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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14

Enhanced Mechanical Properties and Wear Resistance of FeCrAl Alloys at ~ 300°C and Higher Temperatures

Abstract Worldwide, light water reactors (LWRs) have been using zirconium (Zr)-based alloys for the cladding of the uranium dioxide fuel for more than 6 decades. Zr alloys oxidize rapidly in the presence of water and steam at temperatures > 450°C; therefore, they do not respond well to scenarios of loss of coolant accidents. There is a global effort by nuclear materials technologists to find more robust or stronger cladding materials for LWRs. One option is to use an iron-chromium-aluminum (FeCrAl) alloy since they have excellent resistance to high temperature oxidation and superior mechanical properties at LWR operation temperatures. Results show that (1) FeCrAl alloys have better mechanical properties than Zr alloy and are orders of magnitude more resistant to creep at temperatures higher than LWR normal operation conditions. (2) FeCrAl alloys have better resistance to fretting wear than Zr alloys at the normal operation conditions of LWRs.

Materials Science↗

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗

Increased AGE Cross-Linking Reduces the Mechanical Properties of Osteons

Abstract The osteon is the primary structural component of bone, contributing significantly to its unique toughness and strength. Despite extensive research on osteonal structure, the properties of osteons have not been fully investigated, particularly within the context of bone fragility diseases like type 2 diabetes mellitus (T2DM). This study aims to isolate osteons from bovine bone, simulate the effects of increased advanced glycation end-products (AGEs) in T2DM through ribosylation, and evaluate the mechanical properties of isolated osteons. Osteons extracted from the posterior section of bovine femur mid-diaphysis were processed to achieve a sub-millimeter scale for microscale imaging. Subsequently, synchrotron radiation micro-computed tomography was employed to precisely localize and isolate the osteon internally. While comparable elastic properties were observed between control and ribosylated osteons, the presence of AGEs led to decreased strain to failure. Young’s modulus was quantified (9.9 ± 4.9 GPa and 8.7 ± 3 GPa, respectively), aligning closely with existing literature. This study presents a novel method for the extraction and isolation of osteons from bone and shows the detrimental effect of AGEs at the osteonal level.

Materials Science↗