• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.8
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• pp.702-710
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• 2011

This paper aims to verify the applicability of OpenFOAM, the widely recognized open source CFD code, to external flows commonly found in aeronautical problems. To this end, several representative flow cases are selected first from subsonic to supersonic flow fields. Then, the computational results obtained from OpenFOAM are systematically compared against available data from experiments and other numerical codes. It was found that the strength and location of shock are well predicted and the effects of boundary conditions on the computed results are reviewed. Subsonic flow with massive separation is selected to validate the prediction capability of OpenFOAM. Based on the current results, the limitation and possibility of OpenFOAM was confirmed and for future study using OpenFOAM was suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8637-8642
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• 2015

Typical aging for the rubber using the current military adhesive combat boots was spread with a regular aging caused by heat stress. In this study, the aging test of the rubber for combat boots was carried out and the reaction rate constant, k was calculated at aging temperature $60^{\circ}C$, $80^{\circ}C$ and $100^{\circ}C$, using the Arrhenius equation. The lifetime limit was assumed that the tensile strength of the product is reduced to 30%, the elongation is reduced to 50% and abrasion resistance ratio is 380%. ln($P/P_0$) and the lifetime was predicted with the consideration of the activation energy constant. According to the above, the lifetime of the rubber for combat boots with influenced by aging temperature was predicted. As the result, the estimate lifetime at $20^{\circ}C$ was confirmed more than 10 years.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.8
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• pp.719-727
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• 2008

A 3-D compressible Navier-Stokes solver using overlapped grids is developed to predict a flow-field around a hovering rotor. The flow solver is verified by a parametric study with the grid spacing of wake grid, spatial accuracy and turbulence model. Computations are performed with different Chimera grid systems. Computational results are compared with the experimental data of Caradonna et al. for both blade loading and the tip vortex behavior. Numerical results show good agreements with experiments for the distribution of surface pressure and tip vortex behavior. Pressure distributions over the blade have marginal differences for different numerical methods, whereas large discrepancies are seen in the prediction of the wake behavior. Results unexpectedly show that the vortex strength from an automated cut-paste Chimera grid is weaker than that from the conventional Chimera grid.

• Journal of Korean Tunnelling and Underground Space Association
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• v.13 no.3
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• pp.243-260
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• 2011

To predict TBM performance in design stage is indispensable for its successful application. The NTNU model, one of the representative TBM performance prediction models uses two distinct parameters such as DRI and CLI obtained from three different tests on bored rock cores. Based on DRI and CLI, it is possible to predict TBM advance rate and cutter life in the NTNU model. In this study, NTNU testing methods and their related testing equipments were introduced to measure DRl and CLI for the NTNU model. Then, in order to derive their relationships, the two key parameters measured for 39 domestic rocks were compared with physico-mechanical properties of rock such as uniaxial compressive strength and quartz content. Lastly, the experimental results were also compared with NTNU database to verify their reliability.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Geotechnical Engineering
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• v.12 no.4
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• pp.157-178
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• 1996

Current design methods for reinforced earth structures take no account of the magnitude of the strains induced in the tensile members as these are invariably manufactured from high modulus materials, such as steel, where straits are unlikely to be significant. With fabrics, however, large strains may frequently be induced and it is important to determine these to enable the stability of the structure to be assessed. In the present paper internal design method of analysis relating to the use of fabric reinforcements in reinforced earth structures for both stress and strain considerations is presented. For the internal stability analysis against rupture and pullout of the fabric reinforcements, a strain compatibility analysis procedure that considers the effects of reinforcement stiffness, relative movement between the soil and reinforcements, and compaction-induced stresses as studied by Ehrlich 8l Mitchell is used. I Bowever, the soil-reinforcement interaction is modeled by relating nonlinear elastic soil behavior to nonlinear response of the reinforcement. The soil constitutive model used is a modified vertsion of the hyperbolic soil model and compaction stress model proposed by Duncan et at., and iterative step-loading approach is used to take nonlinear soil behavior into consideration. The effects of seepage pressures are also dealt with in the proposed method of analy For purposes of assessing the strain behavior oi the fabric reinforcements, nonlinear model of hyperbolic form describing the load-extension relation of fabrics is employed. A procedure for specifying the strength characteristics of paraweb polyester fibre multicord, needle punched non-woven geotHxtile and knitted polyester geogrid is also described which may provide a more convenient procedure for incorporating the fablic properties into the prediction of fabric deformations. An attempt to define improvement in bond-linkage at the interconnecting nodes of the fabric reinforced earth stracture due to the confining stress is further made. The proposed method of analysis has been applied to estimate the maximum tensions, deformations and strains of the fabric reinforcements. The results are then compared with those of finite element analysis and experimental tests, and show in general good agreements indicating the effectiveness of the proposed method of analysis. Analytical parametric studies are also carried out to investigate the effects of relative soil-fabric reinforcement stiffness, locked-in stresses, compaction load and seepage pressures on the magnitude and variation of the fabric deformations.

