Simulation of casting defects in A356.pdf

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EFFECT OF INTERNAL DEFECTS ON TENSILE PROPERTIES OF A356 CASTING ALLOYS Jie CHENGa*, Norbert HORTa, Karl Ulrich KAINERa, Siyoung KWAKb,c a b c

Helmholtz-Zentrum Geesthach (HZG), Max-Planck-Str. 1, D-21502 Geesthacht, Germany, EU

Korea Institute of Industrial Technology (KITECH), 7-47 Songdo-Dong, 406-840 Incheon, South Korea University of Science & Technology (UST),217 Gajungro, Yuseong-Gu, 305-333 Daejeon, South Korea

Abstract This paper presents both the computational and experimental analysis of internal defects (shrinkage cavity and blow holes) to evaluate their effect on tensile properties of A356 casting alloys. For experimental testing, tensile test specimens with internal defects were produced by hanging an Al alloy wire whose melting point is slightly higher than the feeding temperature of A356 Alloy (700°C~710°C). An alumina-silica ceramic fibre-based non-woven fabric (Ceramic Fibre Paper) was fixed on the wire to create artificial defect after the solidification of molten A356 alloy. Specimens with internal defects of various sizes were produced, and then tensile and impact tests were performed on the specimens. In addition to experimental investigation, computational analysis was conducted to determine the dependence of the alloy tensile properties on the internal defects present. A computational system for finite element analysis of casting components with internal defects was proposed. In this system, reverse engineering was first utilized to obtain the CAD models of internal defects. Then numerical calculations are performed to analyse the shapes of internal defects, reduce them to ellipsoids whose volume-sum approximately covers all points of the given defects, and then generate the final CAD model of the casting with internal defects. Finally, computational analysis using finite element method was performed on the defect-containing casting model. Results obtained by experiments and computer simulations were in agreement with some marginal differences. This agreement verified the reliability of proposed computational system for finite element analysis of casting components with internal defects. Keywords: Internal casting defect, Ellipsoidal-blob approximation, SSM (Shape Simplification Method), MVEE (Minimum Volume Enclosing Ellipsoid), FEM (Finite Element Method) 1.

INTRODUCTION

Casting is widely used in manufacturing industry due to its advantages like being able to create parts with complex geometries, net-shape or near net-shape, and relatively more economical compared to other manufacturing methods. Meanwhile, it also has some disadvantages like limitations on mechanical properties and environmental problems. Among the disadvantages, the one, i.e. limitations on mechanical properties are mostly caused by various casting defects or imperfections. Here, the term casting defect is used for general imperfections in this study [1]. The classification proposed by G. K. Lal [2]was adopted with some modification in this study: casting defects can be generally classified to two types: 1) Surface defects, such as blow, scar, blister, drop, scab, penetration and buckle; and 2) Internal defects, such as blow/gas holes, shrinkage/porosity, inclusions, dross, etc. Their effects on mechanical performance of castings can further be divided into two classes in terms of micro-size defects and macro-size defects, while micro-size refers to defects that are not visible without magnification, and macro-size are that large enough to see with the unaided on non-destructive graphic inspection.

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Most surface defects are readily to be found even by unaided eye, and can be easily corrected by some industry technology such as shot-blast cleaning or grinding [1]. But, internal casting defects, taking examples of internal shrinkage cavities and gas porosity, they cannot be detected with unaided eye and even general product quality control test, like water pressure explosion test, therefore, their effect on the mechanical performance of castings should be pre-considered when design the cast products and assess the qualities of castings. However, the effect of internal defects on the mechanical properties of castings is not fully understood yet, and there is no well accepted method and standard to predict [3], so designers are uncertain how to deal with internal defects in their casting designs. Traditional solutions are specifying extensive quality tests, performing extensive performance testing, and using large factors of safety. All of those solutions do not necessarily guarantee the performance and they are all somewhat costly [4]. Due to the above reasons, it is necessary and important to study the effects of internal defects on castings. But it is somehow impossible to conduct a comprehensive study on various internal casting defects. This is why only internal macro-blowholes and shrinkage cavities were chosen to be studied. Generally, the terminology "internal defects" was used for both macro-blowholes and macro-shrinkages through this research. Specimens with internal defects were made by casting and then put to tensile tests. Also, a computational modelling system was development to model the internal defects for subsequent Finite Element Analysis (FEA). Comparable results obtained from experiments and computer simulation not only enriched the understandings of effect of internal defects on castings, and also verified the reliability of developed modelling method for internal defects, which can be utilized to learn more characteristics of internal defects, and also has the potential to be extended to other internal macro defects such as metallic inclusions and internal sweating. 2.

