• 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.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.

• 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.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.67-76
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• 2009

Statistical analysis was performed using a series of data on RMR, RMR* and crown settlements collected from sites of weathering rock tunnels in Korea. The crown settlements were predicted by recurrence analysis, exponential function, and artificial neural network (ANN) using collected in-situ data. The result of the prediction fitted well compared to the measured settlement in the order of ANN, exponential function, and recurrence analysis. The range of crown settlement predicted by recurrence analysis widely scattered and promised larger settlement than the measured. Also in all method, the predicted value by RMR well matched compared to the measured settlement predicted by RMR*.

• Journal of the Korean GEO-environmental Society
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• v.5 no.3
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• pp.61-70
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• 2004

N-value by the SPT is one of the key parameter for settlement evaluation. However, if the ground is firm, the usual N-value is not blow count of 30cm depth penetration. In such case, if N-value is more than 50 with 30cm penetration, the N-value 50 is applied for settlement analysis. Therefore, in this study, the modified method of N-value estimation is suggested and compared the settlement by Elastic Theory, and the measured field data by Plate Load Test. As the result of this study, it is shown that the settlement by Elastic Theory with the modified N-value is more accurate than settlement by usual N-value. The application of Elastic Theory for pure sand is also evaluated in this paper.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.914-921
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• 2010

When industrial structures are constructed on soft ground, ground subsidence is occurred by problems of bearing capacity. To protect ground subsidence have to improve soft ground, and have to predict settlement estimation for reasonable construction. Artificial Neural Networks(ANN) is adopted for prediction of settlement of construction during the initial design. In the study, Artificial Neural Networks are applied to predict the settlement estimation of initial condition ground and ground improved by D.C.M method. Also, this study compares results of Artificial Neural Networks and results of continuum analysis using Mohr-Coulomb models. In result, settlements of initial condition ground decreased over 0.7 times. Also, by comparing ANN and continuum analysis, coefficient of determination was comparatively high value 0.79. Thought this study, it was confirmed that settlements of improvement ground is predicted using laboratory experiment data.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.786-793
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• 2021

Purpose: An experiment was conducted to analyze the characteristics of the settlement of soft clay soil in the central region of the west coast of Korea, which has a high silt content and is difficult to predict settlement due to various stress histories. Method: Field experiments were conducted for three cases. The settlement amount of the subsidence plate was measured in each case, and the following conclusions were drawn by analyzing Terzaghi's one-dimensional consolidation settlement amount, both the hyperbolic method and the Asaoka method. Result: The predicted value by Terzaghi was analyzed to be the largest in all cases, and it was predicted to be 111% to 187% larger than the subsidence plate settlement value. That is, the subsidence plate settlement value, which is the amount of settlement of the actual ground, showed a settlement of 53.4~89.9% compared to the predicted value of Terzaghi. Therefore, it was analyzed that the expected settlement of the Terzaghi method in the clay soft ground of the central west coast of Korea is more than the actual settlement. Conclusion: It was analyzed that the Asaoka method and the hyperbolic method presented relatively similar results, and in practice, predicting the settlement amount smaller than the actual settlement amount may cause a risk, so the hyperbola analysis method predicted 6~14% larger than the actual settlement amount can be used as a safety side.

• 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 Society of Disaster Information
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• v.18 no.4
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• pp.706-712
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• 2022

Purpose: In this study, field experimental research was conducted to analyze the settlement characteristics of soft ground in the central inland region of Korea and use it in practice. Method: The design predicted values and comparative analysis were performed using the ten settlement measurement data actually measured in the field experiment. For the design prediction value, Terzaghi's one-dimensional consolidation settlement analysis was used. In the experiment, the surface subsidence plate was used for field measurement. Result: The settlement behavior of the predicted value and the actual value was generally similar, but in the settlement value, the actual settlement value showed a settlement behavior of 30% or less compared to the predicted settlement value. The rate of consolidation settlement in this study area was in the range of 9.6% to 27.0%, and the average value was 18.21%. It is analyzed that the prediction of the settlement amount of the silty soils distributed in the inland plains of the central region of Korea can be relatively overestimated. Conclusion: It is judged that precise ground investigation and detailed prediction are necessary because there is a possibility of over-design in the design for predicting the amount of settlement of the silty soils distributed in the inland plains of the central region of Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.502-508
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• 2021

Predicting the settlement of soft ground is an important aspect of soft ground design. In this study, a method is proposed that increases the reliability of settlement predictions based on-site investigation data, including piezocone penetration test results, at the Gimhae-Jinyoung district, adjacent area to the Nakdong River. Soils in the area waweres classified using the Robertson Chart (1986, 1990), and theoretical settlement was calculated using the equations proposed by Terzaghi (1925) and Sanglerat (1972). SPSS was used to obtain the correlation between theoretical and measured settlements. Results produced settlement prediction errors for the Terzaghi and Sanglerat methods of 17.28% and 26.96%, respectively. A correction factor calculated by SPSS correlation analysis for the relation between and theoretical and measured settlements is proposed that improves the reliability of settlement prediction in soils of the classification examined.