9 Vs3 uncertainty (lack of knowledge of medium) Variability within each soil class is important This variability is even larger at depths greater than 3 m Is Vs3 enough? Not always core sampling, thus no dynamic soil parameters
10 Analysis of KiK-net boreholes Similar Vs3 (between 35 and 45 m/s) Different velocity distribution at depth Different site response Is Vs3 enough? After Regnier et al. (21)
11 Vs3 = 4 +/- 5 m/s Vs (m/s) After Regnier et al. (21) Depth(m) No comments! The data speak alone
12 3. We need to know well linear response (example of 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)
13 Identified..q o < ~t Inverting for nonlinear soil properties Equivalent linear main part of foreshock record A main part of mainshock record O just after main part of mainshock record m I lllllll IIIIIIII IIIlllll IIIitll IIIIIIll LtlI_'. - '--FI-fl-flff- I IIIIIll (a) First layer t ll,,jl,,i,,,lll,jt,6 41j r 2 I IIIIIJl lj l-- llrllll I o.of-ffill-itff-tlflllltl I IIIIIIII I IIIIIIII SHEAR STRAIN (%) (b) Second layer Pioneering work by T. Satoh since 9 s I ~7 > '-n >.,q o (a) Use of vertical arrays Inversion of G/Gmax only (a) G/G max Sand and gravel 11 3, 5, (b) G/G max 6.2 Inversion - sand Inversion - gravel.2 Inversion - clay Vucetic and Seed and Idriss (197b) Dorby (1991) γ γ Surface Layer Clay PI = % Intermediate Layer PI = 2%.4.4 Fujisawa Sand Disturbed Samples 4.2 Undisturbed Samples.2 : void ratio Strain De Martin et al. (21) Empirical Relationship (b) Mogi et al. (21) Strain 14 Empirical Relationship
14 Inverting for nonlinear soil properties Assimaki et al. (21) Inverting for G/Gmax and damping ratio
15 An insight of nonlinear soil response ts out ff P o.a a a/2 P o.b P o.c 1 Gandomzadeh (211) a Foundation length 2 sb 3 1m Soil-structure interaction model ρ 1 = 193kg/m 3!5 V s1 = 22m/s!1 Soil profile 1 Soil profile 2 Soil profile 3 2m 2m ρ 2 = 198kg/m 3 V s2 = 4m/s ρ 3 = 24kg/m 3 V s3 = 55m/s Depth (m)!15!2!25!3!35!4!45 ρ = 21kg/m 3 V s = 8m/s (b) Soil profile (#2)! Shear Modulus (MPa) (a) Low-strain shear moduli of profiles (b) Confining pressure dependency Figure 5.3: Low-strain shear moduli and elastic shear
16 e shift of fundamental frequency of soil-structure shear system when soil For example, Figure 5.32 displays iso-values of cumulative dissipated components. Case studies r is acting is quite low. Numerical simulations show this is not a good index energy in soil,tofor three soil-structure systems (Case studies 2, 5 and 8) at end of Three different structures and three different soil profiles are considered. Consequently, we have r9 different from nonlinear behavior. However, amplitude may be more discriminant. case studies. For each case, one linear and four nonlinear analyses (with input computation. The dissipated energy presented here is only due to shear terms. These motions presented in 5.2.3) are performed.linear, Therefore, our parametric study of 45 aterial behavior is assumed consequently, consists aforementioned remark structures are based on second soil profile, and input motion of.25g outcropping PGA different analyses. Table 5.5 displays properties of each case study. dering a nonlinear structure. For each case study, soil response and soil-structure interaction are studied. The is soilapplied at base of model after its division by two An insight of nonlinear soil response response of three different soil profiles are presented in 5.3. The soil-structure interaction is studied in 5.4. Different indexes and control points are defined to simplify way results are displayed. Figure 5.8 shows se indexes and control points in model. y dissipation in soil and maximum strain during opagation out ts a dissipation ff P o.a a/2 P o.b P o.c 1 fy role of different energy dissipation mechanisms in problem and (a) Dissipated energy (b1 and soil profile #2) (b) Dissipated energy (b2 and soil profile #2) of soil nonlinearity on SSI, dissipated energy due to hysteresis behavior computed during wave propagation. For soil, an energy dissipation puted by 136 Chapter 5. Effect of soil nonlinearity on dynamic study 1. SSI : Parametric 3.5!!control points of soil-structure models Figure 5.8: Definition of t) : d"(x, t)dv (5.3) Isoilfield, = ts top ofσ(x, f f represents free Ω Ω t structure, out outcropping and sb base a Foundation length 2 3 sb of soil profile. The control points P o.a, P o.b and P o.c represents points where we bottom boundary of soil layers and also close will study soil and structure responses. The parameter a is length of foundation. (c) Dissipated energy (b3 and soil profile #2) to surface was described before in (d) Legend: (J/m3 ) We observe that at se areas maximum shear strain is in accordance with dissipated energy is larger than or parts. energy at end of wave propagation due to shear Figureand 5.32: Cumulative dissipated.2g.7g components of stress and strains for case studies 2, 5 and 8 obtained for.25g outcropping PGA!5!5 free field Po.A Po.B Po.C!5 Depth Depth Depth These graphs help us to find parts of soil medium that dissipate more energy during!1!1!1!1 wave propagation. The parts that are white in this figure dissipate more than 5J/m3 energy. We observe that!15 soil energy is strongly dissipated at bottom boundary of each!15!15!15 layer and also close to surface where up and downgoing waves are combined. Firstly,!2!2!2!2shear modulus reduction curve is related to confinement stress (equation 5.1), refore!25soil becomes softer by!25getting closer to surface. Secondly, properties of each layer is!25!25 weaker than one below it. Consequently, more energy dissipation is observed at bottom!3!3!3!3 boundary of each soil layer. Thirdly, impedance contrast is higher at boundary between!35!35 layers, thus amplification!35 is also produced, which!35competes with nonlinear effects. The effect of structure weight on low-strain shear modulus is taken into account (see!4!4!4! ). This may change nonlinear behavior of soil particularly around freefoundation. free field free field field!45!45!45 Po.A Po.A Po.A In!45 this work, we neglected effect of initial static condition. This effect changes behavior Po.B Po.B Po.B Po.C Po.C Po.C of!5 soil before applying dynamic loading. In addition, weight of structure and soil!5!5! Isoil (J/m ) Isoil (J/m ) Shear strain (%) Shear strain (%) produces settlement in media that we did not study in our work. Therefore, effect x 1 Depth Dissipated energy is higher at interfaces and close to free surface!5!3 Gandomzadeh (211) (a) Dissipated energy (b) Maximum shear strain (c) Dissipated energy (d) Maximum shear strain Figure 5.36: Maximum shear strain reached during calculation and dissipated energy due to stress and strain shear components for case study 2 with two.1g (two left figures
17 What do we observe? Energy is strongly dissipated at bottom of each layer and close to free surface Since shear strength increases with depth, energy is dissipated in weaker part (transition between layers) Furrmore, 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 refore necessary to instrument not only middle of layers but near ir interfaces
18 Conclusions Sources of uncertainty (variability) in site response 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 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 ir interfaces
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