• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.26-35
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• 2003

This study explains the effects of lubricant and surface treatment on hot forging die life. The mechanical and thermal load, and thermal softening which is happened by the high temperature of die, in hot and warm forging, cause die wear, heat checking and plastic deformation, etc. This study is fur the effects of solid lubricants and surface treatment condition for hot forging die. Because cooling effect and low friction are essential to the long life of dies, optimal surface treatment and lubricant are very important to improve die life for hot forging process. The main factors, which affect die hardness and heat transfer, are surface treatments and lubricants, which are related to thermal diffusion coefficient and heat transfer coefficient, etc. For verifying these effects, experiments are performed for hot ring compression test and heat transfer coefficient in various conditions as like different initial billet temperatures and different loads. The effects of lubricant and surface treatment for hot forging die life are explained by their thermal characteristics. The new developed technique in this study for predicting tool life can give more feasible means to improve the tool life in hot forging process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.335-344
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• 2006

In this study, sequential mixing model (SMM) was proposed based on the Taylor's theory which can be summarized as the fact that longitudinal advection and transverse diffusion occur independently and then the balance between the longitudinal shear and transverse mixing maintains. The numerical simulation of the model were performed for cases of different mixing time and transverse velocity distribution, and the results were compared with the solutions of 1-D longitudinal dispersion model (1-D LDM) and 2-D advection-dispersion model (2-D ADM). As a result it was confirmed that SMM embodies the Taylor's theory well. By the comparison between SMM and 2-D ADM, the relationship between the mixing time and the transverse diffusion coefficient was evaluated, and thus SMM can integrate 2-D ADM model as well as 1-D LDM model and be an explanatory model which can represents the shear flow dispersion in a visible way. In this study, the predicting equation of the longitudinal dispersion coefficient was developed by fitting the simulation results of SMM to the solution of 1-D LDM. The verification of the proposed equation was performed by the application to the 38 sets of field data. The proposed equation can predict the longitudinal dispersion coefficient within reliable accuracy, especially for the river with small width-to-depth ratio.

• Advances in concrete construction
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• v.17 no.5
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• pp.245-255
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• 2024

The problem of carbonation-induced corrosion has become a concern in recent times, especially in the 21^st century, due to the increase in global temperatures and carbon dioxide (CO₂) concentration in the atmosphere possessing a significant threat to the durability of reinforced concrete (RC) structures worldwide, especially in inland tropical regions where carbonation is the most significant concrete degradation mechanism. Therefore, a study was conducted to predict the impact of global warming on the carbonation of RC structures in Lusaka, Zambia, and Tokyo, Japan. The Impact was estimated based on a carbonation meta-model that applies the analytic solution of Fick's 1st law using literature-based concrete mix design data and forecasted local temperature and CO₂ concentration data over a 100-year period with relative humidity assumed constant. The results showed that CO₂ diffusion increased between 17-31%, effecting a 40-45% rise in carbonation coefficient and a significant reduction in corrosion initiation time of 50-52% in the two cities. Moreover, for the same water-cement ratio, Lusaka showed almost twice higher carbonation coefficient values and one third shorter corrosion initiation time compared to Tokyo, mainly due to its higher temperature and low relative humidity. Additionally, the carbonation propagation depth at the end of 100 years was between 12-22 mm in Tokyo and 18-40 mm in Lusaka. These findings indicate that RC structures in these cities are at risk of rapid deterioration, especially in Lusaka, where they are more vulnerable.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.342-356
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• 2016

Purpose: The drying of a thin layer of native cassava starch in a tray dryer was modeled to establish an equation for predicting the drying behavior under given conditions. Methods: Drying tests were performed using samples of native cassava starch over a temperature range of $40-60^{\circ}C$. We investigated the variation in the drying time, dynamic equilibrium moisture content, drying rate period, critical moisture content, and effective diffusivity of the starch with temperature. The starch diffusion coefficient and drying activation energy were determined. A modification of the model developed by Hii et al. was devised and tested alongside fourteen other models. Results: For starch with an initial moisture content of 82% (db), the drying time and dynamic equilibrium moisture content decreased as the temperature increased. The constant drying rate phase preceded the falling rate phase between $40-55^{\circ}C$. Drying at $60^{\circ}C$ occurred only in the falling rate phase. The critical moisture content was observed in the $40-55^{\circ}C$ range and increased with the temperature. The effective diffusivity of the starch increased as the drying temperature increased from 40 to $60^{\circ}C$. The modified Hii et al. model produced randomized residual plots, the highest $R^2$, and the lowest standard error of estimates. Conclusions: Drying time decreased linearly with an increase in the temperature, while the decrease in the moisture content was linear between $40-55^{\circ}C$. The constant drying rate phase occurred without any period of induction over a temperature range of $40-55^{\circ}C$ prior to the falling rate period, while drying at $60^{\circ}C$ took place only in the falling rate phase. The effective diffusivity had an Arrhenius relationship with the temperature. The modified Hii et al. model proved to be optimum for predicting the drying behavior of the starch in the tray dryer.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.190-198
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• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• Korean Journal of Radiology
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• v.19 no.6
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• pp.1161-1171
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• 2018

