• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.6
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• pp.1-14
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• 2007

Optimal design method of nonlinear damping system for seismic response control of adjacent structures is studied in this paper. The objective functions of the optimal design are defined by structural response and total amount of the dampers. In order to obtain a solution minimizing two mutually conflicting objective functions simultaneously, multi-objective optimization technique based on genetic algorithm is adopted. In addition, stochastic linearization method is embedded into the multi-objective framework to efficiently estimate the seismic responses of the adjacent structures interconnected by nonlinear hysteretic dampers without performing nonlinear time-history analyses. As a numerical example to demonstrate the effectiveness of the proposed technique, 20-story and 10-story buildings are considered and MR dampers of which hysteretic behaviors vary with the magnitude of the input voltage are considered as nonlinear hysteretic damper interconnecting two adjacent buildings. The proposed approach can provide the optimal number and capacities of the MR dampers, which turned out to be more economical than the uniform distribution system while maintaining similar control performance. The proposed damper system is verified to show more stable performance in terms of the pounding probability between two adjacent buildings. The applicability of the proposed method to the design problem for optimally placing semi-active control system is examined as well.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.265-288
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• 2023

Process mining has generally analyzed the default logs of Information Systems such as SAP ERP, but as the use of automation software called RPA expands, the logs by RPA bots can be utilized. In this study, the actual status of RPA automation in the field was identified by applying RPA bots to the work of three domestic manufacturing companies (cosmetic field) and analyzing them after leaving logs. Using Uipath and Python, we implemented RPA bots and wrote logs. We used Disco, a software dedicated to process mining to analyze the bot logs. As a result of log analysis in two aspects of bot utilization and performance through process mining, improvement requirements were found. In particular, we found that there was a point of improvement in all cases in that the utilization of the bot and errors or exceptions were found in many cases of process. Our approach is very scientific and empirical in that it analyzes the automation status and performance of bots using data rather than existing qualitative methods such as surveys or interviews. Furthermore, our study will be a meaningful basic step for bot behavior optimization, and can be seen as the foundation for ultimately performing process management.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.113-119
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• 2023

Most infrastructure structures were completed during periods of economic growth. The number of infrastructure structures reaching their lifespan is increasing, and the proportion of old structures is gradually increasing. The functions and performance of these structures at the time of design may deteriorate and may even lead to safety accidents. To prevent this repercussion, accurate inspection and appropriate repair are requisite. To this end, demand is increasing for computer vision and deep learning technology to accurately detect even minute cracks. However, deep learning algorithms require a large number of training data. In particular, label images indicating the location of cracks in the image are required. To secure a large number of those label images, a lot of labor and time are consumed. To reduce these costs as well as increase detection accuracy, this study proposed a learning structure based on mean teacher method. This learning structure was trained on a dataset of 900 labeled image dataset and 3000 unlabeled image dataset. The crack detection network model was evaluated on over 300 labeled image dataset, and the detection accuracy recorded a mean intersection over union of 89.23% and an F1 score of 89.12%. Through this experiment, it was confirmed that detection performance was improved compared to supervised learning. It is expected that this proposed method will be used in the future to reduce the cost required to secure label images.

• Composites Research
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• v.36 no.6
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• pp.454-460
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• 2023

Recently, regulations on greenhouse gas emissions have been strengthened, and the International Maritime Organization (IMO) has been strengthening greenhouse gas regulations with a goal of net 'zero' emissions by 2050. In addition, in the shipbuilding/offshore sector, it is important to reduce operating costs, such as improving propulsion efficiency and lightening structures. In this regard, research is currently being conducted on topology optimization using 3D printed composite materials to satisfy structural lightness and high rigidity. In this study, three topology shapes (hexagonal, square, and triangular) were applied to the interior of a rudder, a ship structure, using 3D printed composite materials. Structural analysis was performed to determine the appropriate shape for the rudder. CFD analysis was performed at 10° intervals from 0° to 30° for each rudder angle under the condition of 8 knots, and the load conditions were set based on the CFD analysis results. As a result of the structural analysis considering the internal topology shape of the rudder, it was confirmed that the triangular, square, and hexagonal topology shapes have excellent performance. The rudder with a square topology shape weighs 78.5% of the rudder with a triangular shape, and the square topology shape is considered to superior in terms of weight reduction.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.5
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• pp.353-359
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• 2024

