A probabilistic fatigue life prediction for adhesively bonded joints via ANNs-based hybrid model

KR Lyathakula, FG Yuan - International Journal of Fatigue, 2021 - Elsevier
The paper is aimed at develo** an efficient and robust probabilistic fatigue life prediction
framework for adhesively bonded joints. This framework calibrates the fatigue life model by …

Fatigue damage diagnostics–prognostics framework for remaining life estimation in adhesive joints

K Reddy Lyathakula, FG Yuan - AIAA journal, 2022 - arc.aiaa.org
This work presents an integrated damage diagnostics–prognostics framework for remaining
useful life (RUL) estimation in the adhesively bonded joints under fatigue loading. A …

Assessment of risks in building inspection services during and post-COVID-19 pandemic

H Tekin - ASCE-ASME Journal of Risk and Uncertainty in …, 2022 - ascelibrary.org
The building industry has been deeply affected by the Covid-19 pandemic due to the
cessation of many businesses and the changes in working methods. Building inspection is …

[書籍][B] Probabilistic Fatigue Life Prediction and Damage Prognostics of Adhesively Bonded Joints via ANNs-Based Hybrid Model

KR Lyathakula - 2021 - search.proquest.com
Adhesively bonded joints have been widely accepted and increasingly used in major load-
carrying structural components due to many advantages over classical mechanical …

Continuous monitoring of COVID-19 pandemic trend for policy making: improvised application of Sen's innovative method

S Dauji - International Journal of Healthcare Technology …, 2023 - inderscienceonline.com
The study examines the efficacy of Sen's Innovative Trend Analysis for early identification of
the start of the rise in daily new SARS-COV2 cases and proposes simple improvisation for …

[PDF][PDF] A framework to quantify uncertainty in critical slip distance in rate and state friction model for earthquakes

S Dana, KR Lyathakula - 2021 - engrxiv.org
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 …