Field performance of a genetic algorithm in the settlement prediction of a thick soft clay deposit in the southern part of the Korean peninsula

Park, Hyun Il; Kim, Kyu-Sun; Kim, Ha Young

doi:10.1016/j.enggeo.2015.07.012

Cited by 19 publications

(13 citation statements)

References 19 publications

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“…For long-term settlement prediction, a Log S-T graph, the hyperbolic method, Asaoka method, Schmertmann theory, and a finite element method (FEM) analysis were performed. The hyperbolic and Asaoka method are variously applied models to predict the long-term settlement of soft ground [15], and Schmertmann (1978) theory is an empirical formula that provides high-level prediction of long-term settlement [16]. The Mohr-Coulomb model applied to the FEM analysis has been used by various researchers, including in the analysis of the settlement mechanism [14] and creep behavior [17] of DCM columns.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Settlement Prediction of Ground Reinforcement Foundation Using a Deep Cement Mixing Method in Reclaimed Land

Lee

Kim²,

Kang

et al. 2022

Buildings

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The greenhouse foundation method requires a lower allowable bearing capacity compared to general buildings, but the high-spec and expensive prestressed high-strength concrete (PHC) pile reinforcement method is mainly applied. Therefore, the deep cement mixing (DCM) method, which is one of the ground reinforcement foundations that replaces the PHC piles and secures structural safety suitable for the greenhouse foundation, was considered. To verify the structural safety of the DCM method, a geotechnical survey and soil test were conducted, and a long-term settlement monitoring system was established. The specifications of the DCM foundation were designed to be 0.8 m in diameter, 3 m × 3 m in width and length, and 3 m in depth. Based on the settlement monitoring data, long-term settlement was predicted considering the greenhouse durability of 15 years. For long-term settlement prediction, the Log S–T, hyperbolic, Asaoka method, Schmertmann theory, and the finite element method (FEM) analysis were performed. In the case of the Log S–T, hyperbolic, and Asaoka method based on actual measurement data, the settlement amount was predicted to be 12.18~20.43 mm, and in the case of the Schmertmann empirical formula, it was predicted to be 19.66 m. The FEM analysis result was 8.89 mm. As the most conservative result, the DCM foundation method designed in this paper had an allowable bearing capacity of 310 kN/m2 and a long-term settlement of 20.43 mm. This is the result of satisfying both the allowable bearing capacity of 100 kN/m2 and the allowable settlement range of 25.4 mm as a foundation. Through this study, it was proven that long-term structural safety can be sufficiently secured when the DCM foundation is constructed on a soft ground through a design that considers the required service life and allowable bearing capacity of the structure. In addition, it was confirmed that the Hyperbolic, Asaoka, and FEM analysis method adopted in this paper can be applied to the long-term settlement behavior analysis of the DCM foundation method.

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Section: Introductionmentioning

confidence: 99%

Long-Term Settlement Prediction of Ground Reinforcement Foundation Using a Deep Cement Mixing Method in Reclaimed Land

Lee

Kim²,

Kang

et al. 2022

Buildings

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“…The scientists also have combined pneumatic fracturing method [19], membranelles vacuum for compressible improvement [20], and compact vacuum consolidation. Beside the development of VCM tools, many scientists also had developed new methods or model analyses, which are numerical and finite analysis about soft soil settlement related to the implementation of VCM [22]- [28].…”

Section: Introductionmentioning

confidence: 99%

The Effectiveness of Vacuum Consolidation to Soft Soil Settlement

Puspita¹,

Capri²

2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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The main issue of building constructions on soft soils is not a uniform settlement of soft ground, which has a slow process that effected construction failures and rising maintenance expenses. For many decades, to the improvement of ground soil stability, then applied using prefabricated vertical drain (PVD). Along the development of science and technologies, which followed by improvement of the soil stability method, that is called as Vacuum Consolidation Method (VCM). The objectives of this study are to determine how the effectiveness of vacuum consolidation with various patterns to soft soil settlement of constructions, and to find the right spacing of PVD installation due to un-uniform settlement of soft soils. The analysis of this study compared the numbers and rates of settlements in preloading, PVD, and VCM with various patterns, and to get a uniform settlement by two scenarios analysis, which are various spacing with single suction pressure (scenario 1) and single spacing with various suction pressures. Based on the result of analysis which showed the settlement of VCM in both patterns are 2.247 m in 105 days (square pattern) and 2.252 m in 90 days (triangular pattern). It means with a triangular pattern has 70.2 more effective than others in the rate of the settlement period. It also showed the VCM has larger than others in volume settlements. The results of 2 scenarios analysis showed that the implementation of scenario one was difficult due to various spacing, while scenario two can be implemented because numbers of settlements depend on suction pressure of the vacuum.

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“…Generally, the geometric condition, boundary condition, or constitutive model of the above methods is inconsistent with the engineering practice, which will affect the accuracy of prediction results [5]. (2) The prognostic method is based on the monitoring data, which includes the Asaoka method [6], hyperbola method [7], three-point method [8], settlement difference method [9], genetic algorithm [10], neural network method [11], grey theory method [12], and so on. This kind of method has attracted the attention of many scholars and is widely used in engineering practice at home and abroad.…”

Section: Introductionmentioning

confidence: 99%

Research on the Grey Verhulst Model Based on Particle Swarm Optimization and Markov Chain to Predict the Settlement of High Fill Subgrade in Xiangli Expressway

Liu

Guo

Zhang

et al. 2019

Mathematical Problems in Engineering

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It is of vital significance to accurately forecast the settlement of high fill subgrade, which is the foundation for disaster prevention and treatment of subgrade. According to the monitoring data of high fill subgrade, a novel model, called PSOMGVM model, based on particle swarm optimization (PSO) and Markov chain is proposed. Firstly, the typical characteristics of settlement curve are analyzed from the aspect of geomechanics theory and based on the grey theory, the grey Verhulst model (GVM) with unequal time-interval is proposed. Then, according to the theory of Markov chain, the grey Verhulst model is built to revise the relative residuals of the GVM, in which the effects of volatility characteristics can be considered. Finally, the PSOMGVM model based on PSO algorithm and Markov chain is set up, which whitens the parameters of the grey interval. In order to demonstrate the fitness and the ability of the proposed model, five competing models are introduced to predict the settlement of the high fill subgrade of Xiangli Expressway in Yunnan Province. Through the analysis of APE, MAPE, and RMSE, it states that the accuracy and performance of the PSOMGVM model outperform the other five competing models for simulative and predictive periods.

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Field performance of a genetic algorithm in the settlement prediction of a thick soft clay deposit in the southern part of the Korean peninsula

Cited by 19 publications

References 19 publications

Long-Term Settlement Prediction of Ground Reinforcement Foundation Using a Deep Cement Mixing Method in Reclaimed Land

Long-Term Settlement Prediction of Ground Reinforcement Foundation Using a Deep Cement Mixing Method in Reclaimed Land

The Effectiveness of Vacuum Consolidation to Soft Soil Settlement

Research on the Grey Verhulst Model Based on Particle Swarm Optimization and Markov Chain to Predict the Settlement of High Fill Subgrade in Xiangli Expressway

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