• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.163-166
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• 1997

Aluminium foam material is a highly porous material having complicated cellular structure defined by randomly distributed air pores in metallic matrix. this structure gives the aluminium a set of properties which cannot be achieved by any of conventional treatments. The properties of aluminium foam material significantly depend on its porosity, so that a desired profile of properties can be tailored by changing the foam density. Melting method is the one of foaming processes, which the production has long been considered difficult to realize becaues of such problems as the low foamability of molten metal, the varying size of. cellular structures, solidification shrinkage and so on. These problems, however, have gradually been solved by researchers and some manufacturers are now producing foamed aluminum by their own methods. Most of all, the parameters of solving problem in electric furnace were stirring temperature, stirring velocity, foaming temper:iture, and so on. But it has not considered about those in induction heating, foaming velocity and foaming temperature in semi-solid state yet. Therefore, this paper presents the effects on these parameter to control cell size, quantity and distribution.

• Fibers and Polymers
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• v.7 no.3
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• pp.295-304
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• 2006

High-bulk worsted yams with different shrinkable and non-shrinkable acrylic fibers blend ratios are produced and then single jersey weft knitted fabrics with three different structures and loop lengths are constructed. The physical properties of produced yams and compression properties of produced fabrics at eight pressure values (50, 100, 200, 500, 1000, 1500 and $2000 g/cm^2$) were measured using a conventional fabric thickness tester. Then, weft-knitted fabric compression behavior was analyzed using a two parameters model. It is found that at 40 % shrinkable fibre blending ratio the maximum yam bulk, shrinkage, abrasion resistance and minimum yarn strength are obtained. It is also shown that high-bulk acrylic yarn has the highest elongation at 20 % shrinkable fibre blend ratio. The statistical regression analysis revealed that the compression behavior of acrylic weft-knitted fabrics is highly closed to two parameter model proposed for woven fabrics. It is also shown that for weft-knitted structure, there is an incompressible layer (V') which resists against high compression load. Acrylic weft-knitted fabrics with knit-tuck structure exhibit higher compression rigidity and lower softness than the plain and knit-miss structures. In addition, at 20 % shrinkable fibre blend ratio, the high-bulk acrylic weft-knitted fabrics are highly compressible.

• Journal of the Korean Ceramic Society
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• v.20 no.4
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• pp.347-355
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• 1983

A batch mixture was prepared as 16mol% CaO-84mol% $ZrO_2$ of regeant-grade powder. The monoclinic Zirconia powder had an average particle size of $9.24 \mu\textrm{m}$ and calcium carbonate powder had a reported purity of 99.7 weight percent and mean particle size of TEX>$24, 37<\mu\textrm{m}$. The specimens were fired at 1400, 1500, 1650 and $1750^{\circ}C$ for 0. 3, 5 and 7 hours respectively. After fired the specimens were investigated using Scaning electron microscopy. Density Porosity Compressive strength Modulus of rupture and Thermal expansion were measured X-ray diffration analysis was also carried out. The results are as follows ; 1) As the firing temperature or soaking time was increased firing linear shrinkage apparent density compressive strength and modulus of rupture increased but apparent porosity decreased, 2) Cubic and monoclinic Zirconia was found at $1400^{\circ}C$ and cubic Ziconia found above $1500^{\circ}C$ 3) The specimens fired at 140$0^{\circ}C$ without soaking display thermal expansion curves by monoclinic〓tetragonal transformation and no tranformation was found at $1400^{\circ}C$ for 5hrs and above $1500^{\circ}C$. 4) The lattice parameter had constant value of 5.1345 $\AA$ through all the ranges of firing temperature 5) The higher the firing temperature was or the longer the soaking time was the larger the grain size was.

• Steel and Composite Structures
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• v.18 no.3
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• pp.547-563
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• 2015

Deflection in a beam of a composite frame is a serviceability design criterion. This paper presents a methodology for rapid prediction of long-term mid-span deflections of beams in composite frames subjected to service load. Neural networks have been developed to predict the inelastic mid-span deflections in beams of frames (typically for 20 years, considering cracking, and time effects, i.e., creep and shrinkage in concrete) from the elastic moments and elastic mid-span deflections (neglecting cracking, and time effects). These models can be used for frames with any number of bays and stories. The training, validating, and testing data sets for the neural networks are generated using a hybrid analytical-numerical procedure of analysis. Multilayered feed-forward networks have been developed using sigmoid function as an activation function and the back propagation-learning algorithm for training. The proposed neural networks are validated for an example frame of different number of spans and stories and the errors are shown to be small. Sensitivity studies are carried out using the developed neural networks. These studies show the influence of variations of input parameters on the output parameter. The neural networks can be used in every day design as they enable rapid prediction of inelastic mid-span deflections with reasonable accuracy for practical purposes and require computational effort which is a fraction of that required for the available methods.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.477-485
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• 2020

Finite element (FE) model based structural damage detection (SDD) methods play vital roles in effectively locating and quantifying structural damages. Among these methods, structural model updating should be conducted before SDD to obtain benchmark models of real structures. However, the characteristics of updating parameters are not reasonably considered in existing studies. Inspired by the l_∞ norm regularization, a novel anti-sparse representation method is proposed for structural model updating in this study. Based on sensitivity analysis, both frequencies and mode shapes are used to define an objective function at first. Then, by adding l_∞ norm penalty, an optimization problem is established for structural model updating. As a result, the optimization problem can be solved by the fast iterative shrinkage thresholding algorithm (FISTA). Moreover, comparative studies with classical regularization strategy, i.e. the l₂ norm regularization method, are conducted as well. To intuitively illustrate the effectiveness of the proposed method, a 2-DOF spring-mass model is taken as an example in numerical simulations. The updating results show that the proposed method has a good robustness to measurement noises. Finally, to further verify the applicability of the proposed method, a six-storey aluminum alloy frame is designed and fabricated in laboratory. The added mass on each storey is taken as updating parameter. The updating results provide a good agreement with the true values, which indicates that the proposed method can effectively update the model parameters with a high accuracy.

