• Steel and Composite Structures
• /
• v.45 no.6
• /
• pp.775-796
• /
• 2022

In this study, a new type of energy absorbers with a functionally graded thickness is investigated, these type of absorbers absorb energy through expanding-folding processes. The expanding-folding absorbers are composed of two sections: a thin-walled aluminum matrix and a thin-walled steel mandrel. Previous studies have shown higher efficiency of the mentioned absorbers compared to the conventional ones. In this study, the effect of thickness which has been functionally-graded on the aluminum matrix (in which expansion occurs) was investigated. To this end, initial functions were considered for the matrix thickness, which was ascending/descending along the axis. The study was done experimentally and numerically. Comparing the experimental data with the numerical results showed high consistency between the numerical and experimental results. In the final section of this study, the best energy absorber functionally graded thickness was introduced by optimization using a third-order genetic algorithm. The optimization results showed that by choosing a minimum thickness of 1.6 mm and the exponential coefficient of 3.25, the most optimal condition can be obtained for descending thickness absorbers.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.9
• /
• pp.55-61
• /
• 2009

This paper presents a modified Phasor Discrete Particle Swarm Optimization (PDPSO) algorithm to configure Community Energy Systems(CESs) in the distribution system. The CES obtains electric power from its own Distributed Generations(DGs) and purchases insufficient power from the competitive power market, to supply power for customers contracted with the CES. When there are two or more CESs in a network, the CESs will continue the competitive expansion to reduce the total operation cost. The particles of the proposed PDPSO algorithm have magnitude and phase angle values, and move within a circle area. In the case study, the results by PDPSO algorithm was compared with that by the conventional DPSO algorithm.

• Journal of Microbiology and Biotechnology
• /
• v.16 no.6
• /
• pp.863-869
• /
• 2006

The behavior of submerged membrane bioreactor (SMBR) filtration systems utilizing rapid air backpulsing as a cleaning technique to remove reversible foulants was investigated using a genetic algorithm (GA). A customized genetic algorithm with suitable genetic operators was used to generate optimal time profiles. From experiments utilizing short and long periods of forward and reverse filtration, various experimental process parameters were determined. The GA indicated that the optimal values for the net flux fell between 263-270 LMH when the forward filtration time ($t_f$) was 30-37 s and the backward filtration time ($t_b$) was 0.19-0.27 s. The experimental data confirmed the optimal backpulse duration and frequency that maximized the net flux, which represented a four-fold improvement in 24-h backpulsing experiments compared with the absence of backpulsing. Consequently, the identification of a region of feasible parameters and nonlinear flux optimization were both successfully performed by the genetic algorithm, meaning the genetic algorithm-based optimization proved to be useful for solving SMBR flux optimization problems.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.4
• /
• pp.547-554
• /
• 2016

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.10
• /
• pp.809-816
• /
• 2014

This paper presents a systematic optimization process for designing an electromagnetic vibration energy harvester using FEA(finite element analysis) to improve computational accuracy and efficiency. A static FEA is used in the optimization process where trend analysis in a short period of time is rather important than precise computation, while a dynamic FEA is used in the verification step for the final result where precise computation is more important. An electromechanical transduction factor can be calculated efficiently by using an approach to use the radial component of magnetic flux density directly instead of an approach to compute the flux density gradient. The proposed optimization process was verified through a case study where simulation and experiment results were compared.

• ETRI Journal
• /
• v.37 no.4
• /
• pp.717-726
• /
• 2015

In this paper, we study an asymmetric two-way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time-division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy-efficient transmission. Our scheme is based on the asymmetric level of the two source nodes' target signal-to-noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.

• Structural Engineering and Mechanics
• /
• v.87 no.6
• /
• pp.555-574
• /
• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2002.05a
• /
• pp.120-120
• /
• 2002

• Journal of Communications and Networks
• /
• v.12 no.2
• /
• pp.150-157
• /
• 2010

Understanding and optimizing the energy consumption of wireless devices is critical to maximize the network lifetime and to provide guidelines for the design of new protocols and interfaces. In this work, we first provide an accurate analysis of the energy performance of an IEEE 802.11 WLAN, and then we derive the configuration to optimize it. We further analyze the impact of the energy configuration of the stations on the throughput performance, and we discuss under which circumstances throughput and energy efficiency can be both jointly maximized and where they constitute different challenges. Our findings are that, although an energy-optimized configuration typically yields gains in terms of throughput as compared against the default configuration, it comes with a reduction in performance as compared against the maximum-bandwidth configuration, a reduction that depends on the energy parameters of the wireless interface.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.12
• /
• pp.2311-2315
• /
• 2009

This paper presents a method to apply energy margin for assesment of total transfer capability (TTC). In order to calculate energy margin, two values of the transient energy function have to be computed. The first value is transient energy that is the sum of kinetic and potential energy at the end of fault. The second is critical energy that is potential energy at controlling UEP(Unstable Equilibrium Point). It is seen that TTC level is determined by not only bus voltage magnitudes and line thermal limits but also transient stability. TTC assessment is compared by the repeated power flow(RPF) method and optimization method.