• Proceedings of the Materials Research Society of Korea Conference
• /
• 2011.05a
• /
• pp.14-14
• /
• 2011

W (tungsten)-alloys will be the most promising plasma facing armor materials in highly loaded plasma interactive components of the next step fusion reactors due to its high melting point, high sputtering resistance and low deuterium/tritium retention. The bonding technology of tungsten to Cu alloy was one of the key issues. In this paper, W/CuCrZr diffusion bonding has been performed successfully by inserting pure metal interlay. The joint microstructure, interfacial elements migration and phase composition were analyzed by SEM, EDS, XRD, and the joint shear strength and micro-hardness were investigated. The mock-ups were fabricated successfully with diffusion bonding and the cladding technology respectively, and the high heat flux test and thermal fatigue test were carried out under actively cooling condition. When Ni foil was used for the bonding of tungsten to CuCrZr, two reaction layers, Ni4W and Ni(W) layer, appeared between the tungsten and Ni interlayer with the optimized condition. Even though Ni4W is hard and brittle, and the strength of the joint was oppositely increased (217 MPa) due primarily to extremely small thicknesses (2~3 ${\mu}m$). When Ti foil was selected as the interlayer, the Ti foil diffused quickly with Cu and was transformed into liquid phase at $1,000^{\circ}C$. Almost all of the liquid was extruded out of the interface zone under bonding pressure, and an extremely thin residual layer (1~2 ${\mu}m$) of the liquid phase was retained between the tungsten and CuCrZr, which shear strength exceeded 160 MPa. When Ni/Ti/Ni multiple interlayers were used for bonding of tungsten to CuCrZr, a large number of intermetallic compound ($Ni_4W/NiTi_2/NiTi/Ni_3T$) were formed for the interdiffusion among W, Ni and Ti. Therefore, the shear strength of the joint was low and just about 85 MPa. The residual stresses in the clad samples with flat, arc, rectangle and trapezoid interface were estimated by Finite Element Analysis. The simulation results show that the flat clad sample was subjected maximum residual stress at the edge of the interface, which could be cracked at the edge and propagated along the interface. As for the rectangle and trapezoid interface, the residual stresses of the interface were lower than that of the flat interface, and the interface of the arc clad sample have lowest residual stress and all of the residual stress with arc interface were divided into different grooved zones, so the probabilities of cracking and propagation were lower than other interfaces. The residual stresses of the mock-ups under high heat flux of 10 $MW/m^2$ were estimated by Finite Element Analysis. The tungsten of the flat interfaces was subjected to tensile stresses (positive $S_x$), and the CuCrZr was subjected to compressive stresses (negative $S_x$). If the interface have a little microcrack, the tungsten of joint was more liable to propagate than the CuCrZr due to the brittle of the tungsten. However, when the flat interface was substituted by arc interfaces, the periodical residual stresses in the joining region were either released or formed a stress field prohibiting the growth or nucleation of the interfacial cracks. Thermal fatigue tests were performed on the mock-ups of flat and arc interface under the heat flux of 10 $MW/m^2$ with the cooling water velocity of 10 m/s. After thermal cycle experiments, a large number of microcracks appeared at the tungsten substrate due to large radial tensile stress on the flat mock-up. The defects would largely affect the heat transfer capability and the structure reliability of the mock-up. As for the arc mock-up, even though some microcracks were found at the interface of the regions, all microcracks with arc interface were divided into different arc-grooved zones, so the propagation of microcracks is difficult.

• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.139-155
• /
• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.42 no.5
• /
• pp.64-72
• /
• 2014

