• Journal of the Korea Concrete Institute
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• v.17 no.4 s.88
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• pp.521-526
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• 2005

Prestressing tendons in a nuclear containment building dome are non-axisymmetrically arranged in most cases. However, simple axisymmetric modeling of the containment has been often employed in practice to estimate structural behavior for the axisymmetric loadings such as an internal pressure. In this case, the axisymmetric approximation is required for the actual tendon arrangements in the dome. Some procedures are proposed that can implement the actual 3-dimensional tendon stiffness and prestressing effect into the axisymmetric model. Prestressing tendons, which are arranged in 3 or 2-ways depending on a containment type, are converted into an equivalent layer to consider the stiffness contribution in meridional and hoop directions. In order to reflect the prestressing effect, equivalent load method and initial stress method are devised and the corresponding loads or stresses are derived in terms of the axisymmetric model. In a companion paper, the proposed schemes are applied into CANDU and KSNP(Korean Standard Nuclear Power Plant) type containments and are verified through some numerical examples comparing the analysis results with those of the actual 3-dimensional model.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.39-48
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• 2020

This study proposes a fast estimation method of dynamic reliability indices or failure probability for SDOF structure subjected to earthquake excitations. The proposed estimation method attempts to derive coefficient function for correcting dynamic effects from static reliability analysis in order to estimate the dynamic reliability analysis results. For this purpose, a total of 60 cases of structures with various characteristics of natural frequency and damping ratio under various allowable limits were taken into account, and various types of approximation coefficient functions were considered as potential candidate models for dynamic effect correction. Each reliability index was computed by directly performing static and dynamic reliability analyses for the given 60 cases, and nonlinear curve fittings for potential candidate models were performed from the computed reliability index data. Then, the optimal estimation model was determined by evaluating the accuracy of the dynamic reliability analysis results estimated from each candidate model. Additional static and dynamic reliability analyses were performed for new models with different characteristics of natural frequency, damping ratio and allowable limit. From these results, the accuracy and numerical efficiency of the optimal estimation model were compared with the dynamic reliability analysis results. As a result, it was confirmed that the proposed model can be a very efficient tool of the dynamic reliability estimation for seismically excited SDOF structure since it can provide very fast and accurate reliability analysis results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.944-951
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• 1988

Global-Local Laminate Variational Model is utilized to investigate the characteristics of interlaminar stresses in thick composite laminates under uniform axial extension. Various laminates with different fiber orientation and stacking sequences are analyzed to observe the behavior of interlaminar normal stresses. From this result, the interlaminar normal stress distribution along the laminate interfaces is examined and discussed with an existing approximation model. The repeated stacking of Poisson's ratio symmetric sublaminates is found to be the best stacking method of thick composite laminates to reduce the interlaminar normal stresses for the prevention of the free-edge delamination.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.33-39
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• 2023

Recently, reinforcement learning has been used to improve the communication performance of flying ad-hoc networks (FANETs) and to design mobility models. Mobility model is a key factor for predicting and controlling the movement of unmmaned aerial vehicle (UAVs). In this paper, we designed and analyzed the performance of Q-learning with fourier basis function approximation and Deep-Q Network (DQN) models for optimal path finding in a three-dimensional virtual environment where UAVs operate. The experimental results show that the DQN model is more suitable for optimal path finding than the Q-learning model in a three-dimensional virtual environment.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.3
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• pp.235-240
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• 2010

Purpose: In this study, we proposed a simple accommodation-dependent crystalline lens with a constant volume and homogeneous refractive index. Methods: We proposed a human crystalline lens with two aspheric surfaces. Two surfaces intersect in two points and straight line between two points was equator(2b). It assumed that the derivative in axial direction was zero at the equator and the radial derivative was zero at the vertex. Proposed human crystalline lens was divided by the equator into the anterior and posterior parts. It was assume that the volume of each part and refractive index of the human crystalline lens were constant during accommodation. Results: For the changes during accommodation, geometrical parameters were determined by different objective distances. Considering the constant volume of each part with the small decrement of the equator, we obtained the paraxial parameters, such as the anterior and posterior vertex radius of curvature and lens thickness. Compared with the experimental data published in the literature, calculated values using simple approximation showed similar change per accommodative stimulus. Conclusions: These results showed that proposed simple approximation using assumption of constant volume and refractive index of the human crystalline lens made it possible to predict changes of geometrical parameters during accommodation.

• The Korean Journal of Pesticide Science
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• v.9 no.2
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• pp.140-145
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• 2005

Quantitative Structure Activity Relationship (QSAR) assumes the relatedness between physical property and biological activity. However, activity data measured at single concentration such as percent activity have not been used extensively for modeling purpose. This probably comes from the fact that these values are qualitative instead of quantitative. To utilize percent activity data for molecular modeling, we classified the whole data into two classes. One class represents the active while the other signifies the inactive. The percent activity data of ${\beta}$-Ketoacetoanilides measured for TLB (Tomato Late Blight) were investigated. CoMFA (Comparative Molecular Field Analysis) was used as a discriminant function. Using CoMFA provides 3D (three dimensional) information, which is crucial for chemical insight. It can also serve as a predictive model. The resultant model classified the given data correctly (98%). When LOO (leave-one-out) crossvalidation procedure was applied, the classification accuracy was 69%. Therefore two class approximation of percent activity data with CoMFA can be utilized to understand the relationship between chemical structure and biological activity and design subsequent chemical analogs.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.167-174
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• 2010

