Study of 3D Pores and Its Relationship with Crack Initiation Factors of Aluminum Alloy Die Castings
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INTRODUCTION
HIGH-PRESSURE die casting (HPDC) of aluminum alloys is widely used in automotive, aerospace, and other fields. However, porosity is one of the main defects of casting. It occurs inevitably during HPDC and has a detrimental impact on the mechanical properties of the casting alloys. Thus, it is very important to understand the type and distribution of the pores to improve mechanical properties of die-casting aluminum alloys. Traditional research methods of porosity are based on metallographic quantitative analysis.[1–4] With the development of high-resolution X-ray computerized tomography, it is possible to observe and quantitatively study pores in three dimensions. Felberbaum and Rappaz[5] observed pores in unmodified and
ZIXIN LI, YUHAI JING, XIUYUAN SUN, KUN YU, ANSHAN YU, XINGWANG JIANG, and X.J. YANG are with the School of Mechanical and Electrical Engineering, Nanchang University, Nanchang 330031, China and also with the Key Laboratory of Near Net Forming in Jiangxi Province, Nanchang 330031, China. Contact e-mail: [email protected] HONGMIN GUO is with the Key Laboratory of Near Net Forming in Jiangxi Province and School of Material Science and Engineering, Nanchang University, Nanchang 330031, China. Manuscript submitted December 10, 2018.
METALLURGICAL AND MATERIALS TRANSACTIONS B
modified Al-Cu alloys by high-resolution X-ray computerized tomography and estimated the curvature of the pores, which pointed out that some adjacent pores in the metallography were connected three-dimensionally. However, their results showed that metallographical analysis based on the cross section would overestimate the number of pores and underestimate their sizes and shape complexity. Thus, X-ray computerized tomography can be used to describe the pore characteristics of die-casting alloys more accurately. It is believed that statistical analysis of pore distribution in castings can provide a basis for the analysis of porosity fracture mechanism and overall process optimization.[6] Tiryakiog˘lu[7] assumed that the pore size of AM50 die castings strictly conformed to the lognormal distribution with 3-parameters but did not conform to the lognormal distribution with 2-parameters. Their research was based on 2D metallographic measurements of pore size. Generally, probability plots are used to test the size of defects if they follow the lognormal,[12] Gumbel,[13] and Weibull distributions.[14] Among these distributions, probability density function of the 2-parameter lognormal distribution can be written as " # 1 ðln x lÞ2 fðxÞ ¼ pffiffiffiffiffiffi exp : ½1 2r2 xr 2p Probability density function of the 3-parameter lognormal distribution can be written as
# ðlnðx sÞ lÞ2 pffiffiffiffiffiffi exp fðxÞ ¼ ; 2r2 ðx sÞr 2p 1
"
½2
where s is the threshold, r is the shape, and l is the scale parameter. Equation [2] can be reduced to a 2-parameter lognormal distribution at threshold values close to zero. Usage of probability plots is subjective and insufficient to test data necessarily for specific distribution. Thus, it is recommended to
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