Yu and Loper (4) have studied the effect of alloying elements on pearlitic and martensitic hardenability of ductile cast iron. The effect of molybdenum, nickel and ...
AFS Trans., 105 (1997) 47-54
A Mechanical Properties Model for Ductile Iron X. Guo, D.M. Stefanescu
L. Chuzhoy, M.A. Pershing, G.L. Biltgen
The University of Alabama, Tuscaloosa
Caterpillar Technical Center, Peoria, Il.
Abstract A mechanical properties model has been developed to quantitatively describe the relationship between selected mechanical properties, such as hardness, tensile strength, and elongation, and the microstructural features of ductile iron. The influence of the microstructural features of ductile iron, including graphite nodule count, nodularity, fraction of graphite, fraction of ferrite, and fraction of pearlite, on the fracture mechanism and the mechanical properties were discussed. The validation tests demonstrated that the mechanical properties of ductile iron can be predicted with reasonable accuracy through the equations developed in this research. The importance of this work is that, when coupling the mechanical properties model with a computational solidification model that includes microstructural evolution, not only average but also local mechanical properties of ductile iron castings can be predicted. This opens a new window of opportunity for casting design, based on local and not on average properties as currently done.
1. Introduction Ductile iron is increasingly being used for critical engineering applications due to its excellent properties and castability. The importance of providing the design engineer with consistent and comprehensive data on commercially produced ductile iron castings cannot be overstated. At present, casting design is based on average properties verified on test coupons. If the mechanical properties of ductile iron can be related quantitatively, through computer modeling, to the final microstructure, and ultimately to the processing conditions, it would be possible to improve the design process by using properties maps over the various sections of the casting. In addition, the mechanical properties could be better controlled by altering manufacturing processing parameters. This concept has been recently successfully applied to gray cast iron for mechanical properties prediction. (1,2) It is well known that the mechanical properties of any engineering material are determined primarily by its microstructure. The factors influencing the mechanical properties of ductile iron include the chemical composition of the matrix, the size, distribution and shape of graphite nodules , the size and morphology of primary dendrites, the pearlite/ferrite ratio, ferrite grain size and the pearlite lamellar spacing. There is a wealth of semi-quantitative knowledge on the effect of microstructure on the mechanical properties of ductile iron. However, because of the unstructured way in which these data were obtained, it is impossible to use them for the generation of generally valid microstructure - properties correlations. On the other hand, most of the data associated with the relationship between mechanical properties and microstructures in the literature have been generated from laboratory heats rather than from commercial iron. The
1
AFS Trans., 105 (1997) 47-54
lack of consistency between laboratory experimental data and commercial production data makes it difficult to properly predict the mechanical properties of ductile iron. The purpose of the present study is to provide the basis for understanding of the mechanical behavior of ductile iron for a rather broad range of composition and microstructure. It is also the purpose of this work to provide the foundation for a data base to be used for a computer microstructure /mechanical properties simulation model. The acceptability of the mechanical properties model for ductile iron should depend not only on the knowledge of the predicted properties (tensile strength, hardness, ductility), but also on the in-depth understanding of the relationship between these mechanical properties and the composition and microstructure of the material.
