• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.3
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• pp.158-169
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• 2019

A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.

• Korean Chemical Engineering Research
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• v.45 no.2
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• pp.133-142
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• 2007

As the environmental pollution caused by excessive uses of chemical fertilizers and pesticides is aggravated, organic farming using pasture and livestock manure is gaining an increased necessity. The application rate of the organic farming materials to the field is determined as a function of crops and soil types, weather and cultivation surroundings. When livestock manure is used for organic farming materials, the volatilization of ammonia from field-spread animal manure is a major source of atmospheric pollution and leads to a significant reduction in the fertilizer value of the manure. Therefore, an ammonia emission model should be presented to reduce the ammonia emission and to know appropriate application rate of manure. In this study, the ammonia emission rate from field-applied pig manure is predicted using an artificial neural network (ANN) method, where the Michaelis-Menten equation is employed for the ammonia emission rate model. Two model parameters (total loss of ammonia emission rate and time to reach the half of the total emission rate) of the model are predicted using a feedforward-backpropagation ANN on the basis of the ALFAM (Ammonia Loss from Field-applied Animal Manure) database in Europe. The relative importance among 15 input variables influencing ammonia loss is identified using the weight partitioning method. As a result, the ammonia emission is influenced mush by the weather and the manure state.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.117-122
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• 2008

Quality control of the concrete pavement in the early stage of curing is very important because it has a conclusive effect on its life span. Therefore, examining and analyzing the initial behavior of concrete pavement must precede an alternative to control its initial behavior. There are largely two influential factors for the initial behavior of concrete pavement. One is the drying shrinkage, and the other is the heat generated by hydration and thermal change inside the pavement depending on the change in the atmospheric temperature. Thus, the coefficient of thermal expansion and drying shrinkage can be regarded as very important influential factors for the initial behavior of the concrete. It has been a general practice up until now to measure the coefficient of thermal expansion from completely cured concrete. This practice has an inherent limitation in that it does not give us the coefficient of thermal expansion at the initial stage of curing. Additionally, it has been difficult to obtain the measurement of drying shrinkage due to the time constraint. This research examined and analyzed the early drying shrinkage of the concrete and measurements of the thermal expansion coefficients to formulate a plan to control its initial behavior. Additionally, data values for the variables of influence were collected to develop a prediction model for the initial behavior of the concrete pavement and the verification of the proposed model. In this research, thermal expansion coefficients of the concrete in the initial stage of curing ranged between $8.9{\sim}10.8{\times}10^{-6}/^{\circ}C$ Furthermore, the effects of the size and depth of the concrete on the drying shrinkage were analyzed and confirmed.

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.37-44
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• 2011

COMS(Chollian) satellite which was launched on June 26, 2010 has three payloads for Ka-band communications, geostationary ocean color imaging and meteorological imaging. In order to make efficient use of the geostationary satellite, a concept of mission operations has been considered from the beginning of the satellite ground control system development. COMS satellite mission operations are classified by daily, weekly, monthly, and seasonal operations. Daily satellite operations include mission planning, command planning and transmission, telemetry processing and analysis, ranging and orbit determination, ephemeris and event prediction, and wheel off-loading set point parameter calculation. As a weekly operation, North-South station keeping maneuver and East-West station keeping maneuver should be performed on Tuesday and Thursday, respectively. Spacecraft oscillator updating parameter should be calculated and uploaded once a month. Eclipse operations should be performed during a vernal equinox and autumnal equinox season. In this paper, operational validations of the major functions in COMS SGCS are presented for the first three month of in-orbit test operations. All of the major functions have been successfully verified and the COMS SGCS will be used for the mission operations of the COMS satellite for 7 years of mission life time and even more.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.4 no.2
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• pp.74-83
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• 2001

The purpose of this study was investigate to the influence of forest roads characteristics and environment factors on the soil erosion, stability and vegetation survival of cut slope in forest roads. The results obtained could be summarized as follows; 1. The correlated factors between slope erosion and variables in cut slope were altitude, convex, degree of slope, length of slope and soil depth. In the stepwise regression analysis, length of slope and soil hardness was a high significant and its regression equation was given by -89.6136 + 15.0667X14 + 16.6713X15($R^2$ = 0.6712). 2. The main factors influencing the stability of cut slope were significant in order of coverage, middle, convex, length of slope and north, and its discriminant equation was given by -1.019 + 0.064X22 - 0.808X8 - 0.622X24 + 0.742X11 - 0.172X14 - 0.545X6 ($R^2$ = 0.793). 3. The centroids value of discriminant function in the stability and unstability estimated to 1.244 and -1.348, respectively. The boundary value between two groups related to slope stability was -0.1038. The prediction rate of discriminant function for stability evaluation of was as high as 91.3%. 4. The dominant species of invasion vegetation on the cut slope consist with Carex humilis, Agropyron tsukushiense var. transiens, Calamagrostis arundinacea, Miscanthus sinensis var. purpurascens, and Ixeris dentata in survey area. The rate of vegetation invasion more increased by time passed. 5. The life form of invasion vegetation in cut slop showed to $H-D_1-R_{2,3}-e$ type of the hemicryptophyte of dormancy form, dissem inated widely by wind and water of dissminule type, moderate extent and narrowest extent of radicoid type, erect form of growth form. 6. The correlated factors between forest enviroment and coverage appeared north, passage years and middle position of slope at 5% level. The forest environment factors influencing the invasion plants in survey area were shown in order to altitude, passage years, rock(none), forest type(mixed) and stone amount. The regression equation was given by 17.5228 - 0.0911X3 + 3.6189X28 15.8493X22 19.8544X25 + 0.3558X26 ($R^2$ = 0.4026).