Objective: The aim of this study was to investigate diffusion tensor (DT) imaging-derived properties of benign oligemia, true "at risk" penumbra (TP), and the infarct core (IC) during the first 3 hours of stroke onset. Materials and Methods: The study was approved by the local animal care and use committee. DT imaging data were obtained from 14 rats after permanent middle cerebral artery occlusion (pMCAO) using a 7T magnetic resonance scanner (Bruker) in room air. Relative cerebral blood flow and apparent diffusion coefficient (ADC) maps were generated to define oligemia, TP, IC, and normal tissue (NT) every 30 minutes up to 3 hours. Relative fractional anisotropy (rFA), pure anisotropy (rq), diffusion magnitude (rL), ADC (rADC), axial diffusivity (rAD), and radial diffusivity (rRD) values were derived by comparison with the contralateral normal brain. Results: The mean volume of oligemia was $24.7{\pm}14.1mm^3$, that of TP was $81.3{\pm}62.6mm^3$, and that of IC was $123.0{\pm}85.2mm^3$ at 30 minutes after pMCAO. rFA showed an initial paradoxical 10% increase in IC and TP, and declined afterward. The rq, rL, rADC, rAD, and rRD showed an initial discrepant decrease in IC (from -24% to -36%) as compared with TP (from -7% to -13%). Significant differences (p < 0.05) in metrics, except rFA, were found between tissue subtypes in the first 2.5 hours. The rq demonstrated the best overall performance in discriminating TP from IC (accuracy = 92.6%, area under curve = 0.93) and the optimal cutoff value was -33.90%. The metric values for oligemia and NT remained similar at all time points. Conclusion: Benign oligemia is small and remains microstructurally normal under pMCAO. TP and IC show a distinct evolution of DT-derived properties within the first 3 hours of stroke onset, and are thus potentially useful in predicting the fate of ischemic brain.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.4
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• pp.165-173
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• 1998

Analytical solutions to predict the movement rate of submerged mound are derived using the convection coefficient and the joint distribution function of wave heights and periods. Assuming that the sediment is moved onshore due to the velocity asymmetry of Stokes' second order nonlinear wave theory, the micro-scale bedload transport equation is applied to the sediment conservation. The nonlinear convection-diffusion equation can then be obtained which governs the migration of submerged mound. The movement rate decreases exponentially with increasing the water depth, but the movement rate tends to increase as the spectral width parameter, $ u$ increases. In comparison of the analytical solution with the measured data, it is found that the analytical solution overestimates the movement rate. However, the agreement between the analytical solution and the measured data is encouraging since this over-estimation may be due to the inaccuracy of input data and the limitation of sediment transport model. In particular, the movement rates with respect to the water depth predicted by the analytical solution are in very good agreement with the estimated result using the discritization technique with the hindcast wave data.

• Korean Journal of Food Science and Technology
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• v.41 no.3
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• pp.272-277
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• 2009

In this research, three dimensional mathematical models were developed to predict the shelf life of tofu packaged in a semi-rigid plastic container. A model combining oxygen transfer through the package and oxygen consumption within the package was considered. According to the results, the model simulations estimated that the number of microorganisms in the filled water was higher than that in the tofu, suggesting the shelf life of packaged tofu was not affected by the number of microorganisms in the tofu product, but rather by the number of organisms in the filled water. Additionally, the effects of the physical properties of the packaging material, such as oxygen permeability through the package, oxygen diffusion coefficient, the initial oxygen concentration in the filled water, and the depth of the filled water in the packaged tofu, were also observed.

• Earthquakes and Structures
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• v.27 no.2
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• pp.127-142
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• 2024

The amount of wave propagation through a rubber concrete construction is the subject of the current investigation. Rubber tire waste was used to make two different types of cement mixtures. One type contains sand substitute in amounts ranging from 15% to 60% of the total volume, while the other has gravel with diameters of 3/8 and 8/15 and 15% sand in the same mixture. A wide variety of concrete forms and compositions were created, and their viscous and solid state characteristics were assessed, along with their short-, medium-, and long-term strengths. Diffusion, density, mechanical strength resistance to compressive force, and ultrasound wave propagation were also assessed. The water-to-cement ratio and plasticizer were used in this investigation. In the second part of the study, an analytical model is presented that simulates the experimental model in predicting the speed of waves and the frequencies accompanying them for this type of mixture. Higher order shear deformation beam theory for wave propagation in the rubberized concrete beam is developed, considering the bidirectional distribution, which is primarily expressed by the density, the Poisson coefficient, and Young's modulus. Hamilton's concept is used to determine the governing equations of the wave propagation in the rubberized concrete beam structure. When the analytical and experimental results for rubber concrete beams were compared, the outcomes were very comparable. The addition of rubber gravel and sandy rubber to the mixture both resulted in a discernible drop in velocities and frequencies, according to the data.