EXPERIMENTS

In this research, A356 with a composition indicated in Table 1 was chosen for tensile specimen material. Table 1. The composition of A356 for specimens

2.1

Elements

Al

Si

Mg

Cu

Fe

Ti

Wt. %

92.23

6.98

0.345

0.008

0.13

0.096

Specimen preparation

Most of previous studies on effect of internal defects used natural defects (defects that resulted from casting process without extensive manual intervention). K. M. Sigh et.al [3] used four different casting geometries to produce specimens with tree levels of radio graphically detectable macro-porosity. Similar method was also applied by M. Avalle, G. Belingardi and M. P. Cavatorta [5]. They used different sprue runners to produce high and middle level porosities. Another method, extracting specimens from porosity area from casting blocks, was used by Y. Nadot, J. Mendez and N. Ranganathan [6]. All those methods produce only specimens with macro-porosity, rather than the isolated macro-shrinkages which are desired in this research. Macroporosity contains lots of internal macro voids, although they make it possible to get more realistic results, but it also brings difficulties to understand their effects, because the effects of voids are interactive. So it is important to find a method of making isolated internal defect which had been a barrier for studies on this field. In this research, internal defects (macro-shrinkage cavities or blowholes) was produced by hanging an Al alloy wire whose melting point is slightly higher than the pouring temperature of A356 (700°C~710°C). On the Al alloy wire, there was a macro-shrinkage-like grain fixed on. The grains are made of alumina-silica ceramic fibre-based non-woven fabric (Ceramic Fibre Paper). Their shapes are irregular with typical size

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about 2~7 mm. Because ceramic fibre paper has characteristics of 1) Light-weight, flexible, good handing strength and good uniformity; 2) Resists temperature as high as 2300 F, fire resistant; 3) Good for die-cut and automatic stamping, so after the solidification of molten A356, the grain would exist inside the castings, and their effects on mechanical properties are assumed to be same with ones of shrinkages. Casted A356 blocks were subsequently T6 heat treated. A356 blocks were heated to 520 C for 8 hours, and cooled rapidly by water quenching. Then, the blocks were kept at room temperature for 12 hours (Natural Aging), and subsequently heated to 160 C for 6 hours and followed with furnace cooling (Artificial Aging). After T6 heat treated, A356-T6 blocks were scanned with RaySacn X-ray inspection system to detect the position of the internal defects, which would be used to guide the machining process for extracting tensile specimens from cast A356-T6 blocks. As soon as the tensile test specimens were extracted, RaySan X-ray inspection system was again used to acquire the shape, size and position information of internal defects for the subsequent computer modelling process, the CT images of final tensile test specimens are shown in Figure 1.

Fig. 1 Dimension and CT images of tensile test specimens 2.2

Experimental results

The tensile tests were performed with MTS® Landmark Servohydraulic System at room temperature in a displacement control mode with the speed of 2 mm per minute. As a result, applied force and elongation data were obtained as shown in Figure 2. Here, the applied force refers to the gripping forces that applied on wedge grip, and elongation was the one measured with the 50 mm axial extensometer. By fitting curves, elastic moduli (E) were obtained for metal mould casted A356-T6 in this study as shown in Figure 3. The yield strengths (0.2% offset) and ultimate strengths of five specimens were calculated and listed in Table 2.

