• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.1 s.53
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• pp.115-124
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• 2009

In this study, a numerical analysis technique was newly developed to evaluate the damage propagation characteristics of concrete structures. To do this, numerical techniques are incorporated for the concrete members up to the compressive damage due to the bending compressive forces after the tensile crack based on the deformation mechanism. Especially, for the compressive damage stage after the tensile crack, the crack propagation process will be analyzed numerically using the concept of an equivalent plastic hinged length. Using this concept, it can be established that section forces, such as axial forces and the moment cracks takes place, can be related to the width of the crack making it possible to analyze the crack extension.

• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.625-638
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• 2007

The damage detection process may appear difficult to be implemented for truss structures because not all degrees of freedom in the numerical model can be experimentally measured. In this context, the damage locating vector (DLV) method, introduced by Bernal (2002), is a useful approach because it is effective when operating with an arbitrary number of sensors, a truncated modal basis and multiple damage scenarios, while keeping the calculation in a low level. In addition, the present paper also evaluates the noise influence on the accuracy of the DLV method. In order to verify the DLV behavior under different damages intensities and, mainly, in presence of measurement noise, a parametric study had been carried out. Different excitations as well as damage scenarios are numerically tested in a continuous Warren truss structure subjected to five noise levels with a set of limited measurement sensors. Besides this, it is proposed another way to determine the damage locating vectors in the DLV procedure. The idea is to contribute with an alternative option to solve the problem with a more widespread algebraic method. The original formulation via singular value decomposition (SVD) is replaced by a common solution of an eigenvector-eigenvalue problem. The final results show that the DLV method, enhanced with the alternative solution proposed in this paper, was able to correctly locate the damaged bars, using an output-only system identification procedure, even considering small intensities of damage and moderate noise levels.

• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.197-204
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• 2019

A tree-length harvesting system using the HAM300, which is mounted on a farm tractor prototype machine, have been recently introduced in South Korea for thinning old (>30 years) forests. However, no research has previously been conducted on the characteristics of residual stand damage associated with cable yarding systems on thinning treatment stands in South Korea. Therefore, there were assessed on the degree and quantity of residual stand damage caused by felling and yarding process to broaden the knowledge of residual stand damage on semi-mechanized skyline thinning operations. This study investigated scar size, direction, area, shape type and their distribution on the residual stand damage caused by felling and yarding operations. Damage to residual trees was generated for 7.4% and 6.9% of residual trees in felling and yarding operations, respectively. Damaged direction of scars was located in front-side (38.9%) and up-side (34.7%) for felling operations while the highest scar damage was found on down-side (44.6%) for yarding operations. Scar heights of felling damage were higher than those of yarding damage. In yarding operation, the most of the scars was located within l0m from the center of the skyline corridor. These results should be useful information for forest managers and landowners to reduce residual stand damages and retain valuable timber volume from thinning treatments.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.303-316
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• 2024

Seismic records are composed of mainshock and a series of aftershocks which often result in the incremental damage to underground structures and bring great challenges to the rescue of post-disaster and the repair of post-earthquake. In this paper, the repetition method was used to construct the mainshock-aftershocks sequence which was used as the input ground motion for the analysis of dynamic time history. Based on the Daikai station, the two-dimensional finite element model of soil-station was established to explore the failure process of station under different seismic precautionary intensities, and the concept of incremental damage of station was introduced to quantitatively analyze the damage condition of structure under the action of mainshock and two aftershocks. An arc rubber bearing was proposed for the shock absorption. With the arc rubber bearing, the mode of the traditional column end connection was changed from "fixed connection" to "hinged joint", and the ductility of the structure was significantly improved. The results show that the damage condition of the subway station is closely related to the magnitude of the mainshock. When the magnitude of the mainshock is low, the incremental damage to the structure caused by the subsequent aftershocks is little. When the magnitude of the mainshock is high, the subsequent aftershocks will cause serious incremental damage to the structure, and may even lead to the collapse of the station. The arc rubber bearing can reduce the damage to the station. The results can offer a reference for the seismic design of subway stations under the action of mainshock-aftershocks.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.717-728
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• 2014

