• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.481-489
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• 2004

Ship collisions and grounding continue to occur regardless of continuous efforts to prevent such accidents. With the increasing demand for safety at sea and for protection of the environment, it is of crucial importance to be able to reduce the probability of accidents, assess their consequences and ultimately minimize or prevent potential damages to the ships and the marine environment. Numerical simulations for actual collision problem are conducted with a special attention with respect to finite element size, fracture criteria and material properties, which require a careful consideration to improve the accuracy. A parametric analysis varying colliding speed, angle, design loading condition is conducted using nonlinear finite element analysis method for 46,00 dwt Product/chemical carrier. The relationship between the absorbed energy and indentation are derived quantitatively using the insights observed from this study, and a novel design concept for assessing the anti-collision performance are proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.84-91
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• 2005

For long time, the takeoff and landing control of airship was worked by human handling. With the development of the autonomous control system, the exact controls during the takeoff and landing were required and lots of methods and algorithms were suggested. This paper presents the result of airship take-off and landing by buoyancy control using air ballonet volume change and performance control of pitch angle for stable flight within the desired altitude. For the complexity of airship's dynamics, firstly, simple PID controller was applied. Due to the various atmospheric conditions, this controller didn't give satisfactory results. Therefore, new control method was designed to reduce rapidly the error between designed trajectory and actual trajectory by learning algorithm using an artificial neural network. Generally, ANN has various weaknesses such as large training time, selection of neuron and hidden layer numbers required to deal with complex problem. To overcome these drawbacks, in this paper, the RBFN (radial basis function network) controller developed. The weight value of RBFN is acquired by learning which to reduce the error between desired input output through and airship dynamics to impress the disturbance. As a result of simulation, the controller using the RBFN is superior to PID controller which maximum error is 15M.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.5
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• pp.441-449
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• 2015

In this paper we perform a linearized buckling analysis using the Kirchhoff plate theory and the von Karman nonlinear strain-displacement relation. Design sensitivity analysis(DSA) expressions for plane elasticity and buckling problems are derived with respect to Young's modulus and thickness. Using the design sensitivity, we can formulate the topology optimization method for minimizing the compliance and maximizing eigenvalues. We develop a topology optimization method applicable to plate buckling problems using the prestress for buckling analysis. Since the prestress is needed to assemble the stress matrix for buckling problem using the von Karman nonlinear strain, we introduced out-of-plane motion. The design variables are parameterized into normalized bulk material densities. The objective functions are the minimum compliance and the maximum eigenvalues and the constraint is the allowable volume. Through several numerical examples, the developed DSA method is verified to yield very accurate sensitivity results compared with the finite difference ones and the topology optimization yields physically meaningful results.

• Journal of the Korean GEO-environmental Society
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• v.17 no.1
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• pp.5-12
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• 2016

Investigation of in-situ ground in cold region is difficult due to low accessibility and environmental factors. In this study, correlation between dynamic cone resistance and shear strength is suggested to estimate the strength of frozen soils by using instrumented dynamic cone penetrometer. Tests were conducted in freezing chamber after preparing sand-silt mixture with 2.3% water content. Vertical stresses of 5 kPa and 10 kPa were applied during freezing, shearing, and penetration phase to compare the dynamic cone resistance and shear strength. The dynamic cone resistance, additionally, is calculated to minimize the effect of energy loss during hammer impact. Experimental results show that as the shear strength increases, the dynamic cone penetration index (DCPI) decreases nonlinearly, while the dynamic cone resistance increases linearly. This study provides the useful correlation to evaluate strength properties of the frozen soils from the dynamic cone penetration and direct shear tests.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.6
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• pp.417-426
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• 2021

Recently, use of the precast concrete (PC) system, which can increase economy by minimizing field work, has rapidly increased. However, the PC system cannot exhibit structural performance under construction, specifically before integration between members. Furthermore, since it is difficult to secure the structural integrity of beam-column joints even after construction, the PC system is vulnerable to progressive collapse. In the PC system, various types of details for PC beam-column joints have been proposed, while the structural/construction details of PC system generally used in Korea differ from those of overseas PC systems. However, studies on the progressive collapse of the domestic PC system are limited. Thus, in this study, we investigated the structural/construction details of PC beam-column joints mainly used in Korea. Based on the investigation, for the prototype PC system with typical joint details, a nonlinear finite element analysis was carried out to evaluate its structural performance under progressive collapse. Further, a parametric study was performed, and the effect of the design parameters was investigated, to recommend a method to improve the progressive collapse resistance of the PC system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.438-446
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• 2019

