• Journal of the Korea Concrete Institute
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• v.17 no.4 s.88
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• pp.551-558
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• 2005

The setting and hardening of concrete is accompanied with nonlinear temperature distribution caused by development of hydration heat of cement. Especially at early ages, this nonlinear distribution has a large influence on the crack evolution. As a result, in order to predict the exact temperature history in concrete structures it is required to examine thermal properties of concrete. In this study, the convection heat transfer coefficient which presents thermal transfer between surface of concrete and air, was experimentally investigated with variables such as velocity of wind, curing condition and ambient temperature. At initial stage, the convection heat transfer coefficient is overestimated by the evaporation quantity. So it is essential to modify the thermal equilibrium considered with the boiling effect. From experimental results, the convection heat transfer coefficient was calculated using equations of thermal equilibrium. Finally, the prediction model for equivalent convection heat transfer coefficient including effects of velocity of wind, curing condition, ambient temperature and boiling effects was theoretically proposed. The convection heat transfer coefficient in the proposed model increases with velocity of wind, and its dependance on wind velocity is varied with curing condition. This tendency is due to a combined heat transfer system of conduction through form and convection to air. From comparison with experimental results, the convection heat transfer coefficient by this model was well agreed with those by experimental results.

• Journal of the Korea Concrete Institute
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• v.26 no.6
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• pp.731-739
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• 2014

This paper describes the evaluation of the impact performance of steel fiber-reinforced concrete based on high-velocity impact experiments using hard spherical balls. In this experimental study, panel specimens with panel thickness to ball diameter (h/d) ratios of 3.5 or less were tested with variables of steel fiber volume fraction, panel thickness, impact velocity, and aggregate size. Test results were compared with each other to evaluate the impact resistance. The results showed that the percentage of weight and surface loss decreased as the steel volume fraction increased. However, the penetration depth increased with up to steel fiber volume fraction of 1.5%. Particularly the results of specimens with 20 mm aggregates showed poorer performance than those with 8 mm aggregates. The results also confirmed that the impact performance prediction formulas are conservative with (h/d) ratios of 3.5 or less. Despite the conservative predictions, the modified NDRC formula and ACE formula predict the impact performance more consistently than the Hughes formula.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.12
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• pp.1005-1011
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• 2016

The fundamental reason for gear noise is transmission error. Transmission error occurs because of STE (static transmission error) and DTE (dynamic transmission error), while a pair of gears is meshing. These errors are generated by the deflection of the teeth and the friction on the surface of the teeth. In addition, the vibration generated by transmission error leads to excited bearings. The bearings support the shafts, and the noise is radiated after exciting the gear casing. The analysis of the contact stress in helical gear tooth flanks indicates that it is due to impact loading, such as the sudden engagement and disengagement of a gear. Stress analysis is performed for different roll positions, in order to determine the most critical roll angle. Dynamic analysis is performed on this critical roll position, in order to evaluate variation in stresses and tooth contact force, with respect to time. In this study, transmission error analysis was implemented on a spur and helical gear with involute geometry and a modified geometry profile. In addition, in order to evaluate the intensity of impact due to sudden engagement and significant backlash, the impact factor was calculated using the finite element analysis results of static and dynamic maximum bending stresses.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.135-143
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• 2006

This study presents the results of a series of laboratory scale slope failure experiments aimed at clarifying the process and the condition leading to the initiation of rainfall-induced slope failures. For the evaluation of hydrologic response of the model slopes in relation the process of failure initiation, measurements were focused on the changes in volumetric water content during the initiation process. The process leading to failure initiation commences by the development of a seepage face. It appears reasonable to conclude that slope failures are a consequence of the instability of seepage area formed at the slope surface during rainfall period. Therefore, this demonstrates the importance of monitoring the development seepage area for useful prediction about the timing of a particular failure event. The hydrologic response of soil slopes leading to failure initiation is characterized by three phases (phase I, II and III) of significant increase in volumetric water content in association with the ingress of wetting front and the rise of groundwater level within the slope. The period of phase III increase in volumetric water content can be used to initiate advance warning towards a failure initiation event. Therefore, for the concept outlined above, direct and continuous monitoring of the change in volumetric water content is likely to provide the possibility for the development of a reliable and effective means of predicting the occurrence of rainfall-induced slope failures.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Food Science of Animal Resources
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• v.30 no.3
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• pp.487-494
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• 2010

Cooked pork can be easily contaminated with Staphylococcus aureus during carriage and serving after cooking. This study was performed to develop growth prediction models of S. aureus to assure the safety of cooked pork. The Baranyi and Gompertz primary predictive models were compared. These growth models for S. aureus in cooked pork were developed at storage temperatures of 5, 15, and $25^{\circ}C$. The specific growth rate (SGR) and lag time (LT) values were calculated. The Baranyi model, which displayed a $R^2$ of 0.98 and root mean square error (RMSE) of 0.27, was more compatible than the Gompertz model, which displayed 0.84 in both $R^2$ and RMSE. The Baranyi model was used to develop a response surface secondary model to indicate changes of LT and SGR values according to storage temperature. The compatibility of the developed model was confirmed by calculating $R^2$, $B_f$, $A_f$, and RMSE values as statistic parameters. At 5, 15 and $25^{\circ}C$, $R^2$ was 0.88, 0.99 and 0.99; RMSE was 0.11, 0.24 and 0.10; $B_f$ was 1.12, 1.02 and 1.03; and $A_f$ was 1.17, 1.03 and 1.03, respectively. The developed predictive growth model is suitable to predict the growth of S. aureus in cooked pork, and so has potential in the microbial risk assessment as an input value or model.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.4
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• pp.588-594
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• 1997

In this study, the shelf-life of Kochujang during storage was predicted through physicochemical and sensory analyses. Amino nitrogen, lightness, characteristics of surface color, pH and number of viable cell counts in Kochujang decreased during storage, while ammonia nitrogen, titratable acidity and viscosity increased. Among the physicochemical analyses, amino nitrogen content exhibited the highest correlation with sensory score. The marginal amounts of amino nitrogen was 170.6mg%. Degradation rate of amino nitrogen was a first order reaction. Q$_{10}$-value and the activation energy of Kochujang during storage were 1.80 and 8.6kca1/mol, respectively. The shelf-life Predicted of Kochujang at each storage temperature was calculated. The shelf-life predicted was 467 days at 1$0^{\circ}C$, 261 days at 2$0^{\circ}C$ and 133 days at 35$^{\circ}C$.

• Food Science and Preservation
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• v.12 no.4
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• pp.344-349
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• 2005

Microwave-assisted process (MAP) was applied to extract antioxidant-related components from Thymus quinquecostatus var. japonica Hara. Microwave power(2,450 MHz, $0{\sim}160$ W) and extraction time($1{\sim}5\;min$) were used as independent variables($X_i$) for central composite design to yield 10 different extraction conditions. Response surface methodology was applied to predict optimum extraction conditions for dependent variables of extracts, such as total yield, total phenolics, flavonoid, and electron donation ability depending on different powers and extraction times of MAP. Determination coefficients($R^2$) of regression equations for dependent variables were higher than 0.93 excluding that of total phenolics, and microwave power was predicted more influential than extraction time in MAP (p<0.05). The optimal extraction time for each dependent variable was ranged from 3.36 to 4.97 min, but microwave power showed wide ranges depending on variables. The superimposed contour maps for maximized dependent variables illustrated extraction conditions of 64 to 100 W in microwave power and 2.9 to 4.0 min in extraction time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.