Recently the distributed topology control algorithm for constructing the Recrystallization Topology in the unstructured peer-to-peer network was proposed. In this paper, we prove that such a hierarchical topology is a scale-free power-law network. We present a model of a construction process of the distributed protocol, and analyze it based on a mean-field approximation and the continuum theory, so that we show that the constructed Recrystallization Topology is a scale-free network. In the proposed model, all nodes are born with some initial attractiveness and the system incorporates the rewiring of some links at every time step. Some old links are removed with the anti-preferential probability, and some new links are added with preferential probability. In other words, according to the distributed algorithm, each node makes connections to the more-preferential nodes having higher hit-ratio than other nodes, while it disconnects the anti-preferential nodes having lesser hit-ratio. This gives a realistic description of the local processes forming the recrystallization topology in unstructured peer-to-peer network. We calculate analytically the degree distribution. The analytic result indicates that the constructed network is a scale-free network, of which the scaling exponent is 3.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.254-265
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• 2021

Purpose: Inspection and diagnosis on the performance and safety through domestic port facilities have been conducted for over 20 years. However, the long-term development strategies and directions for facility renewal and performance improvement using the diagnosis history and results are not working in realistically. In particular, in the case of port structures with a long service life, there are many problems in terms of safety and functionality due to increasing of the large-sized ships, of port use frequency, and the effects of natural disasters due to climate change. Method: In this study, the maintenance history data of the gravity type quay in element level were collected, defined as big data, and a predictive approximation model was derived to estimate the pattern of deterioration and aging of the facility of project level based on the data. In particular, we compared and proposed models suitable for the use of big data by examining the validity of the state-based deterioration pattern and deterioration approximation model generated through machine learning algorithms of GP and SGP techniques. Result: As a result of reviewing the suitability of the proposed technique, it was considered that the RMSE and R² in GP technique were 0.9854 and 0.0721, and the SGP technique was 0.7246 and 0.2518. Conclusion: This research through machine learning techniques is expected to play an important role in decision-making on investment in port facilities in the future if port facility data collection is continuously performed in the future.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.189-203
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• 1992

Any money model should address the most important phenomenon of a monetary economy, which is the phenomenon of the rate of return dominance. Even if the holding returns on financial or nonfinancial assets are higher than the rate of return on fiat money holding, which is typically zero, people still hold and use money. In a period of accelerating inflation, number of dominating assets increases continuously, yet people continue to hold and use money. Wallace's (1980) overlapping generations model cannot address the rate of return dominance phenomenon. His model does not capture the mediun of exchange role of fiat money. In this paper, an overlapping types model of fiat money is constructed, in which different types of consumers have different preferences on different types of goods, are endowed with different types of goods, are located at seperated regions, and live for only two periods. In this model, people hold and use money despite the dominating assets, even if inflation accelates. Money in this case serves as a pure medium of exchange, whereas in Wallace's model, money serves as a pure store of value, and money disappears if a dominating asset exists. An interesting feature of the overlapping types model presented in this paper is that money does not provide a cheap approximation to an idealized and efficient real allocation. A monetary economy is always superior to a nonmonetary economy, because money helps overcome the incompleteness of the overlapping types friction. In a monetary economy, however, a pareto optimal allocation cannot always be achieved, because money cannot always overcome the overlapping types friction itself. Therefore, with the criterion of optimality of real allocations, the monetary economy is more optimal than a nonmonetary economy but less optimal than a complete Arrow-Debreu economy. This feature has important implications on macro modelling. Because of the difficulty in introducing money into a macro model in an essential and endogenous manner as in the overlapping types model of this paper, a macro model typically ignores money and studies real allocations without the money factor. The possible inefficiencies of a monetary economy, relative to a complete real Arrow-Debreu economy, may indicate differences in real allocations between the two models.

• Transactions of the Korean hydrogen and new energy society
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• v.22 no.3
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• pp.386-401
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• 2011

Mathematical models for various steps in coal gasification reactions were developed and applied to investigate the effects of operation parameters on dynamic behavior of gasification process. Chemical reactions considered in these models were pyrolysis, volatile combustion, water shift reaction, steam-methane reformation, and char gasification. Kinetics of heterogeneous reactions between char and gaseous agents was based on Random pore model. Momentum balance and Stokes' law were used to estimate the residence time of solid particles (char) in an up-flow reactor. The effects of operation parameters on syngas composition, reaction temperature, carbon conversion were verified. Parameters considered here for this purpose were $O_2$-to-coal mass ratio, pressure of reactor, composition of coal, diameter of char particle. On the basis of these parametric studies some quantitative parameter-response relationships were established from both dynamic and steady-state point of view. Without depending on steady state approximation, the present model can describe both transient and long-time limit behavior of the gasification system and accordingly serve as a proto-type dynamic simulator of coal gasification process. Incorporation of heat transfer through heterogenous boundaries, slag formation and steam generation is under progress and additional refinement of mathematical models to reflect the actual design of commercial gasifiers will be made in the near futureK.