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of 10
pro vyhledávání: '"Karthik Reddy Lyathakula"'
Autor:
Saumik Dana, Karthik Reddy Lyathakula
Publikováno v:
Artificial Intelligence in Geosciences, Vol 2, Iss , Pp 171-178 (2021)
The critical slip distance in rate and state model for fault friction in the study of potential earthquakes can vary wildly from micrometers to few me-ters depending on the length scale of the critically stressed fault. This makes it incredibly impor
Externí odkaz:
https://doaj.org/article/7ac9ac3145fb484f8d67fbabf70bb30a
Autor:
Sevki Cesmeci, Karthik Reddy Lyathakula, Mohammad Fuad Hassan, Shuangbiao Liu, Hanping Xu, Jing Tang
Publikováno v:
Applied Sciences, Vol 12, Iss 19, p 9501 (2022)
This paper reports numerical studies of an Elasto-Hydrodynamic (EHD) seal, which is being developed for supercritical CO2 (sCO2) turbomachinery applications. Current sCO2 turbomachinery suffers from high leakage rates, which is creating a major roadb
Externí odkaz:
https://doaj.org/article/b9eb58cde4e4448387aacaec87b93960
Autor:
Karthik Reddy Lyathakula, Fuh-Gwo Yuan
Publikováno v:
AIAA Journal. 60:4874-4892
Publikováno v:
Artificial Intelligence in Geosciences. 2:171-178
Publikováno v:
ASME 2022 Power Conference.
This paper deals with numerical studies of a novel Elasto-Hydrodynamic Seal (EHD), which has been developed for supercritical CO2 (sCO2) turbomachinery applications. Current sCO2 turbomachinery suffer from high leakage rates, which is creating a majo
This work presents a framework to inversely quantify uncertainty in the model parameters of the friction model using earthquake data via the Bayesian inference. The forward model is the popular rate- and state- friction (RSF) model along with the spr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6848b916afe2eebe7557e02411b4d359
https://doi.org/10.31224/osf.io/9bf4m
https://doi.org/10.31224/osf.io/9bf4m
Autor:
Karthik Reddy Lyathakula, Fuh-Gwo Yuan
Publikováno v:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2021.
This paper demonstrates a diagnostic-prognostics framework to estimate probabilistic remaining useful life (RUL), in adhesively bonded joints subjected to fatigue loading, by calibrating the predictive model using the diagnostics data and quantifying
Autor:
Karthik Reddy Lyathakula, Fuh-Gwo Yuan
Publikováno v:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2021.
The paper is aimed at developing a probabilistic framework for fatigue life prediction in adhesively bonded joints by calibrating the predictive model, governing adhesive fatigue behavior, using the set of experimental data, and quantifying uncertain
Autor:
Fuh-Gwo Yuan, Karthik Reddy Lyathakula
Publikováno v:
International Journal of Fatigue. 151:106352
The paper is aimed at developing an efficient and robust probabilistic fatigue life prediction framework for adhesively bonded joints. This framework calibrates the fatigue life model by quantifying uncertainty in the fatigue damage evolution relatio
Autor:
Karthik Reddy Lyathakula, Fuh-Gwo Yuan
Publikováno v:
Structural Health Monitoring 2019.
Adhesively bonded joints are increasingly used in structural applications due to many advantages over classical mechanical fasteners. However, they are susceptible to fatigue damage due to the hostile working environment. It is essential to detect, q