• Geotechnical Engineering
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• v.13 no.6
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• pp.5-12
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• 1997

Predictions of settlements under preloading for the improvement of soft soil is a very important element of construction management. Due to the non uniformity, difficulty of estimating resonable soil properties, predictions of settlements and settlement velocities at the design stage seldom agree with the actual future settlements. To overcome this problem, the prediction methods based on the settlement observation of initial preloading stage such as hyperbolic method and Asaoka method have been employed frequently. However the estimating method for the reliability of these predictions at the time of prediction has not been suggested. In this study, comparisons of predicted settlements by hyperbolic met hed and observed settlements are explored through case studies. And a stratagem of estimating reliability of settlement predictions by hyperbolic method is suggested as the result of investigation on the relationship between the initial observed time and error of settlement prediction by hyperbolic method.

• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.332-347
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• 1991

Accurate prediction of future settlement is essential for the settlement control of soft soil by pre-loading method. To predict future settlement in clayey soft soils, several methods like Asaoka method, Hyperbolic Method and Hoshino method are currently being used. These methods predict the future sett1ement by mathmatical treatment of the measured settlement data on the basis of consolidtion theory and empiricism. But the correlation coefficient between the measured and the predicted settlement was relatively low (0.8~0.9). Also, the prediction of future settlemet for the design load is very difficult. In this article, the measured field settlement data was treated as the the field consolidation test. Hence, condolidation coefficient(Cv) and compression index(Cc) was evaluated from the field settlement data. Cv and Cc values from field data was used to calculate the degree of consolidation and settlement at desired time. By this method, the correlation coefficent between the measured and the predicted settlement was significantly increased(0.97~0.99). Also the settlement by the design load after the improvement of soft soil could be predicted reasonably. This method is quite rational and sound but it requires thousands of calculation steps. Today, by the aid of low priced personal computers above mentioned technique could be used much acre economically and effectively than conventional methods. This article presented the mechanisms and capacities of this method and demonstrated the enhanced correlation coefficient when applied to actual field settlement data.

• Journal of the Korean GEO-environmental Society
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• v.13 no.2
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• pp.19-26
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• 2012

In this study, characteristics of consolidation settlement of soft grounds adapting preloading method and vertical drain method were compared. A real measurement settlement is compared with predicted one by the future settlement prediction method like the Asaoka's method, the Hyperbolic method and the Hoshino method. A accuracy of predicted future settlement by the Asaoka's method is relatively higher than the Hyperbolic method or the Hoshino method generally. But in the area conducted with the vertical drain method, settlement prediction accuracy of three methods is similar unlike popular beliefs; Asaoka's is the better method for prediction than others. The study area is also confirmed by investigation of the drainage system after applying the change through the N values, soil physical and mechanical properties were investigated, and physical properties are improved.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.27-33
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• 2003

This study analyzed an application possibility of neural network to overcome problems of conventional settlement prediction. It is very important to estimate settlement in preloading method used to improve soft ground. At present, Hyperbolic method, Hoshino method and Asaoka method are used mostly in the prediction of settlement. But these methods can not predict settlement at the phase of design. On the other hand, neural networks are capable of predicting settlement through accumulated data in the phase of design and this method can be easily applied in practice. In this study Elman neural network is used to estimate future settlement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.4
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• pp.705-713
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• 2016

For the soft ground construction, the factors not considered in the design stage occurs in the construction stage so that they cause the increase of the construction cost due to the structural stability and the design change. The subject of the study is the construction section of the industrial complex access road made in the Ochang region of Chungcheongbuk-do. The study is concerned with selecting the soft ground handling method such as the replacement method using rock debris and the surcharge reflecting the service load as the soft ground handling measure and analyzing the effect of reducing the construction cost with the stability of structures and the reduction of the construction period. The soft ground in the study section consists of sandy and cohesive soil and is 2.4m to 5.5m deep. It is distributed unevenly between the 1.5m to 5.9m stratums under the ground surface. Settlement is not serious, but the future uneven settlement and difference are expected so that the future settlement behavior is estimated by analyzing the site measurement results after the soft ground treatment. Moreover, in consideration of the regional characteristics and economic efficiency, soil with good quality is replaced with rock debris as the replacement material so that 29% of the construction cost is reduced due to the increase of stability and the reduction of duration. If the estimation of the dispersion of the pore water pressure within the dam body and the change of the underground water level and the relation of the actually measured soft ground with consolidation is studied further on the basis of the study, it is expected that the behavior of the soft ground will be correctly estimated in various site conditions.

