• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.10
• /
• pp.1471-1478
• /
• 2010

Microforming processes have recently attracted considerable attention from industry and academia since they enable the production of microscale parts using various materials at a high production rate, minimize material loss, and provide parts with excellent mechanical properties. However, for successful development and applications of the microforming process it is critical to take the tribological size effect into consideration because previous studies have shown that traditional friction models for macroscale forming generate significantly erroneous results in the case of microforming. In this paper, we performed scaled ring compression experiments to investigate the tribological size effect of aluminum and brass materials in microforming. The sensitivity of the interfacial friction to the deformation characteristics of the ring was quantitatively analyzed by the finite element analysis. In addition, a friction model based on slip line field and upper boundary techniques was used to theoretically explain the friction mechanism in microforming.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.10
• /
• pp.1463-1470
• /
• 2010

Microforming, which exploits the advantages of metal forming technology, appears very promising in manufacturing microparts since it enables the production of parts using various materials at a high production rate, it has high material utilization efficiency, and it facilitates the production of parts with excellent mechanical properties. However, the conventional macroscale forming process cannot be simply scaled down to the micro-scale process on the basis of the extensive results and know-how on the macroscale process. This is because a so-called "size effect" occurs as the part size decreases to the microscale. In this paper, we attempt to develop an effective analytical and experimental modeling technique for explaining the effects of the grain size and the specimen size on the behavior of metals in microscale deformation processes. Copper sheet specimens of different thicknesses were prepared and heat-treated to obtain various grain sizes for the experiments. Tensile tests were conducted to investigate the influence of specimen thickness and grain size on the flow stress of the material. In addition, an analytical model was developed on the basis of phenomenological experimental findings to quantify the effects of the grain size and the specimen size on the flow stress of the material in microscale and macroscale forming.

• Journal of the Korean GEO-environmental Society
• /
• v.7 no.5
• /
• pp.41-48
• /
• 2006

Crib wall is one of the segmental grid retaining walls using headers and stretchers to establish the framework of the wall. In this method, grids formed by the intersection of headers and stretchers are generally filled with the gravel to maintain the weight of the wall. Therefore, the construction can be carried out with higher speed and much economically when compared with the concrete retaining wall. Furthermore, it has high drain capacity, and environmentally friendly aspects also have been pointed out because the possibility of the planting at the front of the wall. However, in the crib wall method, the relative movement between the individual headers and stretchers was generally recognized, and stress redistribution in the gravel filling was also observed when subjected to the external loading and self-weight of filling. Therefore, it has been thought that the distribution of the earth pressure in the crib wall system differ from that of the concrete retaining wall. In this study, the surcharge tests using the scaled model crib wall was carried out to observe the distribution of the earth pressure in the segmental grid retaining wall. The earth pressure was measured in the six specified height of wall, and the distribution of the pressure was analyzed. Furthermore, the earth pressure by computation or by the test using the concrete retaining wall was also considered to make comparison.

• Geomechanics and Engineering
• /
• v.20 no.6
• /
• pp.475-484
• /
• 2020

The prediction of the ground conditions ahead of a tunnel face is very important, especially for tunnel boring machine (TBM) tunneling, because encountering unexpected anomalies during tunnel excavation can cause a considerable loss of time and money. Several prediction techniques, such as BEAM, TSP, and GPR, have been suggested. However, these methods have various shortcomings, such as low accuracy and low resolution. Most studies on electrical resistivity tomography surveys have been conducted using numerical simulation programs, but laboratory experiments were just a few. Furthermore, most studies of scaled model tests on electrical resistivity tomography were conducted only on the ground surface, which is a different environment as compared to that of mechanized tunneling. This study performed a laboratory experimental test to extend and verify a prediction method proposed by Lee et al., which used electrical resistivity tomography to predict the ground conditions ahead of a tunnel face in TBM tunneling environments. The results showed that the modified dipole-dipole array is better than the other arrays in terms of predicting the location and shape of the anomalies ahead of the tunnel face. Having longer upper and lower borehole lengths led to better accuracy of the survey. However, the number and length of boreholes should be properly controlled according to the field environments in practice. Finally, a modified and verified technique to predict the ground conditions ahead of a tunnel face during TBM tunneling is proposed.

