The optimization framework of identification for elastoplasticity
Date Issued
2009
Date
2009
Author(s)
Liu, Li-Wei
Abstract
The identification problem of elastoplastic models are addressed and a unified way to estimate the optimal values of model parameters and initial states is proposed. Special attention is drawn to materials as received and structures as existing for which initial values of internal state variables could no longer be assumed to vanish. A comprehensive model of elastoplasticity is formulated first and then a dynamic optimization framework for the identification problem of the elastoplastic model is established. A correct optimality condition of the dynamic optimization problem subjected to constraints in the forms of equalities, inequalities, and complementarity constraints is obtained. The important feature of our results is that they are convex and symplectic. In view of modern trends of digital data acquisition in experiments,e further consider the discrete-time version in addition to the continuous-time optimization problem, and obtain discrete conditions of solution which are proved to preserve the structure of a symplectic group.he algorithm of finding the optimal values of parameters and initial states is proposed. Experimental data were used to identify them in several testing and real cases.
Subjects
elastoplasticity
identification
parameters and initial states
dynamic optimization
complementarity constraints
convexity
symplecticity
Type
thesis
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