Study on instability and damage of a loess slope under strong ground motion by numerical simulation

Chang, Chaoyu; Bo, Jingshan; Qi, Wenhao; Qiao, Feng; Peng, Da

doi:10.1016/j.soildyn.2021.107050

Cited by 20 publications

(5 citation statements)

References 13 publications

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“…For the features of the samples, the corresponding y is obtained through the above equation. When SVR is used for nonlinear regression, there will be other constraints in Equation (1). Therefore, the slack variable ζ i needs to be introduced to relax the constraints and transform the optimal hyperplane problem.…”

Section: Support Vector Machine (Svm)mentioning

confidence: 99%

“…With the development of urbanization in the Loess Plateau region, the high side slopes caused by deep excavation and high fill are frequently encountered in highways, bridges, and architectural engineering. The failure of high slopes in the deep excavation or high fill during construction is becoming more and more prominent [1][2][3]. The high slope threatens the safety of buildings/structures, constructors, and surrounding villages.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Time Series Model for Predicting the Displacement of High Slope in the Loess Plateau Region

Liu

2023

Sustainability

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The physical and mechanical properties of the loess differ from other kinds of soil due to its collapsibility, which has resulted in the complex displacement development law of the loess slope. Therefore, the accurate estimation of the displacement of high slopes in a loess gully region is critical for the safety of people and in construction activities. In the present study, to improve the accuracy of traditional methods, the original cumulative displacement curve was decomposed into trend and fluctuation terms using Empirical Mode Decomposition (EMD) and Wavelet Decomposition (WD). Subsequently, the results were estimated using the Support Vector Machine (SVR) and Long Short-Term Memory Network (LSTM) optimized by Biogeography-based Optimization (BBO), respectively. To select the most appropriate model, SVR, LSTM, EMD-SVR-LSTM, EMD-BBO-SVR-LSTM, and WD-BBO-SVR-LSTM were employed to predict the deformation of a loess slope in the Loess Plateau of China. According to the results, the displacement increases rapidly at the starting stage, and then gradually stabilizes, which is the same as the trend in reality. On comparing the predicted results with field data, it was found that the models with decomposition algorithms achieved higher accuracy. Particularly, the determination coefficient of the EMD-BBO-SVR-LSTM model reaches 0.928, which has better algorithm stability and prediction accuracy than other models. In this study, the decomposition algorithm was applied to the loess slope displacement innovatively, and the appropriate machine learning algorithm adopted for the displacement components. The method improves the accuracy of prediction and provides a new idea for instability warning of loess excavation slopes. The research has implications for urban construction and sustainable development in loess mountainous areas.

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Section: Support Vector Machine (Svm)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Hybrid Time Series Model for Predicting the Displacement of High Slope in the Loess Plateau Region

Liu

2023

Sustainability

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“…Three boreholes were arranged along the main sliding direction on the sliding mass, with a depth of 2 m below the underlying mudstone layer. The layout and field records of the boreholes can be found in the literature [27].…”

Section: Samplingmentioning

confidence: 99%

“…For example, using the Hilbert-Huang transform (HHT) to transform nonlinear and nonstationary seismic records into Hilbert spectra, the instantaneous frequency energy of the loess layer and mudstone layer of the Buzi landslide were compared in terms of time-frequency-energy, and the landslide failure process was studied from an energy perspective [26]. Based on the discrete element theory, landslide models were established using the particle flow code (PFC), and the dynamic responses and motion characteristics of landslides were studied by simulating the motion and interaction between particles under seismic conditions [27,28].…”

Section: Introductionmentioning

confidence: 99%

Influence of Loess–Mudstone Strata Structure on Slope Seismic Stability of Loess Plateau in China

Zhang,

Qi,

Zhao

et al. 2023

Applied Sciences

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The widely distributed loess–mudstone strata structure in the Loess Plateau of China is one of the fundamental reasons for the susceptibility and group occurrence of seismic landslides in the area. This study took the loess landslides induced by the Haiyuan earthquake as a case study. Through extensive field investigations, the loess cover thickness, mudstone dip angle, slope height, and slope angle were chosen as the influencing factors. Together with mathematical statistics and geotechnical tests, two models, one of a loess–mudstone slope and the other of a pure loess slope, were constructed. Their seismic stabilities under different slope angles and slope heights were compared to analyze the influence of the underlying mudstone strata on the loess slope seismic stability. Meanwhile, a sensitivity analysis of these strata factors affecting the seismic stability of the loess–mudstone slope was carried out based on the orthogonal test. The results showed that ignoring the underlying mudstone strata would lead to smaller calculation results than the actual situation. The sensitivity influence of the factors on the loess–mudstone slope seismic stability comprised the slope angle, loess cover thickness, slope height, and mudstone dip angle from high to low.

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“…Zhang researched the settling patterns inside dust removal pipelines and their effects on subsequent operations using Fluent 2022R1 software [17]. Chang studied the deformation and failure process of loess slopes under seismic action using PFC 5.0 [18]. Both physical modeling and numerical simulations play a crucial role in the research conducted by geoscientists.…”

Section: Introductionmentioning

confidence: 99%

The Mechanism of Dust Transportation Based on Wind Tunnel Experiments and Numerical Simulations

Yang,

Li,

Wang

et al. 2024

Water

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The process of dust transportation is widespread, leading to the formation of regions such as the Loess Plateau. In order to understand the mechanisms of dust particle transportation, this study conducted wind tunnel experiments to simulate natural wind-driven dust transport processes. Theoretical derivations were carried out to establish the relationship between particle size and transportation distance, which was then validated through numerical simulations. The following conclusions were drawn: (1) wind tunnel experiments, theoretical derivations, and numerical simulations yielded consistent results, indicating the effectiveness of the wind tunnel experiments; (2) Under the influence of wind forces, the ideal transportation distance of particles is inversely proportional to the square of their size; (3) turbulent wind fields have a minor impact on dust transport, while particle roundness has a significant effect on transport; (4) clay particles and dust particles in loess regions share the same source areas and transport pathways.

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Study on instability and damage of a loess slope under strong ground motion by numerical simulation

Cited by 20 publications

References 13 publications

A Hybrid Time Series Model for Predicting the Displacement of High Slope in the Loess Plateau Region

A Hybrid Time Series Model for Predicting the Displacement of High Slope in the Loess Plateau Region

Influence of Loess–Mudstone Strata Structure on Slope Seismic Stability of Loess Plateau in China

The Mechanism of Dust Transportation Based on Wind Tunnel Experiments and Numerical Simulations

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