Time-Dependent Fragility Functions for Circular Tunnels in Soft Soils

Huang, Zhong-Kai; Argyroudis, Sotirios; Zhang, Dongmei; Pitilakis, Kyriazis; Huang, Hongwei; Zhang, Dongming

doi:10.1061/ajrua6.0001251

Cited by 15 publications

(4 citation statements)

References 70 publications

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“…In the dynamic analysis of geotechnical engineering, the fixed boundary conditions commonly used in static analysis will cause a reflection of dynamic waves on the model boundary, and this phenomenon can be reduced by adopting a wider model range [37,38]. For this reason, a larger model size was used in this numerical simulation, with a length The process of FDM-DEM coupling is to follow the principle of virtual work of continuum element nodes and Newton's second law of discrete element particles in the iterative calculation process.…”

Section: The 3d Fdm-dem Coupling Numerical Modelmentioning

confidence: 99%

“…In the dynamic analysis of geotechnical engineering, the fixed boundary conditions commonly used in static analysis will cause a reflection of dynamic waves on the model boundary, and this phenomenon can be reduced by adopting a wider model range [37,38]. For this reason, a larger model size was used in this numerical simulation, with a length and width of 40 m and height of 21 m. Free field boundaries were set at the four sides and four corners of the model, and a quiet boundary was set at the bottom of the model, which could eliminate the reflection of dynamic waves at the model bottom and achieve an effect similar to an infinite range boundary.…”

Section: The 3d Fdm-dem Coupling Numerical Modelmentioning

confidence: 99%

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Study on the Reinforcement Mechanism of High-Energy-Level Dynamic Compaction Based on FDM–DEM Coupling

et al. 2023

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The high-energy-level dynamic compaction method is widely used in various foundation treatment projects, but its reinforcement mechanism still lags behind the practice. In view of this, a three-dimensional fluid–solid coupling dynamic analysis model was established on the basis of the FDM–DEM coupling method. The variation trends of crater depth, soil void ratio, vertical additional dynamic stress, and pore water pressure during the process of dynamic compaction were analyzed. The results indicate that the curvature of the crater depth fitting curve gradually decreases with the increase in strike times, tending to a stable value. The initial particle structure is altered by the huge dynamic stress induced by dynamic compaction. As strike times increase, the soil void ratio decreases gradually. The vertical additional dynamic stress is the fundamental reason resulting in foundation compaction. Precipitation preloading before dynamic compaction can improve the reinforcement effect of dynamic compaction, making up for the deficiency that the vertical additional dynamic stress attenuates rapidly along the depth direction. The simulated CPT results illustrate that the modulus of foundation soil can be increased by 3–5 times after dynamic compaction. The research results can provide important reference for similar projects.

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Section: The 3d Fdm-dem Coupling Numerical Modelmentioning

confidence: 99%

“…In the dynamic analysis of geotechnical engineering, the fixed boundary conditions commonly used in static analysis will cause a reflection of dynamic waves on the model boundary, and this phenomenon can be reduced by adopting a wider model range [37,38]. For this reason, a larger model size was used in this numerical simulation, with a length and width of 40 m and height of 21 m. Free field boundaries were set at the four sides and four corners of the model, and a quiet boundary was set at the bottom of the model, which could eliminate the reflection of dynamic waves at the model bottom and achieve an effect similar to an infinite range boundary.…”

Section: The 3d Fdm-dem Coupling Numerical Modelmentioning

confidence: 99%

Study on the Reinforcement Mechanism of High-Energy-Level Dynamic Compaction Based on FDM–DEM Coupling

et al. 2023

Self Cite

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“…Seismic fragility curves refect the conditional probability of a slope reaching or exceeding the predefned damage limit states for a given IM level. In addition, fragility curves can provide richer and comprehensive expression for seismic damages of slopes than only failure probability obtained by traditional reliability methods because they are described in the form of certain functions rather than points [16][17][18]. Te selection of an appropriate or optimal IM is one of the key prerequisites to reduce the uncertainty of the PSDM and obtain reliable fragility curves of slopes [19].…”

Section: Introductionmentioning

confidence: 99%

Optimal Intensity Measures for Probabilistic Seismic Stability Assessment of Large Open-Pit Mine Slopes under Different Mining Depths

