Application of artificial neural network for determining elastic constants of a transversely isotropic rock from a single-orientation core

Lee, Yoonsung; Yim, Juhyi; Hong, Seong Wook; Min, Ki‐Bok

doi:10.1016/j.ijrmms.2022.105277

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…ANN model had shown great advantages in dealing with nonlinear relationships. Yoonsung Lee [13] used ANN instead of the strain inversion method to determine the five elastic constants of rocks. The proposed ANN model can be trained extensively by numerical simulation results, which can significantly reduce the computational time required for strain response.…”

Section: Introductionmentioning

confidence: 99%

The study predicts and validates the overburden load and stability behaviors of top slab structures Based on hybrid intelligent modeling

Chen,

Liu

2024

Preprint

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It is important to determine the exact value of the overburden load on the tunnel roof to assess the stability of the roof, ho wever, th is parameter is poorly constrained. Based on this, we use the hybrid intelligence approach to deal with the nonlinear relationship between multiple parameters and the overlying load. Firstly, a multi parameter correlation visualization analysis is performed to determine two hidden layers (E 1 , E 2 ), and four parameters with the most influence on the overlying load were selected, which will be used as sample input parameters. Secondly, the top plate stability prediction is achieved by converting the input and output to a single thermal code, and then adding parameter thresholds that were continuously adjusted with training . This completes the structure of ANN IHHO model . Finally, the model is trained based on data driven by displacement inverse analysis and numerical experiments. The model prediction accuracy was then validated using a confusion matrix form . The validation results show that the trained ANN IHHO model has good accuracy and can predict the top plate stability under the condition of considering four parameters The proposed model provides a new way of thinking to determine the overburden load and stability of the top plate . This study proposes many new research ideas in the process of developing the model : First, the m ulti parameter correlation visualization analysis can be used in studies to assess the degree of correlation between parameters and results, also between parameters and parameters And most importantly, the visualization analysis can intuitively display the correlation degree . the introduction of displacement inverse analysis as a data acquisition method into the ANN model has proven to be feasible, and the method has the advantage of being low cost and easy to implement ; Third, the c onfusion matrix also shows good adaptability in verifying model prediction accuracy, especially for prediction models of rock stability The method proposed in this study to develop the model is also adapted to the prediction of other rock mechanical parameters.

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Section: Introductionmentioning

confidence: 99%

The study predicts and validates the overburden load and stability behaviors of top slab structures Based on hybrid intelligent modeling

Chen,

Liu

2024

Preprint

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“…Yim et al [17] proposed an iterative procedure to determine the five elastic constants by conducting uniaxial compression and Brazilian tests using specimens from a single-orientation core. More recently, strip load tests on single cylindrical test specimens with arbitrary isotropy plane inclinations have been used to determine the full set of transversely isotropic constants without the need to assume approximate relationships between individual parameters or to use special test apparatuses [18,19]. While the strip load test method thus overcomes the limitations of previous methods for determining the transversely isotropic constants on single-core samples, its practicality may still be limited by the computationally expensive strain inversion method involved [18] or the lack of availability of a trained artificial neural network (ANN) [19].…”

Section: Introductionmentioning

confidence: 99%

“…More recently, strip load tests on single cylindrical test specimens with arbitrary isotropy plane inclinations have been used to determine the full set of transversely isotropic constants without the need to assume approximate relationships between individual parameters or to use special test apparatuses [18,19]. While the strip load test method thus overcomes the limitations of previous methods for determining the transversely isotropic constants on single-core samples, its practicality may still be limited by the computationally expensive strain inversion method involved [18] or the lack of availability of a trained artificial neural network (ANN) [19]. Despite ongoing developments with regard to calibration methods to derive transversely isotropic constants from tests on single samples, the most frequently used method remains the one involving measurement results from compression tests performed on multiple samples with different core angles [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Elastic Behavior of Transversely Isotropic Cylindrical Rock Samples under Uniaxial Compression Considering Ideal and Frictional Boundary Conditions

Winkler,

Frühwirt,

Marcher

2023

Applied Sciences

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Conceptualizing sophisticated measurement set-ups as well as testing and evaluation procedures for laboratory experiments on anisotropic rocks requires a basic understanding of the potential specimen behavior. The focus of the present work was therefore to investigate the influence of different transversely isotropic parameters and their ratios on the elastic behavior of cylindrical rock samples in uniaxial compression tests. Parameter sets corresponding to soft anisotropic rocks were chosen based on naturally observed ranges for the five elastic transversely isotropic constants. Analytical results for the radial and vertical strain distributions around the sample circumference and a comparison with finite element simulations are presented. Further, the effect of interface friction between samples and loading platens was analyzed within the numerical models. The results suggest that radial strains around cylindrical anisotropic samples are rarely uniform except for specific combinations of parameters and isotropy plane inclinations. The effect of interface friction was found to have a clear influence on the developing elastic stress and strain distributions for samples with inclined isotropy planes. Nevertheless, no significant influence of frictional boundary conditions on the back-calibrated values of the elastic parameters could be identified, suggesting that friction-reducing measures in uniaxial compression tests on transversely isotropic samples with predominantly linear behavior are not required.

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Dynamical bifurcations in a delayed fractional‐order neural network involving neutral terms

Huang,

Fu,

Liu

et al. 2024

Math Methods in App Sciences

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The stability and bifurcations of a fractional‐order neural network with a neutral delay are nicely contemplated with the help of the Cramer's rule. The three‐neuron neutral‐type fractional‐order neural network (NTFONN) is firstly constructed. Secondly, the Laplace transform of the Caputo fractional‐order derivatives is used. Afterward, using the analytical method of characteristic equations and Cramer's rule, the existence of Hopf bifurcations is obtained. Moreover, it indicates that the neutral delay plays an enormously significant role in remaining network stabilization and controlling the occurrence of Hopf bifurcations in NTFONN. It further detects that the devised NTFONN has outstanding stability performance in comparison with the corresponding integer‐order one. Finally, numerical simulations are developed to confirm the feasibility and validity of the obtained results.

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Application of artificial neural network for determining elastic constants of a transversely isotropic rock from a single-orientation core

Cited by 6 publications

References 19 publications

The study predicts and validates the overburden load and stability behaviors of top slab structures Based on hybrid intelligent modeling

The study predicts and validates the overburden load and stability behaviors of top slab structures Based on hybrid intelligent modeling

Elastic Behavior of Transversely Isotropic Cylindrical Rock Samples under Uniaxial Compression Considering Ideal and Frictional Boundary Conditions

Dynamical bifurcations in a delayed fractional‐order neural network involving neutral terms

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