• Proceedings of the Korea Concrete Institute Conference
• /
• 1990.10a
• /
• pp.57-62
• /
• 1990

This paper is to study the effect of rectilinear confinement in high-strength concrete subjected to a monotonically increasing compressive axial loads. To investigate behavior of columns rectilinearly confined with lateral ties and longitudinal rebars, twelve specimens including two plain concrete specimens were tested. The main variables in this study are volumetric ratio of lateral ties, cistribution of lateral ties, yield strength of logitudinal steel, ratio of area of longitudinal steel to the area of cross section. The test results were not only compared with an empirical model for the stress-strain curve of rectilinearly confined high-strength concrete but also the existing model. The empirical model used calculating column capacity shows better agreement with the test results tham the existing model.

• Journal of the Korea Concrete Institute
• /
• v.11 no.3
• /
• pp.69-80
• /
• 1999

The strengthening of reinforced concrete structures by externally bonded GFRP has become increasingly common in resent years. However the analysis and design method for GFRP plate strengthening of RC beams is not well established yet. The purpose of present paper is, therefore, to define the failure mechanism and failure behavior of strengthened RC beam using GFRP and then to propose a resonable method for the calculation of interface debonding load for those beams. From the experimental results of beams strengthened by GFRP, the influence of length and thickness, width of plate on the interfacial debonding failure behavior of beam is studied and, on the basis of test results, the semi-empirical equation to predict debonding load is developed. The proposed theory based on nonlinear analysis and critical flexural crack width, predicts relatively well the debonding failure load of test beams and may be efficiently used in the analysis and design of strengthened RC beams using GFRP.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.11 no.4
• /
• pp.151-157
• /
• 2003

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model.

• Communications for Statistical Applications and Methods
• /
• v.22 no.4
• /
• pp.361-375
• /
• 2015

A measure of skewness and kurtosis is proposed to test multivariate normality. It is based on an empirical standardization using the scaled residuals of the observations. First, we consider the statistics that take the skewness or the kurtosis for each coordinate of the scaled residuals. The null distributions of the statistics converge very slowly to the asymptotic distributions; therefore, we apply a transformation of the skewness or the kurtosis to univariate normality for each coordinate. Size and power are investigated through simulation; consequently, the null distributions of the statistics from the transformed ones are quite well approximated to asymptotic distributions. A simulation study also shows that the combined statistics of skewness and kurtosis have moderate sensitivity of all alternatives under study, and they might be candidates for an omnibus test.

• Journal of Industrial Convergence
• /
• v.3 no.1
• /
• pp.33-54
• /
• 2005

This article examines customer repurchase intention change. Specially we focus whether pre-purchase expectation and post-purchase satisfactions to retailers contribute to repurchase intention change. The previous works of customer satisfaction and repurchase intention were empirically tested the product based on the disconfirmation theory. But this study present the relations between the satisfaction and repurchase intention to stores. First, this study deliberately classified the types of stores. And I set the repurchase intention process apart into three part for empirical wok. In one part, the effect of trust has on expectation was tested. At the second procedure I test the expectation impact to satisfaction. Part three was about the relations between satisfaction and repurchase. In empirical test, convenience 200 sample was used. For these sample I use questionnaires that include the intensity of repurchase intention to postpurchase dissonance. Statistically regression uses as a solid tool to prove the relations between consumer satisfaction and repurchase. MANOVA results support the level of effect that different each store. They were supported through regression analysis. Also, by MANOVA the difference of them was turned out to be significant.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.13 no.1
• /
• pp.57-64
• /
• 2021

Maneuvering motions of a ship in calm water are studied through the concept of MMG model. Governing forces are defined by the use of available empirical formulae that require only main ship particulars as input variables. In order to validate the calculation tool, a full-scale sea experiment was carried out in Osaka Bay using a 17-m twin-screw passenger ferry. Test execution and data measurement were performed through the utilization of an autopilot control unit and satellite compass. The result of a straight running test confirms the acceptable accuracy in addressing the surge motion problem. Reasonable agreement between simulation and experiment is also confirmed for 5°/5° and 10°/10° zig-zag tests despite the strong environmental disturbance. The current model can generally represent the subject ship maneuvering motions and is promising for the application to other ship hulls.

• Smart Structures and Systems
• /
• v.30 no.2
• /
• pp.209-219
• /
• 2022

The determination for bearing capacity of precast nodular piles is conventionally time-consuming and high-cost by using numerous experiments and empirical methods. This study proposes an intelligent method to evaluate the bearing capacity and shaft resistance of the nodular piles with high efficiency based on long short-term memory (LSTM) approach. A series of field tests are first designed to measure the axial force, shaft resistance and displacement of the combined nodular piles under different loadings, in comparison with the single pre-stressed high-strength concrete piles. The test results confirm that the combined nodular piles could provide larger ultimate bearing capacity (more than 100%) than the single pre-stressed high-strength concrete piles. Both the LSTM-based method and empirical methods are used to calculate the shift resistance of the combined nodular piles. The results show that the LSTM-based method has a high-precision estimation on shaft resistance, not only for the ultimate load but also for the working load.

• Korean Business Review
• /
• v.9
• /
• pp.24-41
• /
• 1996

• Journal of Distribution Science
• /
• v.14 no.11
• /
• pp.129-138
• /
• 2016

Purpose - The ICT(information and communications technologies) development is affecting consumer behaviors on selecting channel or distribution system. This study aims to advance our knowledge about the factors influencing omni-channel behaviors. This study considers the positive brand experience as the moderating variable into the relationship between omini-channel use intention and consumer brand relation. Also, the effect of positive brand experience on consumer-brand relation is researched. Research design, data, and methodology - This study conducted an empirical test with the subject as customers who purchase goods or service through on-off cross channel simultaneously. The research model is developed from prior literatures about influencing variables on channel selection. The structure of this study is designed to identify causal relationships between the variables. 268 survey data from the questionnaire survey which is conducted to target customers who use online and offline channels, is used for empirical analysis. This study validates generality with descriptive statistics and data reliability with Cronbach's alpha value. The exploratory factor analysis is used for value purification. Then, the confirmatory factor analysis is conducted for structural equation modeling. Finally, the execute structural equation modeling is analyzed to confirm the hypotheses Results - First, the two causal influences between perceived performance risk and the propensity of omni-channel and between price consciousness and the propensity of omni-channel are verified through the empirical test. Second, the result identifies that the propensity of omni-channel is influenced on consumer-brand relationship. Third, the AMOS analysis proves that the moderating variable, positive brand experience, has significant positive impact on consumer-brand relationship. This significant relationship is highly supported by the regression analysis between brand experience and propensity of omni-channel because it results that positive brand experience has positive impact on the propensity of omni-channel. All hypotheses are verified to be true. Conclusions - Based on the empirical result, this study confirms that perceived performance risk and price consciousness are the important factors influencing propensity of omni-channel. According to the additional analysis, the moderating variable and positive brand experience plays important role between the propensity of omni-channel and consumer-brand relationship. Furthermore, positive brand experience influences more on consumer-brand relationship than non-positive brand experience.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.5
• /
• pp.836-842
• /
• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.