• Korean Journal of Culture and Social Issue
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• v.15 no.1
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• pp.187-205
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• 2009

Based on the Motivational States Theory(MOST), the present research expanded and complemented Kim(2007)'s proposal to add the Life Satisfaction Expectancy Scale(LSES) to Diener et al's Satisfaction With Life Scale(SWLS) to measure subjective well-being(SWB). In the present study, the Life Satisfaction Motivation Scale(LSMS) was introduced to measure the strength of motivation for life satisfaction in general. Two hundred and eighty six college students participated in this study. Factor analyses revealed a two-factor structure, with the factors corresponding to life satisfaction and life satisfaction expectancy. Measures of internal and temporal reliability show the LSMS to be a good complement for the measure of SWB(The LSMS showed high internal and test-retest reliability). It was found that the addition of the LSES provided a significant increment in predictive power over the SWLS in the prediction of various factors related with well-being prediction. Exceptionally, in the prediction of anger the LSMS had the most predictive power. There were some differences between male and female students in the correlations among life satisfaction, life satisfaction expectancy and life satisfaction motivation and well-being-related factors. The merits of including LSES in the measurement of subjective well-being and the limitations of this study are discussed.

• Journal of agriculture & life science
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• v.46 no.2
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• pp.9-17
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• 2012

In this study, in addition to the green tea - wood fiber hybrid composite boards of previous researches, to make effective use of saw dust of domestic cypress tree with functionalities and application as interior materials, eco-friendly hybrid composite boards were manufactured from wood fiber, green tea and saw dust of cypress tree. We investigated the effect of the component ratio of saw dust and green tea on dynamic MOE (modulus of elasticity). Dynamic MOE was within 1.41~1.65 GPa, and showed the highest value in wood fiber : green tea : saw dust = 50 : 40 : 10 of the component ratio, and had the lowest value in 50 : 30 : 20 of component ratio. These values were 1.4~1.6 times higher than static bending MOE of wood fiber - saw dust - green tea hybrid composite boards, and were 2.0~2.9 times lower than those of green tea - wood fiber hybrid composite boards reported in the previous researches. From the results of correlation regression analyses between dynamic MOE and static strength performances, a very high correlation coefficients were obtained, therefore it was found that static bending strength performances can be estimated with a high reliability from dynamic MOE.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Archives of Plastic Surgery
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• v.38 no.6
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• pp.808-814
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• 2011

Purpose: Despite wide clinical use of breast implants, there is continued concern about the lifespan of these devices. The causes of explantation were infection, deflation of implant and patient's want. The deflation of saline-filled breast implant was related to strength and durability of implant shell. The purpose of this study is to evaluate the clinical durability of saline-filled breast implant through the analysis of duration until deflation occurred, causes, incidence and influencing factors. Methods: Retrospective analyses were conducted on clinical records for 19 cases of deflation of saline-filled breast implant from 201 cases of breast reconstruction with saline-filled implant between May 1995 and June 2011. The authors had been analyzed the causes of deflation, survival duration, symptom, sign, nipple excision, volume of implant, saline filling, method of reoperation, breast cancer stage and combined capsular contracture. Results: The causes of deflation were attributed to the cases that cannot be evaluated the causes in 15 cases, fall down in 1 case, mammography in 2 cases, accidental needle injury in 1 case. Mean survival duration was 4 years and 5 months. The duration of survival was less than 1 year for 5 cases, 1 year to 10 years for 10 cases, more than 10 years for 4 cases. The volume between 201 and 250 cc of deflated breast implant was rated as high by 14.0 percent. The deflation rate of underfilled implants was 11.4 percent, adequate filled implants was 9.3 percent. None of overfilled implant was deflated. The deflation of smooth surface implant was 5 of 152 cases. Textured implant was 14 of 49 cases. The capsular contracture of non-deflated breast implant was 28 of 182 cases and that of deflated breast implant was 6 of 19 cases. Conclusion: The patients who underwent saline-filled breast implant implantation should be informed that their implant could deflate. The analysis of clinical durability and causes of deflation in breast implant was important for the prediction and prevention of reopeation. The authors could suppose the causes of deflation of saline-filled breast implant through history, duration of survival, inspection of the shell of implant.