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TESTING 1-2-3


Revealing Local Mechanical Properties in CGI


Fine-tuning prediction models to account for variations in microstructure could help unlock the full potential of cast materials. A MODERN CASTING STAFF REPORT


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omputer aided lifetime prediction of parts assumes homogenous material behavior. Pro- duction related varia- tions in the microstruc-


ture are not considered, so designers tend to lay out the components conservatively to compensate for these uncertainties. A team of researchers from Magma Foundry Technologies, Schaumburg, Ill.; Audi AG, Ingol- stadt, Germany; and Eisenwerk Bruehl GmbH, Bruehl, Germany, set out to integrate process simulation into computer aided lifetime prediction to achieve more accurate part layouts. Non-uniform cooling conditions


within a casting lead to locally differ- ent microstructures, which result in locally differing mechanical proper- ties. Tese have a significant impact on the behavior of the parts under their application load conditions and their lifetime. Compacted graphite iron (CGI) has two strength-relevant microstructure variables: the shape and size of the graphite particles and the ferrite/pearlite ratio and distribu- tion in the matrix. Te research team felt it necessary to understand and mathematically describe the metal- lurgical process during the solidifica- tion and eutectoid transformation to simulate the development of the microstructure. Te available simula- tion models describing the solidifica- tion were expanded and a new model for the ferrite/pearlite distribution was developed. Te models were validated on test castings and the Audi 3.01 V6 CGI crankcases. Te paper, “Prediction of Microstructure and Local Mechani-


36 | MODERN CASTING July 2013


cal Properties for a CGI crankcase,” by Christof Heisser and J.C. Sturm, Magma; N. Zenker, Audi; and E. Fritsche, Eisenwerke Bruehl, compares and discusses the measured and calcu- lated microstructure distribution and its impact on durability of the castings.


Question Can casting process simulation be


used to predict local casting micro- structure?


1


1 2 3


Background


Te current technological method to design crankcases is to use computer-aided engineering methods, which


assume homogenous behavior. To integrate process simulation into computer-aided lifetime prediction, a


ADDING IT ALL UP Breaking down the latest research is as easy as 1-2-3.


“Prediction of Microstructure and Local Mechanical Properties for a CGI Crankcase”Christof Heisser, Magma Foundry Technologies, Schaumburg, Ill.; N. Zenker, Audi AG, Ingolstadt, Germany; E. Fritsche, Eisenwerke Bruehl GmbH, Bruehl, Germany; and J.C. Sturm, Magma Giessereitechnologie GmbH, Aachen, Germany


Background—Computer-aided lifetime prediction assumes homogenous material behavior. Production related variations in the microstructure are not considered. The research team set out to integrate process simulation into computer aided lifetime prediction to achieve more accurate part layouts. Procedure—Step casting and crankcase samples were used in numerous fatigue test runs. Using the mathematical methods of variance and regression analysis, the researchers developed a correlation between local microstruc- ture and durability using the experimental data. Results and Conclusions—A variance and regression analysis under consid- eration of local graphite morphology and ferrite/pearlite ratio shows good cor- relation between measured and predicted durability values. A model predicting the ferrite/pearlite ratio was developed and validated.


quantitative correlation between the process dependent microstructures and the local durability must be determined and included in the process simulation tool. At the same time, lifetime predic- tion programs need to be enabled to consider local durability values. Te researchers’ first approach was based on durability-relevant microstructure parameters for CGI, such as graphite shape, size and pearlite/ferrite ratio, for the Audi 3.01 V56 crankcase. Te mechanical properties and


microstructures of cast iron are, to a high degree, driven by the metallurgy. To predict the microstructure, the fol- lowing physical and chemical param- eters needed to be considered: • Inoculation of the graphite under consideration of the potency of the inoculants and the phase equilibrium


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