Evaluation of liquefaction probability of earth-fill dam over next 50 years using geostatistical method based on CPT

Imaide, Kazunari; Nishimura, Shin Ichi; Shibata, Toshinobu; Shuku, Takayuki; Murakami, Akira; Fujisawa, Kazunori

doi:10.1016/j.sandf.2019.08.002

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Accurately evaluating the soil liquefaction potential is the first step toward mitigating soil liquefaction hazards. Soil liquefaction risk maps have been prepared by many autonomous bodies in Japan to assess the impact of soil liquefaction in each target area [41][42][43][44]. These maps are essential tools in the development of smart cities, where resilient urban planning and infrastructure are paramount.…”

Section: Comparison Of Self-created and Existing Soil Liquefaction Ri...mentioning

confidence: 99%

AI-Driven Prediction and Mapping of Soil Liquefaction Risks for Enhancing Earthquake Resilience in Smart Cities

Katsuumi,

Cong,

Inazumi

2024

Preprint

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In response to increasing urbanization and the need for infrastructure resilient to natural hazards, this study introduces an AI-driven predictive model designed to assess the risk of soil liquefaction. Utilizing advanced ensemble machine learning techniques, the model integrates geotechnical and geographical data to accurately predict the potential for soil liquefaction in urban areas, with a specific focus on Yokohama, Japan. This methodology leverages comprehensive datasets from geological surveys and seismic activity to enhance urban planning and infrastructure development in smart cities. The primary outputs include detailed soil liquefaction risk maps that are essential for effective urban risk management. These maps support urban planners and engineers in making informed decisions, prioritizing safety, and promoting sustainability. The model employs a robust combination of neural networks and gradient boosting decision trees to analyze and predict data points, assessing soil susceptibility to liquefaction during seismic events. Notably, the model achieves high accuracy in predicting soil classifications and N-values, which are critical for evaluating soil liquefaction risk. Validation against an extensive dataset from geotechnical surveys confirms the model’s practical effectiveness. Moreover, the results highlight the transformative potential of AI in enhancing geotechnical risk assessments and improving the resilience of urban areas against natural hazards.

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Section: Comparison Of Self-created and Existing Soil Liquefaction Ri...mentioning

confidence: 99%

AI-Driven Prediction and Mapping of Soil Liquefaction Risks for Enhancing Earthquake Resilience in Smart Cities

Katsuumi,

Cong,

Inazumi

2024

Preprint

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“…Moreover, liquefaction may occur in loose sandy soils, resulting in decreased soil shear strength as a result of seismic loads during an earthquake [8,10]. Under some conditions, the soil loses the majority of its shear strength as a result of the loss of effective stress and consequently acts like a dense liquid [11,12]. The changing behavior of that soil mass may affect the structure's stability [13].…”

Section: Introductionmentioning

confidence: 99%

“…The outcomes of the site investigation indicate that the soil deposit is comprised primarily of sand from the ground surface to a depth of 30,00 meters, has low to moderate N-SPT values (15), and a high elevation of the groundwater level (-5.00 to -9.00 m), which may indicate liquefaction potential. Imaide et al [11] proposed a novel approach for calculating the probability of liquefaction using CPTs. The regional spread of the liquefaction probability within the examined dam was computed in detail using CPTs, taking into account conversion inaccuracies and the spatial heterogeneity of soil properties.…”

Section: Introductionmentioning

confidence: 99%

Sumatra-fault Earthquake Source Variation for Analysis of Liquefaction in Aceh, Northern Indonesia

Munirwansyah,

Munirwan,

Listia

et al. 2023

TOCIEJ

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Introduction: Areas that are situated on active faults experience a severe risk of earthquakes. During earthquake shocks, pore water pressure increases and soil shear strength decreases, resulting in water saturation of the loose sand layer and the possibility of liquefaction. Banda Aceh is a city on Sumatra Island, northern Indonesia, located on active faults that run along Sumatra Island. Aims: To ascertain the liquefaction potential in Banda Aceh City, it is important to conduct a research analysis on the soil profile below Banda Aceh City. This research focused on earthquake acceleration to determine the strength capacity of soil to withstand loads and wave propagation to minimize infrastructure failure. Methods: The liquefaction potential of Banda Aceh was determined by analyzing N-SPT records from three sites using three different approaches. This liquefaction study considered the cyclic loading and seismic acceleration associated with the Sumatra-fault earthquake source, which has a design magnitude of Mw 9.3. Results: The results of cyclic loading showed that Banda Aceh City has liquefaction potential. Using the 3D surface approach, soil profiling gives a cross-vault-shaped soil profile that shows liquefaction potential starting at 2.5 m and the hard soil layer found at 6.0 to 10 m. Conclusion: This study examined the liquefaction potential of Banda Aceh City. The research was carried out using a simplified approach to determine the liquefaction potential index (LPI) at three-dimensional cross faults of discontinuous sand generated by the Sumatra-fault acceleration of earthquake.

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A review of time-dependent reliability analyses of slopes: Research progress, influencing factors, and future research directions

Xiong

Huang²

2022

Transportation Geotechnics

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Evaluation of liquefaction probability of earth-fill dam over next 50 years using geostatistical method based on CPT

Cited by 6 publications

References 22 publications

AI-Driven Prediction and Mapping of Soil Liquefaction Risks for Enhancing Earthquake Resilience in Smart Cities

AI-Driven Prediction and Mapping of Soil Liquefaction Risks for Enhancing Earthquake Resilience in Smart Cities

Sumatra-fault Earthquake Source Variation for Analysis of Liquefaction in Aceh, Northern Indonesia

A review of time-dependent reliability analyses of slopes: Research progress, influencing factors, and future research directions

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