• Journal of the Korean GEO-environmental Society
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• v.15 no.12
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• pp.97-107
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• 2014

Settlement prediction has been conducted using Hyperbolic, Hoshino, and Monden methods, etc in the fields. These methods are only able to predict settlement after finishing the final filling stage. A new method is proposed to make up for such a weak point. This method was named as SPSFC (Settlement Prediction for Staged Filling Construction) method, which can be able to predict the settlement both the final filling stage and the staged filling from the initial filling stage in soft ground. To verify the applicability of the SPSFC method, firstly. The settlement predicted by the existed methods are compared with that obtained by the SPSFC method. The comparison results indicate the SPSFC has enough reliability to use for prediction of settlement. Secondly. by analyzing the settlement data measured during the initial filling stage, the soil parameters which need to predict the settlement are obtained by the SPSFC method. Then using the obtained soil parameters the time-settlement curve is predicted and compared. The predicted settlement is well matched with the measured one. From the study, the SPSFC method can be possible to predict settlement during the staged filling with only the initial settlement data.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.10a
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• pp.147-158
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• 2001

In general, two methods have been used to predict settlement of soft ground. One method is Terzaghi's one dimensional consolidation theory which gives time-settlement relationship using the standard consolidation test results. The other is forecasting method of ground settlement to be occured in the future using in-situ monitoring data. The above both methods have some defects in application manner or in itself especially in very deep and soft clayey ground. In view of the lessons and experiences of soft ground improvement projects, several techniques were proposed for more accurate theorectical calculation of consolidation settlement as follows ; ① Subdivision of soft ground, ② Consideration of secondary compression, ③ Using the modified compression index, etc. And also, revised hyperbolic fitting method was suggested to minimize the error of predicted future settlement. In addition, revised De-Beer equation of immediate settlement of loose sandy soil was proposed to overcome the tendency to show too small settlement calculation results by original De-Deer equation. And also, considering the various effects of settlement delay in the improved ground by vertical drains, time-settlement caculation equation(Onoue method) was revised to match the tendency of settlement delay by using the characteristics of discharge capacity decreases of vertical drain with time elapse by the pattern of hyperbolic equation.

• Journal of the Korean GEO-environmental Society
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• v.20 no.10
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• pp.29-38
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• 2019

In stability and settlement management of soft ground, the settlement prediction technology has been continuously developed and used to reduce construction cost and confirm the exact land use time. However, the preexistence prediction methods such as hyperbolic method, Asaoka method and Hoshino method are difficult to predict the settlement accurately at the beginning of consolidation because the accurate settlement prediction is possible only after many measurement periods have passed. It is judged as the reason for estimating the future settlement through the proportionality assumption of the slope which the preexistence prediction method computes from the settlement curve. In this study, ARIMA technique is introduced among time series analysis techniques and compared with preexistence prediction methods. ARIMA method was predictable without any distinction of ground conditions, and the results similar to the existing method are predicted early (final settlement).

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.559-575
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• 2021

Due to the increase in ground excavation work, the possibility of ground subsidence accidents is increasing. And it is very difficult to prevent these risk fundamentally through institutional reinforcement such as the special law for underground safety management. As for the various cases of urban ground excavation practice, the ground subsidence behavior characteristics which is predicted using various information before excavation showed a considerable difference that could not be ignored compared to the results real construction data. Changes in site conditions such as seasonal differences in design and construction period, changes in construction methods depending on the site conditions and long-term construction suspension due to various reasons could be considered as the main causes. As the countermeasures, the safety management system through various construction information is introduced, but there is still no suitable system which can predict the effect of excavation and risk assessment. In this study, a web-based system was developed in order to predict the degree of impact on the ground subsidence and surrounding structures in advance before ground excavation and evaluate the risk in the design and construction of urban ground excavation projects. A system was built using time series analysis technique that can predict the current and future behavior characteristics such as ground water level and settlement based on past field construction records with field monitoring data. It was presented as a geotechnical data visualization (GDV) technology for risk reduction and disaster management based on web-based system, Using this newly developed web-based assessment system, it is possible to predict ground excavation impact prediction and risk assessment.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.45-54
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• 2023

The settlement prediction during the design phase is primarily conducted using theoretical methods. However, measurement-based settlement prediction methods that predict future settlements based on measured settlement data over time are primarily used during construction due to accuracy issues. Among these methods, the hyperbolic method is commonly used. However, the existing hyperbolic method has accuracy issues and statistical limitations. Therefore, a weighted nonlinear regression hyperbolic method has been proposed. In this study, two weighting methods were applied to the weighted nonlinear regression hyperbolic method to compare and analyze the accuracy of settlement prediction. Measured settlement plate data from two sites located in Busan New Port were used. The settlement of the remaining sections was predicted by setting the regression analysis section to 30%, 50%, and 70% of the total data. Thus, regardless of the weight assignment method, the settlement prediction based on the hyperbolic method demonstrated a remarkable increase in accuracy as the regression analysis section increased. The weighted nonlinear regression hyperbolic method predicted settlement more accurately than the existing linear regression hyperbolic method. In particular, despite a smaller regression analysis section, the weighted nonlinear regression hyperbolic method showed higher settlement prediction performance than the existing linear regression hyperbolic method. Thus, it was confirmed that the weighted nonlinear regression hyperbolic method could predict settlement much faster and more accurately.