• 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.

• 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 the Korean GEO-environmental Society
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• v.13 no.12
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• pp.35-42
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• 2012

There are many large-scale coastal region landfill and land development by loading to use territory efficiently, this regions are mostly soft clay ground. Constructing structures and road on the soft ground bring about engineering problems like ground shear fracture and a big amount of consolidation by bearing capacity. Improvement of soft soil is required to secure soil strength and settlement control. In improvement of soft soil, predict for the amount of settlement based on field surveyed reports are important element for estimating pre-loading banking height and the final point of consolidation. In this study, there is calculating theoretical settlement by analyzing field surveyed report and ground investigation to improvement of soft soil with pre-loading and vertical drain method. And present settlement prediction method reflect soil characteristics in Gimpo Hangang site by analysing prediction settlement and observational settlement during compaction using hyperbolic, ${\sqrt{s}}$, Asaoka method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5C
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• pp.155-162
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• 2011

Settlement prediction based on field monitored data, which is used to control subsequent surcharges, is very important in construction management for soft ground improvement with the preloading method. Observational settlement prediction methods, which are suggested for an instantaneous loading, have been widely used in fields. However, they have difficulties in the settlement prediction with subsequent surcharge change. In this paper, a simple method to predict the settlement with subsequent surcharge change is suggested. The suggested method adopts assumptions to simplify the complex field condition and utilizes observational methods. The suggested method is applied to a large consolidation test result, FDM analysis results, and field monitored settlement data to confirm its practicability. From the applications, the suggested method produces reasonable prediction results with various subsequent surcharge changes.

• 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.

• Geotechnical Engineering
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• v.14 no.6
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• pp.127-138
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• 1998

In refuse landfills, a considerable amount of settlement occurs due to the decomposition of refuse over several years. In this paper, several prediction methods are applied to the measured settlement data of fresh refuse sites. The effect of biological decomposition on the settlement characteristics is investigated in predicting the long-term settlement of refuse landfill sites in view of the predicted settlement curves and the amount of long-term settlement. Irrespective of the applied models, the long term settlement may not be correctly estimated if the model parameters do not contain the decomposition effects. Among the proposed several prediction methods, Gibson & Lo model and hyperbolic model seem to represent the long-term settlement characteristics, but the power creep law seems to considerably overestimate the long-term settlement.

• Journal of the Korean GEO-environmental Society
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• v.6 no.1
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• pp.53-62
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• 2005

This paper estimates the long-term settlement of Kimpo metropolitan landfill based on measured settlement data from 180 landfill monitors accumulated over a period of 12 years. Comparison of domestic and international settlement records indicate that the domestic compression rate is slightly lower due to greater portion of organic component. Several existing settlement models are used to compare with the observed behavior and also to estimate long-term settlement. The hyperbolic, Gibson & Lo, Bjarngard & Edgers and Power Creep Law models compare well with the measured settlement of the Kimpo metropolitan landfill. The settlement models are further used to estimate long-term settlement. Bjarngard & Edgers and Power Creep Law models result in higher estimates of the long-term settlement compared to the hyperbolic and Gibson & Lo models. Further comparisons indicate that other models, including Sowers and log models, are inapproriate for predicting the long-term settlement of the Kimpo metropolitan landfill.

• Journal of the Korean Geotechnical Society
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• v.16 no.2
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• pp.41-50
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• 2000

본 연구에서는 여러 침하모델들을 매립경과기간이 다른 아홉 개 지역의 실제 스레기 매립지 침하자료들에 적용하였다. 침하모델들을 적용한 결과, 매립연한이 증가할수록 향후 발생가능한 장기침하량도 상당히 감소하는 경향을 보였다. 신선한 쓰레기 매립지에서는 침하모델들마다 예측정도에서 큰 차이를 보이지만, 매립연한이 오래된 매립지들에서는 Power creep law를 제외하고는 예측정도에 있어서 큰 차이를 보이지 않음을 알 수 있었다.

• Geotechnical Engineering
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• v.13 no.2
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• pp.65-76
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• 1997

It has been a growing concern how to use Nanji-Island landfill and other refuse landfills located around metropolitan areas. In this paper, settlement characteristics of Nanji -Island landfill were studied by analyzing the data collected over the period of two years. The settlement characteristics were similar to the analyzed settlement characteristics of 24 refuse landfills in the United States. The model proposed by Bjarngard and Edger(1990) model is considered to be suitable for the long-term prediction of Wnil -Island landfill. The ten-year -period prediction value of Bjarngard and Edger (1990) model is considerably different from that of Power Creep Model. If existing settlement models used for long-term prediction of the settlement characteristics of landfill are not analyzed thoroughly there remains the possibility of including considerable prediction errors.

• 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.