Fatigue reliability assessment in time domain using stochastic-induced random stress loads due to limited experimental data
Sign Up to like & getrecommendations! Published in 2020 at "Engineering Failure Analysis"
DOI: 10.1016/j.engfailanal.2020.104794
Abstract: Abstract This study aims to determine the fatigue reliability of an automotive crankshaft by stochastically inducing random loads because of limited experimental data. Given the difficulties in capturing actual load–time history data from laboratory or… read more here.
Keywords: time; limited experimental; experimental data; random ... See more keywords
Domain Adapted Deep-Learning for Improved Ultrasonic Crack Characterization Using Limited Experimental Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control"
DOI: 10.1109/tuffc.2022.3151397
Abstract: Deep learning is an effective method for ultrasonic crack characterization due to its high level of automation and accuracy. Simulating the training set has been shown to be an effective method of circumventing the lack… read more here.
Keywords: experimental data; ultrasonic crack; deep learning; crack characterization ... See more keywords