This study quantified the storage and annual uptake of carbon by apple trees in orchards as a production-type greenspace, and computed the annual carbon emissions from apple cultivation. Tree individuals in the study orchards were sampled to include the range of stem diameter sizes. The study measured biomass for each part including the roots of sample trees through a direct harvesting method to compute total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at ground level. Annual carbon emissions from management practices such as pruning, mowing, irrigation, fertilization, and use of pesticides and fungicides were estimated based on maintenance data, interviews with managers, and actual measurements. Regression models were developed using stem diameter at ground level (D) as an independent variable to easily estimate storage and annual uptake of the carbon. Storage and annual uptake of carbon per tree increased as D sizes got larger. Apple trees with D sizes of 10 and 15 cm stored 9.1 and 21.0 kg of carbon and annually sequestered 1.0 and 1.6 kg, respectively. Storage and annual uptake of carbon per unit area in study orchards were 3.81 t/ha and 0.42 t/ha/yr, respectively, and annual carbon emissions were 1.30 t/ha/yr. Thus, the carbon emissions were about 3 times greater than the annual carbon uptake. The study identified management practices to reduce the carbon footprint of production-type greenspace, including efficient uses of water, pesticides, fungicides, and fertilizers. It breaks new ground by including measured biomass of roots and a detailed inventory of carbon emissions.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.42 no.5
• /
• pp.13-21
• /
• 2014

This study generated regression models to quantify storage and annual uptake of carbon from five native landscape tree species through a direct harvesting method, and established essential information to estimate carbon reduction effects from urban greenspaces. Tree species for the study included the Chionanthus retusus, Prunus armeniaca, Abies holophylla, Cornus officinalis, and Taxus cuspidata, which are usually planted in cities of middle Korea, but for which no information on carbon reduction is available. Ten tree individuals for each species were sampled reflecting various stem diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute total carbon storage per tree. The annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at breast height or ground level. Regression models were developed using diameter at breast height (dbh) or ground level (dg) as an independent variable to easily estimate storage and annual uptake of carbon per tree for each species. All the regression models showed high fitness with $r^2$ values of 0.92~0.99. Storage and annual uptake of carbon from a tree with dbh of 10 cm were greatest with C. retusus (20.0 kg and 5.9 kg/yr, respectively), followed by P. armeniaca (17.5 kg and 4.5 kg/yr) and A. holophylla (13.2kg and 1.8 kg/yr) in order. A C. officinalis tree and T. cuspidata tree with dg of 10 cm stored 9.3 and 6.3 kg of carbon and annually sequestered 3.2 and 0.6 kg, respectively. The above-mentioned carbon storage equaled the amount of carbon emitted from gasoline consumption of about 23~35 L for C. retusus, P. armeniaca, and A. holophylla, and 11~16 L for C. officinalis and T. cuspidata. A tree with the diameter size of 10 cm annually offset carbon emissions from gasoline use of about 6~10 L for C. retusus, P. armeniaca, and C. officinalis, and 1~3 L for A. holophylla and T. cuspidata. The study breaks new ground to easily quantify biomass and carbon reduction for the tree species by overcoming difficulties in direct cutting and root digging of urban landscape trees.

• Journal of Korean Society of Forest Science
• /
• v.78 no.2
• /
• pp.119-131
• /
• 1989

This experiment was executed to investigate and compare qualitative and quantitative anatomical features in compression wood, opposite wood, and side wood formed in a bent stem, a straight branch, and an exposed horizontal root of Korean red pine(Pinus densiflora S. et Z.). The respective four discs containing compression wood taken at 20cm interval both in stem and branch as well as a disc containing well developed compression wood from horizontal root were analyzed. Percentage of compression wood and eccentricity showed decreasing tendency with the increasing distance in height direction of stem and length direction of branch. The qualitative anatomical features of compression wood appeared to differ from those of side and opposite wood in very gradual tracheid transition from earlywood to latewood, roundish tracheid shape on cross surface, tracheid distortion at tip on radial surface, existence of intercellular space, and helical cavity in tracheid wall. And the differences in these qualitative features among the compression wood, opposite wood, and side wood became less intensive with the decreasing trends in percentage of compression wood and eccentricity. The quantitative anatomical features in compression wood also appeared to be wider in that respective widths of fusiform and uniseriate ray than those of opposite and side wood, but the heights of fusiform and uniseriate ray in compression wood were smaller than in opposite and side wood. The number of horizontal resin canal(fusiform ray) and uniseriate ray, however, showed no differences among the compression wood, opposite wood, and side wood. And the number of vertical resin canal in unit area, $4{\pi}mm^2$ of compression wood was fewer than that in opposite wood, whereas numerous vertical resin canals contained in a growth ring. These rays of compression wood seemed to be characterized by smaller height and wider width than those of opposite and side wood.