2. Literature Review The as-cast microstructure of ductile iron matrix typically contains a mixture of ferrite and pearlite. In the as-cast structure, ferrite generally appears in the form of concentric shells around the graphite nodules. The mechanical properties of as-cast ductile iron strongly depend on the amount and distribution of ferrite in the microstructure. It is known that the ferrite content of the matrix depends on the chemical composition of the ductile iron and on the rate at which it is cooled through the eutectoid transformation range. In order to evaluate the quantitative effects of alloying elements on the microstructure, Venugopalan and Alagarsamy (3) obtained a regression equation for the as-cast fraction of ferrite in the matrix. The equation is a linear multiple regression equation with second-order terms included to account for synergistic effects of molybdenum with nickel and copper: Eq. 1
%f = 69Si + 198Mo - 35Mn - 109Cu - 22Ni - 202MoNi -74CuMo - 73
The composite matrix microhardness (CMMH) of ductile iron can be expressed simply by the rule of mixtures, that is: Eq. 2
CMMH = (HV%f + HVPe%fPe)/100
where HV is the hardness of ferrite, HVPe is the hardness of pearlite, and %f and %fPe are the ferrite and pearlite percents of the matrix, respectively. The ferrite hardness and pearlite hardness were fitted into two multiple regression equations as follows: Eq. 3
HV = 66 + 45Si + 12Mn + 10Cu + 7Ni + 21Mo
Eq. 4
HVPe = 253 + 27Si + 10Mn +14Cu + 17Ni + 26Mo
Linear regression expressions for tensile strength were given as follows: Eq. 5
Tensile Strength (ksi) = 0.10 + 0.36CMMH
Eq. 6
Yield Strength (ksi) = 12 + 0.18CMMH
2
AFS Trans., 105 (1997) 47-54
Venugopalan pointed out that the entire analysis was based on data from keel-block legs, and the equations obtained for properties were not expected to apply to all castings of different section size without some changes in the coefficients. Yu and Loper (4) have studied the effect of alloying elements on pearlitic and martensitic hardenability of ductile cast iron. The effect of molybdenum, nickel and copper in forming ferrite in a variety of ductile iron sections was evaluated by using multiple linear regression analysis. The following equations were obtained: Eq. 7
% Ferrite = 15.6 - 11.9Mn - 13.6Cu + 19D- 8.1Ni -15.9CuD
Eq. 8
HB = 237 + 151Mo + 68.4 Ni +89Cu - 21.3D - 51.7DMo - 20.4DNi
The interaction between alloying elements yielded extremely small coefficients and were neglected. The amount of pearlite is influenced by both alloying elements and cooling rate, with a large amount of scatter in castings having more than 90% pearlite. Excluding that data, the Brinell hardness increases exponential as the pearlite content is increased: Eq. 9
HB = exp ( 5.01 + % Pearlite )
From experiments, Svensson, Wessen and Gonzalez (5) have derived three equations, describing the relations between the fraction of ferrite, silicon content and Brinell hardness: Eq. 10 HB = HB(Si)f + HBPe(Si) (1 - f) Eq. 11 HB(Si) = 54 + 37Si Eq. 12 HBPe(Si)= 167 + 31Si These equations are valid in the interval 1.7 to 4.9 %Si. Nearly all of the previous mentioned mechanical property models of ductile iron have focused on the study of the influence of alloying elements and section size of castings on mechanical properties. The methods are popular because they involve few variables but exhibit good predicted results under limited conditions. In general, these models can only be used for conditions that are similar to the ones for which the models have been derived. With the emergence of computer modeling of microstructure evolution it has become possible to predict the microstructure of ductile iron quantitatively from heat and fluid flow calculations coupled with nucleation and growth kinetics. Once the quantitative relationships between microstructure and mechanical properties of ductile iron are available, computer modeling can become a powerful tool for the control of mechanical properties of ductile iron through manipulation of the processing parameters. The purpose of this work is to formulate a hardness, tensile strength and an elongation model for ductile iron by analyzing the microstructures found in commercial ductile iron castings and evaluating their effects on mechanical properties.