Fig. 2 Tensile test results

Fig. 3 Elastic moduli drawn from tensile tests

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Table 2 Comparison of yield, ultimate strengths and max elongations of tensile specimens Specimen

Yield Strength (MPa)

Difference (%)

Ultimate Strength (MPa)

Difference (%)

Max. Elongation (mm)

Difference (%)

G1TTS#01

143.78

Reference

234.15

Reference

3.00

Reference

G1TTS#02

139.80

-2.78

224.50

-4.12

2.95

-1.67

G1TTS#03

156.41

8.78

187.51

-19.92

0.66

-78.00

G1TTS#04

137.78

-4.17

157.17

-32.88

0.42

-86.00

G1TTS#05

135.44

15.06

146.77

-37.32

0.34

-88.67

3.

COMPUTATIONAL ANALYSIS

3.1

Computational system

Lots of researches have been conducted to study the performance-based guidelines for design of cast components where the amount or location of defects is considered. The previous works on this field are generally divided into two parts: on Micro, and on Macro defects. Since the studies regarding on micro defects are much more systemic than ones of macro defects, the problem falls to how to count macro defects into the consideration of casting’s performance. In previous studies, the author and S. Y. Kwak summarized two exacting methods for counting the effects of internal defects in casting designs: 1) Direct Shape Method (DSM), 2) Material Property Reduction Method (MPRM) and they proposed the third method, named 3) Shape Simplification Method (SSM) [7]. Lately, they further improved the SSM to enable it for modelling multi-defects and generating simplified defect model with more flexible shape [8]. In summary, the developed computational system executes the following the functions: (1) Reverse engineering: voxel information (point cloud) of casting with internal shrinkage cavities was acquired with one of reverse engineering tools, i.e. industrial Computed Tomography X-ray (CT) in this study, and subsequently converted to STL format model which includes the information of both the outer profile of casting and the internal shrinkage cavities; (2) Point clustering: voxel information obtained in step (1) are decomposed to a couple of point groups; (3) Ellipsoidal approximation: Khachiyan method [9] was utilized to find the minimum volume enclosing ellipsoids that cover the given group points; (4) Boolean operation: obtained ellipsoids are merged together and then Boolean cut with CAD model of cast part to get the final cast part model with shape-simplified internal defects. To simplify the procedure of the modelling process for castings with internal defects, a modelling toolkit which couples above four functions, was developed using Python code and implemented into ABAQUS as a customized plug-in toolkit as shown in Figure 4. With the customized ABAQUS plug-in toolkit, the final casting model which includes internal defects can be readily obtained by engineers to be used for subsequent finite element analysis [8]. 3.2

Simulation results

According to experimental conditions, boundary and load conditions were applied to tensile specimens, and then the first order continuum three dimensional 4-node linear tetrahedron elements (Abaqus C3D4 Elements) were generated on the models. All models of tensile specimens were meshed with same element size distribution (size of 2 mm on gripping region, 1mm on gage region and 0.25 mm on defect surface). For tensile test simulation, static analysis was performed using Abaqus Standard. Material properties were calculated based on experimental results of reference specimen, G1TTS#01, and assigned to each model.

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One end of model was fixed and displacement of 5 mm was applied on the other end. As a result, for G1TTS#01 model, von Mises stress on the cross section of gage region increased uniformly, while stress concentrations occurs around the internal defects for those defected specimens. Figure 5 is a plot of the stress distribution in the tensile specimen at the onset of the maximum Von Mises stress. The Von Mises stress was found to increase to the ultimate strength of A356-T6 (G1TTS#01: 234.15MPa) and finally propagate onto the outer surface of the cross section in the gage region. In this study, the assumption that a material stressed up to the ultimate tensile stress would fracture was made to analyze the simulation results. Thus, damages were expected to initiate from the surface of internal defects, and then propagate to nearby materials. Once damages reached the outer surface of the cross section in the gage region, specimens would then fracture. Based on this assumption, it was obtained from the simulation results that maximum Von Mises stress in the defected specimen (e.g., G1TTS#04) increased much more rapidly than the sound specimen (e.g., G1TTS#01), due to the effect of the stress concentration. In turn, the elongations of two specimens at onset of fracture were 2, 70 and 0.42 mm, respectively. G1TTS#04

Fig. 4 Abaqus toolkit for internal defects modelling 4.

