• Title/Summary/Keyword: Soil Prediction Model

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A Prediction of Behavior of Compacted Granite Soils Based on the Elasto-Plastic Constitutive Model (탄,소성 구성모델을 이용한 다짐화강토의 응력-변형률 거동예측)

  • 이강일
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.40 no.2
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    • pp.148-158
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    • 1998
  • The aims of this study are to evaluate the application on the stress-strain behavior of granite Soil using Lade's double work hardening constitutive model based on the theories of elasticity and plasticity. From two different sites of construction work, two disturbed and compacted weathered granite samples which are different in partical size and degree of weathering respectively were obtained. The specimen employed were sampled at Iksan and Pochon in order to predict the constitutive model. Using the computer program based on the regression analysis, 11 soil parameters for the model were determined from the simple tests such as an isotropic compression-expansion test and a series of drained conventional triaxial tests. In conclusion, it is shown that Lade's double work hardening model gives the good applicability for processing of stress-strain, work-hardening, work-softening and soil dilatancy. Therefore, this model in its present form is applicable to the compacted decomposed granite soil.

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Settlement analysis of viscoelastic foundation under vertical line load using a fractional Kelvin-Voigt model

  • Zhu, Hong-Hu;Liu, Lin-Chao;Pei, Hua-Fu;Shi, Bin
    • Geomechanics and Engineering
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    • v.4 no.1
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    • pp.67-78
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    • 2012
  • Soil foundations exhibit significant creeping deformation, which may result in excessive settlement and failure of superstructures. Based on the theory of viscoelasticity and fractional calculus, a fractional Kelvin-Voigt model is proposed to account for the time-dependent behavior of soil foundation under vertical line load. Analytical solution of settlements in the foundation was derived using Laplace transforms. The influence of the model parameters on the time-dependent settlement is studied through a parametric study. Results indicate that the settlement-time relationship can be accurately captured by varying values of the fractional order of differential operator and the coefficient of viscosity. In comparison with the classical Kelvin-Voigt model, the fractional model can provide a more accurate prediction of long-term settlements of soil foundation. The determination of influential distance also affects the calculation of settlements.

Model to Predict Non-Homogeneous Soil Temperature Variation Influenced by Solar Irradiation (일사영향권내 비균질 토양의 열적거동 예측 모델)

  • Kim, Yong-Hwan;Hyun, Myung-Taek;Kang, Eun-Chul;Park, Yong-Jung;Lee, Euy-Joon
    • Journal of the Korean Solar Energy Society
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    • v.26 no.4
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    • pp.1-7
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    • 2006
  • This study is to develop a model to predict the soil temperature variation in Korea Institute of Energy Research using its thermal properties, such as thermal conductivity and diffusivity. Soil depth temperature variation is very important in the design of a proper Ground Source Heat Pump (GSHP) system. This is because the size of the borehole depends on the soil temperature distribution, and this can decrease GSHP system cost. If the thermal diffusivity and thermal conductivity are known, the soil temperature can be predicted by either the Krarti equation or the Spitler equation. Then a comparison with the Krarti equation and Spitler equation data with the real measured data can be performed. Also, the thermal properties can be reasonably approximated by performing a fit of the Krarti and Spitler equations with measured temperature data. This was done and, as a result, the Krarti equation and Spitler equation predicted values very close to the measured data. Although there is about a $0.5^{\circ}C$ difference between the deep subsurface prediction (16m - 60m), with this equation, were expected to have model this Non-Homogeneous Soil Temperature phenomenon properly. So, it has been shown that a prediction of non-homogeneous soil temperature variation influenced by solar radiation can be achieved with a model.

An Analysis of Railroad Trackbed Behavior under Train Wheel Loads (열차 하중에 의한 철도노반의 거동 분석)

  • Park, Chul-Soo;Choi, Chan-Yong;Choi, Chung-Lak;Mok, Young-Jin
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.03a
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    • pp.587-598
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    • 2008
  • In the trackbed design using elastic multi-layer model, the stress-dependent resilient modulus is an important input parameter, which reflects substructure performance under repeated traffic loading. The resilient moduli of crushed stone and weathered granite soil were developed using nonlinear dynamic stiffness, which can be measured by in-situ and laboratory seismic tests. The prediction models of resilient modulus varying with the deviatoric or bulk stress were proposed (Park et al., 2008). To investigate the performance of the prediction models proposed herein, the elastic response of the test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement during the passages of freight and passenger trains. The material types of the test sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 1mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation. The prediction models proposed for resilient modulus were verified by the comparison of the calculated vertical displacements with measured ones during train passages.

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Prediction method of slope hazards using a decision tree model (의사결정나무모형을 이용한 급경사지재해 예측기법)

  • Song, Young-Suk;Chae, Byung-Gon;Cho, Yong-Chan
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.03a
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    • pp.1365-1371
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    • 2008
  • Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model. The slope hazards data of Seoul and Kyonggi Province were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. The statistical analyses using the decision tree model were applied to the entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320m, respectively.

