• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.341-344
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• 2008

Lightweight concrete is known for its advantage of reducing the self-weight of the structures, reducing the areas of sectional members as well as making the construction convenient. Thus the construction cost can be saved when applied to structures such as long-span bridge and high rise building. However, the lightweight concrete requires specific mix design method that is quite different from the typical concrete, since using the typical mix method would give rise the material segregation as well as lower the strength by the reduced weight of the aggregate. In order to avoid such problems, it is recommended to apply the mix design method of self-consolidating concrete for the lightweight concrete. Therefore experimental tests were performed as such mechanical properties(compressive strength, dry density and structural efficiency) of concrete and dry shrinkage according to ACI committee 209.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.677-680
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• 2008

The autogenous shrinkage of HPC is important in that it can lead the early cracks in concrete structures. The purpose of the present study is to explore the autogenous shrinkage of HPC with cellulose fiber and expansive additive and to derive a realistic equation to estimate the autogenous shrinkage model of that. For this purpose, comprehensive experimental program has been set up to observe the autogenous shrinkage for various test series. Major test variables were the quantity of expansive additive and cellulose fiber. Water-cement ratio is fixed with 13%. The autogenous shrinkage of HPC is found to decrease with increasing expansive additive and cellulose fiber. A prediction equation to estimate the autogenous shrinkage of HPC was derived and proposed in this study. The proposed equation shows reasonably good correlation with test data on autogenous shrinkage of HPC.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.801-804
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• 2008

Fiber reinforced plastics (FRP) are light in weight, non-corrosive and exhibits high tensile strength. FRPs having superior material properties to corrosive steels have been widely replacing steel bars or tendons used in concrete structures as flexural reinforcements. Although current design guidelines for estimating shear strength of FRP concrete beam follow the format of conventional reinforced concrete design method, there are noticeable differences among the existing formulas in calculating the contributions of concrete to shear resistance. In this paper, the artificial neural network (ANN) technique is employed as an analytical alternative to existing methods for predicting shear capacity of FRP concrete beams. Influential factors on shear strength were identified through literature review and input in ANN and the ANN was trained for the target ultimate shear obtained from database. The results from ANN were compared with existing formulas for its accuracy. It was found that the developed ANN were more closely predicting the test data than those of the currently available predictive equations.

• Journal of Korean Association for Spatial Structures
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• v.7 no.4
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• pp.73-78
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• 2007

The surrounding ground was much transformed by the lateral movement on the soft ground, and consequently the stake basis was damaged. In this case the installed stake is ratted the passive stake, and is actively being researched. When the unevenly distributed load was applied on the stake, and thus the lateral ground pressure was operated, and then the lateral movement was occurred, and consequently the structure is influenced. However, prediction and mechanism for the relationship of piles and abutment deformation is not sufficient. In this paper, coupled three-dimensional finite element analysis, which can be described solid, plate and frame elements at the same time, is developed by the authors. The lateral movement of bridge abutment for the aspect ratio of steel piles on soft clay is clarified by using developed numerical analysis.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.154-161
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• 2004

The flat dilatometer test(DMT) is a geotechnical tool to estimate in-situ properties of various types of ground materials. The undrained shear strength is known to be the most reliable and useful parameter obtained by DMT. However, the existing relationships which were established for other local deposits depend on the regional geotechnical characteristics. In addition, the flat dilatometer test results have been interpreted using three intermediate indicesmaterial index($I_p$), horizontal stres index($K_p$), and dilatometer modulus($E_p$) and the undrained shear strength is estimated only by using the horizontal stress index($K_D$). In this paper, an artificial neural network was developed to evaluate the undrained shear strength by DMT and the ANN, based on the $p_0,\;p_1,\;p_2,\;{\sigma}'_v_0$, and porewater pressure. The ANN which adopts the back-propagation algorithm was trained based on the DMT data obtained from Korean soft clay. To investigate the feasibility of ANN model, the prediction results obtained from data which were not used to train the ANN and those obtained from existing relationships were compared.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.1041-1050
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• 2001

