• Title/Summary/Keyword: geological engineering model

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Modeling large underground structures in rock formations

  • e Sousa, Luis Ribeiro;Miranda, Tiago
    • Interaction and multiscale mechanics
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    • v.4 no.1
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    • pp.49-64
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    • 2011
  • A methodology for jointed rock mass characterization starts with a research based on geological data and tests in order to define the geotechnical models used to support the decision about location, orientation and shape of cavities. Afterwards a more detailed characterization of the rock mass is performed allowing the update of the geomechanical parameters defined in the previous stage. The observed results can be also used to re-evaluate the geotechnical model using inverse methodologies. Cases of large underground structures modeling are presented. The first case concerns the modeling of cavities in volcanic formations. Then, an application to a large station from the Metro do Porto project developed in heterogeneous granite formations is also presented. Finally, the last case concerns the modeling of large cavities for a hydroelectric powerhouse complex. The finite element method and finite difference method software used is acquired from Rocscience and ITASCA, respectively.

Experimental and numerical study on the earth pressure coefficient in a vertical backfilled opening

  • Jian Zheng;Li Li
    • Geomechanics and Engineering
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    • v.36 no.3
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    • pp.217-229
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    • 2024
  • Determining lateral earth pressure coefficient (EPC) K is a classic problem in geotechnical engineering. It is a key parameter for estimating the stresses in backfilled openings. For backfilled openings with rigid and immobile walls, some suggested using the Jaky's at-rest earth pressure coefficient K0 while other suggested taking the Rankine's active earth pressure coefficient Ka. A single value was proposed for the entire backfilled opening. To better understand the distributions of stresses and K in a backfilled opening, a series of laboratory tests have been conducted. The horizontal and vertical normal stresses at the center and near the wall of the opening were measured. The values of K at the center and near the wall were then calculated with the measured horizontal and vertical normal stresses. The results show that the values of K are close to Ka at the center and close to K0 near the wall. Furthermore, the experimental results show that the horizontal stress is almost the same at the center and near the wall, indicating a uniform distribution from the center to the wall. It can be estimated by analytical solutions using either Ka or K0. The vertical stress is higher near the center than near the wall. Its analytical estimation can only be done by using Ka at the center and K0 near the wall. Finally, the test results were used to calibrate a numerical model of FLAC2D, which was then used to analyze the influence of column size on the stresses and K in the backfilled opening.

Analysis on Geo-stress and casing damage based on fluid-solid coupling for Q9G3 block in Jibei oil field

  • Ji, Youjun;Li, Xiaoyu
    • Geomechanics and Engineering
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    • v.15 no.1
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    • pp.677-686
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    • 2018
  • Aimed at serious casing damage problem during the process of oilfield development by injecting water, based on seepage mechanics, fluid mechanics and the theory of rock mechanics, the multi-physics coupling theory was also taken into account, the mathematical model for production of petroleum with water flooding was established, and the method to solve the coupling model was presented by combination of Abaqus and Eclipse software. The Q9G3 block in Jibei oilfield was taken for instance, the well log data and geological survey data were employed to build the numerical model of Q9G3 block, the method established above was applied to simulate the evolution of seepage and stress. The production data was imported into the model to conduct the history match work of the model, and the fitting accuracy of the model was quite good. The main mechanism of casing damage of the block was analyzed, and some wells with probable casing damage problem were pointed out, the displacement of the well wall matched very well with testing data of the filed. Finally, according to the simulation results, some useful measures for preventing casing damage in Jibei oilfield was proposed.

Impact of Sulfur Dioxide Impurity on Process Design of $CO_2$ Offshore Geological Storage: Evaluation of Physical Property Models and Optimization of Binary Parameter (이산화황 불순물이 이산화탄소 해양 지중저장 공정설계에 미치는 영향 평가: 상태량 모델의 비교 분석 및 이성분 매개변수 최적화)

  • Huh, Cheol;Kang, Seong-Gil;Cho, Mang-Ik
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.13 no.3
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    • pp.187-197
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    • 2010
  • Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

Flood Discharge to Decision of Parameters in Han Stream Watershed (한천유역의 홍수량 산정을 위한 HEC-HMS 모형의 민감도 분석)

  • Jung, Woo-Yul;Yang, Sung-Kee;Kim, Dong-Su
    • Journal of Environmental Science International
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    • v.23 no.4
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    • pp.533-541
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    • 2014
  • The streams in Jeju Island have very distinctive hydrological and geological properties and there are a lot of limits in applying the general flood estimation method. This study presented parameters dominant in the Hancheon stream of Jeju Island by analyzing the sensitivity of parameters of HEC-HMS model regarding rainfall events in the target basin, and extracted the optimal parameter(Time of Concentration of Clark Unit Hydrograph: Kraven II method, Storage Coefficient: Sabol method) by analyzing and comparing it with the flood runoff data observed in the site and Jeju Island's observation data.

A study on EPB shield TBM face pressure prediction using machine learning algorithms (머신러닝 기법을 활용한 토압식 쉴드TBM 막장압 예측에 관한 연구)

  • Kwon, Kibeom;Choi, Hangseok;Oh, Ju-Young;Kim, Dongku
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.24 no.2
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    • pp.217-230
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    • 2022
  • The adequate control of TBM face pressure is of vital importance to maintain face stability by preventing face collapse and surface settlement. An EPB shield TBM excavates the ground by applying face pressure with the excavated soil in the pressure chamber. One of the challenges during the EPB shield TBM operation is the control of face pressure due to difficulty in managing the excavated soil. In this study, the face pressure of an EPB shield TBM was predicted using the geological and operational data acquired from a domestic TBM tunnel site. Four machine learning algorithms: KNN (K-Nearest Neighbors), SVM (Support Vector Machine), RF (Random Forest), and XGB (eXtreme Gradient Boosting) were applied to predict the face pressure. The model comparison results showed that the RF model yielded the lowest RMSE (Root Mean Square Error) value of 7.35 kPa. Therefore, the RF model was selected as the optimal machine learning algorithm. In addition, the feature importance of the RF model was analyzed to evaluate appropriately the influence of each feature on the face pressure. The water pressure indicated the highest influence, and the importance of the geological conditions was higher in general than that of the operation features in the considered site.

