• The Journal of Engineering Geology
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• v.24 no.4
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• pp.643-648
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• 2014

Understanding of fracture networks and rock mass properties during tunnel construction is extremely important for the prediction of dangers during excavation, and for deciding on appropriate excavation techniques and support. However, rapid construction process do not allow sufficient time for surveys and interpretations for spatial distributions of fractures and rock mass properties. This study introduces a new statistical approach for predicting joint distributions at foreside of current excavation face during the excavation process. The proposed methodology is based on a cumulative space diagram for joint sets. The diagram displays the cumulative spacing between adjacent joints on the vertical axis and the sequential position of each joint plotted at equally spaced intervals on the horizontal axis. According to the diagram, the degree of linearity of points representing the regularity of joint spacing; a linear trend of the points indicates that the joints are evenly spaced, with the slope of the line being directly related to the spacing. The linear points which are stepped indicates that the fracture set show clustered distribution. A clustered pattern within the linear group of points indicates a clustered joint distribution. Fractures surveyed from an excavated space can be plotted on this diagram, and the diagram can then be extended further according to the plotted diagram pattern. The extension of the diagram allows predictions about joint spacing in areas that have not yet been excavated. To test the model, we collected and analyzed data during excavation of a 10-m-long tunnel. Fractures in a 3-m zone behind the excavation face were predicted during the excavation, and the predictions were compared with observations. The methodology yielded reasonably good predictions of joint locations.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.89-96
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• 2014

We aimed to evaluate the effects of climatic elements on potato yield and create a model with climatic elements for estimating the potato yield, using the results of the regional adjustment tests of potato. We used 86 data of the yield data of a potato variety, Sumi, from 17 regions over 11 years. According to the results, the climatic elements showed significant level of correlation coefficient with marketable yield appeared to be almost every climatic elements except wind velocity, which was daily average air temperature (Tave), daily minimum air temperature (Tmin), daily maximum air temperature(Tmax), daily range of air temperature (Tm-m), precipitation (Prec.), relative humidity (R.H.), sunshine hours (S.H.) and days of rain over 0.1 mm (D.R.) depending on the periods of days after planting or before harvest. The correlations between these climatic elements and marketable yield of potato were stepwised using SAS, statistical program, and we selected a model to predict the yield of marketable potato, which was $y=7.820{\times}Tmax_-1-6.315{\times}Prec_-4+128.214{\times}DR_-8+91.762{\times}DR_-3+643.965$. The correlation coefficient between the yield derived from the model and the real yield of marketable yield was 0.588 (DF 85).

• Geophysics and Geophysical Exploration
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• v.22 no.1
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• pp.21-28
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• 2019

We perform a 3D tomographic inversion using surface wave dispersion curves to obtain S-velocity model and radial anisotropy beneath Saudi Arabia. The Arabian Peninsula is geologically and topographically divided into a shield and a platform. We used event data with magnitudes larger than 5.5 and epicentral distances shorter than $40^{\circ}$ during 2008 ~ 2014 from the Saudi Geological Survey. We obtained dispersion curves by using the multiple filtering technique after preprocessing the event data. We constructed SH- and SV-velocity models and consequently radial anisotropy model at 10 ~ 60 km depths by inverting Love and Rayleigh group velocity dispersion curves with period ranges of 5 ~ 140 s, respectively. We observe high-velocity anomalies beneath the Arabian shield at 10 ~ 30 km depths and low-velocity anomalies beneath the Arabian platform at 10 km depth in the SV-velocity model. This discrepancy may be caused by the difference between the Arabian shield and the Arabian platform, that is, the Arabian shield was formed in Proterozoic thereby old and cold, while the Arabian platform is covered by predominant Paleozoic, Mesozoic, and Cenozoic sedimentary layers. Also we obtained radial anisotropy by estimating the differences between SH- and SV-velocity models. Positive anisotropy is observed, which may be generated by lateral tension due to the slab pull of subducting slabs along the Zagros belt.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.3
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• pp.374-380
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• 2017

Image analysis and k-mean clustering were conducted to develop a grading system of dried sea cucumber (SC) based on rehydration rate. The SC images were obtained by taking pictures in a box under controlled light conditions. The region of interest was extracted to depict the shape of the SC in a 2D graph, and those 2D shapes were rendered to build a 3D model. The results from the image analysis provided the morphological features of the SC, including length, width, surface area, and volume, to obtain the parameters of the k-mean clustering weight. The k-mean clustering classified the SC samples into three different grades. Each SC sample was rehydrated at $30^{\circ}C$ for 40 h. During rehydration, the flux of each grade was analyzed. Our study demonstrates that the mass transfer rate of SC increased as the surface area increased, and the grade of SC was classified based on rehydration rate. This study suggests that the optimal rehydration process for SC can be achieved by applying a suitable grading system.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.415-423
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• 2010