Control of bone cement volume (PMMA) may be critical for preventing complications in vertebroplasty, the percutaneous injection of PMMA into vertebra. The purpose of this study was to predict the optimal volume of PMMA injection based on CT images. For this, correlation between PMMA volume and textural features of CT images was examined before and after surgery to evaluate the appropriate PMMA amount. The gray level run length analysis was used to determine the textural features of the trabecular bone. Extimation of PMMA volume was done using 3D visualization with semi-automatic segmentation on postoperative CT images. Then, finite element (FE) models were constructed based on the CT image data of patients and PMMA volume. Appropriate material properties for the trabecular bone were assigned by converting BMD to elastic modulus. Structural reinforcement due to the changes in PMMA volume and BMD was assessed in terms of axial displacement of the superior endplate. A strong correlation was found between the injected PMMA volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT images (r=0.90 and -0.90, respectively). FE results suggested that vertebroplasty could effectively reinforce the osteoporotic vertebra regardless of BMD or PMMA volume. Effectiveness of additional PMMA injection tended to decrease. For patients with BMD well lower than 50mg/ml, injection of up to 30% volume of the vertebral body is recommended. However, less than 30% is recommended otherwise to avoid any complications from excessive PMMA because the strength has already reached the normal level.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.6
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• pp.757-762
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• 2010

Owing to the high specific strength and stiffness of composite materials, they are extensively used in mechanical systems and in vehicle industries. However, most mechanical structures experience repeated load and fatigue. Therefore, it is important to perform fatigue analysis of fiber-reinforced composites. The properties of composite laminates vary depending upon the stacking sequence and stacking direction. Fatigue damage of composite laminates occurs according to the following sequence: matrix cracking, delamination, and fiber breakage. In this study, fatigue tests were performed for damage analysis. Fatigue damages, which have to be considered in fatigue analysis, are determined by using the stiffness values calculated from hysteresis loops, and the obtained fatigue damage curve is examined using Mao's equation and Abdelal's equation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.867-872
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• 2010

Unused energy derived from sources in nature can be captured and stored for future use, for example, to recharge a battery or power a device; this process of capturing and storing energy is called energy harvesting. Extensive investigations are being carried out in order to use piezoelectricity to harvest the energy generated by body movements or machine vibrations. This paper presents a simple analytical model that describes the output voltage effectiveness of a Piezocomposite Generating Element (PCGE) from vibration and its experimental verification. PCGE is composed of carbon/epoxy, PZT, and glass/epoxy layers. During the manufacturing process, the stacked layers were cured at $177^{\circ}C$ in an autoclave, which created residual stresses in PCGE and altered the piezoelectric properties of the PZT layer. In the experiments, three kinds of lay-up configurations of PCGE were considered to verify the proposed prediction model and to investigate its capability to convert oscillatory mechanical energy into electrical energy. The predicted performance results are in good agreement with observed experimental ones.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.845-851
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• 2017

Fatigue failure of an autofrettaged pressure vessel with a groove at the outside surface occurs owing to the fatigue crack initiation and propagation at the groove root. In order to predict the fatigue life of the autofrettaged pressure vessel, residual stresses in the autofrettaged pressure vessel were evaluated using the finite element method, and the fatigue properties of the pressure vessel steel were obtained from the fatigue tests. Fatigue life of a pressure vessel obtained through summation of the crack initiation and propagation lives was calculated to be 2,598 cycles for an 80% autofrettaged pressure vessel subjected to a pulsating internal pressure of 424 MPa.

• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3637-3641
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• 2014

In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted $EC_{50}$. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/water partition coefficient (Pow) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR $EC_{50}$ equation = $1.76997-1.12249{\times}TOL+1.21045{\times}MEK$), as well as to SG, VP, and LEL (MLR equation $EC_{50}=15.44388-19.84549{\times}SG+0.05091{\times}VP+1.85846{\times}LEL$). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.