• Journal of the Society of Disaster Information
• /
• v.4 no.2
• /
• pp.52-66
• /
• 2008

It has been a growing concern about reusing Sudokwon landfill 2nd site and other sanitary landfills located around the metropolitan areas. In this paper, settlement characteristics of Sudokwon landfill 2nd site were studied by analyzing the data collected over the period of six years. Three equations are combined in order to modeling the long-term settlement behavior of refuse landfill caused by mechanical secondary composition and secondary composition caused by the decomposition of biodegradable refuse. It is suggested that mechanical secondary composition is linear with respect to the logarithm of time. The models proposed by hyperbolic method and Gibson & Lo model, power creep law are considered to be suitable for the long-term prediction value of Sudokwon landfill 2nd site. The fifteen-year-period prediction value of hyperbolic method and Gibson & Lo model is considerably different from that of power creep law model. The average settlement for Block I in Sudokwon 2nd site is approximately 3.9m with 4 steps of final landfill stages.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.10
• /
• pp.67-76
• /
• 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 Korean Society of Coastal and Ocean Engineers
• /
• v.16 no.2
• /
• pp.64-74
• /
• 2004

In order to accelerate the rate of consolidation settlement, to reduce settlement, and to increase bearing capacity for soft ground under quay wall, sand compaction pile method (SCP) has widely been applied. Improved ground is composite ground which is consisted of the sand pile-surrounding clayey soil. As caisson and upper structures are installed on SCP composite ground, the settlement is compositively occurred by elastic compression of sand compaction piles and also consolidation of the surrounding clay ground. In this study, the combined settlement model is proposed to predict the settlement of SCP composite ground in basis of elastic theory for sand compaction pile and consolidation theory for marine soft clay. Optimization technique was performed based on back-analysis so that real coded genetic algorithm was applied to estimate the parameters of the proposed settlement model. Case analysis was carried out for a domestic SCP composite ground to examine the applicability of the proposed prediction technique.

• Geotechnical Engineering
• /
• v.12 no.4
• /
• pp.61-74
• /
• 1996

Settlement induced by low -level vibration on granular soils is too complect to predict with one or two fact ors. Factors affecting vibration induced settlement were investigated, and a settlement prediction model on granular soils was developed using multifactorial experimental design(MED). Factors such as vibration amplitude, deviatoric stress, confining pressure, soil gradation, duration of vibration, moisture content, and relative density were considered in this study. A special vibratory frame was designed to shake a soil specimen within a triaxial cell. MED allowed the authors to investigate the effect of many factors using a relatively small number of experiments. The most significant factors on settlement were vibrati on amplitued, confining pressure, and defiatoric stress. Comparable settlement was occurred even under low-level vibration ranging from 2.5 to 18mm1sec, and stress am sotropy was found to be an important factor on settlement.

• Journal of the Society of Disaster Information
• /
• v.3 no.1
• /
• pp.37-53
• /
• 2007

Various difficult problems occur due to insufficient bearing capacity or excessive settlements when constructing roads or large complexes. Accurate predictions on the final settlement and consolidation time can help in choosing the ground improvement method and thus enables to save time and expense of the whole project. Asaoka's method is probably the most frequently used for settlement prediction which are based on Terzaghi's one dimensional consolidation theory. Empirical formulae such as Hyperbolic method and Hoshino's method are also often used. However, it is known that the settlement predicted by these methods do not match with the actual settlements. Furthermore these methods cannot be used at design stage when there is no measured data. To find an elaborate method in predicting settlement in embankments using various test results and actual settlement data from domestic sites, Back-Propagation Neural Network(BPNN) and Recurrent Neural Network(RNN) were employed and the most suitable model structures were obtained. Predicted settlement values by the developed models were compared with the measured values as well as numerical analysis results. Analysis of the results showed that RNN yielded more compatible predictions with actual data than BPNN and predictions using cone penetration resistance were closer to actual data than predictions using SPT results. Also, it was found that the developed method were very competitive with the numerical analysis considering the number of input data, complexity and effort in modelling. It is believed that RNN using cone penetration test results can make a highly efficient tool in predicting settlements if enough field data can be obtained.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.6C
• /
• pp.349-358
• /
• 2008

