Geotechnical Characterisation for FEA...14 The Stress-Strain Curve The stress-strain response of...

Geotechnical Characterisation for FEAand its importance for ever larger offshore wind turbines

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Benefits of FEA based design are well understood

But is our approach to geotechnical characterisation efficiently addressing the requirements of FEA?

FEA Based Design

The importance of geotechnical characterisation for FEA for ever larger offshore wind turbines

Monopiles Suction Buckets Gravity Base

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Characterisation Requirements – API/ISO (Clay)


IN SITU LABORATORY PARAMETERS

Cone Penetration Test Density Determination Unit Weight

Triaxial Test (UU) Undrained Shear Strength

Strain Parameter 50

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Characterisation Approach – API/ISO


1. Measure stress-strain response 5. Generate empirical curves

6. Question the representation of this?!

(2. and a strain parameter)

(3. forget about this!)

3. Plot su vs. depth

4. Infer a design profile

2. Define the peak strength

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The FEA Design Approach

Finite element analysis design approach can lead to optimisation of monopile geometry


PISA Clay Site (Byrne et al., 2017) PISA Sand Site (Burd et al., 2017)

But…

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Characterisation Requirements – FEA (Clay)


IN SITU LABORATORY MODELS (No. PARAMS)

CPT Classification

HV-MCC (15)

SANICLAY-B (11)

NGI-ADP (11)

B-SCLAY1S (11)

FUGRO-PIMS (5)

Seismic CPT Triaxial undrained compression

Pressuremeter Triaxial undrained extension

Triaxial drained compression

Triaxial drained extension

Local strain

Oedometer

Direct simple shear

Resonant column

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Because of this...

The FEA model is what allows us to expand the foundation design space beyond the empirically derived

But be careful…

The Power of the Constitutive Model


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Unnecessary Correlation?

Because without the right dataset

The empiricism starts creeping back in.


? !

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Staying Ahead of the Game

So, before investigating our soil we need to consider how best to model it


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The Existing Approach

We’re used to doing this:


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The Stress-Strain Curve

A representative stress-strain curve is the objective of the constitutive model selection

But review and definition is too often left to the design stage?

At the design stage it could be too late to expand or refine the dataset


or

G/G

max

or E

/Em

ax

a or

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The stress-strain response of soil can be highly complex:


Effect of drainage condition

Sand

So, for sands we need to consider:

o Both drained AND undrained testing

o Permeability tests (and method)

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Effect of soil state

Sand Clay

So, we need to consider:

o Soil and stress states

beyond in situ

o Site-wide soil unit

elevations

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Stress path dependency (Whyte et al., 2019) Stress path dependency (Ladd & DeGroot, 2003))

SandClay

Triaxial compression

Triaxial extension

So we need to consider:

o Different modes of shearing:

compression, extension, DSS

o Triaxial stress path variations

Sturm (2017)

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On top of everything else…


Sample disturbance effects (Mayne et al. 2009)

Clay Sand

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Laboratory Test Scheduling

Despite numerous limitations, laboratory testing currently offers the best dataset for constitutive model

calibration outside of the in situ state

Testing should be scheduled with a model(s) in mind


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G/G

max

or E

/Em

ax

a or

CAU data

LS data

RC data used to define stiffness to ~0.01%-0.05% (depending on soil)

Available local strain data were used to derive trend for 0.01% > strain < 0.5%

Triaxial or DSS data typically only used at strain > 0.2% - 0.5%

Small Strain Interpretation


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At strains > ~0.2%, stress mobilisation can be derived based on monotonic DSS or triaxial data;

Transition between datasets needs to be considered for calibration curves, if spliced

Larger Strain Interpretation


Transition point of small-strain and large strain curves

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Note on Empirical Curves

Empirical modulus reduction curves are very useful

However, they are typically based on laboratory only datasets

This means that the range of rigidity index (Gmax/su) of the curves is limited to typical values derived in the lab


Clay Curves (Vardanega & Bolton, 2013; Vucetic & Dobry, 1991) Sand Curves (Oztoprak & Bolton, 2013)

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New Insights from In Situ Stiffness?

Laboratory Gmax/su values may be far lower than those derived based on high quality in situ Gmax data

Impact could be significant for fatigue and serviceability analysis of foundations


0

10

20

30

40

50

60

0 1000 2000 3000 4000

Dep

th B

SF [m

]

Gmax/su [-]

RC and BE Data

Seismic Data

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0001 0.001 0.01 0.1 1 10 100

G/G

max

[-]

[%]

G/Gmax Calibrated

PI=15%

PI=50%

PI=200%

Steeper curve = larger reduction in stiffness at low strain required to maintain same su

su from high quality sample data

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Site-Wide Design


Calibrated model response Recalibrate?

(position specific)

Or normalise?

(site-wide)

Soil Units

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Model Calibration


Model parameters correlated to a normalised

unit measure (e.g. soil state)

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Model Parameterisation


Su [kPa]

Profiling performed for unit measure and

model parameters derived accordingly

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Normalised Parameterisation Clay

Collection of triaxial compression data from same OC clay unit at several North Sea sites


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Normalisation for strength mobilisation


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Normalisation for strain mobilisation


Stress-strain response can then be derived for

any interval where G0 and su are profiled (i.e.

using CPT)

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Model was implemented within Fugro-PIMS model and calibrated against PISA clay site:


Whyte et al. (2019) - Formulation and implementation of a practical multi-surface soil plasticity model (Computers & Geotechnics – under review)

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Normalised Parameterisation Sand

Example dataset for response of North Sea sand with variable fines content


-6

-4

-2

0

2

4

6

8

10

30 40 50 60 70 80 90 100 110

vol

,fina

l[%

]

Dr [-]

CIDc <10% fines

CIDc >10% fines

-6

-4

-2

0

2

4

6

8

10

0 50 100 150 200 250 300 350 400

vol

,fina

l[%

]

qc/'v0

CIDc <10% fines

CIDc >10% fines

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Calibration (drained response) curves were generated based on volumetric response indicators


0

200

400

600

800

0 5 10 15 20

q [k

Pa]

[%]

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Indicator points were correlated to normalised CPT qc as in indicator of in situ state


0.01

0.1

1

10

0 200 400

vol

@di

latio

n[%

]

qc/'v0

CIDc data

Calibration line

0.01

0.1

1

10

100

0 200 400

@di

latio

n[%

]

qc/'v0

CIDc data

CIUc data

Calibration line

-6

-4

-2

0

2

4

6

8

10

0 100 200 300 400 500

vol

,fina

l[%

]

qc/'v0

CIDc <10% fines

CIDc >10% fines

Calibration line(s)

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Conclusions

FEA can provide design optimisation and minimise design risk but only where supported by robust geotechnical characterisation

The earlier in the project stage the FEA model requirements are considered the more efficient the design process will become

Requirements for supplementary investigation (driven by design) can be minimised or avoided

Key influencing factors on stress-strain response must be considered ahead of specifying laboratory testing

Normalisation of the stress-strain response and correlation of model parameters to CPT state parameters can provide a useful basis for site-wide parameterisation


Thank You

Geotechnical Characterisation for FEA...14 The Stress-Strain Curve The stress-strain response of...

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