Analytical Approach for Inverse Reconstruction of Eigenstrains and Residual Stresses in Autofrettaged Spherical Pressure Vessels

Faghidian, S. Ali

doi:10.1115/1.4035980

Cited by 32 publications

(6 citation statements)

References 27 publications

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“…Also, it is noted that there are reliable alternative solution techniques in the scientific literature for the solution of structural problems, which are assumed to have the series solution form of the primary (kinematic) or secondary (kinetic) field variables. 51–57…”

Section: Transverse Free Vibration Of Short-fiber Reinforced Composit...mentioning

confidence: 99%

Dynamic analysis of short-fiber reinforced composite nanobeams based on nonlocal strain gradient theory

Gul

2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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This study deals with the dynamic behavior of short-fiber reinforced composite nanobeams. It is assumed that short-fibers are aligned or randomly distributed in the composite nanobeams. Nonlocal strain gradient theory is applied to composite nanobeam mechanics including Euler–Bernoulli and Timoshenko beam models. The transverse vibration of these composite nanobeams is investigated for various boundary conditions. Approximate Ritz method is used for obtaining the natural frequencies of short-fiber reinforced composite nanobeams. In addition to vibration analysis, wave propagation in short-fiber reinforced composite nanobeams is investigated and wave dispersion relations are analytically obtained for both Euler-Bernoulli and Timoshenko beam models. The vibration and wave dispersion results of short-fiber reinforced composite nanobeams are obtained for aligned and randomly distributed cases. The results obtained from this paper showed that there is no significant difference between the aligned and randomly oriented short-fiber composite nanobeams. This provides great convenience to designers where it is not possible to orient the reinforcement material in composites. The present study may be useful for the mechanical analysis and design of micro/nano-electromechanical systems (MEMS/NEMS), nanoprobes, nanosensors, nanoactuators, and atomic force microscopes.

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Section: Transverse Free Vibration Of Short-fiber Reinforced Composit...mentioning

confidence: 99%

Dynamic analysis of short-fiber reinforced composite nanobeams based on nonlocal strain gradient theory

Gul

2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…The size-dependent physical characteristics of nano-structures can be effectively realized by the analysis of the wave dispersion. Examination of dispersive waves can be, furthermore, exploited for inverse determination of the gradient characteristic parameters applying the inverse theory approach [56,57].…”

Section: Wave Dispersion Characteristicsmentioning

confidence: 99%

Dynamic Characteristics of Mixture Unified Gradient Elastic Nanobeams

Faghidian

Tounsi

2022

FU Mech Eng

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The mixture unified gradient theory of elasticity is invoked for the rigorous analysis of the dynamic characteristics of elastic nanobeams. A consistent variational framework is established and the boundary-value problem of dynamic equilibrium enriched with proper form of the extra non-standard boundary conditions is detected. As a well-established privilege of the stationary variational theorems, the constitutive laws of the resultant fields cast as differential relations. The wave dispersion response of elastic nano-sized beams is analytically addressed and the closed form solution of the phase velocity is determined. The free vibrations of the mixture unified gradient elastic beam is, furthermore, analytically studied. The dynamic characteristics of elastic nanobeams is numerically evaluated, graphically illustrated, and commented upon. The efficacy of the established augmented elasticity theory in realizing the softening and stiffening responses of nano-sized beams is evinced. New numerical benchmark is detected for dynamic analysis of elastic nanobeams. The established mixture unified gradient elasticity model provides a practical approach to tackle dynamics of nano-structures in pioneering MEMS/NEMS.

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“…Fatigue loading and the resulting crack propagation are significant issues in the industry (1,2). Researchers have attempted to increase the fatigue lifetime of industrial equipment and materials by employing various methods, including geometry-related technologies such as autofrettage (3), and manufacturing procedures such as welding (4). As a result, numerous researchers have attempted to improve the fatigue behavior of materials, geometries and estimate their fatigue lifetime.…”

Section: Introductionmentioning

confidence: 99%

Effect of Training Data Ratio and Normalizing on Fatigue Lifetime Prediction of Aluminum Alloys with Machine Learning

Matin,

Azadi

2024

IJE

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It is critical to evaluate the estimation of the fatigue lifetimes for the piston aluminum alloys, particularly in the automotive industry. This paper investigates the effect of different normalization methods on the performance of the fatigue lifetime estimation using Extreme Gradient Boosting (XGBoost), as a supervised machine learning method. For this purpose, the dataset used in this study includes various physical and experimental inputs related to an aluminum alloy and the corresponding fatigue lifetime outputs. Furthermore, before fitting the XGBoost model, different fatigue lifetime preprocessing methods were utilized and evaluated using metrics such as Root Mean Square Error (RMSE), Determination Coefficient (R 2 ), and Scatter Band (SB). The results indicate that modeling fatigue lifetime with logarithmic values as a preprocessing method excels when XGBoost is trained with 100% of the data. However, other normalization methods demonstrate superior accuracy in estimating test data with a 20% test and 80% train set split.

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Analytical Approach for Inverse Reconstruction of Eigenstrains and Residual Stresses in Autofrettaged Spherical Pressure Vessels

Cited by 32 publications

References 27 publications

Dynamic analysis of short-fiber reinforced composite nanobeams based on nonlocal strain gradient theory

Dynamic analysis of short-fiber reinforced composite nanobeams based on nonlocal strain gradient theory

Dynamic Characteristics of Mixture Unified Gradient Elastic Nanobeams

Effect of Training Data Ratio and Normalizing on Fatigue Lifetime Prediction of Aluminum Alloys with Machine Learning

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