Pore network models are useful tools to investigate soil pore geometry. These models provide quantitative information of pore geometry from 3D images. This study presents a pore network model to quantify pore structure and hydraulic characteristics. The objectives of this work were to apply the pore network model to characterize pore structure from large images to quantify pore structure, calculate water retention and hydraulic conductivity properties from a three dimensional soil image, and to combine measured hydraulic properties from experiments with calculated hydraulic properties from image. Soil samples were taken from a site located at the Baltimore science center, which is located inside of the city. Undisturbed columns were taken from the site and scanned with a computer tomographer at resolutions of 22 ${\mu}m$. Pore networks were extracted by medial-axis transformation and were used to measure pore geometry from one of the scanned samples. Water retention and unsaturated hydraulic conductivity values were calculated from the soil image. Properties of soil bulk density, water retention and unsaturated hydraulic conductivity were measured from three replicates of scanned soil samples. 3D image analysis provided accurate detailed pore properties such as individual pore volumes, pore length, and tortuosity of all pores. These data made possible to calculate accurate estimations of water retention and hydraulic conductivity. Combination of the calculated and measured hydraulic properties gave more accurate information on pore sizes over wider range than measured or calculated data alone. We could conclude that the hydraulic property computed from soil images and laboratory measurements can describe a full structure of intra- and inter-aggregate pores in soil.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.260-276
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• 2024

The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

• Ocean and Polar Research
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• v.28 no.4
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• pp.407-413
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• 2006

The effect of water temperature and photoperiod on the oxygen consumption of the fasted juvenile parrot fish, Oplegnathus fasciatus was investigated to provide empirical data for the early-stage culture management and bioenergetic growth model of the species. The mean body weight of the juvenile used for the experiment was $21.5{\pm}1.9g$, and the oxygen consumption rate was measured under four water temperatures (10, 15, 20 and $25^{\circ}C$) and three photoperiods (24L:0D, 12L:12D and OL:24D) with an interval of 5 minutes for 24 hours using a continuous flow-through respirometer. In each treatment three replicates were set up and 15 juveniles were totally involved. The oxygen consumption rates increased with increasing water temperature under all photoperiod treatments (P<0.001). Mean oxygen consumption rates at 10, 15, 20 and $25^{\circ}C$ ranged $202.1{\sim}403.4,\;306.7{\sim}502.2,\;536.7{\sim}791.0\;and\;879.9{\sim}1,077.4mg\;O_2\;kg^{-1}h^{-1}$, respectively. $Q_{10}$ values ranged $1.58{\sim}2.30$ between 10 and $15^{\circ}C,\;2.44{\sim}3.06$ between 15 and $20^{\circ}C\;and\;1.86{\sim}2.6y9$ between 20 and $25^{\circ}C$, respectively. Mean oxygen consumption rates of O. fasciatus were the highest in continuous light (24L:0D) followed by 12L:12D and 0L:24D (P<0.001). The oxygen consumption of fish exposed to the 12L:12D photoperiod was significantly higher during the light phase than during the dark phase under all temperature treatments (P<0.001). In summary, oxygen consumption rates of the juvenile parrot fish increase with increasing water temperature and lengthening daylight period; and, thereby, changes in water quality resulted from the depletion of oxygen under high temperature and long daylight photoperiod conditions should be monitored.

• KCID journal
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• v.17 no.2
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• pp.57-70
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• 2010

This study was performed to analyze the affect of water supply capacity followed by allocating flood control volume in heightening reservoir, of which Baekgog reservoir was selected as a case study in here. Baekgog reservoir is located in Jincheon county, Chungbuk province, of which full water level will be heightened from EL. 100. 1m to EL. 102.1m, and total storage from 21.75M $m^3$ to 26.67M $m^3$. Flood inflow with 200year frequency was estimated to 997 $m^3$/s in peak flow and 22.54M $m^3$ in total volume. Reservoir flood routing was conducted to determine flood limited water levels, which was determined to have scenarios such as EL 97-98-99m in periods of 6.21.-7.20., 7.21.-8.20., and 8.21.-9.20., respectively, EL 97-97-97m, EL 98-98-98m in present reservoir, and EL 99-100-101m, EL 99-99-99m, and EL 100-100-100m in heightened reservoir. Reservoir inflow was simulated by DAWAST model. Annual paddy irrigation requirement was estimated to 33.19M $m^3$ to 2,975ha. Instream flow was allocated to 0.14mm/d from October to April. Operation rule curve was drawn using inflow, irrigation and instream flow requirements data. In case of withdrawal limit reservoir operation using operation rule curve, reduction rates of annual irrigation supply before and after flood control by reservoir were 2.0~4.3% in present size and 1.5~3.6% in heightened size. Reliability on water supply was decreased from 77.3% to 63.6~68.2% in present size and from 81.6% to 72.7~79.5% in heightened size. And reduction rates of water storage at the end of year before and after flood control by reservoir were 7.3~16.5% in present size and 7.7~16.9% in heightened size. But water supplies were done without any water deficiency through withdrawal limit reservoir operation in spite of low flood regulating water level.

• The Journal of the Korea Contents Association
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• v.4 no.2
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• pp.7-12
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• 2004

The technique of birdeye image generation of terrain through the use of satellite digital images and digital maps are very important elements and have applications in fanning establishment as well as the actual design of several construction works in complex fields. This paper studies stereo perspective image generation as a possibility through 3-dimensional analysis combined with digital elevation data and remotely sensed images. For this, first of all, ortho-images generated by very accurate GCP and DEM from contour file makes 3-dimensional terrain analysis possible and allows stereo­viewing at the highway construction planning sites. So, we developed the technical methods for the 3-dimensional approach on the planning sites of highways by use of perspective orthoimages. From this research, diverse terrain analysis is possible through stereo perspective image generation, and can leads to various application in road construction through gain study results from access to realtime virtual spatial on the objects area in korea.