3
AFS Trans., 105 (1997) 47-54
3. Experimental work The ductile iron samples used in this study were provided by three commercial foundries. They were cut from either ASTM specified keel blocks or “Y” blocks. In addition, in order to study the influence of cooling rate on the microstructure of ductile iron, four groups of cylindrical samples (the diameters of samples were 63.5, 33, 25.4, 19, 15.2 and 12.7 mm ) were poured in an experimental area at Caterpillar Inc. and examined in the Solidification Laboratory at The University of Alabama. 3.1 Microstructural Characterization Tensile strength samples were received from three different commercial foundries and examined by both optical microscope and SEM. The samples were cast from the standard ASTM grades listed in Table 1. Table 1 Specified tensile properties of ASTM A536 grades examined Grade
Tensile
0.2% Yield
strength
strength
Elongation
MPa
ksi
MPa
ksi
%
65-45-12
448
65
310
45
12
80-55-06
552
80
379
55
6
100-70-03
690
100
483
70
3
3.1.1 Typical microstructure The typical microstructure of the commercial ductile iron studied is presented in Fig. 1. Fig. 1a shows the mostly pearlitic microstructure typical of 100-70-03 ductile iron, while Fig. 1b presents the mostly ferritic microstructure characteristic of 65-45-12 ductile iron. 3.1.2 Graphite Nodule Count Ductile iron nodule count is one of the important factors in achieving the desired mechanical properties. Nodule count affects mechanical properties through its influence on microstructure. In general, as the nodule count increases, the diffusion distance of carbon that migrates from the matrix to the nodules decreases. During the eutectoid reaction this promotes a higher percentage of ferrite.(6) Therefore, when a high as-cast ferrite content is needed, a higher nodule count is desired. For this reason, as nodule count increases, tensile strength, yield strength and hardness decrease, while elongation increases. (7,8,9) On the other hand, a higher nodule count can reduce the tendency for carbide formation.(9,10) In addition, nodule size also affects mechanical properties. Doshi et al.(11) reported that nodule size has little effect on elongation in both hard and soft ductile iron and also has little effect on tensile strength in relatively soft ductile iron. However, increasing the nodule size decreased the tensile strength of the harder ductile irons.
4
AFS Trans., 105 (1997) 47-54
Cooling rate during solidification has a significant influence on ductile iron nodule count. Generally speaking, faster cooling rate results in higher nodule count. This effect is consistent with nucleation and growth theories.(12) These theories suggest that, as the rate of solidification increases, the size of the stable nuclei that will grow decreases. In other words, thinner sections will have higher nodule count. In fact, for a given casting, not only different sections have different cooling rates, but also at the edge and at the center of each section different cooling rates will be obtained. Consequently, the nodule count at different locations of the casting will be different. Fig. 2 shows the relationship between nodule count, sample diameter (cooling rate), and location within the sample. In Fig. 2a, an example of the experimental data and the fitting curve is shown. It can be seen that as the diameter of the sample decreases, the nodule count increases. Fig. 2b presents only the fitting curves for all sample diameters. The nodule count decreases from the edge to the center of the sample because of decreasing cooling rate away from the mold-casting interface. However, starting at mid-radius, the nodule count increases and reaches a peak value at the center of the sample. This can be explained through segregation of elements that increase undercooling, and thus favor a higher nucleation potential. The graphite nodule size varies with distance from the edge in the opposite way to nodule count (Fig. 3), as expected. Distributions like those presented in Fig. 2 and Fig. 3, show the importance of addressing the issue of local properties. 3.1.3 Pearlite Lamellar Spacing A typical pearlite structure is presented in Fig. 4. It is seen that some pearlite colonies exhibit a lamellar structure, while in others, cementite appears as dispersed particles or short flakes, which makes it difficult or even impossible to evaluate the lamellar spacing quantitatively. In general, it was noticed that the higher cooling rate produced finer pearlite structure, as expected. 3.2 Fracture Analysis To establish a reliable mechanical property model, it is necessary to have a clear understanding of fracture mechanism of ductile iron. The plastic deformation characteristics of annealed ductile irons have been studied extensively by Gilbert. (13,14). Adewara and Loper(15) conducted a systematic study on crack initiation and propagation in fully ferritic ductile iron. A fracture model for fully ferritic ductile iron as well as effects of pearlite and carbides on crack initiation and propagation in ductile iron are well documented. (16,17) At the onset of plastic deformation, voids have been found to form at the poles of graphite nodules. Formation of these voids is assumed to correspond to crack initiation. Crack propagation was assumed to occur by a linking of nodules through fracturing of the inter-nodule matrix bridges along grain boundaries. Voigt and co-workers (18,19,20,21) conducted a series of studies in which surface crack initiation and propagation were carefully observed by in-situ SEM while increasing strain at room temperature. To accurately predict the complex fracture behavior of cast irons, a model must take into account not only the complex elastic-plastic behavior of the work hardening matrix microconstituents, but also the localized stress fields that interact with each other and with the microscopic applied stress. However, this kind of information on as-cast commercial ductile irons under tensile stress is limited.
