Eeffect of Boron addition on the microstructure and mechanical properties of ductile iron, GJS-500-7 grade was studied. Three cast batches with the Boron content of 10, 49 and 131ppm were cast in a casting geometry containing plates with thicknesses of 7, 15, 30, 50 and 75mm. Microstructure analysis, tensile test, and hardness test were performed on the samples which were machined from the casting plates. Addition of 49 ppm Boron decreased pearlite fraction by an average of 34±6% in all the cast plates. However, minor changes were observed in the pearlite fraction by increasing Boron from 49 to 131 ppm. Variation in the plate thickness did not affect the pearlite fraction. The 0.2% offset yield and ultimate tensile strength was decreased by an average of 11±1% and 18±2%, respectively. Addition of 49 ppm Boron decreased Brinell hardness by 16±1%, while 11±2% reduction was obtained by addition of 131ppm Boron.

The manufacturing process gives cast iron castings properties which are dependent on component design, metallurgy and casting method. Factors such as local wall thickness influences the coarseness and type of microstructure and the castings will have local properties depending on the local metallurgical and thermal history. The stress/strain behaviour of cast materials is typically determined by performing a tensile test in a tensile test machine. The deformation behaviour will normally be determined by two mechanisms, namely, elastic and plastic phenomena. The plastic behaviour is based on dislocation movements in the lattice. Commonly, the deformation history of cast iron involves elastic, plastic and crack phases. The cast iron material has a complex microstructure and first order equations cannot be used to predict the deformation during loading. Until methods have been developed, the characterization of complex microstructure materials such as cast iron has to be determined by use of empirical methods. The empirical methods have to couple the internal microstructure and composition of the material with deformation phenomena during loading. The paper will show a method to characterize tensile test curves of cast iron materials which can be used to couple deformation phenomena with for example microstructure. The equations are aimed to make the tensile test curve ready for curve fitting and optimization in two steps. Each stress/strain curve is like a finger print of the material and requires well performed tests and some advices are given. The paper also wants to encourage researchers and people working with tensile testing to get out more of their effort to measure strength of cast iron materials and connect the result to the microstructure of the specimens. 

This paper investigates the effect of the solidification conditions and silicon content on the mechanical properties of ductile iron and presents empirical models for predicting the tensile behavior based on the microstructural characterizations. Two ductile iron grades of GJS-500-7 and GJS-500-14 were cast with silicon content of 2.36% and 3.71%, respectively. The cast geometry consisted of six plates with different thicknesses that provided different cooling rates during the solidification. Microstructure analysis, tensile and hardness tests were performed on the as-cast material. Tensile behavior was characterized by the Ludwigson equation. The tensile fracture surfaces were analyzed to quantify the fraction of porosity. The results showed that graphite content, graphite nodule count, ferrite fraction and yield strength were increased by increasing the silicon content. A higher silicon content resulted in lower work hardening exponent and strength coefficient on the Ludwigson equation. The results for 0.2% offset yield and the Ludwigson equation parameters were modeled based on microstructural characteristics, with influence of silicon content as the main contributing factor. The models were implemented into a casting process simulation to enable prediction of microstructure-based tensile behavior. A good agreement was obtained between measured and simulated tensile behavior, validating the predictions of simulation in cast components with similar microstructural characteristics.

This article describes a method to predict mechanical properties of cast iron materials and illustrates how to use the predictions in computer-aided tools for the analysis of castings subjected to load. It outlines some ways to predict the hardness and elastic modulus of cast iron without going into dislocation theory. The article discusses modeling of hardness in cast iron based on a regular solution equation in which the properties of each phase depend on chemical composition and coarseness. It describes the evaluation of material parameters from the tensile stress-strain curve. The article concludes with an illustration of a finite-element method (FEM) model containing heterogeneous mechanical properties using local material definitions.

This study focuses on the modelling and simulation of local mechanical properties of compacted graphite iron cast at different section thicknesses and three different levels of silicon, ranging from about 3.6% up to 4.6%. The relationship between tensile properties and microstructure is investigated using microstructural analysis and statistical evaluation. Models are generated using response surface methodology, which reveal that silicon level and nodularity mainly affect tensile strength and 0.2% offset yield strength, while Young′s modulus is primarily affected by nodularity. Increase in Si content improves both the yield and tensile strength, while reduces elongation to failure. Furthermore, mechanical properties enhance substantially in thinner section due to the high nodularity. The obtained models have been implemented into a casting process simulation, which enables prediction of local mechanical properties of castings with complex geometries. Very good agreement is observed between the measured and predicted microstructures and mechanical properties, particularly for thinner sections.