This study examined the effects of non - personality behavior of supervisors on the job exhaustion and organizational effectiveness of nurses. A survey in the form of a questionnaire was completed by 250 nurses working at three general hospitals located in Seoul and Gyeonggi from September 20 to October 31, 2014. The collected data were analyzed by frequency analysis, factor analysis, correlation, and linear regression analysis using the SPSS program. The results of the analysis were as follows. First, the effects of the non-personality behavior of supervisors on the job exhaustion of nurses were statistically significant. Second, the effects of non-personality behavior of supervisors on the organizational effectiveness of nurses were statistically significant in job satisfaction, organizational commitment, and organizational citizenship behavior. Third, the effects of job exhaustion on organizational effectiveness of nurses was statistically significant for job satisfaction, job exhaustion, and organizational citizenship behavior. Because the non-personality behavior of a supervisor can have a negative effect on the exhaustion of a nurse's job and the organizational effectiveness, there should be a wide range of human resources and effective task allocations in a hospital to reduce job burnout and increase job satisfaction. In addition, it is necessary for the boss to develop desirable leadership education, appropriate modeling, and reduce their negative influence in the workplace.

• Health Policy and Management
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• v.34 no.1
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• pp.68-77
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• 2024

Background: Depressive disorders can be categorized into daily depression and clinical depression. The experience of depressive disorder can increase health care utilization due to decreased treatment compliance and somatization. On the other hand, the clinical depression group may also experience social prejudice associated with the illness, which can limit their access to health care utilization. In terms of the significance of health care utilization as a factor in individual and social issues, this study aims to compare the health care utilization of the clinical depression group with that of the non-depressed group and the daily depression group. Methods: The analysis utilized the inverse probability of treatment weighting based on the generalized propensity score. Results: As a result of the analysis, clinical depression and daily depression were higher among women, low-income groups, individuals with low education levels, and so forth. The clinical depression group was also higher among individuals who were not economically active, did not have private health insurance, or had multiple chronic diseases. The number of outpatient department visits in the depression group was significantly higher than in the non-depressed group. In addition, the number of outpatient department visits for the clinical depression group was significantly higher than that for the daily depression group. Outpatient medical expenses were higher in the depression group than in the non-depressed group, and there was no significant difference between the clinical depression group and the daily depression group. Conclusion: Health care utilization was higher in the depression group than the non-depressed group, it was also higher in the clinical depression group than the daily depression group.

• Journal of the Korean GEO-environmental Society
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• v.25 no.6
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• pp.5-12
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• 2024

Currently, a grouting method that minimizes damage to the reservoir embankment by injecting solidification agent at low pressure is commonly used to ensure waterproofing and safety of the embankment, but the use of solidification agents can cause issues, such as a decrease in durability and a lack of clear method for determining the mixing ratio. In this study, when the base ground and solidification agent were stirred and mixed at various weight mixing ratios, the permeability coefficient and strength of the mixture were confirmed through laboratory tests, and the optimal mixing ratio was suggested through analysis of the test results. The specimen for the laboratory test was produced considering the mixing ratio of the solidification agent. The specimen for the permeability coefficient test was tested by producing one each of cohesionless and cohesive soil for a mixing amount of 1.5 kN/m³ of solidification agent, and the permeability test results confirmed that the water barrier performance was secured below the permeability coefficient value required by various design criteria. A total of 24 specimens for the strength test were produced, 3 for each of 5 mixing amounts for cohesive soil and 3 mixing amounts for cohesionless soil. The strength test results showed that the uniaxial compressive strength tends to increase linearly with increasing curing time for both cohesionless soil and cohesive soil when the mixing amount is less than 2.0 kN/m³. Therefore, the optimal mixing ratio applied to the site is determined to be mixing amount of 1.5 kN/m³ and 2.0 kN/m³. Finally, numerical analysis reflecting test results was conducted on design case for improvement projects for aging reservoirs embankment to verify the water barrier performance and safety improvement effects.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.42-52
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• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.

• Journal of the Korea Concrete Institute
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• v.27 no.4
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• pp.331-341
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• 2015

The main purpose of this study is reducing the cost and effort for characterization of tensile strength of fiber reinforced concrete, in order to use in structural design. For this purpose, in this study, test for fiber reinforced concrete was carried out. Because fiber reinforced concrete is consisted of diverse material, it is hard to define the correlation between mix proportions and strength. Therefore, compressive strength test and tensile strength test were carried out for the range of smaller than 100 MPa of compressive strength and 0.25~1% of steel fiber volume fraction. as a results of test, two types of tensile strength were highly affected by compressive strength of concrete. However, increase rate of tensile strength was decreased with increase of compressive strength. Increase rate of tensile strength was decreased with increase of fiber volume fraction. Database was constructed using previous research data. Because estimation equations for tensile strength of fiber reinforced concrete should be multiple variable function, linear regression is hard to apply. Therefore, in this study, we decided to use the ANN(Artificial Neural Network). ANN was constructed using multiple layer perceptron architecture. Sigmoid function was used as transfer function and back propagation training method was used. As a results of prediction using artificial neural network, predicted values of test data and previous research which was randomly selected were well agreed with each other. And the main effective parameters are water-cement ratio and fiber volume fraction.