Short Introduction of a New Generalized Damage Model

In LS-DYNA, several constitutive models exhibit properties that are based on Continuum Damage Mechanics (CDM) [1]. Associated isotropic or anisotropic stress degradation represents softening and failure behavior of metals (e.g. *MAT_104), composites (e.g. *MAT_221), polymers (e.g. *MAT_187), and other material types. As an alternative, sophisticated (e.g. stress state dependent) damage models such as GISSMO [2, 3] or DIEM [4] can be used as add-ons to a wide range of standard material models via *MAT_ADD_EROSION. With the release of LS-DYNA version R9, a new keyword *MAT_ADD_GENERALIZED_DAMAGE (MAGD) was added as a further step towards an even more versatile tool in this area. The primary idea was to provide non-isotropic (tensor type) damage with multiple independent damage variables. Users can define the entries of the damage tensor by functional input (*DEFINE_FUNCTION) to achieve maximum flexibility. The evolution of damage variables is driven by strain based values that can be determined in a number of ways. They can either be arbitrary history variables of the accompanying material model, or quantities derived from the plastic strain tensor. Therefore transformations of that tensor to the principal strain system or to the local system of material directions can be selected. Besides the possibility of using individual plastic strain tensor components as damage driving quantities, functional combinations of them are also allowed through the keyword *DEFINE_FUNCTION. For the damage evolution laws itself, the GISSMO approach can be used where corresponding input variables (such as stress state dependent failure strain, regularization, etc.) can be defined separately for each damage parameter. As a matter of fact, MAGD is a very flexible tool to incorporate non-isotropic damage into existing material models. The first successful application was done for aluminum extrusions, which show marked directional dependencies of failure strain [5]. This presentation will describe the underlying theory of MAGD, explain the various input options, and demonstrate its main functionalities using simple numerical examples.