Process driven Material Parameter Identification and Data Management
N. Bessert (Altair Engineering) A huge amount of effort is spent to develop new materials. To participate the innovation potential of new material property you need to feed you simulations with the appropriate material parameters. Therefore the identification of the material parameters is a key point. As soon as material state becomes inhomogeneous in the experiment a FEM model is needed to take the inhomogeneous state into account. In addition to this, numerical methods are needed to identify the unknown material parameters. On the other hand, it is important to know about the correlation between material parameters of the same material but of different charges. Therefore, the existing parameters need to be accessible for such kinds of investigations. Identifying material parameters by hand and leaving the data on the disk will not lead to a satisfying understanding of the material. The innovative potential may be wasted. The following presentation shows a concept of process driven material parameter identification for LSDYNA with an integrated data management system. In this way the material parameters are identified in a reproducible manner and the data is accessible for all kind of future evaluation. So this directly confirms to the Six Sigma rules for the repeatability of processes.
https://www.dynamore.de/en/downloads/papers/06-forum/papers/material-validation/process-driven-material-parameter-identification/view
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Process driven Material Parameter Identification and Data Management
N. Bessert (Altair Engineering) A huge amount of effort is spent to develop new materials. To participate the innovation potential of new material property you need to feed you simulations with the appropriate material parameters. Therefore the identification of the material parameters is a key point. As soon as material state becomes inhomogeneous in the experiment a FEM model is needed to take the inhomogeneous state into account. In addition to this, numerical methods are needed to identify the unknown material parameters. On the other hand, it is important to know about the correlation between material parameters of the same material but of different charges. Therefore, the existing parameters need to be accessible for such kinds of investigations. Identifying material parameters by hand and leaving the data on the disk will not lead to a satisfying understanding of the material. The innovative potential may be wasted. The following presentation shows a concept of process driven material parameter identification for LSDYNA with an integrated data management system. In this way the material parameters are identified in a reproducible manner and the data is accessible for all kind of future evaluation. So this directly confirms to the Six Sigma rules for the repeatability of processes.
D-I-4.pdf
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