Using Micro-CT Scanning to Quantitative Characterize Porosity in High Pressure Die Castings and Semi-Solid Castings

Article Preview

Abstract:

Porosity is one of the main defects that limits the performance of castings. Porosity in aluminum castings can originate from several sources, including the volumetric shrinkage occurring during solidification, the precipitation of dissolved hydrogen, and entrapment of gasses such as air, boiling water, vaporized lubricants, etc. Traditional methods of identifying and measuring porosity in castings include 2D x-rays, sectioning and polishing, and Archimedes density measurements, but none of these provide a satisfactory quantitative estimate of the size, total volume and distribution of the pores. X-ray CT scanning is a relatively new method that generates not only a 3-dimensional view of the size and distribution of the pores, but can also provide quantitative information of the volume, surface area, size, shape and position of each pore within a casting. Micro-CT scanning is a specialized sub-category of CT scanning, which provides excellent resolution of fine porosity (a resolution limit of 4 microns in one of the case-stores presented in this paper), but it should be noted that the resolution limit in CT scanning techniques is related to sample size. This paper describes results from micro-CT scanning studies of two high pressure die castings and a semi-solid casting, and provides quantitative data on the total porosity content, and the porosity distribution. The paper will also demonstrate the capabilities of the micro-CT scanning process to provide a quantitative comparison of the porosity content in these different types of aluminum castings.

You might also be interested in these eBooks

Info:

Periodical:

Solid State Phenomena (Volume 327)

Pages:

33-44

Citation:

Online since:

January 2022

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2022 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Daquan Li, Fan Zhang, S. P. Midson, Xiaoguang Liang, Hui Yao, Recent Developments of Rheo-Diecast Components for Transportation Markets,, Solid State Phenomena 285, 2019, 417-422.

DOI: 10.4028/www.scientific.net/ssp.285.417

Google Scholar

[2] Beckmann, R. Grupp, A. Haibel, M. Huppmann, M. Nöthe, A. Pyzalla, W. Reimers, A. Schreyer, R. Zettler, In-Situ synchrotron X-ray microtomography studies of microstructure and damage evolution in engineering materials,, Advanced engineering materials, 9, 2007, 939-950.

DOI: 10.1002/adem.200700254

Google Scholar

[3] E. Maire, P. J. Withers, Quantitative X-ray tomography,, International Materials Reviews, 59, 2014, 1-4.

Google Scholar

[4] R. Cepuritis, E. J. Garboczi, S. Jacobsen, Three dimensional shape analysis of concrete aggregates fines produced by VSI crushing,, Powder Technology, 308, 2017, 410-421.

DOI: 10.1016/j.powtec.2016.12.020

Google Scholar

[5] J. F. Barrett, N. Keat, Artifacts in CT: Recognition and avoidance, RadioGraphics, 24, (2004).

DOI: 10.1148/rg.246045065

Google Scholar

[6] Gianni Nicoletto, Giancarlo Anzelotti, and Radomila Konečná. X-Ray Computed Tomography vs. Metallography for Pore Sizing and Fatigue of Cast Al-Alloys,, Procedia Engineering 2, no. 1, 2010, 547–54.

DOI: 10.1016/j.proeng.2010.03.059

Google Scholar

[7] Patrick Hairy, Yves Gaillard, Valeris Buecher & Amaury Chabod, Quantification of Defects in Pressure Die Casting (Part III), 3D Analysis by Tomography", Fonderie et Fondeur d'Aujourd,hui, No. 271, January, 2008, pp.8-22.

Google Scholar

[8] Andrew Good, Industrial CT at a Glance,, Die Casting Engineer, September 2013, p.40.

Google Scholar

[9] Alejandro Golob, Quality Control Best Practices: Introducing Industrial CT Scanning into Your Quality Assurance Process,, Die Casting Engineer, May 2015, p.14.

