• Kyungpook Mathematical Journal
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• v.64 no.1
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• pp.95-111
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• 2024

The filled function method is useful in solving unconstrained global optimization problems. However, depending on the type of function, and parameters used, there are limitations that cause difficultiies in implemenations. Exponential and logarithmic functions lead to the overflow effect, requiring iterative adjustment of the parameters. This paper proposes a polynomial-filled function that has a general form, is non-exponential, nonlogarithmic, non-parameteric, and continuously differentiable. With this newly proposed filled function, the aforementioned shortcomings of the filled function method can be overcome. To confirm the superiority of the proposed filled function algorithm, we apply it to a set of unconstrained global optimization problems. The data derived by numerical implementation shows that the proposed filled function can be used as an alternative algorithm when solving unconstrained global optimization problems.

• Bulletin of the Korean Chemical Society
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• v.25 no.8
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• pp.1125-1129
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• 2004

This work assesses the potential of natural Analcime Zeolite as an adsorbent for preconcentration of lead (II) traces. Lead is quantitatively retained on 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol by column method with Analcime in the pH range of 5-6.5 and 2 mL $min^{?1}$ flow rate. Lead was removed from the column with 10.0 mL of 4 M hydrochloric acid and was determined by anodic stripping differential pulse voltammetry. 0.5ppb detection limit was obtained and linear dynamic range was 3 to $1.2{\times}10^5$ ppb in final solution with correlation coefficient of 0.999 and relative standard deviation of ${\pm}$ 1.2% (for eight replicate determination of 2.5 ${\mu}g\;mL^{?1}$ of lead). Various parameters such as the effect of pH, flow rate, instrumental conditions and interferences of some ions on the determination of lead have been studied in detail for optimization of conditions. The method was successfully applied for determination of lead in various samples.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1353-1362
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• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1472-1479
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• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).

• Geomechanics and Engineering
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• v.10 no.6
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• pp.709-726
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• 2016

Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.4 s.247
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• pp.381-388
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• 2006

The objective of this study is to predict the etching characteristics using spray characteristics for the optimization on the etching process of Lead-Frame. The etching characteristics such as etching factor, uniformity were investigated on the actual operating conditions. The correlation between the etching characteristics and the spray ones obtained by measurement were analyzed to simulate the etching characteristics according to actual conditions of lead-frame etching process. These conditions of lead-frame process were spray pressure, distance from nozzle tip to substrate, pipe pitch, and nozzle pitch. To improve the etching characteristics in the lead-frame process, effects of the various operating conditions should be understood in detail. The spray characteristics obtained by experiment using PDA system were simulated by the Monte-Carlo method. The etching process model was coded by Java language. It was found that simulation results generally agreed well with the measured results of etching characteristics in lead-frame etching process. The optimal operating parameters were successfully found under variable conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.29-34
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• 2017

In this paper, we report a method of improving the productivity of lead wire fabricated through the rolling process by increasing its linear velocity. The most important point to consider when raising the linear velocity is that the original specifications must still be adhered to. In other words, the dimensional tolerance must be satisfied when increasing the linear velocity of the wire without causing cracks. However, if the linear velocity of the wire is increased, the degree of reduction must also be increased, which causes more damage to the wire and increases the load on its surface. Therefore, we studied a three step rolling process which can satisfy the specifications of the wire produced through the two step rolling process and improve the productivity. In this study, only the roll gap of the three-stage rolling roller is assumed to be a variable, while the other conditions are the same as the field conditions. In addition, through the PIANO (Process Integration, Design and Optimization) tool, the (optimum?) surface roughness and maximum stress are maintained.

• Progress in Medical Physics
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• v.27 no.3
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• pp.125-130
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• 2016

Dual energy computed tomography (DECT) is used to classify two materials and quantify the mass density of each material in the human body. An energy modulation filter based DECT could acquire two images, which are generated by the low- and high-energy photon spectra, in one scan, with one tube and detector. In the case of DECT using the energy modulation filter, the filter should perform the optimization process for the type of materials and thicknesses for generating two photon spectra. In this study, Geant4 Monte-Carlo simulation toolkit was used to execute the optimization process for determining the property of the energy modulation filter. In the process, various materials used for the energy modulation filter are copper (Cu, $8.96g/cm^3$), niobium (Nb, $8.57g/cm^3$), stannum (Sn, $7.31g/cm^3$), gold (Au, $19.32g/cm^3$), and lead (Pb, $11.34g/cm^3$). The thickness of the modulation filter varied from 0.1 mm to 1.0 mm. To evaluate the overlap region of the low- and high-energy spectrum, Geant4 Monte-Carlo simulation is used. The variation of the photon flux and the mean energy of photon spectrum that passes through the energy modulation filter are evaluated. In the primary photon spectrum of 80 kVp, the optimal modulation filter is a 0.1 mm lead filter that can acquire the same mean energy of 140 kVp photon spectrum. The lead filter of 0.1 mm based dual energy CBCT is required to increase the tube current 4.37 times than the original tube current owing to the 77.1% attenuation in the filter.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.477-480
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• 2003

Packet losses in the Internet can dramatically degrade quality of multimedia streams. Forward Error Correction (FEC) is one of the best methods that can protect data from packet erasures by means of sending additional redundant information. Proposed control algorithm provides the possibility of receiving real-time multimedia streams of given quality wifth minimal traffic overhead. The traffic optimization is reached by adjusting packet size as well as block code parameters. Calculations and simulation results show that for non-bursty network conditions traffic optimization can lead to more than 50% bandwidth reduction.

• Advances in Computational Design
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• v.6 no.1
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• pp.15-30
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• 2021

With improvement in innovative manufacturing technologies, it became possible to fabricate any complex shaped structural design for practical applications. This allows for the fabrication of curvilinearly stiffened pressure vessels and pipes. Compared to straight stiffeners, curvilinear stiffeners have shown to have better structural performance and weight savings under certain loading conditions. In this paper, an optimization framework for designing curvilinearly stiffened composite pressure vessels and pipes is presented. NURBS are utilized to define curvilinear stiffeners over the surface of the pipe. An integrated tool using Python, Rhinoceros 3D, MSC.PATRAN and MSC.NASTRAN is implemented for performing the optimization. Rhinoceros 3D is used for creating the geometry, which later is exported to MSC.PATRAN for finite element model generation. Finally, MSC.NASTRAN is used for structural analysis. A Bi-Level Programming (BLP) optimization technique, consisting of Particle Swarm Optimization (PSO) and Gradient-Based Optimization (GBO), is used to find optimal locations of stiffeners, geometric dimensions for stiffener cross-sections and layer thickness for the composite skin. A cylindrical pipe stiffened by orthogonal and curvilinear stiffeners under torsional and bending load cases is studied. It is seen that curvilinear stiffeners can lead to a potential 10.8% weight saving in the structure as compared to the case of using straight stiffeners.