• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.566-574
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• 2021

The process of cavitation involves generation, growth, coalescence, and collapse of small bubbles and is tremendously influenced by bubble-bubble interactions. To understand these interactions, a new cavitation model based on the transport equation is proposed herein. The modified Rayleigh-Plesset equation is analyzed to determine the bubble growth rate by assuming equal-sized spherical bubble clouds. The source term in the transport equation is then derived according to the bubble growth rate with the bubble-bubble interaction. The proposed model is validated by various test simulations, including microscopic bubble cloud evolution as well as macroscopical two- and three-dimensional cavitating flows. Compared with previous models, namely the Kunz and Zwart cavitation models, the newly proposed model does not require adjustable parameters and generally results in better predictions both microscopic and macroscopical cases. This model is more physical.

• Trans-
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• v.14
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• pp.65-92
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• 2023

The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.

• Earthquakes and Structures
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• v.25 no.1
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• pp.15-26
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• 2023

It is of great importance to assess the residual displacement demand in the performance-based seismic design. In this paper, a hybrid deep learning model for predicting the residual displacement spectra under near-fault (NF) ground motions is proposed by combining the long short-term memory network (LSTM) and back-propagation (BP) network. The model is featured by its capacity of predicting the residual displacement spectrum under a given NF ground motion while considering the effects of structural parameters. To construct this model, 315 natural and artificial NF ground motions were employed to compute the residual displacement spectra through elastoplastic time history analysis considering different structural parameters. Based on the resulted dataset with a total of 9,450 samples, the proposed model was finally trained and tested. The results show that the proposed model has a satisfactory accuracy as well as a high efficiency in predicting residual displacement spectra under given NF ground motions while considering the impacts of structural parameters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.3
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• pp.150-159
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• 2019

The bond analysis model equation was proposed through the regression analysis of the experimental values of bond behavior for each rebar. In order to verify the appropriateness of the bond analysis model equation, the bond behaviors calculated by the proposed bond analysis model, BPE model and CMR model were compared with experimental values. The proposed bond model showed the closest behavior to the experimental values when compared to other analysis models. The former models can not consider the different properties of GFRP rebar according to composed materials, mixing and manufacturing method and the latter has limitation to express the relationships between bond behavior because of derived formula by numerical analysis. This study proposed the analytical model different considering bond mechanism according to surface type. In order to verity the appropriateness of the bond analytical model, the bond behaviors calculated by the proposed bond analytical model, BPE model and CMR model were compared with experimental values. The proposed bond model showed the closest behavior to the experimental values when compared to other analysis models.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.121-129
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• 2012

In this paper, we proposed WBAN system model to management an application that requires low rate data transfer in IEEE 802.15.4. We have to use different wireless sensor network technology to transfer different date rate and emergency message in medical application service. A suitable system model for WBAN and a WBAN MAC protocol in order to solve these existing system problems are proposed. Firstly, the priority queuing was applied to contention access period, and the system model which could guarantee transmission of a MAC command frame was proposed. Secondly, the MAC frame was newly defined to use the system model which was proposed above. Thirdly, WBAN CSMA/CA back-off algorithm based on data transmission rate was proposed to enhance data throughput and transmission probability of the data frame which does not have priority in the proposed WBAN system. The proposed algorithm is designed to be variable CSMA/CA algorithm parameter, depending on data rate. For the evaluation of WBAN CSMA/CA algorithm, we used Castalia. As a result of the simulation, it is found that the proposed system model can not only relieve loads of data processing, but also probability of collision was decreased.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.259-270
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• 2013

A speaker's intentions can be represented by domain actions (domain-independent speech act and domain-dependent concept sequence pairs). Therefore, it is essential that domain actions be determined when implementing dialogue systems because a dialogue system should determine users' intentions from their utterances and should create counterpart intentions to the users' intentions. In this paper, a neural network model is proposed for classifying a user's domain actions and planning a system's domain actions. An integrated neural network model is proposed for simultaneously determining user and system domain actions using the same framework. The proposed model performed better than previous non-integrated models in an experiment using a goal-oriented dialogue corpus. This result shows that the proposed integration method contributes to improving domain action determination performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2281-2285
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• 2011

An algorithm for extracting SPICE MOS level 2 model parameters for the high voltage MOSFET DC model is proposed. The optimization method for analyzing the nonlinear data of the current-voltage curve using the Gauss-Newton algorithm is proposed and the pre-process step for calculating the threshold voltage and the mobility is proposed. The drain current obtained from the proposed method shows the maximum relative error of 5.6% compared with the drain current of 2-dimensional device simulation for the high voltage MOSFET.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.781-784
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• 2005

The feed drive inclination significantly influences product quality, machine tool accuracy and life time. However, the accurate measurement of the inclination needs the skilled engineers and the accurate leveling instruments such as spirits or electric levels. In this study a novel methodology for the estimation of inclination angle of machine tool feed drive is proposed. The proposed methodology utilizes the motor current signals and a new mathematical model of machine tool feed drive considering inclination. The experiment results showed that the proposed method successfully estimates the inclination angle, as well as newly proposed model also enhances the accuracy of the machine tool feed drive model by introducing the inclination effects.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.261-266
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• 2004

In this paper, the software reliability growth model which incorporates the periodic maintenance after the release is proposed. Using the proposed model, the debugging and periodic maintenance cost subject to the required level of the software reliability are investigated. An optimal software release time is derived for a fixed interval of periodic maintenance. To validate the proposed model, release times obtained in this study are compared with examples. The proposed investigation is expected to be served as one of factors in determining the release time of the software where periodic maintenance is considered.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.183-189
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• 2011

An alignment algorithm for strapdown inertial navigation systems is proposed, in which the psi angle error model is utilized. The proposed alignment algorithm is derived from the Psi angle error model which has been widely used in real-time navigation systems. The equation for expecting steady state alignment error is also derived. The proposed algorithm was verified through real-time experiments. Experimental results show that the proposed algorithm can be used in the inertial navigation system and GNSS/INS integrated navigation system to get an initial attitude of the vehicle.