• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.253-261
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• 2024

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4367-4381
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• 2023

Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called "Digital I&C PSA - Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)", which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017-2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.2
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• pp.155-163
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• 2007

High Strength Concrete (HSC) has weakness that in a fire, it is spalled and brittles. The phenomenon of spalling is made by water vapor's (resulting from evaporation in the material at over $100{^{\circ}C}$)' being confined in watertight concrete. As the concrete strength increases, the degree of damage caused by the spalling becomes more serious because of the permeability. It is reported that the polypropylene(PP) fiber has an important role in protecting concrete from spalling and the optimum dosage of PP fiber is 0.2%. This study was conducted on the nonreinforced concrete specimens. The high-temperature behavior of high-strength reinforced concrete columns with various concrete strength and various dosage of PP fibers was investigated in this study. The results show that the ratio of unstressed residual strength of columns increases as the concrete strength increases and the ratio of unstressed residual strength of columns increases as the dosage of PP fiber increases from 0% to 0.2%, however, the effect of fiber dosage on residual strength of column barely changes above 0.2%.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.98-106
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• 2019

The coefficient and exponent of the MUSLE(Modified Universal Soil Loss Equation) runoff factor in the SWAT(Soil and Water Assessment Tool) model are 11.8 and 0.56 respectively, which are equally applied to the estimation of soil erosion regardless of land use. they could derive overestimation or underestimation of soil erosion, which can cause problems in the selection of soil erosion-vulnerable area and evaluation of reduction management. However, there are no studies about the estimation of coefficients and exponent for the MUSLE runoff factor by land use and their applicability to the SWAT model. Thus, in order to predict soil erosion and sediment behavior accurately through SWAT model, it is necessary to estimate the coefficient and exponent of the MUSLE runoff factor by land use and evaluate its applicability. In this study, the coefficient and exponent of MUSLE runoff factor by land use were estimated for Gaa-cheon Watershed, and the differences in soil erosion and sediment from SWAT model were analyzed. The coefficient and exponent of runoff factor estimated by this study well reflected the characteristics of soil erosion in domestic highland watershed. Therefore, in order to apply the MUSLE which developed based on observed data of US agricultural basin to the domestic watershed, it is considered that a sufficient modification and supplementation process for the coefficient and exponent of the MUSLE runoff factor depending on land use is necessary. The results of this study can be used as a basic data for selecting soil erosion vulnerable area in the non-point source management areas and establishing and evaluating soil erosion reduction management.

• Korean Journal of Environment and Ecology
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• v.30 no.2
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• pp.165-172
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• 2016

Mallard and Spot-billed ducks that are typical wintering water birds use the wide rice field in the center of the water system as a wintering ground. I try to figure out the daily movement distance from Home-Range to wintering ground for mallard and spot-billed ducks in Mangyunggang, Dongjingang where located in central region. In 2015 wintering period by using a Cannon-net, I attached WT-300 to 5 mallard and 5 spot-billed ducks. Daily movement distance is an overall average 0.89km, the largest distance was 31.09km. Daily movement distance of mallard was 0.97km, the largest distance was 28.78km. Daily movement distance of Spot-billed ducks was 0.80km, the largest distance was 33.39km. Home-Range analysis is used by the SHP files that is compatible with GIS and ArcGIS 9.0 Animal Movement Extension, it was analyzed using the Minimum Convex Polygon Method (MCP) and the Kernel Density Estimation (KDE). The behavior rights of two kinds of ducks was $490.34km^2$ by Minimum Convex Polygon Method (MCP) ($SD=311.20km^2N=10$), an important habitats Kernel Density Estimation (KDE 50%) was $42.24km^2$. Home-Range of Mallard (MCP) was $568.02km^2$, it is wider than home-range(MCP) of spot-billed duck $397.13km^2$ relatively, the core habitats of mallard is $53.05km^2$, it is wider than mallard's core habitats(KDE 50%) $29.26km^2$ relatively.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Korean Journal of Materials Research
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• v.4 no.8
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• pp.906-914
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• 1994

