Research Papers

Microstructure Modeling and Ultrasonic Wave Propagation Simulation of A206–Al2O3 Metal Matrix Nanocomposites for Quality Inspection

[+] Author and Article Information
Yuhang Liu

Department of Industrial and Systems Engineering,
University of Wisconsin–Madison,
3255 Mechanical Engineering,
1513 University Avenue,
Madison, WI 53706
e-mail: liu427@wisc.edu

Jianguo Wu

Department of Industrial and Systems Engineering,
University of Wisconsin–Madison,
3255 Mechanical Engineering,
1513 University Avenue,
Madison, WI 53706
e-mail: wu45@wisc.edu

Shiyu Zhou

Department of Industrial and Systems Engineering,
University of Wisconsin–Madison,
3270 Mechanical Engineering,
1513 University Avenue,
Madison, WI 53706
e-mail: szhou@engr.wisc.edu

Xiaochun Li

Department of Mechanical and Aerospace Engineering,
University of California,
Los Angeles, 48-121G Eng IV,
Los Angeles, CA 90095
e-mail: xcli@seas.ucla.edu

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received February 9, 2015; final manuscript received June 25, 2015; published online October 1, 2015. Assoc. Editor: Donggang Yao.

J. Manuf. Sci. Eng 138(3), 031008 (Oct 01, 2015) Paper No: MANU-15-1075; doi: 10.1115/1.4030981 History: Received February 09, 2015; Revised June 25, 2015

Ultrasonic testing is a promising alternative quality inspection technique to the expensive microscopic imaging to characterize metal matrix nanocomposites. However, due to the complexity of the wave–microstructure interaction, and the difficulty in fabricating nanocomposites of different microstructural features, it is very challenging to build reliable relationships between ultrasonic testing results and nanocomposites quality. In this research, we propose a microstructure modeling and wave propagation simulation method to simulate ultrasonic attenuation characteristic for A206–Al2O3 metal matrix nanocomposites (MMNCs). In particular, a modified Voronoi diagram is used to reproduce the microstructures and the numeric method elastodynamic finite integration technique (EFIT) is used to simulate the wave propagation through the generated microstructures. Linear mixed effects model (LME) is used to quantify the between-curve variation of ultrasonic attenuation from both experiment and simulation. Permutation test is employed to quantify the similarity of the quantified variation between experiment and simulation. This research supports the experimental results through the simulation approach and provides a better understanding of the relationship between attenuation curves and the microstructures.