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Soil Salt Prediction Modeling for the Estimation of Irrigation Water Requirements for Dry Field Crops in Reclaimed Tidelands (간척지 밭작물의 관개용수량 추정을 위한 토양염분예측모형 개발)

  • 손재권;구자웅;최진규
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.36 no.2
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    • pp.96-110
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    • 1994
  • The purpose of this study is to develop soil salt prediction model for the estimation of irrigation water requirements for dry field crops in reclaimed tidelands. The simulation model based on water balance equation, salt balance equation, and salt storage equation was developed for daily prediction of sa]t concentration in root zone. The data obtained from field measurement during the growing period of tomato were used to evaluate the applicability of this model. The results of this study are summarized as follows: 1.The optimum irrigation point which maximizes the crop yield in reclaimed tidelands of silt loam soil while maintaining the salt concentration within the tolerance level, ws found to be pF 1.6, and total irrigation requirement after transplanting was 602mm(6.7 mm/day)for tomato. 2.When the irrigation point was pF 1.6, the deviation between predicted and measured salt concentration was less than 4 % at the significance level of 1 7% 3.Since the deviations between predicted and measured values data decrease as the amount of irrigation water increases, the proposed model appear to be more suitable for use in reclaimed tidelands. 4.The amount of irrigation water estimated by the simulation model was 7.2mm/day in the average for cultivating tomato at the optimum irrigation point of pF 1.6.The simulation model proposed in this study can be generalized by applying it to other crops. This, model, also, could be further improved and extended to estimate desalinization effects in reclaimed tidelands by including meteorological effect, capillary phenomenon, and infiltration.

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An Assessment of a Resilient Modulus Model by Comparing Predicted and Measured Elastic Deformation of Railway Trackbeds (철도노반의 탄성변위 예측 및 측정을 통한 회복탄성계수 모델 평가)

  • Park, Chul-Soo;Kim, Eun-Jung;Oh, Sang-Hoon;Kim, Hak-Sung;Mok, Young-Jin
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.10a
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    • pp.1404-1414
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    • 2008
  • In the mechanistic-empirical trackbed design of railways, the resilient modulus is the key input parameter. This study focused on the resilient modulus prediction model, which is the functions of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered soil, and crushed-rock soil mixture. The model is composed with the maximum Young's modulus and nonlinear values for higher strain in parallel with dynamic shear modulus. The maximum values is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement during the passages of freight and passenger trains. The material types of sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 0.6mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation.

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An overview of applicability of WEQ, RWEQ, and WEPS models for prediction of wind erosion in lands

  • Seo, Il Whan;Lim, Chul Soon;Yang, Jae Eui;Lee, Sang Pil;Lee, Dong Sung;Jung, Hyun Gyu;Lee, Kyo Suk;Chung, Doug Young
    • Korean Journal of Agricultural Science
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    • v.47 no.2
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    • pp.381-394
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    • 2020
  • Accelerated soil wind erosion still remains to date to cause severe economic and environmental impacts. Revised and updated models to quantitatively evaluate wind induced soil erosion have been made for specific factors in the wind erosion equation (WEQ) framework. Because of increasing quantities of accumulated data, the WEQ, the revised wind erosion equation (RWEQ), the wind erosion prediction system (WEPS), and other soil wind erosion models have been established. These soil wind erosion models provide essential knowledge about where and when wind erosion occurs although naturally, they are less accurate than the field-scale. The WEQ was a good empirical model for comparing the effects of various management practices on potential erosion before the RWEQ and the WEPS showed more realistic estimates of erosion using easily measured local soil and climatic variables as inputs. The significant relationship between the observed and predicted transport capacity and soil loss makes the RWEQ a suitable tool for a large scale prediction of the wind erosion potential. WEPS developed to replace the empirical WEQ can calculate soil loss on a daily basis, provide capability to handle nonuniform areas, and obtain predictions for specific areas of interest. However, the challenge of precisely estimating wind erosion at a specific regional scale still remains to date.

Modeling Soil Temperature of Sloped Surfaces by Using a GIS Technology

  • Yun, Jin I.;Taylor, S. Elwynn
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.43 no.2
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    • pp.113-119
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    • 1998
  • Spatial patterns of soil temperature on sloping lands are related to the amount of solar irradiance at the surface. Since soil temperature is a critical determinant of many biological processes occurring in the soil, an accurate prediction of soil temperature distribution could be beneficial to agricultural and environmental management. However, at least two problems are identified in soil temperature prediction over natural sloped surfaces. One is the complexity of converting solar irradiances to corresponding soil temperatures, and the other, if the first problem could be solved, is the difficulty in handling large volumes of geo-spatial data. Recent developments in geographic information systems (GIS) provide the opportunity and tools to spatially organize and effectively manage data for modeling. In this paper, a simple model for conversion of solar irradiance to soil temperature is developed within a GIS environment. The irradiance-temperature conversion model is based on a geophysical variable consisting of daily short- and long-wave radiation components calculated for any slope. The short-wave component is scaled to accommodate a simplified surface energy balance expression. Linear regression equations are derived for 10 and 50 cm soil temperatures by using this variable as a single determinant and based on a long term observation data set from a horizontal location. Extendability of these equations to sloped surfaces is tested by comparing the calculated data with the monthly mean soil temperature data observed in Iowa and at 12 locations near the Tennessee - Kentucky border with various slope and aspect factors. Calculated soil temperature variations agreed well with the observed data. Finally, this method is applied to a simulation study of daily mean soil temperatures over sloped corn fields on a 30 m by 30 m resolution. The outputs reveal potential effects of topography including shading by neighboring terrain as well as the slope and aspect of the land itself on the soil temperature.

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Evaluation of Maximum Dry Unit Weight Prediction Model Using Deep Neural Network Based on Particle Size Analysis (입도분석에 기반한 Deep Neural Network를 이용한 최대 건조 단위중량 예측 모델 평가)

  • Kim, Myeong Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.65 no.3
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    • pp.15-28
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    • 2023
  • The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R2 of 0.70 or more, and DNN analysis showed R2 of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.