Nonmonotonic effect of chemical heterogeneity on interfacial crack growth at high-angle grain boundaries in Fe-Ni-Cr alloys

Wang, Yuchu; Ghaffari, Bita; Taylor, Christopher D.; Lekakh, Semen Naumovich; Engler-Pinto, Carlos; Godlewski, Larry; Huo, Yang; Li, Mei; Fan, Yanqin

doi:10.1103/physrevmaterials.7.073606

Cited by 5 publications

(1 citation statement)

References 51 publications

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“…Wang et al's study [66] highlights the significant role of chemical heterogeneity in the deformation behaviors of GBs when subjected to cyclic mechanical loading. Their primary focus was on understanding crack propagation in Fe-Ni-Cr alloy, a complex process highly sensitive to various influencing factors [67][68][69].…”

Section: Role Of Chemical Heterogeneity In Gbs' Deformation Behaviorsmentioning

confidence: 99%

Metastable grain boundaries: the roles of structural and chemical disorders in their energetics, non-equilibrium kinetic evolution, and mechanical behaviors

He,

Wang,

Fan

2024

J. Phys.: Condens. Matter

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Complex environments in advanced manufacturing usually involve ultrafast laser or ion irradiation which leads to rapid heating and cooling and drives grain boundaries (GBs) to non-equilibrium states, featuring distinct energetics and kinetic behaviors compared to conventional equilibrium or near-equilibrium GBs. In this topical review, we provide an overview of both recent experimental and computational studies on metastable GBs, i.e. their energetics, kinetic behaviors, and mechanical properties. In contrast to GBs at thermodynamic equilibrium, the inherent structure energy of metastable GBs exhibits a spectrum instead of single value for a particular misorientation, due to the existence of microstructural and chemical disorder. The potential energy landscape governs the energetic and kinetic behaviors of metastable GBs, including the ageing/rejuvenating mechanism and activation barrier distributions. The unique energetics and structural disorder of metastable GBs lead to unique mechanical properties and tunability of interface-rich nanocrystalline materials. We also discuss that, in addition to structural disorder, chemical complexity in multi-components alloys could also drive the GBs away from their ground states and, subsequently, significantly impact on the GBs-mediated deformation. And under some extreme conditions such as irradiation, structural disorders and chemical complexity may simultaneously present at interfaces, further enriching of metastability of GBs and their physical and mechanical behaviors. Finally, we discuss the machine learning techniques, which have been increasingly employed to predict and understand the complex behaviors of metastable GBs in recent years. We highlight the potential of data-driven approaches to revolutionize the study of disorder systems by efficiently extracting the relationship between structural features and material properties. We hope this topical review paper could shed light and stimulate the development of new GBs engineering strategies that allow more flexibility and tunability for the design of nano-structured materials.

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Section: Role Of Chemical Heterogeneity In Gbs' Deformation Behaviorsmentioning

confidence: 99%

Metastable grain boundaries: the roles of structural and chemical disorders in their energetics, non-equilibrium kinetic evolution, and mechanical behaviors

He,

Wang,

Fan

2024

J. Phys.: Condens. Matter

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Time series prediction model using LSTM-Transformer neural network for mine water inflow

Shi,

Wang,

et al. 2024

Sci Rep

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Mine flooding accidents have occurred frequently in recent years, and the predicting of mine water inflow is one of the most crucial flood warning indicators. Further, the mine water inflow is characterized by non-linearity and instability, making it difficult to predict. Accordingly, we propose a time series prediction model based on the fusion of the Transformer algorithm, which relies on selfattention, and the LSTM algorithm, which captures long-term dependencies. In this paper, Baotailong mine water inflow in Heilongjiang Province is used as sample data, and the sample data is divided into different ratios of the training set and test set in order to obtain optimal prediction results. In this study, we demonstrate that the LSTM-Transformer model exhibits the highest training accuracy when the ratio is 7:3. To improve the efficiency of search, the combination of random search and Bayesian optimization is used to determine the network model parameters and regularization parameters. Finally, in order to verify the accuracy of the LSTM-Transformer model, the LSTM-Transformer model is compared with LSTM, CNN, Transformer and CNN-LSTM models. The results prove that LSTM-Transformer has the highest prediction accuracy, and all the indicators of its model are well improved.

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Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM

Yao,

Nie,

2024

Sci Rep

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To accurately understand the deformation behavior of surrounding rock in the jiugongshan No.2 high ground stress tunnel and optimize construction parameters for improved efficiency, on-site monitoring was used to gather data on rock deformation and initial support contact pressure. A WOA-LSTM regression prediction model was proposed, and excavation advance depth was optimized using numerical simulation. The WOA-LSTM regression prediction model demonstrated high accuracy in tunnel deformation monitoring. The absolute errors between predicted and actual values of tunnel settlement and convergence at various measurement points average 2.53 − 04 mm and 1.96 − 04 mm, with relative errors averaging 2.15% and 2.34%. These results meet the requirements for guiding construction. Additionally, based on the results of numerical simulation calculations, when the step length is 12 m during the construction of high-stress tunnels using the benching method, excavation advances of 2 m and 3 m result in settlement and convergence increases of 35.1% and 63.4%, and 25.5% and 55.2%, respectively, compared to an excavation advance of 1 m. However, no sudden jumps in these values were observed, indicating that with a 3 m excavation advance, the integrity of the surrounding rock remains in good condition, effectively guiding safe and rapid construction methods.

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Nonmonotonic effect of chemical heterogeneity on interfacial crack growth at high-angle grain boundaries in Fe-Ni-Cr alloys

Cited by 5 publications

References 51 publications

Metastable grain boundaries: the roles of structural and chemical disorders in their energetics, non-equilibrium kinetic evolution, and mechanical behaviors

Metastable grain boundaries: the roles of structural and chemical disorders in their energetics, non-equilibrium kinetic evolution, and mechanical behaviors

Time series prediction model using LSTM-Transformer neural network for mine water inflow

Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM

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