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Choi, H. , Cho, W.-H. , Konishi, H. , Kou, S. , and Li, X. , 2013, “ Nanoparticle-Induced Superior Hot Tearing Resistance of A206 Alloy,” Metall. Mater. Trans. A, 44(4), pp. 1897–1907.
Wu, J. , Zhou, S. , and Li, X. , 2013, “ Acoustic Emission Monitoring for Ultrasonic Cavitation Based Dispersion Process,” ASME J. Manuf. Sci. Eng., 135(3), p. 031015.
Wu, J. , Zhou, S. , and Li, X. , 2015, “ Ultrasonic Attenuation Based Inspection Method for Scale-Up Production of A206–Al2O3 Metal Matrix Nanocomposites,” ASME J. Manuf. Sci. Eng., 137(1), p. 011013.
Sun, Y. , 2012, “ Microstructure Modification by Nanoparticles in Aluminum and Magnesium Matrix Nanocomposites,” Master's thesis, University of Wisconsin–Madison, Madison, WI.
Ghavam, K. , Bagheriasl, R. , and Worswick, M. J. , 2013, “ Analysis of Nonisothermal Deep Drawing of Aluminum Alloy Sheet With Induced Anisotropy and Rate Sensitivity at Elevated Temperatures,” ASME J. Manuf. Sci. Eng., 136(1), p. 011006.
Lou, M. , Li, Y. B. , Li, Y. T. , and Chen, G. L. , 2013, “ Behavior and Quality Evaluation of Electroplastic Self-Piercing Riveting of Aluminum Alloy and Advanced High Strength Steel,” ASME J. Manuf. Sci. Eng., 135(1), p. 011005.
Yang, Y. , and Li, X. , 2007, “ Ultrasonic Cavitation-Based Nanomanufacturing of Bulk Aluminum Matrix Nanocomposites,” ASME J. Manuf. Sci. Eng., 129(2), pp. 252–255.
Li, X. , Yang, Y. , and Weiss, D. , 2008, “ Theoretical and Experimental Study on Ultrasonic Dispersion of Nanoparticles for Strengthening Cast Aluminum Alloy A356,” Met. Sci. Technol., 26(2), pp. 12–20.
Drury, J. C. , 2004, Ultrasonic Flaw Detection for Technicians, Silverwing Limited, Swansea, UK.
Ying, Y. , 2012, “ A Data-Driven Framework for Ultrasonic Structural Health Monitoring of Pipes,” Ph.D. thesis, Carnegie Mellon University, Pittsburgh, PA.
Schmerr, L. W. , 1998, Fundamentals of Ultrasonic Nondestructive Evaluation: A Modeling Approach, Plenum Press, New York.
Krautkrämer, J. , and Krautkrämer, H. , 1990, Ultrasonic Testing of Materials, Springer Science & Business Media, New York.
Szilard, J. , 1982, Ultrasonic Testing: Non-Conventional Testing Techniques, Wiley, New York.
Lowet, G. , and Van der Perre, G. , 1996, “ Ultrasound Velocity Measurement in Long Bones: Measurement Method and Simulation of Ultrasound Wave Propagation,” J. Biomech., 29(10), pp. 1255–1262. [PubMed]
Mathieu, V. , Anagnostou, F. , Soffer, E. , and Haiat, G. , 2011, “ Numerical Simulation of Ultrasonic Wave Propagation for the Evaluation of Dental Implant Biomechanical Stability,” J. Acoust. Soc. Am., 129(6), pp. 4062–4072. [PubMed]
Sears, F. M. , and Bonner, B. P. , 1981, “ Ultrasonic Attenuation Measurement by Spectral Ratios Utilizing Signal Processing Techniques,” IEEE Trans. Geosci. Remote Sens., 19(2), pp. 95–99.
Li, M. , Landers, R. G. , and Leu, M. C. , 2014, “ Modeling, Analysis, and Simulation of Paste Freezing in Freeze-Form Extrusion Fabrication of Thin-Wall Parts,” ASME J. Manuf. Sci. Eng., 136(6), p. 061003.
Niu, L. , Cao, H. , He, Z. , and Li, Y. , 2014, “ Dynamic Modeling and Vibration Response Simulation for High Speed Rolling Ball Bearings With Localized Surface Defects in Raceways,” ASME J. Manuf. Sci. Eng., 136(4), p. 041015.
Shen, N. , and Ding, H. , 2014, “ Physics-Based Microstructure Simulation for Drilled Hole Surface in Hardened Steel,” ASME J. Manuf. Sci. Eng., 136(4), p. 044504.
Virieux, J. , 1986, “ P-SV Wave Propagation in Heterogeneous Media: Velocity–Stress Finite-Difference Method,” Geophysics, 51(4), pp. 889–901.
Kampanis, N. A. , Dougalis, V. , and Ekaterinaris, J. A. , 2008, Effective Computational Methods for Wave Propagation, CRC Press, Boca Raton, FL.
Bossy, E. , and Grimal, Q. , 2011, “ Numerical Methods for Ultrasonic Bone Characterization,” Bone Quantitative Ultrasound, Springer, New York, pp. 181–228. [PubMed] [PubMed]
Fellinger, P. , Marklein, R. , Langenberg, K. , and Klaholz, S. , 1995, “ Numerical Modeling of Elastic Wave Propagation and Scattering With EFIT—Elastodynamic Finite Integration Technique,” Wave Motion, 21(1), pp. 47–66.
Haïat, G. , Naili, S. , Grimal, Q. , Talmant, M. , Desceliers, C. , and Soize, C. , 2009, “ Influence of a Gradient of Material Properties on Ultrasonic Wave Propagation in Cortical Bone: Application to Axial Transmission,” J. Acoust. Soc. Am., 125(6), pp. 4043–4052. [PubMed]