Google Scholar

[10] Christiane Maierhofer, Philipp Myrach, Mathias Röllig, Florian Jonietz, Bernhard Illerhaus, Dietmar Meinel, Uwe Richter, and Ronald Miksche, Characterization of Pores in High Pressure Die Cast Aluminum Using Active Thermography and Computed Tomography,, 42nd Annual Review of Progress in Quantitative Nondestructive Evaluation, AIP Conf. Proc. 1706, 110009-1–110009-8;.

DOI: 10.1063/1.4940580

Google Scholar

[11] Itamar Brill, Branden Kappes & Stephen Midson, An Initial Evaluation of CT Scanning for Measuring and Characterizing Porosity in Aluminum Die Castings,, Trans. North American Die Casting 2018 Congress, paper number T18-083.

Google Scholar

[12] Abdel Rahman Dakak, Valérie Kaftandjian, Philippe Duvauchelle & Patrick Bouvet, Establishment of Acceptance Criteria for Tomography Inspection of Aluminium Alloy Castings,, International Symposium on Digital Industrial Radiology and Computed Tomography, 2 – 4 July 2019 in Fürth, Germany (DIR 2019).

Google Scholar

[13] Itamar Brill, Dawson Tong, Branden Kappes and Stephen Midson, Using Micro-CT Scanning to Characterize Porosity in Aluminum Die Castings,, Trans. North American Die Casting 2019 Congress, paper number T19-081.

DOI: 10.4028/www.scientific.net/ssp.327.33

Google Scholar

[14] Danielle M. Barna, Dawson Tong, Branden Kappes, Stephen Midson & Douglas Nychka, Using Sphericity Calculations to Identify the Source of Porosity in Aluminum Castings,, Trans. North American Die Casting 2020 Congress.

Google Scholar

[15] J. Li, B. Oberdorfer, P. Schumacher, Determining Casting Defects in Thixomolding Mg Casting Part by Computed Tomography, In: M. Tiryakioğlu, W. Griffiths, M. Jolly. (eds) Shape Casting. The Minerals, 2019, Metals & Materials Series. Springer, Cham. https://doi.org/10.1007/978-3-030-06034-3_9.

DOI: 10.1007/978-3-030-06034-3_9

Google Scholar

[16] J. Li, Bernd Oberdorfer, Daniel Habe, Peter Schumacher,. (2018) Determining casting defects in near-net shape casting aluminum parts by computed tomography,, Frontiers of Mechanical Engineering. 13. , 2018, 1-5. 10.1007/s11465-018-0493-y.

DOI: 10.1007/s11465-018-0493-y

Google Scholar

[17] L. DeChiffre, S. Carmignato, J.-P. Kruth, R. Schmitt & A. Weckenmann, Industrial Applications of Computed Tomography,, CIRP Annals - Manufacturing Technology, 63, 2004, 655-677.

DOI: 10.1016/j.cirp.2014.05.011

Google Scholar

[18] Greg Wallace, Andrew P. Jackson, Stephen P. Midson & Qiang Zhu, High-Quality Aluminum Turbocharger Impellers Produced by Thixocasting,, Transactions of Nonferrous Metals Society of China, 20, Issue (9), 2010, 1786-1791.

DOI: 10.1016/s1003-6326(09)60375-7

Google Scholar

[19] William E. Lorensen, and Harvey E. Cline. Marching Cubes: A High Resolution 3D Surface Construction Algorithm,, SIGGRAPH Comput. Graph. 21, no. 4, August, 1987, 163–69.

DOI: 10.1145/37402.37422

Google Scholar

[20] Product Design for Die Casting, North American Die Casting publication number 206, (2015).

Google Scholar

[21] Jessada Wannasin, Marc Fucks, Jiyong Lee, Cheol-Ung Lee, Narasimha Rao & Merton C. Flemings, GISS Technology: Principles and Application in Die Casting,, Solid State Phenomena, 285, 2019, 470-475.

DOI: 10.4028/www.scientific.net/ssp.285.470

Google Scholar

[22] Thixomolding: What's That?, Design News, April, 2000, available at www.designnews.com/materials-assembly/thixomolding-whats.

Google Scholar