• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.128-141
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• 2010

Drought indices such as SPI(Standard Precipitation Index) and PDSI(Palmer Drought Severity Index) estimated using ground observations are not enough to describe detail spatial distribution of drought condition. In this study, the drought index with improved spatial resolution was estimated by using the CART algorithm and ancillary data such as MODIS NDVI, MODIS LST, land cover, rainfall, average air temperature, SPI, and PDSI data. Estimated drought index using the proposed approach for the year 2008 demonstrates better spatial information than that of traditional approaches. Results show that the availability of satellite imageries and various associated data allows us to get improved spatial drought information using a data mining technique and ancillary data and get better understanding of drought condition and prediction.

• Tunnel and Underground Space
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• v.14 no.6 s.53
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• pp.440-449
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• 2004

Rock mass includes natural discontinuities such as joints and faults during its formation. Discontinuities are also referred as planes of weakness because of their weak mechanical characteristics. In the design of underground structures, it is necessary to consider the properties of discontinuities to insure the stability. During the excavation of a tunnel, these discontinuities have to be identified as early as possible so that proper change in excavation method or support design can be made accordingly. The excavation of the tunnel in a stable rock mass causes a 3-dimensional arching effect around the excavation face. It was revealed by previous studies that the existence of a weak zone or a fault zone ahead of tunnel foe induces a typical displacement tendency of convergence. For better understanding of the meaning of influence/trend lines of various displacement components, three-dimensional numerical analyses were conducted while varying deformation moduli, thicknesses and orientations of discontinuities. Numerical results showed that the changes in influence/trend lines of various displacement components were very similar to those by measurements. The discrepancies from the expected values were dependent on the physical properties, thicknesses and orientations of discontinuities.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.1
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• pp.69-79
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• 2008

Prediction of ground condition ahead of tunnel face might be the most important factor to prevent collapse during tunnel excavation. In this study, a non-destructive method to evaluate the phase velocity in model rock mass using wavelet transform of surface wave was proposed aiming at ground condition assessment ahead of tunnel face. Model tests using gypsum as a rocklike material composed of two layers were performed. A Piezoelectric actuator with frequencies ranging from 150 Hz to 5 kHz was selected as a harmonic source. The acceleration history was measured with two accelerometers. Wavelet transform analysis was used to obtain the dispersion curves from the measured data. The experimental results showed that the near-field effects can be neglected if the distance between two receivers is chosen to be three times the wavelength. A simple inversion method using weighted factor based on the normal distribution was proposed. The inversion results showed that the predicted phase velocity agreed reasonably well with the measured one when the wavelength influence factor was 0.2. The depth of propagation of surface wave was from 0.42 to 0.63 times the wavelength. The range of wavelength varying with phase velocity in dispersion curve matched well with that estimated by inversion technique.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.15-26
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• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1266-1266
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• 2001

Pasture composition, an important attribute determining sward condition and value, is normally assessed by hand separation, drying and measuring weight contribution of each species in the mixture. This is a tedious, time and labour consuming procedure. NIRS has demonstrated the potential for predicting botanical composition of swards, but most of the work has been carried out on dry samples. The aim of this work was to evaluate the feasibility of developing NIR models for predicting the white clover and ryegrass content in fresh or dry mixtures artificially prepared from pure samples of both species. Mixtures from pure stands of white clover(Trifolium repens) and perennial ryegrass (Lolium perenne) were prepared with different proportions (0 to 100%) of each species (fresh weight). A total of 55 samples were made (11 mixtures,5 cuts). Spectra (400 to 2500 nm) were taken from fresh chopped (rectangular cuvettes, transport sample module) samples, in a NIR Systems 6500 scanning monochromator controlled by the software NIRS 3 (Infrasoft International), which was also utilized for calibration development. Different math treatments (derivative order, subtraction gap and smooth segment) and a scatter correction treatment of the spectra (SNV and Detrend) were tested. Equations were developed by modified partial least squares. Prediction accuracy evaluated by cross-validation, showed that percentage of clover or ryegrass, as contribution in dry weight, can be successfully percentage of clover or ryegrass, as contribution in dry weight, can be successfully predicted either on fresh or dried samples, with equations developed by different math treatments. Best equations for fresh samples were developed including a first, second, or third derivative, whereas for dry samples best equations included a second or third derivative. Standard errors of ross validation were about 6% for fresh and 3.6% for dry samples, Coefficient of determination of cross validation (1-VR) were over 0.95 times the value of SECV for fresh samples and over 8 times the value of SECV for dry samples. Scatter correction (SNV and Detrend) in general improved prediction accuracy. It is concluded more precise on dried and ground samples, it can be used with an acceptable error level and less time and labour, on fresh samples.

