• Journal of Aerospace System Engineering
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• v.17 no.1
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• pp.88-96
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• 2023

KOMPSAT (Korean Multi-Purpose Satellite) is a Low-Earth-Orbit (LEO) satellite under development in Korea. Its performance has been steadily improving. At this time, power demand of the payload increased according to performance improvement of the payload. Accordingly, design of the satellite, such as design of the internal power supply device and the configuration of the solar array, was changed. Thus, many considerations are required according to an increase in power when designing power EGSE (Electric Ground Support Equipment) for supplying power to satellites and conduct satellite integration tests. This paper deals with matters to be considered when designing power EGSE according to changes in satellite power requirements according to payloads and increase in power requirements.

• Steel and Composite Structures
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• v.51 no.2
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• pp.117-126
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• 2024

There are many challenges in the construction of large-section tunnels, such as extremely soft rock and fractured zones. In order to solve these problems, the confined concrete support technology is proposed to control the surrounding rocks. The large-scale laboratory test is carried out to clarify mechanical behaviours of the combined confined concrete and traditional I-steel arches. The test results show that the bearing capacity of combined confined concrete arch is 3217.5 kN, which is 3.12 times that of the combined I-steel arch. The optimum design method is proposed to select reasonable design parameters for confined concrete arch. The parametric finite element (FE) analysis is carried out to study the effect of the design factors via optimum design method. The steel pipe wall thickness and the longitudinal connection ring spacing have a significant effect on the bearing capacity of the combined confined concrete arch. Based on the above research, the confined concrete support technology is applied on site. The field monitoring results shows that the arch has an excellent control effect on the surrounding rock deformation. The results of this research provide a reference for the support design of surrounding rocks in large-section tunnels.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.348-359
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• 2007

The conventional mobile VPN services assumed the mobile communications occur between the MN in foreign networks and the CN in the home network. However, if a MN wants to communicate with another MN in a foreign network, it could degrade the performance of the mobile VPN service because of the triangular routing problem. In this paper, we propose a route optimization mechanism based on the mobile VPN using an x-HA allocated by diameter MIP in order to support the efficient communication between the mobile VPN users in foreign networks. The i-HA maintains the VPN-TIA as well as the x-HoA as the CoAs to solve the security problem and to provide an efficient route optimization simultaneously. Moreover, we proposed revised IPSec tunnel configuration to reduce the IPSec tunnel overheads at a MN when the MN communicates with several MNs in the foreign networks at the same time. The VPN server, a security management entity in the home network, notifies an additional IPSec tunnel establishment between the x-HAs where the communication peers are registered. The simulation result showed that the proposed scheme decreases the end-to-end packet delay time and improves the throughput after the handoff compared to the existing mechanism.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.43-50
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• 2021

A Leg Mating Unit (LMU) is a device utilized during the float-over installation of offshore structures that include hyperelastic pads and mating part. The hyperelastic pads absorb the loads, whereas the mating part works as guidance between topside and supporting structures during the mating sequence of float-over installation. In this study, the design optimization of an LMU for the float-over installation of floating-type offshore structures is conducted to enhance the performance and to satisfy the requirements defined by classification society regulations. The initial dimensions of the LMU are referred to the dimensions of those used in fixed-type float-over installation because only the location and the number of LMUs are known. The two-parameter Mooney-Rivlin model is adopted to describe the hyperelastic pads under given material parameters. Geometric variables, such as the thickness, height, and width of members, as well as configuration variables, such as the angle and number of members, are defined as design variables and are parameterized. A sampling-based design sensitivity analysis based on latin hypercube sampling method is performed to filter the important design variables. The design optimization problem is formulated to minimize the total mass of the LMU under maximum von Mises stress and reaction force constraints.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.243-248
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• 2022

Weight optimization was performed for a rotorcraft shaft system using one-dimensional Euler-Bernoulli beam elements. Torsion, shaft support stiffness such as bearings, flange mass are all considered. To guarantee structural dynamic stability, eigenvalue analysis was performed to avoid critical speed and tooth mesh excitation form the gearbox. The weight optimization was performed by adjusting the thickness and radius while the length of the shaft was fixed, and the optimization process was divided into two stages. In the first, the weight is optimized with the torsional strength constraint. In the second, the difference between the primary mode of shaft and the critical speed is maximized so that the primary mode of the shaft can avoid the critical speed while the constraint on the torsional strength of the shaft is satisfied according to the standard for shaft system stability (AMC P 706-201, 1974). The proposed method was verified by comparing the results of the optimal design using the given one-dimensional beam elements with the stress results of the 3D finite element and the actual manufactured shaft.

• ETRI Journal
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• v.25 no.6
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• pp.510-516
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• 2003

In this paper, we describe the development of a platform-based SoC of a 32-bit smart card. The smart card uses a 32-bit microprocessor for high performance and two cryptographic processors for high security. It supports both contact and contactless interfaces, which comply with ISO/IEC 7816 and 14496 Type B. It has a Java Card OS to support multiple applications. We modeled smart card readers with a foreign language interface for efficient verification of the smart card SoC. The SoC was implemented using 0.25 ${\mu}m$ technology. To reduce the power consumption of the smart card SoC, we applied power optimization techniques, including clock gating. Experimental results show that the power consumption of the RSA and ECC cryptographic processors can be reduced by 32% and 62%, respectively, without increasing the area.

• Smart Structures and Systems
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• v.20 no.1
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• pp.53-60
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• 2017

Reinforced concrete shear wall is one of the most common structural forms for high-rise buildings, and seismic energy dissipation techniques, which are effective means to control structural vibration response, are being increasingly used in engineering. Reinforced concrete-mild steel damper stiffness-tandem energy dissipation coupling beams are a new technology being gradually adopted by more construction projects since being proposed. Research on this technology is somewhat deficient, and this paper investigates design principles and methods for two types of mild steel dampers commonly used for energy dissipation coupling beams. Based on the conception design of R.C. shear wall structure and mechanics principle, the basic design theories and analytic expressions for the related optimization parameters of dampers at elastic stage, yield stage, and limit state are derived. The outcomes provide technical support and reference for application and promotion of reinforced concrete-mild steel damper stiffness-tandem energy dissipation coupling beam in engineering practice.

• Clinical and Experimental Pediatrics
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• v.61 no.11
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• pp.339-347
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• 2018

Acute kidney injury (AKI) is characterized by abrupt deterioration of renal function, and its diagnosis relies on creatinine measurements and urine output. AKI is associated with higher morbidity and mortality, and is a risk factor for development of chronic kidney disease. There is no proven medication for AKI. Therefore, prevention and early detection are important. Physicians should be aware of the risk factors for AKI and should monitor renal function in high-risk patients. Management of AKI includes optimization of volume status and renal perfusion, avoidance of nephrotoxic agents, and sufficient nutritional support. Continuous renal replacement therapy is widely available for critically ill children, and this review provides basic information regarding this therapy. Long-term follow-up of patients with AKI for renal function, blood pressure, and proteinuria is recommended.