A comparative study by using two different log-periodic power laws on acoustic emission signals from LiF specimens under compression

التفاصيل البيبلوغرافية
العنوان: A comparative study by using two different log-periodic power laws on acoustic emission signals from LiF specimens under compression
المؤلفون: Mastrogiannis, D. Andreopoulos, S.I. Potirakis, S.M.
سنة النشر: 2019
الوصف: The deformation of solid materials up to the point of fracture is followed by acoustic emission (AE) signals. The cumulative acoustic energy released during such a process seems to generally follow a power law form, which is compatible with the view that the fracturing process is a phenomenon with developing critical dynamics. In the present work, the cumulative energy released by the AE signals emitted during the deformation of LiF samples has been calculated and fitted by two different fitting functions, which are both power laws decorated with log-periodic corrections. The comparison of the produced results would lead to the conclusion of whether each one of the two equations can produce valid acoustic energy release modeling, which can describe the fracturing procedure of solid materials and its underlying mechanics. It should be noted that one of the models managed to fit the experimental data more accurately in the majority of the cases studied. We show that both of the studied log-periodic models managed to acceptably fit the data, which means that this field of study could possible lead to new methods of predicting the time point of a material's failure. In conclusion, this comparative study reveals that these models could be a valuable tool in cases of monitoring materials or structures being under load at the region of their mechanical tolerance. © 2018 Elsevier Ltd
اللغة: English
URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______2127::8d50d1e02ae651fd12496917c5055bf1
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3035418
حقوق: OPEN
رقم الأكسشن: edsair.od......2127..8d50d1e02ae651fd12496917c5055bf1
قاعدة البيانات: OpenAIRE