• Journal of computational fluids engineering
• /
• v.13 no.4
• /
• pp.96-106
• /
• 2008

We review a series of studies on turbulent skin friction drag reduction in wall-turbulence recently conducted in Japan. First, an identity equation relating the skin friction drag and the Reynolds shearstress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• 한국전산유체공학회:학술대회논문집
• /
• 2008.03a
• /
• pp.347-354
• /
• 2008

We introduce a series of studies on turbulent skin friction drag reduction in wall-turbulence. First, an identity equation relating the skin friction drag and the Reynolds shear stress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• 한국전산유체공학회:학술대회논문집
• /
• 2008.10a
• /
• pp.347-354
• /
• 2008

We introduce a series of studies on turbulent skin friction drag reduction in wall-turbulence. First, an identity equation relating the skin friction drag and the Reynolds shear stress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• Journal of Intelligence and Information Systems
• /
• v.3 no.2
• /
• pp.1-9
• /
• 1997

These papers propose an evolutionary algorithm for re-using output of waste fuel of light water reactor system in nuclear power plants. Evolutionary algorithm is useful for optimization of the large space problem. The wastes contain several re-useable elements, and they should be carefully selected and blended to satisfy requirements as input material to the heavy water nuclear reactor system. This problem belongs to a NP-hard like the 0/1 Knapsack problem. Two evolutionary strategies are used as a, pp.oximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method, which performs the feasible teat and solution evaluation by using the vectorized data in problem. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.3
• /
• pp.231-238
• /
• 2002

As a modeling method where the merits of fuzzy inference system and evolutionary computation are put together, evolutionary fuzzy modeling performs global approximate optimization. The paper proposes fuzzy clustering as fuzzy rule generation process which is one of the most important steps in evolutionary fuzzy modeling. With application of fuzzy clustering into the experiment or simulation results, fuzzy rules which properly describe non-linear and complex design problem can be obtained. The efficiency of evolutionary fuzzy modeling can be improved utilizing the membership degrees of data to clusters from the results of fuzzy clustering. To ensure the validity of the proposed method, the real design problem of an automotive inner trim is applied and the global approximation is achieved. Evolutionary fuzzy modeling is performed for several cases which differ in the number of clusters and the criterion of rule selection and their results are compared to prove that the proposed method can provide proper fuzzy rules for a given system and reduce computation time while maintaining the errors of modeling as a satisfactory level.

• Journal of the Korea Society for Simulation
• /
• v.21 no.4
• /
• pp.65-73
• /
• 2012

Due to the development of technology related to a weapon system and the info-communication, the battle system of a warship has to manage many kinds of human intervention tactics according to the complicated battlefield environment. Therefore, many kinds of studies about M&S(Modeling & Simulation) have been carried out recently. The previous M&S system based on an agent, however, has simply used non-flexible(or fixed) tactics. In this paper, we propose an agent modeling methodology which has reinforcement learning function for spontaneous(active) reaction and generation evolution learning Function using Genetic Algorithm for more proper reaction for warship battle. We experiment with virtual 1:1 warship combat simulation on the west sea so as to test validity of our proposed methodology. We consequently show the possibility of both reinforcement and evolution learning in a warship battle.

• Journal of the Korea Society for Simulation
• /
• v.12 no.1
• /
• pp.73-83
• /
• 2003

This paper presents armed vehicle BAttle Group Simulation model(called BAGSim) which is an object-oriented simulation system for representing battle group engagement consisting of tanks and helicopters. BAGSim is designed in the evolutionary software life cycle approach with the Unified Software Development Process, and implemented with C++ language. BAGSim consists of a preprocessor for engagement scenario definition and simulation data set up, a main processor for triggering engagement event and advancing simulation clock, and a post processor to record simulation histories. Application scenario covers several type of engagement among command tanks, fight tanks, scout helicopters, attack helicopters, anti-tank guided missiles, and decoys. Thus, BAGSim can be effectively used as an analytic tool to examine some operational concepts and tactics, further experimentally fine tune tank design options.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.6
• /
• pp.2697-2710
• /
• 2018

Owing to the development of Internet of Things (IoT), the fifth-generation (5G) wireless communication is going to foresee a substantial increase of mobile traffic demand. Energy efficiency and spectral efficiency are the challenges in a 5G network. Non-orthogonal multiple access (NOMA) is a promising technique to increase the system efficiency by adaptive power control (PC) in a 5G network. This paper proposes an efficient PC scheme based on evolutionary game theory (EGT) model for uplink power-domain NOMA system. The proposed PC scheme allows users to adaptively adjusts their transmit power level in order to improve their payoffs or throughput which results in an increase of the system efficiency. In order to separate the user signals, a successive interference cancellation (SIC) receiver installed at the base station (BS) site. The simulation results demonstrate that the proposed EGT-based PC scheme outperforms the traditional game theory-based PC schemes and orthogonal multiple access (OMA) in terms of energy efficiency and spectral efficiency.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.9
• /
• pp.1521-1526
• /
• 2007

This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

• Journal of KIISE:Information Networking
• /
• v.37 no.3
• /
• pp.228-233
• /
• 2010

During wireless network operations, adaptive power control is an effective way to enhance the network performance. In this paper, a new online power control scheme is proposed based on the evolutionary game theory. To converge a desirable network equilibrium, the proposed scheme adaptively adjusts a transmit power level in a distributed online manner. With a simulation study, we demonstrate that the proposed scheme improves network performance under widely diverse network environments.