| dc.description.abstract | Large deformation analysis has become recently centre of attraction in
geotechnical design. It is used to predict geotechnical boundary value
problems such as, excessive movement of soil masses like landslides or
soil-structure interaction like pile installations. Wrong understanding and
simulation of each mentioned problem could lead to significant costs
and damages, therefore, robust approaches of modelling are needed.
Throughout the past decades many numerical methods aiming to
simulate large deformations have been introduced as for example,
Discrete Element Method (DEM), Smooth Particle Hydrodynamics
(SPH), Updated Lagrangian Finite Element Method (UL-FEM) and
Material Point Method (MPM). They are varying in basic theories,
capabilities and accuracy. But, the complexity is the feature which is quite
common in all them and it is attributed to the unclear response of soil
body under excessive deformations. As a result these methods are
involving many uncertainties in input parameters. Determination of
these parameters is always difficult, because reproducing larg
deformations in the laboratory is difficult and needs advanced and
expensive facilities. As a result the introduction of a methodology for
estimation of the model parameters adopted for large deformation
analysis is extremely needed.
Inverse analysis approaches have proved to be able to overcome
complex engineering problem in different fields. In geotechnical
engineering, inverse analysis is typically employed to back-calculate the
input parameter set of a model to best reproduce monitored
observations. Accordingly, its application attempts to clarify the effective
soil conditions and allows for an update of the design based on the insitu
measurements. Numerous researches have been fulfilled to evaluate
the performance of this approach in geotechnical problem, however,
rarely the application of this methodology to the problems involving
large deformations have been addressed.
This thesis is addressing these issues by combining inverse analysis
methods with advanced numerical methods and soil constitutive models.
The proposed methodology is applied to two popular large deformation
engineering problem i.e. landslides and soil-structure interaction,
particularly cone penetration tests modelling. Different case studies are
addressed; two methods of Smoothed Particle Hydrodynamic and
Material Point Method are adopted as numerical models, depending on
the case study. Similarly, various constitutive models ranging from the
simple Mohr-Coulomb to the advanced ones such as Hardening soil and
Hypoplastic model are employed. The employed inverse analysis
algorithm also varies by the type of the numerical models and required
computation time of the forward model. Particularly, two algorithm are
selected, a gradient-based method (modified Gauss-Newton method)
and an evaluation based one (Species- based Quantum Particle Swarm
Optimization).
In each case the strength and shortcoming of the adopted methods as
well as the role played by the adopted benchmarks and the type of
observation in model calibration is assessed. A concept of in-situ
recalibration of the model is defined and its importance is highlighted.
This method is used to determine advanced constitutive model
parameters using in-situ tests and geometrical observations.
As a conclusion, the research shows how using an inverse analysis
algorithm may improve the modelling of geotechnical problems
involving large deformations and, particularly, facilitate model calibration
and discovering the shortcoming and strength of the numerical models. [edited by Author] | it_IT |
