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Effect of freezing range on reducing casting defects through 3D sand-printed mold designs

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Abstract

Additive manufacturing (AM) is accepted as a transformative technology for rapid production of parts based on digital models through direct printing of a range of materials (e.g., metals, polymers, and ceramics). Recent advancements in the binder-jetting AM process (i.e., 3D sand-printing (3DSP)) enables direct production of sand molds and cores for metal casting. AM has been attractive to manufacturers due to the ability to produce complex and customized parts in low batch production. Traditional mold design for gravity castings experience higher scrap rates due to challenges in controlling turbulence and air entrapment. In this research, mathematically designed sprue geometries that can be produced via 3DSP are presented along with their effect on mechanical and metallurgical properties of castings through numerical modeling, computational simulation, and experimental validation. The casting properties are contrasted to conventional straight sprue castings for two different alloys: aluminum alloy 319 and gray cast iron class 30. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), computed tomography scanning (CT), and 3-point bending tests are performed to characterize microstructure, casting defects, elemental composition, and mechanical properties for castings of each gating system design. For aluminum alloy 319, a statistically significant increase of 10% in flexural strength was found using the conical-helix sprue geometry as well as a reduction of 25% in casting defects. In gray cast iron class 30, no statistically significant differences are found between the flexural strength of the conical-helix and benchmark straight sprue as expected in a short freezing range alloy.

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Abbreviations

\({h}_{sprue}\) :

Total sprue height (m)

\(\alpha , r\) :

Angular frequency and radius of the conical-helix

\(a, b\) :

Geometric parameters of the parabolic profile

\(\forall\) :

Volume of air (m3)

\({C}_{air}\) :

Entrainment rate sensitivity coefficient

\(\rho\) :

Fluid density (kg/m3)

\({T}_{m}\) :

Melting temperature (K)

\(\eta\) :

Absolute viscosity (Pa s)

\(k\) :

Turbulence kinetic energy (J/kg)

\({g}_{n}\) :

Gravity normal to melt surface (m/s2)

\({L}_{t}\) :

Turbulence length scale (m)

\(\sigma\) :

Surface tension coefficient (kg/s2)

\({\sigma }_{flex}\) :

Flexural stress in 3-point bending test

\(F\) :

Applied force on sample in 3-point bending test

\(L\) :

Length between supports in 3-point bending test

\(w\) :

3-Point bending test sample width

\(t\) :

3-Point bending test sample thickness

CHC:

Conical-helix sprue design casting

PC:

Parabolic sprue design casting

SC:

Straight sprue design casting

YMT:

Yen Multilevel Thresholding algorithm

Me:

Maximum Entropy algorithm

Re:

Rényi Entropy algorithm

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Acknowledgements

This material is based upon work supported by the National Science Foundation (NSF) under Career Award, #1944120. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE1255832. The authors would also like to thank America Makes for its financial support through AM4MC grant, Hazelton Casting Company for providing the resources for experimentation, FAME Lab for support during casting of the aluminum alloy 319 samples, and the Center for Quantitative Imaging (CQI)—Tim Stecko for his help in acquiring CT scanning data. Thank you to Dr. Robert Voigt for his expert input during the development of this work. The authors also thank Flow 3D-CAST for providing extended research license and PA Department of Community and Economic Development for their (in part) support of this publication.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Pennsylvania State University, 330 Leonhard Building, University Park, PA, 16802, USA

    Daniel Martinez, Philip King, Santosh Reddy Sama, Jay Sim & Guha Manogharan

  2. Department of Industrial and Manufacturing Engineering, Pennsylvania State University, 106 Leonhard Building, University Park, PA, 16802, USA

    Hakan Toykoc

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Appendix

Appendix

Table 3 Image analysis results for aluminum alloy 319
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Table 4 Image analysis results for gray cast iron class 30
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Martinez, D., King, P., Sama, S.R. et al. Effect of freezing range on reducing casting defects through 3D sand-printed mold designs. Int J Adv Manuf Technol 126, 569–581 (2023). https://doi.org/10.1007/s00170-023-11112-x

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