• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.41-41
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• 2010

In this research, to study tungsten carbide alloy(Co 0.5%) ultra precision turning possibility that is used Glass Molding Press(GMP) using conventional (Rake angle $-25^{\circ}$) single crystal diamond bite observed machining surface condition, surface roughness($R_a$), diamond bite cutting edge after tungsten carbide alloy ultra precision turning. Suggested and designed optimum chamfer bite shape to suggest ultra precision optimum bite using Finite Element Analysis(FEM). After machining tungsten carbide alloy ultra precision turning using optimum chamfer bite and comparing with conventional bite machine result and studied optimum chamfer bite design inspection and also tungsten carbide ultra precision turning possibility for high temperature compression glass lens molding.

• Computers and Concrete
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• v.2 no.2
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• pp.97-110
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• 2005

Rheological behaviour of fresh concrete is an important factor in controlling concrete quality. It is recognized that the measurement of the slump is not a sufficient test method to adequately characterize the rheology of fresh concrete. To further understand the slump measurement and its relationship to the rheological properties, an elasto-viscoplastic, 2-D axisymmetric finite element (FE) model is developed. The FE model employs the Bingham material model to simulate the flow of a slump test. An experimental program is carried out using the Slump Rate Machine (SLRM_II) to evaluate the finite element simulation results. The simulated slump-versus-time curves are found to be in good agreement with the measured data. A sensitivity study is performed to evaluate the effects of yield stress, plastic viscosity and cone withdrawal rate on the measured flow curve using the FE model. The results demonstrate that the computed yield stress compares well with reported experimental data. The flow behaviour is shown to be influenced by the yield stress, plastic viscosity and the cone withdrawal rate. Further, it is found that the value of the apparent plastic viscosity is different from the true viscosity, with the difference depending on the cone withdrawal rate. It is also confirmed that the value of the final slump is most influenced by the yield stress.

• Geomechanics and Engineering
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• v.4 no.3
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• pp.191-208
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• 2012

Due to rapid industrialisation, large scale infrastructure development is taking place worldwide. This includes railways, high speed highways, elevated roads etc. To meet the demands of society and industry, many innovative techniques and materials are being developed. In developed nations like USA, Japan etc. for railways applications, new material like geocells, geogrids are being used successfully to enable fast movement of vehicles. The present research work was aimed to develop design methodologies for improvement of grounds subjected to cyclic loads caused by moving vehicles on roads, rail tracks etc. Deformation behavior of ballast under static and cyclic load tests was studied based on square footing test. The paper presents a study of the effect of geo-synthetic reinforcement on the (cumulative) plastic settlement, of point loaded square footing on a thick layer of granular base overlying different compressible bases. The research findings showed that inclusion of geo-synthetics significantly improves the performance of ballasted tracks and reduces the foundation area. If the area is kept same, higher speed trains can be allowed to pass through the same track with insertion of geosynthetics. Similarly, area of machine foundation may also be reduced where geosynthetics is provided in foundation. The model tests results have been validated by numerical modeling, using $FLAC^{3D}$.

• Steel and Composite Structures
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• v.27 no.3
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• pp.273-283
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• 2018

Nonlinear low velocity impact response of sandwich beam with laminated composite face sheets and soft core is studied based on Extended High Order Sandwich Panel Theory (EHSAPT). The face sheets follow the Third order shear deformation beam theory (TSDT) that has hitherto not reported in conventional EHSAPT. Besides, the two dimensional elasticity is used for the core. The nonlinear Von Karman type relations for strains of face sheets and the core are adopted. Contact force between the impactor and the beam is obtained using the modified Hertz law. The field equations are derived via the Ritz based applied to the total energy of the system. The solution is obtained in the time domain by implementing the well-known Runge-Kutta method. The effects of boundary conditions, core-to-face sheet thickness ratio, initial velocity of the impactor, the impactor mass and position of the impactor are studied in detail. It is found that each of these parameters have significant effect on the impact characteristics which should be considered. Finally, some low velocity impact tests have been carried out by Drop Hammer Testing Machine. The contact force histories predicted by EHSAPT are in good agreement with that obtained by experimental results.

• Smart Structures and Systems
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• v.19 no.3
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• pp.299-307
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• 2017

The magneto-electro-elastic (MEE) material under thermal environment exhibits pyroelectric and pyromagnetic coefficients resulting in pyroelectric and pyromagnetic effects. The pyroelectric and pyromagnetic effects on the behavior of multiphase MEE sensors bonded on top surface of a mild steel beam under thermal environment is presented in this paper. The aim of the study is to find out how samples having different volume fractions of the multiphase MEE composite behave in sensor applications. This is studied at optimal location on the beam, where the maximum electric and magnetic potentials are induced due to pyroelectric and pyromagnetic effects under clamped-free and clamped-clamped boundary conditions. The sensor which is bonded on the top surface of the beam is modeled using 8-node brick element. The MEE sensor bonded on mild steel beam is subjected to uniform temperature rise of 50K. It is assumed that beam and sensor is perfectly bonded to each other. The maximum pyroelectric and pyromagnetic effects on electric and magnetic potentials are observed when volume fraction is ${\nu}_f=0.2$. The boundary conditions significantly influence the pyroelectric and pyromagnetic effects on electric and magnetic potentials.

