• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.395-402
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• 2005

Recently Multidisciplinary Design Optimization Based on Independent Subspaces (MDOIS), an MDO (multidisciplinary design optimization) algorithm, has been proposed. In this research, an MDO problem is defined for design of a belt integrated seat considering crashworthiness, and MDOIS is applied to solve the problem. The crash model consists of an airbag, a belt integrated seat (BIS), an energy absorbing steering system, and a safety belt. It is found that the current design problem has two disciplines - structural nonlin- ear analysis and occupant analysis. The interdisciplinary relationship between the disciplines is identified and is addressed in the system analysis step in MDOIS. Interdisciplinary variables are belt load and stiffness of the seat, which are determined in system analysis step. The belt load is passed to the structural analysis subspace and stiffness of the seat back frame to the occupant analysis subspace. Determined design vari- ables in each subspace are passed to the system analysis step. In this way, the design process iterates until the convergence criterion is satisfied. As a result of the design, the weight of the BIS and Head Injury Crite- rion (HIC) of an occupant are reduced with specified constraints satisfied at the same time. Since the system analysis cannot be formulated in an explicit form in the current example, an optimization problem is formu - lated to solve the system analysis. The results from MDOIS are discussed.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.315-320
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• 2009

Thermoeconomics or exergoeconomics can be classified into the three fields of cost estimating, cost optimization, and internal cost analysis. The objective of cost estimating is to estimate each unit cost of product and allocate each cost flow of product such as electricity or hot water. The objective of optimization is to minimize the input costs of capital and energy resource or maximize the output costs of products under the given constraints. The objective of internal cost analysis is to find out the cost formation process and calculate the amount of cost flow at each state, each component, and overall system. In this study, a new thermoeconomic methodology was proposed in the three fields. The proposed methodology is very simple and obvious. That is, the equation is only each one, and there are no auxiliary equations. Any energy including enthalpy and exergy can be applied and evaluated by this equation. As a new field, the cost allocation methodology on cool air or hot air produced from an air-condition system was proposed. Extending this concept, the proposed methodology can be applied to any complex system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.7
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• pp.945-950
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• 2002

Shape optimization of a flow system is done to obtain the required effects, in the engineering fields. Most of these designs are accomplished by empirical or numerical analysis. In empirical analysis, it is difficult to obtain an optimal shape in the feasible design region. And, in numerical method, it usually needs much calculation expenses for shape optimization, because of design sensitivity analysis. In this study, we used the growth-strain method having only one distributed parameter such as a design variable. It optimizes a shape by making a distributed parameter such as dissipation energy uniform in a flow system, and then applied to two-flow systems. In order to overcome the stability occurred in numerical analysis performed by Azegami, the equation of volumic strain has been modified. Also, the shapes were compared with the known optimal shapes for the flow systems. Consequently, we confirm that the modified growth-strain method is very efficient and practical in shape optimization of the flow systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1484-1487
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• 1996

An Automatic coking control system was developed to achieved substantial energy and labor savings through the stabilization and optimization of coke oven operation. With the aim of saving energy and labor, the coke department has been advanced automation and systematization. A typical examples of automation is Center Position Control System(CPCS) for coke oven. This system is proved effective in improvement of center position accuracy.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.44-50
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• 2023

For Wi-Fi and IoT wireless systems, high-capacity wireless communication technology is being applied using MIMO OFDM. Because of virtu0al subcarriers in the practical MIMO OFDM system, the pilot subcarriers cannot be spaced equally. Thus, it is difficult to obtain a good mean square error (MSE) performance of the channel estimate. This paper proposes applicable methods and the newly discovered locations of pilot subcarriers in four transmitted antennas resulting in a good MSE performance with proposed optimization algorithms.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.2
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• pp.53-69
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• 2010

This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therefore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.238-243
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• 2013

In this paper, a novel approach for optimized installation and operations of battery energy storage system (BESS) and electric double layer capacitor (EDLC) modules for the renewable energy based intermittent generation is presented for them to be connected with an electric power grid. In order to make use of not merely the high energy density of battery but also the high power density of EDLC modules, it is very useful to devise the hybrid system which combines BESS and EDLC modules. The proposed method adopts the linear programming to calculate the optimized capacity as well as the quadratic programming to transmit the optimal operational signals to BESS and EDLC modules. The efficiency of this methodology will be demonstrated in the experimental study with the real data of wind speed in Texas.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.380-387
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• 2015

A lead slowing-down spectrometer (LSDS) system is a promising nondestructive assay technique that enables a quantitative measurement of the isotopic contents of major fissile isotopes in spent nuclear fuel and its pyroprocessing counterparts, such as $^{235}U$, $^{239}Pu$, $^{241}Pu$, and, potentially, minor actinides. The LSDS system currently under development at the Korea Atomic Energy Research Institute (Daejeon, Korea) is planned to utilize a high-flux ($>10^{12}n/cm^2{\cdot}s$) neutron source comprised of a high-energy (30 MeV)/high-current (~2 A) electron beam and a heavy metal target, which results in a very intense and complex radiation field for the facility, thus demanding structural shielding to guarantee the safety. Optimization of the structural shielding design was conducted using MCNPX for neutron dose rate evaluation of several representative hypothetical designs. In order to satisfy the construction cost and neutron attenuation capability of the facility, while simultaneously achieving the aimed dose rate limit (< $0.06{\mu}Sv/h$), a few shielding materials [high-density polyethylene (HDPE)eBorax, $B_4C$, and $Li_2CO_3$] were considered for the main neutron absorber layer, which is encapsulated within the double-sided concrete wall. The MCNP simulation indicated that HDPE-Borax is the most efficient among the aforementioned candidate materials, and the combined thickness of the shielding layers should exceed 100 cm to satisfy the dose limit on the outside surface of the shielding wall of the facility when limiting the thickness of the HDPE-Borax intermediate layer to below 5 cm. However, the shielding wall must include the instrumentation and installation holes for the LSDS system. The radiation leakage through the holes was substantially mitigated by adopting a zigzag-shape with concrete covers on both sides. The suggested optimized design of the shielding structure satisfies the dose rate limit and can be used for the construction of a facility in the near future.