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.

Copyright © 2016 by ASME
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Fig. 1

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

Grahic Jump Location
Fig. 2

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

Grahic Jump Location
Fig. 3

Example of Voronoi diagram with 20 random points

Grahic Jump Location
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

Grahic Jump Location
Fig. 5

Microstructures generated using different parameters α, β, and N

Grahic Jump Location
Fig. 6

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

Grahic Jump Location
Fig. 7

Simulation procedure using VEFIT and attenuation measurement

Grahic Jump Location
Fig. 8

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

Grahic Jump Location
Fig. 9

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

Grahic Jump Location
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)

Grahic Jump Location
Fig. 11

Illustration of permutation test on population means of two data sets

Grahic Jump Location
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.




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In