5
AFS Trans., 105 (1997) 47-54
Four commercial ductile iron samples that have been fractured through tensile strength tests were studied by SEM. The samples were cut through the fracture surface perpendicularly. The sampling position as well as the polishing plane and examined areas are shown in Fig. 5. During the tensile test sample necking would occur. Before the sample fractures, because of the necking, a maximum stress is obtained at the area near the fracture surface, while away from the fracture a much lower stress is obtained. By examining the microstructural change along the longitudinal direction fracture development can be understood. The SEM micrographs in Fig. 6 show the microstructural evolution along the longitudinal direction in as-cast ferritic ductile iron. At the area A, some small voids have been found to form at the poles of graphite nodules along the tensile direction (Fig. 6a). Deformation of graphite nodules occurred and many oval-shaped rather than spheroidal graphite nodules were found. At area B, much larger voids have been found, which means void growth occurred under a larger stress, (Fig. 6b). With increased stress, voids continued to form and grow. Progressively, the matrix pulled away from the graphite nodules (Fig. 6c). At the area near the fractured surface, D, the matrix between graphite nodules necked and eventually fractured (Fig. 6d). Finally, fracturing of the inter-nodule matrix bridges linked up and fracture took place. Duplicate microstructural examination were carried out and very similar results were obtained for each pair of tests. The experimental results verified Adewara and Loper's model. A careful SEM examination on two as-cast pearlitic ductile iron tensile test samples was carried out. In these samples the ferrite content was less than 10%. It is evident that there was little void formation around the nodules before fracture since pearlite sustained the bulk of the load applied on the sample and was not capable of appreciable plastic deformation, as shown in Fig. 7. Obviously, pearlite colonies in ductile iron offer some constraint to free plastic deformation of the ferrite structure. This resulted in a change in the model of crack initiation, from the ductile model by void formation and growth and linking, to a model by micro-shear mechanism in the pearlite structure in ductile iron. In other words, there are two completely different fracture mechanisms for ferritic and pearlitic ductile irons. However, the stress-raising ability of graphite nodules and their capacity to nucleate cracks were similar for ferritic and pearlitic ductile iron. It is generally accepted that increasing the ferrite content will increase ductility and decrease tensile strength. From the above discussion, it is concluded that in order to predict the tensile strength and ductility of ductile irons, the fraction of ferrite and of pearlite, as well as graphite nodularity must be included in the mechanical properties model.
4. Formulation of mechanical properties models 4.1 Hardness model The proposed model for calculation of hardness is as follows: Eq. 13 HB K HBGr fGr HB f HBPe fPe HBFe3C fFe3C where Eq. 14a
HB HBFe Ci X i% i
and
6
AFS Trans., 105 (1997) 47-54
HBPe C1 Ci %X i C2 n Pe
Eq. 14b
i
where HB HBPe, HBGr, HBFe3C and HBFe are the hardness of ferrite, pearlite, graphite, carbide, and pure iron, respectively, f, fPe, fGr and fFe3C are the fraction of ferrite, pearlite, graphite and carbide, respectively, Pe is the lamellar spacing of pearlite, %Xi is the weight percentage of the alloying elements, and K, C1, C2, Ci and n are constants which can be determined experimentally. It is noted that in this model there is an additional coefficient K before the term HBGr. Since graphite nodules are very small, when hardness is measured, not only the graphite itself, but also the matrix under the graphite will affect hardness. The coefficient K takes this phenomenon into account. 4.2 Tensile strength model The proposed model for calculation of tensile strength is described by the following equation: n Eq. 15 = (1 fGr )( f fPe Pe )
In this equation,and Pe may take different forms. For example, similar to the Hall-Petch equation, we can assume that: k k o Eq. 16 and Pe oPe Pe d Pe o
o
where , Pe are the tensile strength of ferrite and pearlite in a reference standard condition, respectively, d is the average diameter of ferrite grains, and k, kPe are constants. Under certain circumstances, such as constant cooling rate, and Pe can have constant values. n in Eq. 15 is a shape factor for graphite nodules. Its maximum value is unity. 4.3 Elongation model The proposed elongation model has the expression: n Eq. 17 (1 fGr )( f Pe f Pe )
where and Pe are the elongation of ferrite and pearlite, respectively.