A Model Study of Processing Methods of Seismic Refraction Data for Mapping Geological Discontinuities - GRM, GLI, Tomography (지질불연속면에 대한 탄성파 굴절법탐사 자료처리 고찰 - GRM, GLI, Tomography)

  • Kim, Ji-Soo;Kim, Su-Hyun;Lee, Jun-Ho;Kim, Won-Ki;Lee, Yong-Jae
    • The Journal of Engineering Geology
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    • v.16 no.4 s.50
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    • pp.327-335
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    • 2006
  • Three processing strategies of seismic refraction data are tested in terms of velocity and depth profiles or structures for mapping of geological discontinuities: GRM(generalized reciprocal method), GLI(generalized linear inversion), Tomography. The test data used in this study are the shot gathers reconstructed by numerical modeling for the structures of 3 planar layers(horizontal, inclined), the buried vertical fracture zones, and vertical fault zones. Tomography is shown to be very efficient for mapping of more complicated tone such as vertical fault and buried fracture zones, whereas GRM and GLI can be useful for horizontal and/or inclined layers, probably on their bases of analysis of first arrivals in travel time curves.

Risk identification, assessment and monitoring design of high cutting loess slope in heavy haul railway

  • Zhang, Qian;Gao, Yang;Zhang, Hai-xia;Xu, Fei;Li, Feng
    • Structural Monitoring and Maintenance
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    • v.5 no.1
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    • pp.67-78
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    • 2018
  • The stability of cutting slope influences the safety of railway operation, and how to identify the stability of the slope quickly and determine the rational monitoring plan is a pressing problem at present. In this study, the attribute recognition model of risk assessment for high cutting slope stability in the heavy haul railway is established based on attribute mathematics theory, followed by the consequent monitoring scheme design. Firstly, based on comprehensive analysis on the risk factors of heavy haul railway loess slope, collapsibility, tectonic feature, slope shape, rainfall, vegetation conditions, train speed are selected as the indexes of the risk assessment, and the grading criteria of each index is established. Meanwhile, the weights of the assessment indexes are determined by AHP judgment matrix. Secondly, The attribute measurement functions are given to compute attribute measurement of single index and synthetic attribute, and the attribute recognition model was used to assess the risk of a typical heavy haul railway loess slope, Finally, according to the risk assessment results, the monitoring content and method of this loess slope were determined to avoid geological disasters and ensure the security of the railway infrastructure. This attribute identification- risk assessment- monitoring design mode could provide an effective way for the risk assessment and control of heavy haul railway in the loess plateau.

Extraction kaolin minesin Hadong Area using ASTER image (ASTER 영상 자료를 이용한 하동지역 고령토 광산 분포 추출)

  • LEE, Hong-Jin;KIM, In-Joon;PARK, Maeng-Eon;CHI, Kwang-Hoon;BAEK, Seung-Gyun;KO, Kyoungtae
    • Journal of The Geomorphological Association of Korea
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    • v.21 no.4
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    • pp.121-131
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    • 2014
  • This study analyzed the spectral reflectance characteristics of kaolinite and ASTER(Advanced Spaceborne Thermal Emission and Reflectance Radiometer) image to extract the distribution of kaolin mines in Hadong area, Gyeongsangnam-do. The band ratio model was applied to extract kaolinite using difference of wavelength absorption band distinct feature of minerals from ASTER image which is the major mineral of kaolin mines. According to the spectral reflectance curve of kaolinite, it showed the absorption features around 0.96 and $2.18{\mu}m$ by Al-OH. Also, it affected 1.24 and $1.38{\sim}1.41{\mu}m$ by OH. Applying for new band ratio model from the spectral features of kaolinite to ASTER image, it is possible to make the distribution map of mining traces including present- developing kaolin mines.

Groundwater pollution risk mapping using modified DRASTIC model in parts of Hail region of Saudi Arabia

  • Ahmed, Izrar;Nazzal, Yousef;Zaidi, Faisal
    • Environmental Engineering Research
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    • v.23 no.1
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    • pp.84-91
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    • 2018
  • The present study deals with the management of groundwater resources of an important agriculture track of north-western part of Saudi Arabia. Due to strategic importance of the area efforts have been made to estimate aquifer proneness to attenuate contamination. This includes determining hydrodynamic behavior of the groundwater system. The important parameters of any vulnerability model are geological formations in the region, depth to water levels, soil, rainfall, topography, vadose zone, the drainage network and hydraulic conductivity, land use, hydrochemical data, water discharge, etc. All these parameters have greater control and helps determining response of groundwater system to a possible contaminant threat. A widely used DRASTIC model helps integrate these data layers to estimate vulnerability indices using GIS environment. DRASTIC parameters were assigned appropriate ratings depending upon existing data range and a constant weight factor. Further, land-use pattern map of study area was integrated with vulnerability map to produce pollution risk map. A comparison of DRASTIC model was done with GOD and AVI vulnerability models. Model validation was done with $NO_3$, $SO_4$ and Cl concentrations. These maps help to assess the zones of potential risk of contamination to the groundwater resources.