scholarly journals Standardization of Low Cycle Fatigue Testing Method at Liquid Helium Temperature.

Author(s):  
Ken-ichi SUZUKI
Author(s):  
M.K. Lamvik ◽  
D.A. Kopf ◽  
S.D. Davilla ◽  
J.D. Robertson

Last year we reported1 that there is a striking reduction in the rate of mass loss when a specimen is observed at liquid helium temperature. It is important to determine whether liquid helium temperature is significantly better than liquid nitrogen temperature. This requires a good understanding of mass loss effects in cold stages around 100K.


1975 ◽  
Vol 15 (7) ◽  
pp. 819-823 ◽  
Author(s):  
Yoshihiko Tsukamoto ◽  
Shinri Horiuchi ◽  
Toˆru Yoshizawa

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4070
Author(s):  
Andrea Karen Persons ◽  
John E. Ball ◽  
Charles Freeman ◽  
David M. Macias ◽  
Chartrisa LaShan Simpson ◽  
...  

Standards for the fatigue testing of wearable sensing technologies are lacking. The majority of published fatigue tests for wearable sensors are performed on proof-of-concept stretch sensors fabricated from a variety of materials. Due to their flexibility and stretchability, polymers are often used in the fabrication of wearable sensors. Other materials, including textiles, carbon nanotubes, graphene, and conductive metals or inks, may be used in conjunction with polymers to fabricate wearable sensors. Depending on the combination of the materials used, the fatigue behaviors of wearable sensors can vary. Additionally, fatigue testing methodologies for the sensors also vary, with most tests focusing only on the low-cycle fatigue (LCF) regime, and few sensors are cycled until failure or runout are achieved. Fatigue life predictions of wearable sensors are also lacking. These issues make direct comparisons of wearable sensors difficult. To facilitate direct comparisons of wearable sensors and to move proof-of-concept sensors from “bench to bedside,” fatigue testing standards should be established. Further, both high-cycle fatigue (HCF) and failure data are needed to determine the appropriateness in the use, modification, development, and validation of fatigue life prediction models and to further the understanding of how cracks initiate and propagate in wearable sensing technologies.


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