• Progress in Medical Physics
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• v.10 no.1
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• pp.23-32
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• 1999

Combined MRI and Relaxogram approach was introduced as a very useful tool for fat study. The phantoms simulating homogeneous mixture of fat and non-fat environments were measured with spin echo pulse sequence on a 0.15 T whole body imager. From 45 scans, the Tl values were obtained by fitting the data to continuous distribution (CONTIN) of relaxation time. This relaxogram gives broad distributions of relaxation time, which are characterized by a number of peaks with characteristic T1 values. Two distinct peaks in relaxogram were observed and identified as signals from com oil and gelatin gel. This model system can be served as simulating the distribution of fat in muscle. Also the relative ratio of two components, which is proportional to the area under the peak, is estimated and compared to nominal values. Based on the good agreement between two predictions, the values from our proposed method agreed with nominal values within $\pm$7 % error. The effects of different concentration of contrast agent and different region of interest are presented. To optimize total scan times, the minimum required data points and so further reduction in total scan times are discussed.

• Magazine of the Korea Concrete Institute
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• v.11 no.1
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• pp.279-288
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• 1999

The creep of concrete structures caused by variable stresses is generally calculated by step-by-step method based on the superposition of creep function. Although most practical application is carried out by this linear assumption. significant deviations between predictions and experiments have been observed when unloading takes place, that is. stress is reduced. This shows that the superposition of creep function does not describe accurately the effect of sustained compressive preload. The main purpose of this study is to propose a creep analysis model which is expressed with both creep function and creep recovery function where increase or decrease of stress is repeated. In these two function method, the creep behavior is modelled by using linear creep law for loading and creep recovery law for unloading. To apply two function method to time analysis of concrete structures, the calculation method of creep strain increment under varying stress is proposed. The calculation results based on the present method correlates very well with test data, but the conventional superposition method exhibits large deviation from test results. This paper provides a more accurate method for the time dependent analysis of concrete structures subjected to varying stress, i.e. increasing or decreasing stress. The present method may be efficiently employed in the revision of future concrete codes.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.91-99
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• 2014

The common-rail injectors are the most critical component of the CRDI diesel engines that dominantly affect engine performances through high pressure injection with exact control. Thus, from now on the advanced combustion technologies for common-rail diesel injection engine require high performance fuel injectors. Accordingly, the previous studies on the numerical and experimental analysis of the diesel injector have focused on a optimum geometry to induce proper injection rate. In this study, computational predictions of performance of the diesel injector have been performed to evaluate internal flow characteristics for various needle lift and the spray pattern at the nozzle exit. To our knowledge, three-dimensional computational fluid dynamics (CFD) model of the internal flow passage of an entire injector duct including injection and return routes has never been studied. In this study, major design parameters concerning internal routes in the injector are optimized by using a CFD analysis and Response Surface Method (RSM). The computational prediction of the internal flow characteristics of the common-rail diesel injector was carried out by using STAR-CCM+7.06 code. In this work, computations were carried out under the assumption that the internal flow passage is a steady-state condition at the maximum needle lift. The design parameters are optimized by using the L16 orthogonal array and polynomial regression, local-approximation characteristics of RSM. Meanwhile, the optimum values are confirmed to be valid in 95% confidence and 5% significance level through analysis of variance (ANOVA). In addition, optimal design and prototype design were confirmed by calculating the injection quantities, resulting in the improvement of the injection performance by more than 54%.

• Korean Journal of Environmental Biology
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• v.34 no.1
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• pp.56-62
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• 2016

Pest population density models are very important to monitor the initial occurrence and to understand the continuous fluctuation pattern of pest in pest management. This is one of the major issues in agriculture because these predictions make pesticides more effective and environmental impact of pesticides less. In this study, we combined and predicted the mortality change of pest caused by pesticides with temperature change and population dynamic model. Sensitive strain of two-spotted spider mite (Tetranychus urticae Koch) with kidney bean leaf as host was exposed to mixed acaricide, Acrinathrin-Spiromesifen and organotin acaricide, Azocyclotin, at 20, 25, 30, and $35^{\circ}C$, respectively. There was significant difference in mortality of T. urticae among pesticides and temperatures. We used DYMEX to simulate population density of T. urticae and predicted that the initial management time and number of chemical control would be changed in the future with climate change. There would be implications for strategies for pest management and selection process of pesticide in the future corresponding climate change.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Explosives and Blasting
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• v.17 no.4
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• pp.67-88
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• 1999