In performing the reliability analysis for predicting the settlement with time of alluvial clay layer at Kobe airport, the uncertainties of geotechnical properties were examined based on the stochastic and probabilistic theory. By using Terzaghi's consolidation theory as the objective function, the failure probability was normalized based on AFOSM method. As the result of reliability analysis, the occurrence probabilities for the cases of the target settlement of ${\pm}10%,\;{\pm}25%$ of the total settlement from the deterministic analysis were 30~50%, 60%~90%, respectively. Considering that the variation coefficients of input variable are almost similar as those of past researches, the acceptable error range of the total settlement would be expected in the range of 10% of the predicted total settlement. As the result of sensitivity analysis, the factors which affect significantly on the settlement analysis were the uncertainties of the compression coefficient Cc, the pre-consolidation stress Pc, and the prediction model employed. Accordingly, it is very important for the reliable prediction with high reliability to obtain reliable soil properties such as Cc and Pc by performing laboratory tests in which the in-situ stress and strain conditions are properly simulated.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.4
• /
• pp.73-81
• /
• 2012

In this study, the settlement data of 32 center cored rockfill dams (total 39 monitored data) were collected and analyzed to develop the method to predict the crest settlement of a CCRD after impounding by using the internal settlement data occurred during construction. An artificial neural network (ANN) modeling was used in developing the method, which was considered to be a more reliable approach since in the ANN model dam height, core width, and core type were all considered as input variables in deriving the crest settlement, whereas in conventional methods, such as Clements's method, only dam height is used as a variable. The ANN analysis results showed a good agreement with the measured data, compared to those by the conventional methods using regression analysis. In addition, a simple procedure to use the ANN model for engineers in practice was provided by proposing the equations used for given input values.

• Journal of Ocean Engineering and Technology
• /
• v.5 no.1
• /
• pp.35-44
• /
• 1991

This study was carried out for the purpose of pre-estimating long-term settlement under condition of actual field soil's property, in case of building up industrial sites on the marine deposit silty clay located at West Coast in Korea. This study analyzed Hyperbolic Method, Square Root Time Method and Exponential Function Method with utilization of measured survey values of settlement in In-Cheon Namdong Industrial Sites. In the future, for the continuos utilization, it seemed to be needed that further the survey values of fields should be accurartely measured for the analysis of more accurate pre-estimate about long-term settlement. Among the prediction methods of settlement Hyperbolic Method seemed to be the best fitting method for measured data. The settlement equations were derived from above three methods, for long-term settlements.

• Journal of the Korean Geotechnical Society
• /
• v.26 no.7
• /
• pp.147-159
• /
• 2010

The settlement prediction is very important in preloading method for a construction site on the soft ground. At the design stage, however, it is hard to predict the settlement exactly due to limitations of the site survey. Most of the settlement prediction is performed by a regression settlement curve based on the field data during construction. In Korea, hyperbolic method has been most commonly used to align the settlement curve with the field data, because of its simplicity and many application cases. The results from hyperbolic method, however, may differ by data selections or data fitting methods. In this study, the analyses using hyperbolic method were performed about the field data of $\bigcirc\bigcirc$ site in Pusan. Two data fitting methods, using an axis transformation or an alternative method which is a direct regression method, were applied with various data groups. If data was used only after the ground water level being stabilized, fitting results using both methods were in good agreement with the measured data. Regardless of the information about the ground water level, the alternative method gives better results with the field data than the method using an axis transformation.

• Journal of the Korean GEO-environmental Society
• /
• v.13 no.10
• /
• pp.5-13
• /
• 2012

In this study, the degrees of consolidation were evaluated by analyzing the long-term settlement measured at the 3 work sites with soft ground in Gyeongnam Area. The Hyperbolic, Hoshino and Asaoka method were used, which were focused on prediction of long-term settlement of land on the basis of field measurement data. And the applicability of the settlement prediction method according to the measurement periods was investigated by analyzing the degree of consolidation at the target areas after dividing the terms into early and latter parts. According to the results obtained at the early stage of consolidation, the Hyperbolic method appeared to be in the highest applicability level, which was followed by Asaoka and Hoshino method in the order of level. In the case of latter stage of consolidation, Asaoka method appeared to be in the highest applicability level, which was followed by and the Hyperbolic, Hoshino method in the order of level.