Fig. 5 Contour of von Mises stress distribution

COMPARISON OF RESELTS

Computational and experimental results of load-carrying capacity and maximum elongations of gage length of each tensile specimen (except G1TTS#01) are plotted in Figure 6. Since the material property data for computational analysis were taken from experimental results of G1TTS#01, so it is reasonable that computational and experimental results of G1TTS#01 match well to each other, and thus is not plotted. For results of G1TTS#02~#05, although computational results differed from experimental results in various degrees, most computational results were compared with experimental ones with errors less 5%; one exceptional case was 9.96% (Load carrying capacity of G1TTS#05). The big error may caused by the inaccurate modelling of internal defects, or the experimental error. More accurate models of internal defects should be made to investigate the relationship between modelling and computational results in further study. However, considering the complex characteristics of internal casting defects, the obtained computational results are acceptable. 5.

CONCLUSIONS

Tensile testing results showed that the internal defects created had various effects on tensile properties. Elongation was most drastically affected (up to 88.67% reduction), followed by tensile load bearing capacity and ultimate tensile strength (up to 37.32% reduction) and yield strength (up to 15.06% reduction). There was almost no measureable effect on elastic modulus. In addition, an easy-to-use computational system was proposed to simulate the tensile tests. Results obtained by experiments and computer simulations were in agreement with some marginal differences. This

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agreement verified the reliability of proposed computational system for finite element analysis of casting components with internal defects.

Fig. 6 Comparison of applied force versus Elongation histories ACKNOWLEDGEMENTS This research was supported by Korea University of Science & Technology (UST) and Korea Institute of Industrial Technology (KITECH). The acknowledgment is given to them hereby. REFERENCES [1]

ASM INTERNATIONAL, Casting Design and Performance,

[2]

LAL, G. K., CHOUDHURY, S.K., Fundamentals of Manufacturing Processes, 2005. 61 p.

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SIGL, K. M., HARDIN, R.A., STEPHENS, R. I., and BECKERMANN, C., Fatigue of 8630 Cast Steel in the presence of Porosity, International Journal of Cast Metals Research, 2004, vol.17, nr. 3, pp 130-146

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MONROE, R., Porosity in Castings, AFS Transactions 2005 © American Foundry Society, Schaumburg, IL USA, Paper 05-245(04), 1~28 p.

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AVALLE, M., BELINGARDI, G., and CAVATORTA, M. P., Static and Fatigue Strength of a Die Cast Aluminum Alloy under Different Feeding Conditions, Presented at EUROMAT 2001, Rimini 10–14, June, 2001

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NADOT, Y., Propagation Lifetime from the Surface and Internal Defects in the Ultra High Cycle Fatigue Regime, The Open Materials Science Journal, 2008, nr. 2, page 35-39

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KWAK, S. Y., CHENG, J., KIM. J. T., and CHOI, J. K., Structural Analysis Considering Shrinkage Defect of Cast Part, International Journal of Cast Metals Research, 2008, vol. 21, nr. 1-4, page 319-323

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CHENG, J., KWAK, S. Y., and HWANG, H. Y., Development of Casting Shrinkage Cavity Modeling Toolkit for Finite Element Analysis using Ellipsoidal Approximation Technique, International Journal of Cast Metals Research, Special Edition, 2011, vol. 24, nr. 3, page 238-242

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