• Title/Summary/Keyword: Settlement Prediction Methods

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A Study on Settlement Prediction of Concrete-faced Rockfill Dam Using Measured Data During Construction and After Impounding (시공 중 및 담수 후 계측데이터를 이용한 CFRD의 침하량 예측 연구)

  • Lee, Chungwon;Kim, Yongseong
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.2
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    • pp.5-13
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    • 2015
  • In the present study, the prediction methods of the crest settlement after impounding and the maximum internal settlement during dam construction were proposed through the analysis on settlement data at 38 monitored points of 36 Concrete-Faced Rockfill Dams (CFRDs). The results from this analysis provided that the crest settlement and the maximum internal settlement are increased in proportion to the dam height and the void ratio. However, the relationship between internal settlement and dam height for each void-ratio range plotted in semi-logarithmic scale is the nearly same. Also, the prediction of the crest settlement of the CFRD is possible through the maximum internal settlement during dam construction. In addition, it seems that the valley shape highly affects the dense dam body with high construction modulus. The results of this study will provide the useful tool for the design, construction and management of CFRDs.

Prediction of Crest Settlement of Center Cored Rockfill Dam using an Artificial Neural Network Model (인공신경망기법을 이용한 중심차수벽형 석괴댐의 정부침하량 예측)

  • Kim, Yong-Seong;Kim, Bum-Joo;Oh, Sang-Eun
    • Journal of The Korean Society of Agricultural Engineers
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    • v.54 no.4
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    • pp.73-81
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    • 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.

A Study on the Practical Estimation Technique of a Long-term Settlement by the Observation Results in the Field (현장계획에 의한 연약지반의 장기 침하 예측지법에 관한 실증적 연구)

  • 서수봉;김수삼
    • Journal of Ocean Engineering and Technology
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    • v.5 no.1
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    • pp.35-44
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    • 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.

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Estimation of the Degree of Consolidation using Settlement and Excess Pore Water Pressure (침하량과 과잉간극수압을 이용한 압밀도의 추정)

  • 이달원;임성훈
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.3
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    • pp.111-121
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    • 2002
  • This study was performed to estimate the degree of consolidation using excess pore water pressure in the very soft ground. The final settlement prediction methods by Hyperbolic, Asaoka and Curve fitting methods from the measured settlement data were used to compare with the degree of consolidation estimated by excess pore water pressure. The dissipated excess pore water pressure during embankment construction and the peak excess pore water pressure on the completed embankment were used for the estimation of the degree of consolidation. After completion of embankment, it was concluded that the degree of consolidation estimated from dissipated excess pore water pressure was more reliable than that from the peak excess pore water pressure. And, the degree of consolidation estimated from the surface settlement was nearly the same as settlement of each layer. The degree of consolidation estimated from dissipated excess pore water pressure was a little larger than that from settlement.

A Study on the Long-term Settlements Characterlistics and Settlement Prediction of Soft Ground in West-South Region (서남권 연약지반의 장기침하 특성과 침하예측에 관한 연구)

  • Lee, Seungho;Jung, Jisu;Ji, Younghwan;Kim, Sungmun
    • Journal of the Korean GEO-environmental Society
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    • v.13 no.4
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    • pp.77-91
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    • 2012
  • Recently, construction of housing sites, complexes, roads, ports and airports is increasing for high-intensity use of the country and balanced development between regions. Presently, constructions are being conducted at soft ground. Consequently, engineering problems as long-term settlement of the ground, differential settlement, local structural damage have been reported consistently at construction site. In particular, long-term subsidence of the ground as various constructions and loads by the load will necessarily occur in the soft ground of west-south coast and inland coast. Therefore, in this study, regional proper analysis methods of the Hyperbole method, Hosino method, $\sqrt{S}$ method, Asaoka method etc as existing long-term settlement prediction methods have been examined and a study on new prediction method was conducted through deduction of a generalized equation. Correlation coefficients of soil properties and construction conditions has been analyzed and a matching coefficient of long-term settlement characteristics has been deducted. Comparison and analysis of monitoring data and numerical analysis results of 16 local area have been conducted.

Estimates of Settlement in Field Ground Using Neural Networks (인공신경망을 이용한 현장지반의 장래 침하량 산정)

  • 김영수;정성관;이상웅;이동현
    • 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.

Prediction of Final Settlement on Soft Ground (연약지반에서 최종침하량의 예측방법)

  • 임성훈;강예묵;이달원;김지훈
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1998.10a
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    • pp.449-454
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    • 1998
  • This study was performed of the research for accurate prediction of consolidation settlement at initial consolidation time. In order to analysis the program is developed which is able to analysis behavior of settlement caused by gradual load increment, and simulated consolidation using whole measured settlement data and that from beginning of embankment to end of it. The former result agrees with measured data and the latter it overestimated 13% larger than measured data. It was found the time which takes to be eliminated effect of gradual step load. This method is compared with the results from Asaoka, Hyperbolic and Tan's hyperbolic method respectively Asaoka and Tan's hyperbolic methods we in good agreement with this method. But classical hyperbolic method overestimated about 32%.

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A Comparative Study between BPNN and RNN on the Settlement Prediction during Soft Ground Embankment (연약지반상의 성토시 침하예측에 대한 BPNN과 RNN의 비교 연구)

  • Kim, Dong-Sik;Chae, Young-Su;Kim, Young-Su;Kim, Hyun-Dong;Kim, Seon Hyung
    • Journal of the Society of Disaster Information
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    • v.3 no.1
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    • pp.37-53
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    • 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.

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The Optimization of Hyperbolic Settlement Prediction Method with the Field Data for Preloading on the Soft Ground (쌍곡선법을 이용한 계측 기반 연약지반 침하 거동 예측의 최적화 방안)

  • Choo, Yoon-Sik;Kim, June-Hyoun;Hwang, Se-Hwan;Chung, Choong-Ki
    • Journal of the Korean Geotechnical Society
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    • v.26 no.7
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    • pp.147-159
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    • 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.

Calculation of Consolidation Settlement considering Primary and Secondary Settlement (1차와 2차 침하를 고려한 압밀침하량 계산식의 제안)

  • Lee, Dal-Won;Jeong, Seong-Gyu
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2003.10a
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    • pp.159-162
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    • 2003
  • In this study, it was proposed that a modified equation for estimating consolidation settlement on soft clay ground, which separate total settlement into primary and secondary settlement equation. The settlement by the proposed equation and by the measured settlements from laboratory model test was compared and verified for its application. It was appeared that the proposed equation from the laboratory model test approached to be more realistic comparing to the result of Terzaghi's equation. From the above application, it was concluded that the final settlement prediction by the Hyperbolic, Asaoka methods is needed to measure the initial period of settlement but the proposed equation could be much applicable in the lacking condition of measured data of the initial period.

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