• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.227-232
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• 2008

The present study was investigated the local heat transfer characteristics and temperature distribution on the louver fin by using the expansion model. Heat transfer rate, frost mass and temperature distribution of the louver fin under frosting condition were experimentally investigated. Local heat transfer rate and heat flux on the louver were analyzed by the conduction heat transfer between top and lower part of the louver. The experimental key parameter was brine inlet temperature(-5, -10, $-15^{\circ}C$). The heat transfer performance and frost mass at brine temperature of $-15^{\circ}C$ were increased by maximum 3 time than the brine temperature of $-5^{\circ}C$. At all experimental case, local heat transfer rate and heat flux of the louver were almost symmetry at the louver number of 6. Especially, local heat transfer rate and heat flux were maximum increased on the louver number of 4 and 8.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.05a
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• pp.11-12
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• 2017

This study aims to analyze the properties of the temperature change in vertical reinforcements in outdoor wall structures in winter in relation to the different methods of bubble sheet installation, and to subsequently determine the possibility of initial frost damage to the concrete as a result of low temperature. As for the experimental variables, double bubble sheets were used as curing materials, and the curing method was to model the part where the slab and the wall intersect and the rebar is exposed, and to measure the change of temperature around the exposed rebar in accordance with the change of the coating curing. It was found that by employing curing method B, which is to install the bubble sheet between the vertical reinforcements, the most vulnerable area, which is 50mm below(④) the surface of the concrete, would be lowered to sub-zero temperature 20 hours later than when using curing method A, and that therefore it is more effective to install the bubble sheet between the vertical reinforcements for the prevention of initial frost damage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.593-598
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• 2018

Computational fluid dynamics was used to develop a heat-recovery ventilator for preventing freezing in cold weather. An optimal internal return damper was applied, and a prototype was made for frost and freezing experiments. A total of 16 models were used to design the optimal internal return damper with the maximum exhaust recirculation ratio. The exhaust recirculation ratio of the exhaust air to the outdoor air was 59.9-62.3%. The tests showed that frost and freezing did not occur at outdoor air temperatures of $-15^{\circ}C$ or higher in both exhaust recirculation operation and normal operation. However, at an outdoor air temperature of $-20^{\circ}C$, no freezing occurred in the outdoor air area when the internal return damper was opened by 45 degrees. Heat recovery ventilators for preventing cold weather frost and freezing should be operated in two operation modes: normal and exhaust recirculation mode. An operating algorithm was developed for the heat-recovery ventilator operating in normal mode when the outdoor temperature is higher than $-15^{\circ}C$ and recirculation mode when the temperature is lower.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.381-394
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• 2005

In order to estimate the damage of orchards due' to natural disasters such as typhoon, severe rain, freezing or frost, it is necessary to estimate the number of fruit bearing before and after the damage. To estimate the fruit bearing after the damages are easily done by delegations, but it cost too high to survey every insured farm household and calculate the fruit bearing before the damage. In this article, we suggest to use a random coefficient model to predict the numbers of fruit bearing in the orchards before the damage based on the tree age and the area information.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.71-78
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• 2023

Employee turnover is one of the most important challenges facing modern organizations. It causes job experiences and skills such as distinguished faculty members in universities, rare-specialized doctors, innovative engineers, and senior administrators. HR analytics has enhanced the area of data analytics to an extent that institutions can figure out their employees' characteristics; where inaccuracy leads to incorrect decision making. This paper aims to develop a novel model that can help decision-makers to classify the problem of Employee Turnover. By using feature selection methods: Information Gain and Chi-Square, the most important four features have been extracted from the dataset. These features are over time, job level, salary, and years in the organization. As one of the important results of this research, these features should be planned carefully to keep organizations their employees as valuable assets. The proposed model based on machine learning algorithms. Classification algorithms were used to implement the model such as Decision Tree, SVM, Random Frost, Neuronal Network, and Naive Bayes. The model was trained and tested by using a dataset that consists of 1470 records and 25 features. To develop the research model, many experiments had been conducted to find the best one. Based on implementation results, the Neural Network algorithm is selected as the best one with an Accuracy of 84 percents and AUC (ROC) 74 percents. By validation mechanism, the model is acceptable and reliable to help origination decision-makers to manage their employees in a good manner.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• Journal of the Korean Geotechnical Society
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• v.39 no.5
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• pp.51-63
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• 2023

Numerical analysis was conducted to determine the effect of soil behavior by thawing and freezing of seasonal frozen soil on pile foundations. The analysis was performed using the finite element method (FEM) to simulate soil-pile interaction based on the atmosphere temperature change. Thermomechanical coupled modeling using FEM was applied with the temperature-dependent nonlinear properties of the frozen soil. The analysis model cases were applied to the MCR and HDP models to simulate the elastoplastic behavior of soil. The numerical analysis results were analyzed and compared with various conditions having different length and width sizes of the pile. The results of the numerical analysis showed t hat t he HDP model was relat ively passive, and t he aspect and magnit ude of t he bearing capacit y and displacement of the pile head were similar depending on the length and width of the pile conditions. The vertical displacement of the pile head by thawing and freezing of the ground showed a large variation in displacement for shorter length conditions. In the MCR model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0387 and 0.0277 m, respectively. In the HDP model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0367 and 0.0264 m, respectively. The results of the pile bearing capacity for the two elastoplastic models showed a larger difference in the width condition than the length condition of the pile, with a maximum of about 14.7% for the width L condition, a maximum of about 5.4% for M condition, and a maximum of about 5.3% for S condition. The significance of the effect on the displacement of the pile head and the bearing capacity depended on the pile-soil contact area, and the difference depended on the presence or absence of an active layer in the soil and its thickness.

• Journal of Energy Engineering
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• v.19 no.3
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• pp.151-155
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• 2010

Adequate visibility through a vehicle windshield and frost melting period are critical aspects of major design parameters. To make progress in this area, a good understanding of the flow behavior and heat transfer characteristics produced by the HVAC module is required. The computational study was used to perform the parametric investigation into the defroster nozzle's performance with a full-scale model. The study highlights the drawbacks of current designs and points the way to improve passive defrosting mechanism. The results show that the current design of the defroster nozzles deliver the maximum airflow in the vicinity of the lower part of the windshield, which yields unsatisfactory visibility. Defrosting performance was excellent when the injection angle of the defrost nozzle was 45 degree. The numerical analysis satisfies the criteria provided by NHTSA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• Transactions of the KSME C: Technology and Education
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• v.3 no.1
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• pp.1-13
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• 2015

In this study, a new dynamic VRF-type heat pump simulation model is proposed which incorporates frosting and defrosting models. Toward this end, a simple frosting model based on the perfect analogy, and lumped system based defrost model, are proposed. Then, frosting and defrosting models are incorporated into a dynamic heat pump model which adopts segment-by-segment local heat exchanger model and map-based variable speed compressor model. Thus, the model can naturally represent locally uneven frosting and defrosting on the heat exchanger surface. Developed simulation model is validated against available experimental data to show good agreement within 10% error for capacity and COP. Finally, developed dynamic heat pump model is applied to annual heating season simulation to show that seasonal COP of heat pump is degraded by 7% due to frosting and defrosting.