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The determination of the interaction factor of adjacent loads under variable amplitude loading is difficult. In this paper, two new nonlinear accumulation damage models are proposed based on the material damage state. Besides considering loading sequence, load interference, and mean stress effect, the proposed models consider the effect of material damage state and then modify the key parameter δ by introducing the load cycle ratio and the amount of material memory degradation in order to express the damage state. Verifying by different materials' test data and comparing with the existing models shows the proposed models good predictive ability and reliability. Further, in this method, there are no new variables introduced, no complex nested calculations, and only one conventional parameter that is easy to obtain by experimental fitting. Furthermore, the proposed models are convenient for fatigue life prediction in practical engineering problems. [ABSTRACT FROM AUTHOR]

New nonlinear fatigue damage accumulation model is established on the basis of material memory theory and fatigue driving energy damage parameters to evaluate high-cycle fatigue life under multilevel variable amplitude loading. The loading interaction factor is constructed on the basis of damage degree and then the model is modified to consider the effect of loading interaction on fatigue damage accumulation. The two proposed models are convenient for calculation and have only two parameters that can be easily identified through experiments. In accordance with the test data of aluminum alloy Al-2024-T42, titanium alloy Ti-6Al-4V, nodular cast iron GS61, Q235B welded joint, and hot-rolled 16Mn steel, the two models developed in this study have been verified to predict fatigue life effectively. For multilevel loading, the modified model achieves higher prediction accuracy and its results are closer to the actual test data compared with those of the other models. [ABSTRACT FROM AUTHOR]

AbstractConsidering the differences between individuals, in this paper, an uncertainty analysis model for predicting rupture risk of atherosclerotic arteries is established based on a back-propagation artificial neural network. The influence of isotropy and anisotropy on the rupture risk of atherosclerotic arteries is analyzed, and the results demonstrate the effectiveness of the artificial neural network in predicting the rupture risk. Moreover, the rupture risk of atherosclerotic arteries at different inflation sizes are simulated. This study contributes to a better understanding of the underlying mechanisms of atherosclerotic arteries rupture and promotes the advancement of artificial neural networks in atherosclerosis research. [ABSTRACT FROM AUTHOR]

Soft biological tissues, such as arterial tissue, have the ability to grow and remodel in response to damage. Computational method plays a critical role in understanding the underlying mechanisms of tissue damage and healing. However, the existing healing model often requires huge computation time and it is inconvenient to implement finite element simulation. In this paper, we propose a computationally efficient gradient-enhanced healing model that combines the advantages of the gradient-enhanced damage model, the homeostatic-driven turnover remodeling model, and the damage-induced growth model. In the proposed model, the evolution of healing-related parameters can be solved explicitly. Additionally, an adaptive time increment method is used to further reduce computation time. The proposed model can be easily implemented in Abaqus, requiring only a user subroutine UMAT. The effectiveness of proposed model is verified through a semi-analytical example, and the influence of the variables in the proposed model is investigated using uniaxial tension and open-hole plate tests. Finally, the long-term development of aneurysms is simulated to demonstrate the potential applications of the proposed model in real biomechanical problems. [ABSTRACT FROM AUTHOR]

Abstract: A general numerical model was presented to analyze the interval inverse hyperbolic heat conduction problem, with Bregman distances and weighted Bregman distances as regularization terms. By using the interval finite element method and interval extension theory, the direct and inverse models were established for uncertainties. The eight-point isoparametric elements were applied for the discretization in the space domain, and the Precise algorithm in time domain was empolyed. The inverse problems were implicitly formulated as optimization problems, using squared residues between the calculated and measured quantities as the objective function of the inverse identification. Results show that the proposed numerical models can identify single and combined interval thermal parameters and boundary conditions for hyperbolic heat transfer problems accurately and efficiently. [Copyright &y& Elsevier]

• The modified Corten-Dolan model excellently captures the load interaction effect. • Generalized expression of the new model gives a unified theoretical formulation. • The new-introduced validation scheme comprehensively investigates applicability. • The new model has much better prediction ability than the existing models. Corten-Dolan nonlinear damage accumulation model can well describe the fatigue behavior of engineering materials and structures under variable amplitude loads, while the determination of parameter d is difficult and still open. In this paper, a new improved version of Corten-Dolan model is proposed in which the parameter d is modified by introducing the power form of the stress ratio between two consecutive load levels to reflect the nonlinear effect of load interaction. Furthermore, a generalized expression of the new model is developed, which gives a unified theoretical formulation for the presented and some typical existing versions. The proposed model is validated by comparison with existing versions based on the experimental data of typical engineering materials under two-level and multilevel loads. An effective validation scheme is introduced to comprehensively investigate the validity and applicability of the developed model. In this scheme, parts of data those are not used in modeling are regarded as the check data to examine the prediction accuracy. The results show that the developed model can well reflect load interaction effect and give more satisfactory prediction of fatigue life. [ABSTRACT FROM AUTHOR]