Numerical simulation of forming processes has become an important
means for material selection, tool design, and process
optimization. A critical component of simulation is an accurate
material constitutive model, describing the response of the
material under possible modes of deformation. The accuracy, in
turn, is linked to the tests and techniques applied for the
identification of constitutive models. This book elaborates on the
identification of textile composite models using a new inverse
method by means of a signal-to-noise weighting scheme, and two
constitutive equations based on a phenomenological invariant-based
approach. A full identification of the models for a typical woven
fabric is applied using sets of data from standard testing methods,
including a modified picture frame test. The identification
framework makes it possible to include all sets of data from
several deformation modes, along with their given test
non-repeatabilities. The method has been presented in a general
manner and it can be applied in other applications, where
non-repeatability of measurements and the lack of agreement between
identification parameters in different modes are practical
problems.
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