5. Experimental measurement and evaluation of model parameters Forty ductile iron samples were obtained from three different commercial foundries. The evaluation of their mechanical properties was performed in the respective foundries. The microstructures were examined in the lab with an optical microscope having an image analysis system, and by SEM. The fraction of graphite was measured in the same manner as described in a previous paper.(1) The experimental results show that there is no significant difference between measured data and the data calculated from the phase diagram. Accordingly, the data calculated from the phase diagram were used as fraction of graphite in the MPM.
7
AFS Trans., 105 (1997) 47-54
5.1 Hardness model As mentioned before, since the pearlitic structure in ductile iron did not show regular lamellar structure, it was difficult to use lamellar spacing as a parameter in the pearlite hardness equation (Eq. 14b). However, it is well accepted that pearlite lamellar spacing is a function of compositions and cooling rates. Based on these considerations and on the analysis of the experimental data, the pearlite hardness equation was written as Eq. 18 HBPe = 223 + 50(Mn + Cu + Cr + Mo) + 10 Ni +20(dT/dt - 0.5) where dT/dt is the cooling rate at 850 oC For the samples used in this study, the Si content varied in a narrow range and averaged about 2.5% Si. The hardness of ferrite in each sample shows little variation and has a value within the range of 135 -150 HB. Both Svensson’s model (Eq. 11) and Venugopalan's model (Eq. 3) were tested. For most of the samples used in this study, the HBevaluated with Eq. 11 was 145, which is consistent with the measured data. Since there are no significant alloying elements in the ductile iron samples, the ferrite hardness values calculated from Svensson's model showed little error. Subsequently, Eq. 11 was used to evaluate ferrite hardness in the mechanical properties model. Based on this discussion Eq. 13 was modified, and the hardness model was derived to be: Eq. 19 HB =100 fGr + HB f + HBPe f Pe where HBPe is given by Eq. 18. A comparison between measured hardness and the hardness calculated with Eq. 19 is shown in Fig. 8. It is seen that a good correlation between measured and calculated data was obtained on the samples poured in the Caterpillar experimental area. 5.2 Tensile strength model By using multiple regression analysis, the following equation was found for the tensile strength: n Eq. 20 (1 fGr )(482.2 f 991.5 fPe )
Since all samples analyzed in this study had very good nodularity, n was simply taken as unity. The influence of nodularity on tensile strength needs to be further studied. The comparison of measured and calculated tensile strength data is shown in Fig. 9. Eq. 20 is valid for typical, well modified and inoculated, commercial ductile irons. However, if significant free cementite is present, or if the nodularity is poor, a considerable error may be obtained. 5.3 Elongation model The equation for elongation was also obtained through regression analysis: n Eq. 21 (1 fGr )(26.2 f 5.61 f Pe )
A comparison of measured and calculated elongation data is presented in Fig.10.
6. Validation of the mechanical properties models To validate the mechanical properties models, two test castings, having six cylindrical bars, were poured in resin bonded sand molds. The bar diameters were 12.7, 15.2, 19, 25.4, 33 and 8
AFS Trans., 105 (1997) 47-54
63.5 mm. One test casting met ASTM 65-45-12 grade standards and the other met ASTM 10070-03 grade standards. A comparison between calculated and measured hardness data as a function of matrix structure and sample size is given in Fig. 11. One of the important requirements of a mechanical properties model is its ability to calculate local properties. A comparison between the calculated and the measured hardness map obtained from two 33 mm diameter bars is given in Fig. 12 for both ferritic and pearlitic ductile irons. From Fig. 11 and Fig. 12, it is conclude that this hardness model works very well. Once the microstructure evolution model is combined with the hardness model, the local hardness of ductile iron can be predicted. Since sufficient tensile strength and elongation data from the cylindrical bars were not available, the validation of tensile strength and elongation models was carried out on commercial ductile iron samples which were not used in the model derivation. The validation results are given in Table 2 are satisfactory. Table 2 Validation of tensile strength, elongation and hardness Tensile strength, MPa No.
calc. exp.