• Smart Structures and Systems
• /
• v.6 no.9
• /
• pp.1057-1077
• /
• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• Wind and Structures
• /
• v.23 no.1
• /
• pp.1-18
• /
• 2016

This work experimentally and numerically analyzes the flow configurations and the dynamic wind loads on panels of rectangular L/h 5:1 cross section mounted on a structural frame of rectangular bars of L/h 0.5:1, corresponding to a radar structure. The fluid dynamic interaction between panels and frame wakes imposes dynamic loads on the panels, with particular frequencies and Strouhal numbers, different from those of isolated elements. The numerical scheme is validated by comparison with mean forces and velocity spectra of a panel wake obtained by wind tunnel tests. The flow configuration is analyzed through images of the numerical simulations. For a large number of panels, as in the radar array, their wakes couple in either phase or counter-phase configurations, changing the resultant forces on each panel. Instantaneous normal and tangential force coefficients are reported; their spectra show two distinct peaks, caused by the interaction of the wakes. Finally, a scaled model of a rectangular structure comprised of panels and frame elements is tested in the boundary layer wind tunnel in order to determine the influence of the velocity variation with height and the three-dimensionality of the bulk flow around the structure. Results show that the unsteady aerodynamic loads, being strongly influenced by the vortex shedding of the supporting elements and by the global 3-D geometry of the array, differ considerably on a panel in this array from loads acting on an isolated panel, not only in magnitude, but also in frequency.

• Journal of the Society of Naval Architects of Korea
• /
• v.57 no.3
• /
• pp.140-151
• /
• 2020

It is important to identify the location of ship hull blocks with exact block identification number when scheduling the shipbuilding process. The wrong information on the location and identification number of some hull block can cause low productivity by spending time to find where the exact hull block is. In order to solve this problem, it is necessary to equip the system to track the location of the blocks and to identify the identification numbers of the blocks automatically. There were a lot of researches of location tracking system for the hull blocks on the stockyard. However there has been no research to identify the hull blocks on the stockyard. This study compares the performance of 5 Convolutional Neural Network (CNN) models with multi-view image set on the classification of the hull blocks to identify the blocks on the stockyard. The CNN models are open algorithms of ImageNet Large-Scale Visual Recognition Competition (ILSVRC). Four scaled hull block models are used to acquire the images of ship hull blocks. Learning and transfer learning of the CNN models with original training data and augmented data of the original training data were done. 20 tests and predictions in consideration of five CNN models and four cases of training conditions are performed. In order to compare the classification performance of the CNN models, accuracy and average F1-Score from confusion matrix are adopted as the performance measures. As a result of the comparison, Resnet-152v2 model shows the highest accuracy and average F1-Score with full block prediction image set and with cropped block prediction image set.

• Nuclear Engineering and Technology
• /
• v.48 no.2
• /
• pp.533-544
• /
• 2016

This paper provides a reference to determine the seal performance of metallic O-rings for a reactor pressure vessel (RPV). A nonlinear elastic-plastic model of an O-ring was constructed by the finite element method to analyze its intrinsic properties. It is also validated by experiments on scaled samples. The effects of the compression ratio, the geometrical parameters of the O-ring, and the structure parameters of the groove on the flange are discussed in detail. The results showed that the numerical analysis of the O-ring agrees well with the experimental data, the compression ratio has an important role in the distribution and magnitude of contact stress, and a suitable gap between the sidewall and groove can improve the sealing capability of the O-ring. After the optimization of the sealing structure, some key parameters of the O-ring (i.e., compression ratio, cross-section diameter, wall thickness, sidewall gap) have been recommended for application in megakilowatt class nuclear power plants. Furthermore, air tightness and thermal cycling tests were performed to verify the rationality of the finite element method and to reliably evaluate the sealing performance of a RPV.

• Earthquakes and Structures
• /
• v.22 no.2
• /
• pp.185-201
• /
• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.19 no.1
• /
• pp.7-17
• /
• 2016

The present study experimentally considers dynamic performance of large floating wave-offshore hybrid power generation platform in extreme conditions. In order to evaluate the motion performance of the large floating hybrid power generation platform, 1/50 scaled model was manufactured. A mooring line was also manufactured, and free-decay and static pull-out tests were carried out to check the mooring model. A mooring line table was introduced to satisfy the water depth, and environmental conditions were checked. Motion responses in regular waves were measured and complicated environmental conditions including wave, wind, and current were applied to see the dynamic performance in extreme/survival conditions. Maximum motion and acceleration were judged following the design criteria, and maximum offset and mooring tension were also checked based on the rule. The characteristics of hybrid power generation platform are discussed based on these data.