Ground settlements induced by tunnel excavation cause the foundations of the neighboring superstructures to deform. An expert system called NESASS was developed to analyze the structural safety of such superstructures. NESASS predicts the trend of ground settlements to be resulted from tunnel excavation and carries out a safety analysis for superstructures on the basis of the predicted ground settlements. Using neural network techniques, NESASS learns a data base consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure and, in turn, determines the safety of the structure. In addition, NESASS predicts the patterns of cracks to be formed on the structure using Dulacskas model for crack evaluation. In this study, the ground settlements measured from the Seoul subway construction sites were collected and sorted with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to verify the reliability of the proposed neural network structure. A comparison of the ground settlement trends predicted by NESASS with the measured ones indicates that NESASS leads to reasonable predictions. An examples is presented in this paper where NESASS is used to evaluate the safety of a structure subject to deformation due to tunnel excavation near to the structure.

• Journal of the Korean GEO-environmental Society
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• v.9 no.5
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• pp.45-52
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• 2008

The present study has extended OpenSees, which is an open-source software framework DOS program for developing applications to idealize geotechnical and structural problems, for the static analysis of axial load capacity and settlement of single piles in MS Windows environment. The Windows version of OpenSees as improved by this study has enhanced the DOS version from a general purpose software program to a special purpose program for driven and bored pile analysis with additional features of pre-processing and post-processing and a user friendly graphical interface. The method used in the load capacity analysis is the numerical methods based on load transfer functions combined with finite elements. The use of empirical nonlinear T-z and Q-z load transfer curves to model soil-pile interaction in skin friction and end bearing, respectively, has been shown to capture the nonlinear soil-pile response under settlement due to load. Validation studies have shown the static load capacity and settlement predictions implemented in this study are in fair agreement with reference data from the static loading tests.

• Journal of the Korean Chemical Society
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• v.27 no.5
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• pp.330-339
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• 1983

The CNDO/2 and STO-3G calculations were performed on nitrogen, oxygen, and sulfur compounds in order to examine the effect of interactions between two nonbonding (n) orbitals in the same molecule separated by N intervening $\sigma$ bonds based on the PMO approach. Calculated basis level energies, energy splittings, and interaction energy changes for both chain and cyclic model compounds were qualitatively compared with the corresponding predictions derived from perturbational formalism for n-n orbital interactions and successfully explained in terms of the derived energy expressions. In general, through-space interaction term could be neglected in the N and O systems. And the calculated results were explained simply by through-bond interaction term. As a result, through-bond interaction placed n- below n+ for odd systems and n+ below n- for even systems. Also energy splittings in odd systems were larger than those in even systems. However, in the cases of cis-ethylene diamine and o-phenylene diamine(conformer VI in Table 4), through-space interaction term was found to be substantial and the opposing effects of through-space and through-bonds interactions were observed. Finally it was found that the interactions between two n orbitals on S atoms always had some contribution of the destabilizing through-space interaction term. This result was consistent with the fact that the lone pair lobes of third elements were larger in size than those of the second period elements.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.301-316
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• 1995

experimental and computational studies ore carried out to investigate the natural convection of the single phase flow in a tank with a heated horizontal plate facing downward. This is a simplified model for investigations of the influence of a core melt at the bottom of a reactor vessel on the thermal hydraulic behavior in a oater filled cavity surrounding the vessel. In this case the vessel is simulated by a hexahedron insulated box with a heated plate Horizontally mounted at the bottom of the box. The box with the heated plate is installed in a water filled hexahedron tank. Coolers are immersed in the U-type water volume between the box and the tank. Although the multicomponent flows exist more probably below the heated plate in reality, present study concentrates on the single phase flow in a first step prior to investigating the complicated multicomponent thermal hydraulic phenomena. In the present study, in order to get a better understanding for the natural convection characteristics below the heated plate, the velocity and temperature are measured by LDA(Laser Doppler Anemometry) and thermocouples, respectively. And How fields are visualized by taking pictures of the How region with suspended particles. The results show the occurrence of a very effective circulation of the fluid in the whole How area as the heater and coolers are put into operation. In the remote region below the heated plate the new is nearly stagnant, and a remarkable temperature stratification can be observed with very thin thermal boundary. Analytical predictions using the FLUTAN code show a reasonable matching of the measured velocity fields.