Evaluation and Implementation of Model Uncertainties
in Geotechnical Design
Presenter: Prof. Dr.-Ing. Kerstin Lesny
HafenCity University  Hamburg  Germany
Geo-Risk 2017, Denver
C20a/ Reliability- and Risk-Based Code Developments, Part I
Members of the TC205/TC304 discussion group
Sami Oguzhan Akbas
Witold Bogusz
Sébastien Burlon
Kerstin Lesny (discussion leader)
Giovanna Vessia
Kok Kwang Phoon
Chong Tang
Limin Zhang
Discussion report available on the ISSMGE website:
http://140.112.12.21/issmge/TC205_304_reports/
Comments are welcome!
(Quelle: www.kunterbuntich.de)
Geo-Risk 2017  Denver/Colorado
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Definition of Model Uncertainty
 Model:
calculation model, not the whole geotechnical model
including e.g. the ground model
 Deviation of:
real behavior
calculated behavior
 Type of model: analytical, empirical, semi-empirical closed-form solutions
numerical (e.g. FE) model
ideal situation
calculated behavior
real behavior
Geo-Risk 2017  Denver/Colorado
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Model Uncertainty Assessment
Model factor approach:
MF = Xmeas/Xcal
or
1/MF = Xcal/Xmeas
with: MF = model factor or bias
X = load, a resistance, a displacement, etc.
 applicable only where a unique design quantity X exists
 Xmeas to be collected from a load test database which needs to cover the whole
range of possible design situations and shall fulfill specific requirements to
provide sufficient information.
 Appropriate methods for interpretation of load-displacement curves for ULS
and SLS problems!
Geo-Risk 2017  Denver/Colorado
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Model Uncertainty Assessment
Representative quantity approach:
MF = Xmeas/Xcal
or
1/MF = Xcal/Xmeas
same as before, but: X = representative quantity characterizing the behavior of
the structure
 Examples: head displacements of a laterally loaded flexible pile, top displacements of retaining walls, lateral strain in neighboring buildings due to excavation
 reduction of model uncertainty to a single quantity questionable in case of
complex structures, e.g. retaining walls
Two-step approach:
 Combination of numerical analyses and load test results to establish a
generalized model factor for specific design model.
Geo-Risk 2017  Denver/Colorado
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Model Uncertainty Assessment
Intrinsic uncertainties:
 ground conditions: spatial variabilty
consideration of subsoil characteristics within design method
(degree of simplification)
determination of soil parameters (correlations to field tests or lab
tests)
 load test execution: measurement errors, interpretation and evaluation of load test
results, selection of load tests for database, lack of information,
personal experience
Cannot be eliminated!
Implementation in design possible:
 as a random model factor in RBD
 as a deterministic model factor in LRFD
(but not necessarily a constant value!)
Geo-Risk 2017  Denver/Colorado
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Our Wish List on the Path to an Ideal Code
 to further close the gap between theoretically based, complex approaches and
the daily design practice of 'normal' geotechnical engineers, i.e. to provide a
bridge between different 'languages speaking' or different 'ways of thinking’
 to promote “ease of use”
 to promote gathering and to provide later access to data of successes and
failures of geotechnical structures to learn and to verify our design models
Geo-Risk 2017  Denver/Colorado
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Conclusions
 model uncertainties to be evaluated using extensive databases covering all
possible design situations under natural, but also under laboratory conditions
 intrinsic uncertainties (e.g. soil variability, measurement errors etc. ) can hardly
be seperated
 use of deterministic (not constant) model factors in LRFD formats is possible, at
least for standard design situations
Proper transformation and acceptance in the engineering practice
important!
Geo-Risk 2017  Denver/Colorado
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