Protopappas, V. C. , Kourtis, I. C. , Kourtis, L. C. , Malizos, K. N. , Massalas, C. V. , and Fotiadis, D. I. , 2007, “ Three-Dimensional Finite Element Modeling of Guided Ultrasound Wave Propagation in Intact and Healing Long Bones,” J. Acoust. Soc. Am., 121(6), pp. 3907–3921. [PubMed]
Gopalakrishnan, S. , Chakraborty, A. , and Mahapatra, D. R. , 2007, Spectral Finite Element Method: Wave Propagation, Diagnostics and Control in Anisotropic and Inhomogeneous Structures, Springer, New York.
Bossy, E. , Laugier, P. , Peyrin, F. , and Padilla, F. , 2007, “ Attenuation in Trabecular Bone: A Comparison Between Numerical Simulation and Experimental Results in Human Femur,” J. Acoust. Soc. Am., 122(4), pp. 2469–2475. [PubMed]
Leckey, C. A. , Miller, C. A. , and Hinders, M. K. , 2011, “ 3D Ultrasonic Wave Simulations for Structural Health Monitoring,” Report No. NF1676L-13045.
Guz, I. A. , and Rushchitsky, J. , 2007, “ Computational Simulation of Harmonic Wave Propagation in Fibrous Micro-and Nanocomposites,” Compos. Sci. Technol., 67(5), pp. 861–866.
Maio, L. , Memmolo, V. , Ricci, F. , Boffa, N. , Monaco, E. , and Pecora, R. , 2015, “ Ultrasonic Wave Propagation in Composite Laminates by Numerical Simulation,” Compos. Struct., 121, pp. 64–74.
Yang, Y. , Lan, J. , and Li, X. , 2004, “ Study on Bulk Aluminum Matrix Nano-Composite Fabricated by Ultrasonic Dispersion of Nano-Sized SiC Particles in Molten Aluminum Alloy,” Mater. Sci. Eng. A, 380(1), pp. 378–383.
Nave, M. , Dahle, A. , and St John, D. , “ The Role of Zinc in the Eutectic Solidification of Magnesium–Aluminium–Zinc Alloys,” Magnesium Technology 2000, the Minerals, Metals, and Materials Society, pp. 243–250.
Ghosh, S. , Nowak, Z. , and Lee, K. , 1997, “ Quantitative Characterization and Modeling of Composite Microstructures by Voronoi Cells,” Acta Mater., 45(6), pp. 2215–2234.
Fan, Z. , Wu, Y. , Zhao, X. , and Lu, Y. , 2004, “ Simulation of Polycrystalline Structure With Voronoi Diagram in Laguerre Geometry Based on Random Closed Packing of Spheres,” Comput. Mater. Sci., 29(3), pp. 301–308.
Du, Q. , Faber, V. , and Gunzburger, M. , 1999, “ Centroidal Voronoi Tessellations: Applications and Algorithms,” SIAM Rev., 41(4), pp. 637–676.
Suzudo, T. , and Kaburaki, H. , 2009, “ An Evolutional Approach to the Numerical Construction of Polycrystalline Structures Using the Voronoi Tessellation,” Phys. Lett. A, 373(48), pp. 4484–4488.
Krautkrämer, J. , and Krautkrämer, H. , 1983, Ultrasonic Testing of Materials, Springer, New York.
Chassignole, B. , El Guerjouma, R. , Ploix, M.-A. , and Fouquet, T. , 2010, “ Ultrasonic and Structural Characterization of Anisotropic Austenitic Stainless Steel Welds: Towards a Higher Reliability in Ultrasonic Non-Destructive Testing,” NDT & E Int., 43(4), pp. 273–282.
Chinta, P. K. , and Kleinert, W. , 2014, Elastic Wave Modeling in Complex Geometries Using Elastodynamic Finite Integration Technique, 11th European Conference on Non-Destructive Testing (ECNDT 2014), Prague, Czech Republic, Oct. 6–10.
Villagomez, C. , Medina, L. , and Pereira, W. , 2012, “ Open Source Acoustic Wave Solver of Elastodynamic Equations for Heterogeneous Isotropic Media,” IEEE International on Ultrasonics Symposium (IUS), pp. 1521–1524.
Zheng, R. , Le, L. H. , Sacchi, M. D. , Ta, D. , and Lou, E. , 2007, “ Spectral Ratio Method to Estimate Broadband Ultrasound Attenuation of Cortical Bones In Vitro Using Multiple Reflections,” Phys. Med. Biol., 52(19), p. 5855. [PubMed]
Grin, Y. , Wagner, F. R. , Armbrüster, M. , Kohout, M. , Leithe-Jasper, A. , Schwarz, U. , Wedig, U. , and von Schnering, H. G. , 2006, “ CuAl 2 Revisited: Composition, Crystal Structure, Chemical Bonding, Compressibility and Raman Spectroscopy,” J. Solid State Chem., 179(6), pp. 1707–1719.
Zhou, W. , Liu, L. , Li, B. , Song, Q. , and Wu, P. , 2009, “ Structural, Elastic, and Electronic Properties of Al–Cu Intermetallic From First-Principles Calculations,” J. Electron. Mater., 38(2), pp. 356–364.
Gałecki, A. , and Burzykowski, T. , 2013, Linear Mixed-Effects Models Using R: A Step-By-Step Approach, Springer, New York.
Pinheiro, J. C. , and Bates, D. M. , 2000, Mixed-Effects Models in S and S-PLUS, Springer Science & Business Media, New York.
Anderson, T. W. , 2003, An Introduction to Multivariate Statistical Analysis, Wiley, New York.
Good, P. , 2000, Permutation Tests, Springer, New York.
Benjamini, Y. , and Hochberg, Y. , 1995, “ Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing,” J. R. Stat. Soc. Ser. B (Methodological), 57(1), pp. 289–300.
Virieux, J. , 1984, “ SH-Wave Propagation in Heterogeneous Media: Velocity–Stress Finite-Difference Method,” Geophysics, 49(11), pp. 1933–1942.