Elongation, %
error calc. exp. %
Brinell hardness error calc. exp. HB error % %
A03
620
592
28
+4.7
10.9
11.4
-0.5
-4.4
201
217
-16
-7.4
A09
687
669
18
+2.7
8.73
9.6
-0.87
-9.06
219
228
-9
-3.95
A10
639
674.5
-35.5
-5.3
9.66
8.9
0.76
8.54
211.5
228
-16.5
-7.24
A11
751
719.3
31.7
4.41
6.68
6.2
0.48
7.74
235
241
-6
-2.5
B08
738
731.9
6.1
0.83
7.26
6
1.26
21
232
229
3
1.31
B12
787
825.5
-38.5
-4.66
5.23
6
-0.77
-12.8
249.6
255
-5.4
-2.1
B13
803.5
856.8
-53.3
-6.2
4.74
5
-0.26
-5.2
268.2
255
13.2
5.18
B15
793.5
824
-30.5
3.7
4,78
5
-0.22
-4.4
263.6
255
8.6
3.37
7. Conclusions It was demonstrated that the mechanical properties of ductile iron studied in this work, including hardness, tensile strength and elongation, are mainly dependent on the fractions of graphite, ferrite, and pearlite as well as on the nodularity of graphite. If the fraction of each microstructural component is known, the mechanical properties of ductile irons can be predicted with reasonable accuracy through the equations developed in this research. The microstructural features required by the model can be obtained either through local metallographic analysis , or through computational modeling of solidification , if the model includes microstructure evolution. This opens the window for the design of casting based on local and not average properties.
9
AFS Trans., 105 (1997) 47-54
References 1. X. Guo, A. Catalina, D. M. Stefanescu, L. Chuzhoy and M. Pershing, "Simulation of Mechanical Properties of Gray Cast Iron," MSC- 3 , Beijing, Dec. 1996. 2. X. Guo, A. Catalina, D. M. Stefanescu, L. Chuzhoy and M. Pershing, Private Communication, 1997. 3 D. Venugopalan and A. Alagarsamy, " Effects of Alloy Additions on the Microstructure and Mechanical Properties of Commercial Ductile Iron," AFS Trans. Vol.98, 1990, pp 395-400. 4. S. K. Yu and C. R. Loper Jr., "The Effect of Molybdenum, Copper, and Nickel on the Pearlitic and Martensitic Hardenability of Ductile Cast Irons," AFS Trans., Vol. 96, 1988, pp 811-822. 5. I. L. Svensson, M. Wessen and A. Gonzalez, " Modeling of Structure and Hardness in Nodular Cast Iron Castings at Different Silicon Contents," Proceedings of Modeling of Casting; Welding and Advanced Solidification Process VI, TMS, Edited by T. S. Piwonka, V. Voller and L. Katgerman, 1993, pp 29-36. 6. J. H. Doubrava S. F. Cater, Jr., and J. F. Wallace, " The Influence of Processing Variables on the Matrix Structure and Nodularity of Ductile Iron, " AFS Trans., 1981, pp 229-250. 7. C. R. Loper, Jr., "Processing and Control of Ductile Iron," AFS Trans., 1969, pp1-7, 8. P. Trojan, W Bargeron, and R. Flinn, "The Evaluation of Nodularizers and Post Inoculants For Ductile Iron, " AFS Trans., 1967, pp 611-624. 9. A. S. Amin and C. R. Loper, Jr., "Cerium and Rare Earth in Ductile Iron," AFS Trans., 1978, pp505512. 10. C. R. Loper, Jr., " Nodule Count Is Important," Foundry, 1969.9., pp75-81. 11. G. F. Ruff, and B. K. Doshi, "Relation Between Mechanical Properties and Graphite Structure in Cast Iron, Part II: Ductile Iron," Modern Casting, 1980.7. pp70-74. 