A Prediction Method for Long-Term Settlement of Higly Organic Soft Soil

Kamao, Shoji

doi:10.21660/2019.60.8169

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Based on existing research, the current methods for predicting ground settlement mainly include purely theoretical calculation methods based on soil consolidation principles [17][18][19], various curvefitting methods based on measured settlement data commonly used in engineering [20][21], and emerging dynamic prediction methods represented by artificial neural network analysis [22][23][24]. In the process of settlement prediction, purely theoretical calculation methods based on ground consolidation settlement principles are overly complex and involve numerous parameters, making them less convenient to use.…”

Section: Introductionmentioning

confidence: 99%

Prediction of dredged soil settlement based on improved BP neural network

Li,

Liu

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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Based on the measured settlement data from the Reclamation Project of Eastern Hengsha Shoal, two improved BP neural networks optimized by the particle swarm optimization (PSO) algorithm and genetic algorithm (GA) respectively are employed to predict the long-term consolidation settlement of the dredged soil in the reclamation area. By comparing the prediction results of the improved neural networks with those obtained from standard BP neural network and various curve fitting methods including hyperbola method, Hoshino method, and Asaoka method, as well as field-measured data, the improved neural network methods are validated to have a better predictive performance. The error analysis results indicate that compared with the standard BP neural network and curve-fitting prediction methods, the improved BP neural networks exhibit smaller prediction errors in terms of MAE, MSE, RMSE, MAPE, etc., and have a closer match between the predicted settlement values and the actual values. The selected GA-BP and PSO-BP neural network prediction methods in this study demonstrate higher prediction accuracy. Meanwhile, GA-BP demonstrates higher prediction accuracy and generalization ability than PSO-BP, but PSO-BP shows faster convergence in terms of prediction speed. The preferred methods presented in this paper exhibit good robustness and high reliability, which can achieve accurate prediction of dredged soil settlement. Additionally, unlike the traditional curve-fitting methods, the selected methods can effectively reduce the influence of subjective factors during the settlement prediction, and provide a new approach for settlement prediction, which can be effectively utilized as a substitute for long-term settlement monitoring and give reference for the design of settlement control of foundation of further construction projects.

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Section: Introductionmentioning

confidence: 99%

Prediction of dredged soil settlement based on improved BP neural network

Li,

Liu

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Zhou and Shoji analyzed the change in settlement of the soft foundation of an expressway under surcharge unloading and reloading. It was observed that the settlement occurred mostly during the period of filling and surcharge preloading, and the rate of settlement decreased during reloading after surcharge unloading, but it was not accomplished quickly after the reloading period [5,6]. Yang and LI presented a settlement rate method for determining surcharge removal time for an embankment on soft ground.…”

Section: Introductionmentioning

confidence: 99%

Controlling the Settlement of the Low Embankment on Soft Ground by Surcharge Preloading Method

Nguyen¹

2023

GEOMATE

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Preloading with surcharge is the most common technique of ground improvement used in highway engineering. At the end of the preloading period, the surcharge load is removed, and most or all of the primary settlement and some of the secondary settlement would have occurred. The soil beneath the embankment becomes over-consolidated, resulting in the elimination or a huge reduction in post-construction settlement. When pre-compression is applied to a relatively free-draining material, consolidation times are short, and therefore primary settlements can be effectively controlled by using a preload equal to the final load over a limited period of time. The subsequent movements associated with unloading/reloading will be small and will occur rapidly. In these cases, the main source of long-term displacements is likely to be secondary compression settlements. In this paper, a laboratory investigation of one-dimensional consolidation of clayey soils was carried out and a formula has been proposed to compute the postconstruction settlement of low embankment. The results show that the settlement increases with the increasing amplitude of the cyclic load, and the effectiveness of surcharge preloading depends on the difference between the surcharge and the amplitude of the cyclic load.

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Experience in forecasting long-term settlements of energy facilities based on monitoring data analysis

Ter-Martirosyan

Сидоров

2021

IOP Conf. Ser.: Mater. Sci. Eng.

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The article discusses the problem of predicting the long-term settlement of reactor compartments of nuclear power plant with a long history of operation and ongoing creep processes. The features of determining the time of the primary consolidation and the application of the parameters of the secondary consolidation are considered. With regard to the existing buildings of the reactor compartments of a nuclear power plant, a forecast of long-term deformations of the base was made, from the present time to 2062, which is the end of the operation period. The analysis and comparison of the obtained results with the data of geotechnical monitoring were also carried out. Analytical forecasting showed a high accuracy in determining the end time of filtration consolidation, however, a comparison of the values of the obtained creep settlements to date and the rate of their development shows significant differences, which makes it necessary to take into account the real picture of deformation for further forecasting in terms of operation time. Possible technological reasons for discrepancies in the results of calculations and geotechnical monitoring are analyzed, as well as theoretical reasons like imperfections of the analytical method used and the possible application of modern numerical methods.

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A Prediction Method for Long-Term Settlement of Higly Organic Soft Soil

Cited by 3 publications

References 2 publications

Prediction of dredged soil settlement based on improved BP neural network

Prediction of dredged soil settlement based on improved BP neural network

Controlling the Settlement of the Low Embankment on Soft Ground by Surcharge Preloading Method

Experience in forecasting long-term settlements of energy facilities based on monitoring data analysis

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