• Journal of the Korean Geotechnical Society
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• v.29 no.1
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• pp.121-133
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• 2013

This paper presents the results of an investigation into the pull-out capacity characteristics of screw anchor piles. Theoretical background of screw anchor pile (SAP) was first discussed. A series of reduced-scale model tests were performed on a number of cases with different SAP geometries such as pitch and diameter of screw as well as relative density of the model ground. The applicability of the pull-out capacity prediction equations were also examined based on the test results. It was shown that the pitch of screw has negligible effect on the pull-out capacity, while the diameter of screw has relatively large effect on pull-out capacity under a given condition. Practical implications of the findings from this study are discussed in great detail.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.6
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• pp.695-701
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• 1998

Researches on unused energy are being continued because of the limited fossil fuel and the destruction of environment. Therefore this study was peformed as follows. The collectable amount of exhausted heat for an air-conditioning was calculated by the subway thermal environment prediction program. And the electric power needed by conventional heat source equipments was compared with one by unused heat source equipments when the exhausted heat was used by heat pump in heating and hot water supplying. The results are summarized as follows; 1) Forced ventilation should be conducted to keep optimal temperature in subway tunnel in summer as well as in winter. According to the simulation, temperature in tunnel was higher than that on the ground in summer when the forced ventilation was conducted only in winter. 2) Ventilating time should be calculated out to the optimal condition for not only saving power of ventilation fan but reusing exhausted heat. By the simulation, it is certain that the exhausted heat should be eliminated in air-conditioning time. 3) The use of exhausted heat source heat pump could save 8% of electric power per hour in comparison with existing heat pump. It was based on a present heat generation and traffic for ventilating time of general air-conditioning, but could be different by ventilating time. 4) As the traffic increases up to 1.5 or 2 times, electric power consumption of the conventional heat pump increases to 11% or 13.5% per mean hour in comparison with that of the exhausted heat source heat pump, though all-day ventilation.

• Korean Journal of Agricultural Science
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• v.25 no.2
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• pp.247-259
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• 1998

Analyses which loads were regarded as instant load and gradual step load were performed with data measured on gradually loaded field, and the results were inspected to find effect of load condition, and final settlements predicted by Hyperbolic, Tan's, Asaoka's, and Monden's method were compared with each other. According to above analyses, the following conclusions were obtained. Settlement curves which loads were regarded as instant load and gradual step load were beginning to coincide at time of twice duration of embankment. On the ground installed vertical drain, the result of Hyperbolic, Tan's, Asaoka's, Monden's, curve fitting I, and curve fitting II (simple, Carrillo) methods make conclude that Asaoka, curve fitting I, and curve fitting II methods agree with measured settlement.

• Journal of the Korean Geotechnical Society
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• v.29 no.12
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• pp.45-56
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• 2013

Abrams equation could be effectively applied to predict strength of cement-admixed clay and clay-water content to cement content ratio is a fundamental parameter for governing strength. This paper analyses unconfined compression strength varying with $w_c/C$ and curing time using laboratory test results. An attempt is made to identify strength of composite soil of cement and clay according to variation of Abrams coefficients and curing time. The value B, which was considered to be constant value in past researches, needs to be considered as parameter variable with curing time. From Abrams equation a correlation was formed for unconfined compression strength with mixing conditions by $w_c/C$ and curing time as dependent variable. Regression results in this paper could be used to predict strength of cement-admixed clay at various mixing conditions.

• Journal of the Korean GEO-environmental Society
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• v.13 no.8
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• pp.25-33
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• 2012

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to consider various geographies and geotechnical conditions. When the tunnel is under construction, examination of accurate safety and prediction of behavior are overcome the limits of predicting behavior by Artificial Neural Network in this study. First, construct the suitable structure after the data of field was made sure by the multi-layer back propagation, then apply with algorithm. Employ the result of measured data from database, and consider the influence factor of tunnel, like supporting pattern, RMR, Q, the types of rock, excavation length, excavation shape, excavation over, to carry out the reliable analysis through field applicability of Artificial Neural Network. After studying, using the ANN model to predict the shearing displacement, convergence displacement, underground displacement, Rock bolt output follow the excavation over of tunnel construction field, then determine the field applicability with ANN through field measured value and comparison analysis when tunnel is being constructed.