• Steel and Composite Structures
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• v.24 no.5
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• pp.635-641
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• 2017

Safety service improvement and development of efficient maintenance strategies for corroded steel structures are undeniably essential. Therefore, understanding the influence of damage caused by corrosion on the remaining load-carrying capacities such as tensile strength is required. In this study, artificial neural network (ANN) approach is proposed in order to produce a simple, accurate, and inexpensive method developed by using tensile test results, material properties and finite element method (FEM) results to train the ANN model. Initially in reproducing corroded model process, FEM was used to obtain tensile strength of artificial corroded plates, for which surface is developed by a spatial autocorrelation model. By using the corroded surface data and material properties as input data, with tensile strength as the output data, the ANN model could be trained. The accuracy of the ANN result was then verified by using leave-one-out cross-validation (LOOCV). As a result, it was confirmed that the accuracy of the ANN approach and the final output equation was developed for predicting tensile strength without tensile test results and FEM in further work. Though previous studies have been conducted, the accuracy results are still lower than the proposed ANN approach. Hence, the proposed ANN model now enables us to have a simple, rapid, and inexpensive method to predict residual tensile strength more accurately due to corrosion in steel structures.

• Advances in concrete construction
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• v.6 no.1
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• pp.87-102
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• 2018

Utilization of waste tires may be considered as one of the solution to the problems faced by the local authorities in disposing them. Reclaimed rubber (RR) is being used in concrete for replacing conventional aggregates. This research work is focused on the strength prediction of reclaimed rubber concrete using a Genetic Algorithm (GA) for M40 grade of concrete and comparing it with experimental results. 1000 sets were taken and 100 iterations were run during training of GA models. A base study has been carried out in this research work partially replacing cement with three types of fillers such as Plaster of Paris (POP), Fly Ash (FA) and Silica Fume (SF). A total of 243 cubes were cast and tested for compression using a Universal Testing Machine. It was found that SF produced maximum strength in concrete and was used in the main study with reclaimed rubber. Tests were conducted on 81 cube samples with a combination of optimum SF percent and various proportions of RR replacing coarse aggregates in concrete mix. Compressive strength tests of concrete at 7, 14 and 28 days reveal that the maximum strength is obtained at 12 percent replacement of cement and 9 percent replacement of coarse aggregates respectively. Moreover the GA results were found to be in line with the experimental results obtained.

• Smart Structures and Systems
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• v.22 no.2
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• pp.175-183
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• 2018

Time-series data often contain one of the most valuable pieces of information in many fields including manufacturing. Because time-series data are relatively cheap to acquire, they (e.g., vibration signals) have become a crucial part of big data even in manufacturing shop floors. Recently, deep-learning models have shown state-of-art performance for analyzing big data because of their sophisticated structures and considerable computational power. Traditional models for a machinery-monitoring system have highly relied on features selected by human experts. In addition, the representational power of such models fails as the data distribution becomes complicated. On the other hand, deep-learning models automatically select highly abstracted features during the optimization process, and their representational power is better than that of traditional neural network models. However, the applicability of deep-learning models to the field of prognostics and health management (PHM) has not been well investigated yet. This study integrates the "residual fitting" mechanism inherently embedded in the wavelet transform into the convolutional neural network deep-learning structure. As a result, the architecture combines a signal smoother and classification procedures into a single model. Validation results from rotor vibration data demonstrate that our model outperforms all other off-the-shelf feature-based models.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.1
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• pp.66-77
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• 1999

For this study It was measured the seam puckering based on the mechanical properties of tencel under the proper condition of needlework and machine sewing analyzed the mechanical properties which re influenced to the seam puckering and estimated the seam puckering based on the mechanical properties. The results of this study are as follows : There are three types of the seam puckering for each step which is caused by repeated washing and press. Concerning the seam puckering with the number of washing the more the number of washing is increased the less the seam puckering is decreased. Concerning the mecanical properties of the sample with the seam puckering. The seam puckering is related to LT positively B, 2HB, T, W negatively Among the mechanical properties LT, B, 2HB, T, W are most influenced to the seam puckering. Judging from the result of estimating seam puckering based on mechanical properties the estimate-formula is satisfied in this study.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.1
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• pp.22-29
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• 1999

This paper descrived the changes of peel strength wrinkle recovery and dimensional stability after fusing 4 different wool face fabrics with 3 different fusible interlinings. The fusing condition was conducted by fusing press machine under 4kg.f/cm2 at 15$0^{\circ}C$. To determine the effect of the varous physical properties of the fused fabrics face fabrics and interlinings on the peel strength wrinkle recovery and dimensional stability(hygral expansion and relaxation shrinkage) of fused fabrics correlation among the KES values of fused fabrics face fabrics and interlinings to the peel strength rinkle recovery and dimensional stability of fused fabrics were expeerimentally analyzed,. As the results the peel strength was mainly influenced by the cover factor of face fabric and interlinings. After fusing wrinkle recovery and hygral expansion were decreased. The cover factor wrinkle recovery weight thickness shear rigidity and frictional properties of face fabric and the thickness of fused fabrics were not influence to the wrinkle recovery of fused fabrics. In addition the dimensional stabilities of fused fabrics were mainly influenced by the tensile and frictional properties of the wrinkle recovery of fused fabrics. In addition the dimensional stabilities of fused fabrics were mainly influenced by the tensile and frictional properties of the face fabrics.