Plastic behavior of two-phase intermetallic compounds based on $LI_{2}$-type $(Al, Cr)_3$ Ti was investigated using compression test at R.T. and 77K. $LI_{2}$ single phase alloys and two-phase alloys consisting of mainly $LI_{2}$ phase and a few or 20% second phases were selected from AI-Ti-Cr phase diagram. In general, compared with Llz single phase, two-phase alloys consisting of 20% second phase showed relatively high yield strength and poor ductility. Among the alloys, however, AI-21Ti-23Cr alloy consisting of 20% $Cr_{2}Al$ phase showed available ductility as well as high yield strength. Plastic behavior of $LI_{2}$ single phase alloys and two-phase alloys consisting of a few% $Cr_{2}Al$ was also investigated. Homogenization of arc melted ingots substantially reduced the amount of second phases but introduced extensive pore. When Cr content increased in $Ll_{2}$ single phase alloys after the homogenization, the volume fraction of pore in the alloys decreased, and no residual pore was observed in two-phase alloys consisting of a few% $Cr_{2}Al$ phase. Environmental effect on the ductility of the alloys was investigated using compression test at different strain rates($1.2 \times 10^{-4}/s$ and $1.2 \times 10^{-2}/s$). Environmental embrittlement was least significant in A1-25Ti-10Cr alloy consisting of LIZ single phase among the alloys tested in this study. However, based on the combined estimation of the pore formation, environmental embrittlement and ingot cast structure, AI-21Ti-23Cr alloy consisting of 20% $Cr_{2}Al$ as the second phase is expected to show the best tensile elongation behavior.

• The Korean Journal of Physiology
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• v.1 no.2
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• pp.169-175
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• 1967

An experiment was designed to see if the hippocampus exerts any influence upon the aggressive behavior of male rats. Fighting between rats was observed for the estimation of aggressiveness. Seventeen rats in which the hippocampus was almost totally removed through a small hole with a diameter around 3 mm made in the neocortex at the boundary between the parietal and occipital lobes (hippocampal group), 8 rats with similar neocortical damage alone (operated control group), and 17 normal control rats (normal group) were prepared and subjected to the experiment 3 months after the operation. Applying electric shock of short duration to the feet in a box with grid floor, a fight was provoked between an animal belonging to the hippocampal group and one belonging to the nor-mal group, between a rat of the hippocampal group and one of the operated control group, and also between a rat of the operated control group and one of the normal group. Three observers judged the performance of each animal independently and described it as winning, defeated, tied, or non-fighting. Fifteen shocked trials were administered to each pair of animals with around 2 minutes' interval between each trial. An animal received a 'judging score' of 3 when it won more frequently than was defeated, a judging score of 2 when it won as frequently as was defeated, when all fights were tied, or when no fighting occurred, while it received a judging score of 1 when it won less frequently than was defeated. Group differences in performances were analyzed in terms of judging score using Kolmogorov-Smirnov test for one sample. The results obtained were as follows: 1. In the fights between the hippocampal and the normal groups, the hippocampal animals made significantly better judging scores than the normal animals did (Table 1). 2. There was no significant difference between the hippocampal and the operated control group as to the judging scores they made in the course of fights between the two groups. However, the hippocampal animals tended to dominate over the operated control group as judged by comparing the total 'winning' of the former (30) to that of the latter (14) (Table 2). 3. The total judging score made by the operated control group in the course of the fights against the normal group was not significantly superior to that made by the normal group (Table 3). It was inferred from the above results that, though inconspicuous, the hippocampus tended to exert an inhibitory influence upon the aggressive behavior of male rats.

• Journal of Distribution Research
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• v.16 no.4
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• pp.29-64
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• 2011

Overview of Research: Product availability is one of important competences of store to fulfill consumer needs. If stock-outs which means a product what consumer wants to buy is not available occurs, consumer will face decision-making uncertainty that leads to consumer's negative responses such as consumer dissatisfaction on store. Stockouts was much studied in the field of academia as well as practice in other countries. However, stock-outs has not been researched at all in Marketing and/or Distribution area in Korea. The main objectives of this study are to find out determinants of consumer responses such as Substitute, Delay, and Leave(SDL) when consumer encounters out-of-stock situation and then to examine the effects of these factors on consumer responses. Specifically, this study focuses on situational characteristics(e.g., purchase urgency and surprise), store characteristics (e.g., product assortment and store convenience), and consumer characteristics (e.g., brand loyalty and store loyalty). Then, this study empirically investigates relationships these factors with consumers behaviors such as product substitution, purchase delay, and store switching.