In this study, we developed a depth-damage function based on flood damage survey with focusing on building damage in urban area. We designed items for the questionnaire survey to develop a depth-damage function which estimates the amount of damage based on inundation depth targeting Dongducheon, Korea, which has experienced severe inundation damage due to significant flooding in July 2011. Based on the survey of the area, we developed a depth-damage function and used this to estimate the real amount of damage on buildings in the inundation area. To assess the damage on buildings, we categorized buildings into two groups; namely residential buildings and commercial buildings. Also, in order to calculate the real amount of damage caused by flooding, properties and detailed damaged items were sub-divided into two groups for the survey; facilities loss (wall paper, floor paper, painting, electrical facilities, and boilers) and furnishing loss (furniture, electronic products, and daily necessities. We expect this study on the process for developing depth-damage function and on the investigation research for flooded area to help in the efficient implementation of all kinds of disaster management policies and the attainment of a society safe from disaster.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• Tribology and Lubricants
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• v.36 no.1
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• pp.1-10
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• 2020

Large-area two-dimensional (2D) materials synthesized by chemical vapor deposition on donor substrates are promising functional materials for conductors, semiconductors, and insulators in flexible and transparent devices. In most cases, 2D materials should be transferred from a donor substrate to a target substrate; however, 2D materials are prone to damage during the transfer process. The damages to 2D materials during transfer are caused by contamination, tearing, and chemical doping. For the commercialization of 2D materials, a damage-free, large-area, and productive transfer process is needed. However, a transfer process that meets all three requirements has yet to be developed. In this paper, we review the recent progress in the development of transfer processes for 2D materials, and discuss the principles, advantages, and limitations of each process. The future prospects of transfer processes are also discussed. To simplify the discussion, the transfer processes are classified into four categories: wet transfer, dry transfer, mechanical transfer, and electro-chemical transfer. Finally, the "roll-to-roll" and "roll-to-plate" dry transfer process is proposed as the most promising method for the commercialization of 2D materials. Moreover, for successful dry transfer of 2D materials, it is necessary to clearly understand the adhesion properties, viscoelastic behaviors, and mechanical deformation of the transfer film used as a medium in the transfer process.

• Journal of the Microelectronics and Packaging Society
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• v.9 no.4
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• pp.17-23
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• 2002

The more productive and stable fabrication can be obtained by applying chemical mechanical polishing (CMP) process to shallow trench isolation (STI) structure in 0.18 $\mu\textrm{m}$ semiconductor device. However, STI-CMP process became more complex, and some kinds of defect such as nitride residue, tern oxide defect were seriously increased. Defects like nitride residue and silicon damage after STI-CMP process were discussed to accomplish its optimum process condition. In this paper, we studied how to reduce torn oxide defects and nitride residue after STI-CMP process. To understand its optimum process condition, We studied overall STI-related processes including trench depth, STI-fill thickness and post-CMP thickness. As an experimental result showed that as the STI-fill thickness becomes thinner, and trench depth gets deeper, more tern oxide were found in the CMP process. Also, we could conclude that low trench depth whereas high CMP thickness can cause nitride residue, and high trench depth and over-polishing can cause silicon damage.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.36-40
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• 2008

This study is analyzed by the simulation of automotive steering system. The maximum equivalent stress of $2.2418{\times}109Pa$ and the maximum total displacement of 0.014929m are shown at the universal joint and its lower part respectively. As the minimum cycle of 34.047 is shown at the universal joint in case of fatigue analysis, it is possible to have greatest damage at this part. In case of natural frequency analysis at vibration, its frequency of 47 to 59Hz is occurred generally. The maximum total displacement of 0.5m is shown at handle on the natural frequency of 57 to 58Hz. And the displacement over 2m is shown at the lower part of universal joint on the natural frequency of 58 to 59Hz. As the basis of the simulation analysis of steering system, passenger's comfort of car body can be improved in the design of practical part and the design effect necessary to safe driving can be promoted.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.48-55
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• 1997

A useful method to detect tool breakage suing neural network of cutting force signal is porposed and implemented in a basic cutting process. Cutting signal is gathered by tool dynamometer and normalized as a preprocessing. The cutting force signal level is continually monitored and compared with the predefined level. The neural network has been trained normalized sample data of the normal operation and cata-strophic tool failure using backpropagation learning process. The develop[ed system is verified to be very effective in real-time usage with minor modification in conventional cutting processes.