Search results for "crack growth rate"

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Evaluation of crack-closure by second harmonic thermoelastic stress analysis

2022

The work illustrates a new experimental approach to evaluate crack-closure in samples undergoing Fatigue Crack-Growing. Crack-closure leaves a peculiar signature on both amplitude and phase of the harmonic of the temperature signal at twice the loading frequency (Second Harmonic), due to the periodic nature of the internal elastic compression stresses. Thermoelastic Stress Analysis (TSA) is successfully applied to reveal such signatures on Single-Edge-Notched steel samples. A methodology is also proposed to evaluate the Crack-Opening-Load from temperature data. The work finally explores the influence of crack-closure on crack-tip identification and on the evaluation of the Stress Intensity …

Experimental stress analysisExperimental techniquesFatigue cracksMechanical EngineeringThermoelastic stress analysisIndustrial and Manufacturing EngineeringCrack growth ratesSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineMechanics of MaterialsCrack closureModeling and SimulationSecond harmonicsFatigue crack propagationGeneral Materials ScienceInternational Journal of Fatigue
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Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys

2022

Fatigue cracks are a major defect in metal alloys, and specifically, their study poses defect evaluation challenges in aluminum aircraft alloys. Existing inline inspection tools exhibit measurement uncertainties. The physical-based methods for crack growth prediction utilize stress analysis models and the crack growth model governed by Paris’ law. These models, when utilized for long-term crack growth prediction, yield sub-optimum solutions and pose several technical limitations to the prediction problems. The metaheuristic optimization algorithms in this study have been conducted in accordance with neural networks to accurately forecast the crack growth rates in aluminum alloys. Through ex…

VDP::Teknologi: 500crack growth rate; artificial intelligence; deep learning; aluminum aircraft alloys; fatigue crack growth predictionGeneral Materials ScienceMaterials
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