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Fig. 3

Example of Voronoi diagram with 20 random points

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Fig. 2

Microstructures for pure A206 and A206–Al2O3 MMNCs. Left panel: experimental micrographs. Right panel: simulated microstructures.

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Fig. 1

Illustration of the ultrasonic testing using ultrasonic attenuation curves [3]

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Fig. 4

The microstructure modeling process: (a) initial Vononoi diagram, (b) after edge dissolving step controlled by α and β, (c) after assigning random thickness to each edge, and (d) the random thickness assigning process

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Fig. 5

Microstructures generated using different parameters α, β, and N

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Fig. 6

Examples of input phantom, wave propagation snapshots, and transducer output by VEFIT

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Fig. 7

Simulation procedure using VEFIT and attenuation measurement

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Fig. 8

The comparison of experimental attenuation curves and the simulated attenuation curves with different simulation parameters (attenuation units: dB/mm, frequency unit: MHz)

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Fig. 9

The influence of α and β on the attenuation curves (N = 1200)

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Fig. 10

Histograms of the fitted random effects and residuals for the experimental measurements of A206-5 wt. % Al2O3 (top) and simulated attenuation curves shown in Fig. 8(c3) (bottom)

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Fig. 11

Illustration of permutation test on population means of two data sets

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Fig. 12

Illustration of the permutation test. (a) and (b): Figs. 8(c) versus 8(c3), p-value = 0.99; (c) and (d): Figs. 8(b) versus 8(c3), p-value = 0.06. The vertical dashed lines denote the observed test statistics.



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