The influence of a chill on the mechanical properties and microstructural features in grey cast iron has been studied. Some of the main findings were that the chill refined the microstructure and modified the graphite distribution from A to D/E. Eutectic cell size was reduced by 60–70%. The Brinell hardness increased while the Vickers hardness, measured in dendrite arms, was unaffected. Fatigue testing in four point bending showed that the fatigue limit was increased by 20–30% in the chilled samples. An increase in tensile strength, proof strength and Young’s modulus was also observed in the chilled samples. The increase in fatigue limit was approximately twice as high as the increase in tensile strength. A possible explanation could be that the eutectic cell size had a more pronounced effect on the fatigue limit than on the tensile strength.

The mechanical behaviour and performance of a ductile iron component is highly dependent on the local variations in solidification conditions during the casting process. Here we show a framework which combine a previously developed closed chain of simulations for cast components with a micro-scale Finite Element Method (FEM) simulation of the behaviour and performance of the microstructure. A casting process simulation, including modelling of solidification and mechanical material characterization, provides the basis for a macro-scale FEM analysis of the component. A critical region is identified to which the micro-scale FEM simulation of a representative microstructure, generated using X-ray tomography, is applied. The mechanical behaviour of the different microstructural phases are determined using a surrogate model based optimisation routine and experimental data. It is discussed that the approach enables a link between solidification- and microstructure-models and simulations of as well component as microstructural behaviour, and can contribute with new understanding regarding the behaviour and performance of different microstructural phases and morphologies in industrial ductile iron components in service.

Numerical simulations of component behavior and performance is critical to develop optimized and robust load-bearing components. The reliability of these simulations depend on the description of the components material behavior, which for e.g. cast and polymeric materials exhibit component specific local variations depending on geometry and manufacturing parameters. Here an extension of a previously presented strategy, the closed chain of simulations for cast components, to predict and incorporate local material data into Finite Element Method (FEM) simulations on multiple scales is shown. Manufacturing process simulation, solidification modelling, material characterization and representative volume elements (RVE) provides the basis for a microstructure-based FEM analysis of component behavior and a simulation of the mechanical behavior of the local microstructure in a critical region. It is discussed that the strategy is applicable not only to cast materials but also to injection molded polymeric materials, and enables a common integrated computational microstructure-based approach to optimized components.

How can an in principal binary alloy of iron and carbon show so many fascinating phenomena and still today give surprises to users, foundrymen and researchers? This paper points out some critical steps in the understanding of the whole chain, from the melt to a cast iron product in service. The understanding of the material is gradually improved, assisted by the advances of other fields, e.g. analyzing methods and computational techniques. The heart in cast iron is the graphite, which is a highly difficult phase to understand but gives the material its unique properties. The linkage between understanding and modelling is necessary to calculate/simulate the processes occurring, where the precipitation, nucleation and growth of the different phases are the keys. Proper nucleation and growth models have been introduced to predict e.g. primary precipitation of austenite and graphite, eutectic growth of different morphologies of graphite or cementite and austenite, solid state transformation of austenite into ferrite and pearlite in both grey and ductile irons, and now gives realistic microstructures and solidification curves for most practical cases. The microstructure formation models gives input to shrinkage and volume calculations to predict porosities, and to predictions of mechanical properties. By linking microstructure formation models, characterization models for mechanical properties and Finite Element Analysis (FEA) it is today possible to use local properties in simulations of the behavior of cast iron components.  

Many phenomena in cast iron, however, still remain unexplained. As one student labelled one of his experimental files on ductile iron, cast iron materials and simulations are indeed a never ending story, with a bright future in industrial applications.

Due to design and process-related factors, there are local variations in the microstructure and mechanical behaviour of cast components. This work establishes a Digital Image Correlation (DIC) based method for characterisation and investigation of the effects of such local variations on the behaviour of a high pressure, die cast (HPDC) aluminium alloy. Plastic behaviour is studied using gradient solidified samples and characterisation models for the parameters of the Hollomon equation are developed, based on microstructural refinement. Samples with controlled microstructural variations are produced and the observed DIC strain field is compared with Finite Element Method (FEM) simulation results. The results show that the DIC based method can be applied to characterise local mechanical behaviour with high accuracy. The microstructural variations are observed to cause a redistribution of strain during tensile loading. This redistribution of strain can be predicted in the FEM simulation by incorporating local mechanical behaviour using the developed characterization model. A homogeneous FEM simulation is unable to predict the observed behaviour. The results motivate the application of a previously proposed simulation strategy, which is able to predict and incorporate local variations in mechanical behaviour into FEM simulations already in the design process for cast components.