Che

Chang

Wang

2023

Shock and Vibration

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The dynamic stability of slopes is the key to ensure the safety of a large open-pit mine during and after a strong earthquake. This study was mainly focused on the identification of optimal intensity measures (IMs) for the probabilistic seismic stability assessment of large open-pit mine slopes within the framework of performance-based earthquake engineering (PBEE). To this end, four open-pit slopes with different mining depths were constructed as the reference cases for the numerical investigation. The randomness of input ground motions and the uncertainty of material properties of the slopes were also considered. A total of 96 ground-motion records and 29 common IMs were selected for testing. By a series of nonlinear time-history analyses, the probabilistic seismic demand models (PSDMs) between the minimum factor of safety (FOS) of slopes and all considered IMs were developed. The optimal IMs with respect to FOS were identified based on the evaluation of five criteria: correlation, efficiency, practicality, proficiency, and sufficiency. The impacts on seismic fragility and FOS response hazard of the slopes were discussed when using different IMs. The results reveal that sustained maximum velocity (SMV) and velocity spectrum intensity (VSI) are recognized as the optimal IM for a mining depth of 50 m and 100 m, respectively. However, Housner intensity (HI) is observed to have the best predictability for both the mining depths of 200 m and 300 m. Moreover, for the three most commonly used IMs, peak ground velocity (PGV) is superior to peak ground acceleration (PGA) and spectral acceleration at first mode period (Sa (T1)) for different mining depths. Finally, based on the evaluations of seismic fragility and FOS response hazard, the uncertainty of seismic stability prediction of open-pit slopes can be greatly reduced when using a more appropriate or optimal IM.

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“…The natural geotechnical parameters exhibit significant randomness and fuzziness, rendering geotechnical engineering a highly complex and nonlinear system [1][2][3]. Consequently, the issue of parameter uncertainty has become a bottleneck in theoretical analysis and numerical simulation of geotechnical mechanics.…”

Section: Introductionmentioning

confidence: 99%

Study on Soil Parameter Evolution during Ultra-Large Caisson Sinking Based on Artificial Neural Network Back Analysis

Liang

Zhang

et al. 2023

Sustainability

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The determination of soil parameters in geotechnical engineering and their variations during the construction process have long been a focal point for engineering designers. While the artificial neural network (ANN) has been employed for back analysis of soil parameters, its application to caisson sinking processes remains limited. This study focuses on the Nanjing Longtan Yangtze River Bridge project, specifically the south anchoring of an ultra-large rectangular caisson. A comprehensive analysis of the sinking process was conducted using 400 finite element method (FEM) models to obtain the structural stress and earth pressure at key locations. Multiple combinations of soil parameters were considered, resulting in a diverse set of simulation results. These results were then utilized as training samples to develop a back-propagating artificial neural network (BP ANN), which utilized the structural stress and earth pressure as input sets and the soil parameters as output sets. The BP ANN was individually trained for each stage of the sinking process. Subsequently, the trained ANN was employed to predict the soil parameters under different working conditions based on actual monitoring data from engineering projects. The obtained soil parameter variations were further analyzed, leading to the following conclusions: (1) The soil parameters estimated by the ANN exhibited strong agreement with the original values from the geological survey report, validating their reliability; (2) The surrounding soil during the caisson sinking exhibited three distinct states: a stable state prior to the arrival of the cutting edges, a strengthened state upon the arrival of the cutting edges, and a disturbed state after the passage of the cutting edges; (3) In the stable state, the soil parameters closely resembled the original values, whereas in the strengthened state, the soil strength and stiffness significantly increased, while the Poisson’s ratio decreased. In the disturbed state, the soil strength and stiffness were slightly lower than the original values. This study represents a valuable exploration of back analysis for caisson engineering. The findings provide important insights for similar engineering design and construction projects.

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Time-Dependent Fragility Functions for Circular Tunnels in Soft Soils

Cited by 15 publications

References 70 publications

Study on the Reinforcement Mechanism of High-Energy-Level Dynamic Compaction Based on FDM–DEM Coupling

Study on the Reinforcement Mechanism of High-Energy-Level Dynamic Compaction Based on FDM–DEM Coupling

Optimal Intensity Measures for Probabilistic Seismic Stability Assessment of Large Open-Pit Mine Slopes under Different Mining Depths

Study on Soil Parameter Evolution during Ultra-Large Caisson Sinking Based on Artificial Neural Network Back Analysis

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