Advanced X-ray Computed Tomography of Voids and Porosity in As-Cast FeMnAl Steel Alloy Material
Abstract
The X-ray computed tomography (XCT) technique is a widely applicable and powerful nondestructive inspection modality to evaluate and analyze 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 US Army Combat Capabilities Development Command (CCDC) 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 inches) thick by 76.2 mm (3 inches) wide by 76.2 mm (3 inches) long, which had been sectioned from an industrially cast ingot (tilde12,000 lb), were individually scanned by XCT using a conventional 450-kV X-ray source and a solid-state flat panel detector. Due mainly to the thickness of the blocks, as well as a desire to keep geometric unsharpness relatively small, which affected overall scan geometry (setup), 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 percent- 90 percent , the response through the block was only 5 percent- 10 percent. This report covers the XCT scanning parameters and overall protocol used to mitigate the very low intensity throughput and achieve acceptable scan image results; the overall quality of the FeMnAl blocks and the image processing methods used to segment porosity and void features in the blocks; and quantitative results of porosity and void content, number of overall pores/voids, and pore/void volume distribution.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2020
- Accession Number
- AD1101570
Entities
People
- Bryan A. Cheeseman
- Daniel Field
- Krista R Limmer
- William H. Green
Organizations
- United States Army Research Laboratory