Lattice structures exhibit good thermal performance due to the high surface-to-volume ratio. Previous studies have investigated the thermal conductivity to improve the performance of lattice structures. However, the conventional approach simplifies the geometry of lattice structures using limited design parameters due to the high computational or experimental costs. This study introduces a lattice structure with optimal thermal conductivity. We propose a lattice beam shape that overcomes the existing design limitations through shape optimization using artificial intelligence. First, the beam shape of the body-centered (BC) lattice structure is modeled as a smooth Bézier curve. Second, the coordinates of the control points of the Bézier curve are randomly set to obtain training data. Finally, the optimal beam shape is designed by generating a beam shape with excellent effective thermal conductivity through a neural network combined with a genetic algorithm. A mechanism of optimized thermal conductivity is suggested and the optimal beam shape is compared with a lattice structure with optimal elastic stiffness. The results of this study are expected to provide an appropriate structural solution for lattice structures under various thermal conditions in the future.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.380-385
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• 2004

The efficiency of complex slurry preparation route for developing the high performance SiC matrix of RS-SiCf/SiC composites has been investigated. The green bodies for RS-SiC materials prior to the infiltration of nw/ten silicon were prepared with various C/SiC complex matrix slurries, which associated with both different sizes of starting SiC particles and blending ratios of starting SiC and carbon particles. The characterization of RS-SiC materials was examined by means of SEM, TEM, EDS and three point bending test. Based on the mechanical property-microstructure correlation, process optimization methodology is also discussed. The flexural strength of RS-SiC materials greatly depended on the content of residual Si. The decrease of starting SiC particle size in the C/SiC complex slurry was effective for improving the flexural strength of RS-SiC materials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.22-37
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• 2013

Content distribution to a large number of concurrent clients stresses both server and network. While the server limitation can be circumvented by deploying server clusters, the network limitation is far less easy to cope with, due to the difficulty in measuring and balancing network load. In this paper, we use two useful network load metrics, the worst link stress (WLS) and the degree of interference (DOI), and formulate the problem as partitioning the clients into disjoint subsets subject to the server capacity constraint so that the WLS and the DOI are reduced for each session and also well balanced across the sessions. We present a network load-aware partition algorithm, which is practicable and effective in achieving the design goals. Through experiments on PlanetLab, we show that the proposed scheme has the remarkable advantages over existing schemes in reducing and balancing the network load. We expect the algorithm and performance metrics can be easily applied to various Internet applications, such as media streaming, multicast group member selection.

• Korean Journal of Materials Research
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• v.24 no.9
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• pp.451-457
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• 2014

We developed a high-performance methane gas sensor based on a $SnO_2$ hollow hemisphere array structure of nano-thickness. The sensor structures were fabricated by sputter deposition of Sn metal over an array of polystyrene spheres distributed on a planar substrate, followed by an oxidation process to oxidize the Sn to $SnO_2$ while removing the polystyrene template cores. The surface morphology and structural properties were examined by scanning electron microscopy. An optimization of the structure for methane sensing was also carried out. The effects of oxidation temperature, film thickness, gold doping, and morphology were examined. An impressive response of ~220% was observed for a 200 ppm concentration of $CH_4$ gas at an operating temperature of $400^{\circ}C$ for a sample fabricated by 30 sec sputtering of Sn, and oxidation at $800^{\circ}C$ for 2 hr in air. This high response was enabled by the open structure of the hemisphere array thin films.

• Advances in aircraft and spacecraft science
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• v.1 no.3
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• pp.331-351
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• 2014

The paper presents the development of numerical models referred to a morphing actuated aileron. The structural solution adopted consists of an internal part made of a composite chiral honeycomb that bears a flexible skin with an adequate combination of flexural stiffness and in-plane compliance. The identification of such structural frame makes possible an investigation of different actuation concepts based on diffused and discrete actuators installed in the skin or in the skin-core connection. An efficient approach is presented for the development of aeroelastic condensed models of the aileron, which are used in sensitivity studies and optimization processes. The aerodynamic performances and the energy required to actuate the morphing surface are evaluated and the definition of a general energetic performance index makes also possible a comparison with a rigid aileron. The results show that the morphing system can exploit the fluid-structure interaction in order to reduce the actuation energy and to attain considerable variations in the lift coefficient of the airfoil.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1119-1143
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• 2014

Lightweight trust mechanism with lightweight cryptographic primitives has emerged as an important mechanism in resource constraint wireless sensor based mobile devices. In this work, outlier detection in lightweight Mobile Ad-hoc NETworks (MANETs) is extended to create the space of reliable trust cycle with anomaly detection mechanism and minimum energy losses [1]. Further, system is tested against outliers through detection ratios and anomaly scores before incorporating virtual programmable nodes to increase the efficiency. Security in proposed system is verified through ProVerif automated toolkit and mathematical analysis shows that it is strong against bad mouthing and on-off attacks. Performance of proposed technique is analyzed over different MANET routing protocols with variations in number of nodes and it is observed that system provide good amount of throughput with maximum of 20% increase in delay on increase of maximum of 100 nodes. System is reflecting good amount of scalability, optimization of resources and security. Lightweight modeling and policy analysis with lightweight cryptographic primitives shows that the intruders can be detection in few milliseconds without any conflicts in access rights.