Abstract

The X-ray computed tomography (XCT) technique is a widely applicable and powerful non-destructive inspection modality for evaluation and analysis of geometrical and physical characteristics of materials, especially internal structures and features. XCT is applicable to metals, ceramics, plastics, and polymer and mixed composites, as well as components and materiel. The Army Research Laboratory (ARL) and its partners are currently investigating the use of cast iron-manganese-aluminum (FeMnAl) steel alloy material in support of weight reduction initiatives in Army Development Programs. Steel alloy FeMnAl has been identified as a key enabling material technology to reduce the weight in ground combat vehicle systems. A set of FeMnAl blocks each approximately 50.8 mm (2 in.) thick by 76.2 mm (3 in.) wide by 76.2 mm (3 in.) long, which had been sectioned from an industrially cast ingot (∼12,000 lbs.), were individually scanned by XCT using a conventional 450 kV X-ray source and a solid-state flat panel detector. Mainly due to the thickness of the blocks, as well as a desire to keep geometric unsharpness relatively small which affected overall scan geometry (set up), the scans had a very low response at the detector through the FeMnAl blocks. With the calibrated detector response through air (i.e., around a block) at 85–90% the response through the block was only 5–10%. The XCT scanning parameters and overall protocol used to mitigate the very low-intensity throughput and achieve acceptable scan image results will be discussed. Image processing (IP) methods used to segment porosity features in the FeMnAl blocks will also be discussed.

References

References
1.
American Society for Testing and Materials (ASTM)
,
1995
, “
Standard Practice for Computed Tomographic (CT) Examination
,” Designation: E 1570-95a, Columbus, OH.
2.
Dennis
,
M. J.
,
1989
, “Industrial Computed Tomography,”
Nondestructive Evaluation and Quality Control
, Vol.
17
,
American Society for Metals (ASM) International, ASM Handbook Committee
,
Materials Park/Novelty, OH
.
3.
Newton
,
T. H.
, and
Potts
,
D. G.
, eds.,
1981
, “Technical Aspects of Computed Tomography,”
Radiology of the Skull and Brain
, Vol.
5
,
The C. V. Mosby Company
,
St. Louis, MO
.
4.
Stanley
,
J. H.
,
1986
,
Physical and Mathematical Basis of CT Imaging
,
American Society for Testing and Materials (ASTM)
, ASTM CT Standardization Committee (E7.01.07), ASTM Tutorial: Section 3,
Columbus, OH
.
5.
American Society for Testing and Materials (ASTM)
,
1995
, “
Standard Guide for Computed Tomography (CT) Imaging
,” Designation: E 1441-95a, Columbus, OH.
6.
Muehlhauser
,
B.
,
2015
,
Optimizing Image Signal to Noise Ratio Using Frame Averaging
,” North Star Imaging Blog, https://4nsi.com/blog/2015/10/21/optimizing-image-signal-to-noise-ratio-using-frame-averaging/, Accessed March 31, 2020.
7.
Shannon
,
C. E.
,
1949
, “
Communication in the Presence of Noise
,”
Proc. Inst. Radio Eng.
,
37
(
1
), pp.
10
21
.
8.
Buades
,
A.
,
Coll
,
B.
, and
Morel
,
J. M.
,
2005
, “
A Non-Local Algorithm for Image Denoising
,”
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
,
San Diego, CA
, vol.
2
, pp.
60
65
.
9.
Buades
,
A.
,
Coll
,
B.
, and
Morel
,
J. M.
On Image Denoising Methods
,” (PDF) 123 Seminars Only, http://www.123seminarsonly.com/Seminar-Reports/029/42184313-10-1-1-100-81.pdf, Accessed March 31, 2020.
10.
Bruker Corporation
,
2013
,
Manual for Bruker-microCT CT-Analyser v. 1.13
, Bruker-microCT N.V.,
Billerica, MA
. http://www.bruker.com
11.
Ferreira
,
T.
, and
Rasband
,
W.
,
2012
, “
ImageJ User Guide—IJ 1.46r
,” https://imagej.nih.gov/ij/docs/guide/, Accessed March 31, 2020.
12.
Richards
,
V.
,
2013
,
Chapter 4: Risering of Castings
, Missouri University of Science and Technology, Course MET 307 - Metals Casting, Rolla, MO.
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