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• Korea journal of population studies
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• v.19 no.1
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• pp.5-44
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• 1996

Wornen's lahor market participation as well as the policy concern for wider utilization of married women, have continuously grown up. However, research efforts on the determinants of women's labor market participation, in the context of the relationship hetween life courses and active entry into lahor market, has been far behind the growing interest in this field. This study has conducted an event histoiry analysis of women's labor market transition utilizing personal occupational history data collected by the Korea Institute for Women's Development in 1991. The analysis is divided into tow parts: First part introduces logit regression to analyze the determinants of women's labor market participation and exit. The second part employs Cox regression to see the variation of transition rate between employment and non-employment. The result shows that there is a wide variation in women's labor market participation according to age, cohort, and family formation. Special note is needed for the significantly negative effect of marriage and child birth on labor market participation. The transition pattern of lower class women with less education fits well to the prediction of neo-classical economics; but the tendency of highly educated women's regression to non-employment reveals the strong influence of the unfavorable labor market structure, which can be better explained by the neo-structuralist perspective. There is a strong trade-off between productive and reproductive labor of women, which can only be corrected by strong policy implementation, such as extended child care facilities, abolition of discriminatory employment practices, and expansion of flexible part-time employment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.128-139
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• 2017

Railway is one of the public transportation systems along with shipping and aviation. With the recent introduction of high speed train, its proportion is increasing rapidly, which results in the higher risk of catastrophic failures. The wheel bearing to support the train is one of the important components requiring higher reliability and safety in this aspect. Recently, many studies have been made under the name of prognostics and health management (PHM), for the purpose of fault diagnosis and failure prognosis of the bearing under operation. Among them, the most important step is to extract a feature that represents the fault status properly and is useful for accurate remaining life prediction. However, the conventional features have shown some limitations that make them less useful since they fluctuate over time even after the signal de-noising or do not show a distinct pattern of degradation which lack the monotonic trend over the cycles. In this study, a new method for feature extraction is proposed based on the observation of relative frequency energy shifting over the cycles, which is then converted into the feature using the information entropy. In order to demonstrate the method, traditional and new features are generated and compared using the bearing data named FEMTO which was provided by the FEMTO-ST institute for IEEE 2012 PHM Data Challenge competition.

• Journal of Radiation Protection and Research
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• v.44 no.4
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• pp.128-148
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• 2019

Massive environmental monitoring has been conducted continuously since the Fukushima Daiichi Nuclear Power accident in March of 2011 by different monitoring methods that have different features together with migration studies of radiocesium in diverse environments. These results have clarified the characteristics of radiological environments and their temporal change around the Fukushima site. At three months after the accident, multiple radionuclides including radiostrontium and plutonium were detected in many locations; and it was confirmed that radiocesium was most important from the viewpoint of long-term exposure. Radiation levels around the Fukushima site have decreased greatly over time. The decreasing trend was found to change variously according to local conditions. The air dose rates in environments related to human living have decreased faster than expected from radioactive decay by a factor of 2-3 on average; those in pure forest have decreased more closely to physical decay. The main causes of air dose rate reduction were judged to be radioactive decay, movement of radiocesium in vertical and horizontal directions, and decontamination. Land-use categories and human activities have significantly affected the reduction tendency. Difference in the air dose rate reduction trends can be explained qualitatively according to the knowledge obtained in radiocesium migration studies; whereas, the quantitative explanation for individual sites is an important future challenge. The ecological half-lives of air dose rates have been evaluated by several researchers, and a short-term half-life within 1 year was commonly observed in the studies. An empirical model for predicting air dose rate distribution was developed based on statistical analysis of an extensive car-borne survey dataset, which enabled the prediction with confidence intervals. Different types of contamination maps were integrated to better quantify the spatial data. The obtained data were used for extended studies such as for identifying the main reactor that caused the contamination of arbitrary regions and developing standard procedures for environmental measurement and sampling. Annual external exposure doses for residents who intended to return to their homes were estimated as within a few millisieverts. Different forms of environmental data and knowledge have been provided for wide spectrum of people. Diverse aspects of lessons learned from the Fukushima accident, including practical ones, must be passed on to future generations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1413-1424
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• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.