12.A. G. Gay, Elements of Physical Metallurgy, Addison-Wesley Publishing Company, Inc. 1959, pp6368. 13. G. M. Gilbert. "The Stress-Strain Properties of Nodular Cast Irons in Tension and Compression, " BCIRA Journal, Mar. 1964, pp170-193 14. G. Jolley and G. M. Gilbert, "Segregation in Nodular Irons and Its Influence on Mechanical Properties," The British Foundryman, Vol.60, 1967, p79 15. J. O. T. Adewara and C. R. Loper Jr., "Crack Initiation and Propagation in Fully Ferritic Ductile Iron," AFS Trans., Vol.84, 1976, pp527-534 16. J. O. T. Adewara and C. R. Loper Jr., "Effect of Carbides on Crack Initiation and Propagation in Ductile Iron," AFS Trans., Vol.84, 1976, pp507-512 17. J. O. T. Adewara and C. R. Loper Jr., "Effect of Pearlite on Crack Initiation and Propagation in Ductile Iron," AFS Trans., Vol.84, 1976, pp513-526 18. R. C. Voigt and L. Eldoky, "Microstructural Aspects of Fracture in Ductile irons," Advanced Casting Technology, ASM, Edited by J. Easwaran, Nov. 1987, pp153-165 19. L. Eldoky and R. C. Voigt, "Fracture of Ferritic Ductile Cast Iron," AFS Trans. Vol.94, 1986, pp621630 20. R. C. Voigt and L. Eldoky, "Crack Initiation and Propagation in Quenched and Tempered Ductile Cast Iron," AFS Trans., Vol.94, 1986, pp631-636 21. R. C. Voigt and L. Eldoky, "Crack Initiation and Propagation in As-Cast and Fully Pearlitic Ductile Cast Iron," AFS Trans., Vol.94, 1986, pp637-644
10
AFS Trans., 105 (1997) 47-54
Figures
(a) mainly pearlite matrix
(b) mainly ferrite matrix
Fig. 1 Typical as-cast microstructure of ductile iron
a)
b)
Fig. 2 The distribution of nodule count in samples with different diameters
11
AFS Trans., 105 (1997) 47-54
Fig. 3 The distribution of the average diameter of graphite nodules in samples with different diameters.
Fig. 4 Typical pearlite structure in ductile iron (SEM)
12
AFS Trans., 105 (1997) 47-54
Examined area
D
C B A
Fracture surf ace
20 mm
Polishing plane
12.7 mm
Fig. 5 Sampling position
a)Typical microstructure at area A
c) Typical microstructure at area C
b) Typical microstructure at area B
d) Typical microstructure at area D
Fig. 6 The SEM microstructural evolution along the longitudinal direction in tensile fractured as-cast ferritic ductile iron. 13
AFS Trans., 105 (1997) 47-54
Fig. 7 The SEM microstructure in tensile fractured as-cast ductile iron having a mostly pearlitic matrix.
Fig. 8 Comparison of calculated and measured hardness
14
AFS Trans., 105 (1997) 47-54
Fig. 9 Comparison of calculated and measured tensile strength
Fig. 10 Comparison of elongation calculated and measured
Fig. 11 Calculated and experimental mid radius Brinell Hardness data for bars of different diameters
15
AFS Trans., 105 (1997) 47-54
275 Pearlitic / ferrite duc tile iron
Br inell hardness
250
measured calculated
225 200
175 Ferritic / pearlite ductile iron
150 -1
-0.5 0 0.5 1 Nodimenional distance, x/D (0-center of the sample)
Fig. 12 The hardness map of a 33 mm diameter cylindrical specimen for both ferritic and pearlitic ductile irons
16