• Computers and Concrete
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• v.12 no.2
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• pp.169-186
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• 2013

The aim of this paper is to determine the effect of soil-structure interaction and time dependent material properties on behavior of concrete box-girder highway bridges. Two different finite element analyses, one stage and construction stage, have been carried out on Komurhan Bridge between Elazi$\breve{g}$ and Malatya province of Turkey, over Fırat River. The one stage analysis assume that structure was built in a second and material properties of structure not change under different loads and site conditions during time. However, construction stage analysis considers that construction time and time dependent material properties. The main and side spans of bridge are 135 m and 76 m, respectively. The bridge had been constructed in 3 years between 1983 and 1986 by balanced cantilever construction method. The parameters of soil-structure interaction (SSI), time dependent material properties and construction method are taken into consideration in the construction stage analysis while SSI is single parameter taking into consideration in the one stage analysis. The 3D finite element model of bridge is created the commercial program of SAP2000. Time dependent material properties are elasticity modulus, creep and shrinkage for concrete and relaxation for steel. Soft, medium, and firm soils are selected for evaluating SSI in both analyses. The results of two different finite element analyses are compared with each other. It is seen that both construction stage and SSI have a remarkable effect on the structural behavior of the bridge.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.961-975
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• 2016

The hierarchically penalized support vector machine (H-SVM) has been developed to perform simultaneous classification and input variable selection when input variables are naturally grouped or generated by factors. However, the H-SVM may suffer from estimation inefficiency because it applies the same amount of shrinkage to each variable without assessing its relative importance. In addition, when analyzing imbalanced data with uneven class sizes, the classification accuracy of the H-SVM may drop significantly in predicting minority class because its classifiers are undesirably biased toward the majority class. To remedy such problems, we propose the weighted adaptive H-SVM (WAH-SVM) method, which uses a adaptive tuning parameters to improve the performance of variable selection and the weights to differentiate the misclassification of data points between classes. Numerical results are presented to demonstrate the competitive performance of the proposed WAH-SVM over existing SVM methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5476-5496
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• 2016

Energy efficiency of resource-constrained wireless sensor networks is critical in applications such as real-time monitoring/surveillance. To improve the energy efficiency and reduce the energy consumption, the time series data can be compressed before transmission. However, most of the compression algorithms for time series data were developed only for single variate scenarios, while in practice there are often multiple sensor nodes in one application and the collected data is actually multivariate time series. In this paper, we propose to compress the time series data by the Lasso (least absolute shrinkage and selection operator) approximation. We show that, our approach can be naturally extended for compressing the multivariate time series data. Our extension is novel since it constructs an optimal projection of the original multivariates where the best energy efficiency can be realized. The two algorithms are named by ULasso (Univariate Lasso) and MLasso (Multivariate Lasso), for which we also provide practical guidance for parameter selection. Finally, empirically evaluation is implemented with several publicly available real-world data sets from different application domains. We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity. The results show that ULasso and MLasso are superior to or at least equivalent to compression performance of LTC and PLAMlis. Particularly, MLasso can significantly reduce the smooth multivariate time series data, without breaking the major trends and important changes of the sensor network system.

• Composites Research
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• v.36 no.4
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• pp.246-252
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• 2023

A secondary barrier made of glass fiber reinforced composites has been installed infinitely using automatic bonding machine(ABM) in membrane type LNG cargo containment system (CCS). At the same time, significant thermal stress due to cryogenic heat shrinkage has occurred in the composite on the non-bonding area between the adhesive fixation at both ends. There have been studies from the perspective of structural safety evaluation taking this into account, but none that have analyzed mechanical property taking an prolonged length into account. In this study, 2-parameter Weibull distribution statistical analysis was used to standardize reliable mechanical property for actual length, taking into account the composite's brittle fracture of ceramic material with wide fracture strength dispersion. Related experimental data were obtained by performing uniaxial tensile tests at specific temperatures below cryogenic condition considering LNG environment. As a result, the mechanical strength increased about 1.5 times compared to -20℃ at -70℃ and initial non-linear behavior of fiber stretched was suppressed. As the temperature decreased until the cryogenic, the mechanical strength continued to increase due to cold brittleness. The suggested mechanical property in this study would be employed to secure reliable analysis support material property when assessing the safety of secondary barrier's structures.

• Korean Journal of Dental Materials
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• v.44 no.2
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• pp.129-139
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• 2017

This study investigated the colors and mechanical properties of layered dental composites. Four nanocomposite resins (Aelite LS, Grandio, Tetric EvoCeram, Filtek Z350XT) and a silorane-based composite resin (P90) were used for overlying and underlying materials, respectively, with different thickness combinations. Colors, translucency parameter (TP), flexural and compressive properties were evaluated. All tested specimens had different color coordinates, although all were of A3 shade. Color coordinates and TP values of layered specimens better matched those of the corresponding overlying product as the thickness of the overlying product was increased. High TP values were related with high $b^*$ value differences between specimens (p<0.05). Both flexural strength and modulus, compressive strength and modulus of layered specimens with different thickness combinations were mostly lower than those of the corresponding overlying products, respectively, in their non-layered state.