2012
DOI: 10.1016/j.compgeo.2012.02.001
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Application of a Hill-Climbing technique to the formulation of a new cyclic nonlinear elastic constitutive model

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Cited by 40 publications
(18 citation statements)
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“…>10 -1 %) and in the very small strain range (<10 -3 %) respectively as defined by Vucetic (1994) [37]. This highlighted the importance 34 of independent optimum calibration for the material damping related to the shear and compressional response at the respective relevant strain levels.…”
mentioning
confidence: 95%
“…>10 -1 %) and in the very small strain range (<10 -3 %) respectively as defined by Vucetic (1994) [37]. This highlighted the importance 34 of independent optimum calibration for the material damping related to the shear and compressional response at the respective relevant strain levels.…”
mentioning
confidence: 95%
“…This may be partially mitigated by increasing either the nonlinearity of the backbone curve (e.g. [12,13]) or by adopting a variable scaling factor, as demonstrated in Taborda and Zdravkovic [9].…”
Section: Constitutive Modelmentioning
confidence: 99%
“…This model is formulated in threedimensional stress-strain space and incorporates a wide range of features designed to allow both the accurate simulation of cyclic soil behaviour [9] and the analysis of static problems, often in conjunction with a plastic model [10,11]. According to the cyclic nonlinear elasticity framework, the soil response is defined by two components: a base stress-strain relationship (also called "backbone curve") and a set of rules establishing the unloading/reloading behaviour.…”
Section: Constitutive Modelmentioning
confidence: 99%
“…which are used depending on the type of application. Although Hill Climbing suffers from a drawback of getting stuck at the local maxima/minima, it is used in applications such as wind power system [1], evacuation route planning [2], modelling of soil behavior [3], forward planning [4] and many other applications because it is simple and easy to implement. There are different variants of Hill Climbing algorithm and these variants have evolved based on the need to make the search effective in addressing a particular problem.…”
Section: Introductionmentioning
confidence: 99%
“…As already mentioned in [3], there are a few instances where the exact values of model parameters are not derived, instead they are found in the heuristically defined search space. By this method, the model is fine-tuned to simulate accurate behavior of the system.…”
mentioning
confidence: 99%