• Advances in nano research
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• v.10 no.5
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• pp.423-435
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• 2021

This paper examines the thermal post-buckling behaviors of graphene-reinforced metal matrix composite (GRMMC) laminated cylindrical panels which possess in-plane negative Poisson's ratio (NPR) and rest on an elastic foundation. A panel consists of GRMMC layers of piece-wise varying graphene volume fractions to obtain functionally graded (FG) patterns. Based on the MD simulation results, the GRMMCs exhibit in-plane NPR as well as temperature-dependent material properties. The governing equations for the thermal post-buckling of panels are based on the Reddy's third order shear deformation shell theory. The von Karman nonlinear strain-displacement relationship and the elastic foundation are also included. The nonlinear partial differential equations for GRMMC laminated cylindrical panels are solved by means of a singular perturbation technique in associate with a two-step perturbation approach and in the solution process the boundary layer effect is considered. The results of numerical investigations reveal that the thermal post-buckling strength for (0/90)_5T GRMMC laminated cylindrical panels can be enhanced with an FG-X pattern. The thermal post-buckling load-deflection curve of 6-layer (0/90/0)_S and (0/90)_3T panels of FG-X pattern are higher than those of 10-layer (0/90/0/90/0)_S and (0/90)_5T panels of FG-X pattern.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.77-86
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• 1996

In this paper we deal with the problem of recovering 3-D motion and structure from a time-varying 2-D velocity vector field. A great deal has been done on this topic, most of which has concentrated on finding necessary and sufficient conditions for there to be a unique 3-D solution corresponding to a given 2-D motion. While previous work provides useful theoretical insight, in most situations the known algorithms have turned out to be too sensitive to be of much practical use. It appears that any robust algorithm must improve the 3-D solutions over time. As a step toward such algorithm, we present a method for recovering 3-D motion and structure from a given time-varying 2-D velocity vector field. The surface of the object in the scene is assumed to be locally planar. It is also assumed that 3-D velocity vectors are piecewise constant over three consecutive frames (or two snapshots of flow field). Our formulation relates 3-D motion and object geometry with the optical flow vector as well as its spatial and temporal derivatives. The linearization parameters, or equivalently, the first-order flow approximation (in space and time) is sufficient to recover rigid body motion and local surface structure from the local instantaneous flow field. We also demonstrate, through a sensitivity analysis carried out for synthetic and natural motions in space, that 3-D motion can be recovered reliably.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.139-145
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• 2024

This study aims to elucidate the mechanism involved in the hydrolysis of the hexacyanoferrate(III) complex ion (Fe(CN)₆^3-) and the mechanism leading to the formation of Prussian blue (Fe^III₄[Fe_II(CN)₆]₃·xH₂O, PB) in acidic aqueous solutions at moderately elevated temperatures. Hydrolysis constitutes a crucial step in generating PB through the widely used single-source or precursor method. Recent PB syntheses predominantly rely on the single-source method, where hexacyanoferrate(II/III) is the exclusive reactant, as opposed to the co-precipitation method employing bare metal ions and hexacyanometalate ions. Despite the widespread adoption of the single-source method, mechanistic exploration remains largely unexplored and speculative. Utilizing UV-vis spectrophotometry, negative-ion mode liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS), and a devised reaction, this study identifies crucial intermediates, including aqueous Fe^2+/3+ ions and hydrocyanic acid (HCN) in the solution. These two intermediates eventually combine to form thermodynamically stable PB. The findings presented in this research significantly contribute to understanding the fundamental mechanism underlying the acid-catalyzed hydrolysis of the hexacyanoferrate(III) complex ion and the subsequent formation of PB, as proposed in the sequential mechanism introduced herein. This finding might contribute to the cost-effective synthesis of PB by incorporating diverse metal ions and potassium cyanide.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.843-859
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• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1698-1711
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• 2024

Heat pipe cooled reactors have gained attention as a potential solution for nuclear power generation in space and deep sea applications because of their simple design, scalability, safety and reliability. However, under complex operating conditions, a control strategy for variable load operation is necessary. This paper presents a two-dimensional transient characteristics analysis program for a heat pipe cooled reactor and proposes a variable load control strategy using the recuperator bypass (CSURB). The program was verified against previous studies, and steady-state and step-load operating conditions were calculated. For normal operating condition, the predicted temperature distribution with constant heat pipe temperature boundary conditions agrees well with the literature, with a maximum temperature difference of 0.4 K. With the implementation of the control strategy using the recuperator bypass (CSURB) proposed in this paper, it becomes feasible to achieve variable load operation and return the system to a steady state solely through the self-regulation of the reactor, without the need to operate the control drum. The average temperature difference of the fuel does not exceed 1 % at the four power levels of 70 %,80 %, 90 % and 100 % Full power. The output power of the turbine can match the load change process, and the temperature difference between the inlet and outlet of the turbine increases as the power decreases.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.95-105
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• 2003

Because the basic assumptions of deterministic user equilibrium assignment that all network users have perfect information of network condition and determine their routes without errors are known to be unrealistic, several stochastic assignment models have been proposed to relax this assumption. However. it is not easy to solve such stochastic assignment models due to the probability distribution they assume. Also. in order to avoid all path enumeration they restrict the number of feasible path set, thereby they can not preciously explain the travel behavior when the travel cost is varied in a network loading step. Another problem of the stochastic assignment models is stemmed from that they use heuristic approach in attaining optimal moving size, due to the difficulty for evaluation of their objective function. This paper presents a logit-based stochastic assignment model and its solution algorithm to cope with the problems above. We also provide a stochastic user equilibrium condition of the model. The model is based on path where all feasible paths are enumerated in advance. This kind of method needs a more computing demand for running the model compared to the link-based one. However, there are same advantages. It could describe the travel behavior more exactly, and too much computing time does not require than we expect, because we calculate the path set only one time in initial step Two numerical examples are also given in order to assess the model and to compare it with other methods.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1021-1028
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• 2005

The general solution for classification and regression problems can be found by matching and modifying matrices with the information in real world and then these matrices are teaming in neural networks. This paper treats primary space as a real world, and dual space that Primary space matches matrices using kernel. In practical study, there are two kinds of problems, complete system which can get an answer using inverse matrix and ill-posed system or singular system which cannot get an answer directly from inverse of the given matrix. Further more the problems are often given by the latter condition; therefore, it is necessary to find regularization parameter to change ill-posed or singular problems into complete system. This paper compares each performance under both classification and regression problems among GCV, L-Curve, which are well known for getting regularization parameter, and kernel methods. Both GCV and L-Curve have excellent performance to get regularization parameters, and the performances are similar although they show little bit different results from the different condition of problems. However, these methods are two-step solution because both have to calculate the regularization parameters to solve given problems, and then those problems can be applied to other solving methods. Compared with UV and L-Curve, kernel methods are one-step solution which is simultaneously teaming a regularization parameter within the teaming process of pattern weights. This paper also suggests dynamic momentum which is leaning under the limited proportional condition between learning epoch and the performance of given problems to increase performance and precision for regularization. Finally, this paper shows the results that suggested solution can get better or equivalent results compared with GCV and L-Curve through the experiments using Iris data which are used to consider standard data in classification, Gaussian data which are typical data for singular system, and Shaw data which is an one-dimension image restoration problems.

• Analytical Science and Technology
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• v.13 no.5
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• pp.584-591
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• 2000

The separation of Nd from the simulated $U_3Si/Al$ spent fuel solution with sequential two-step anion exchange separation has been studied. To prepare the simulated $U_3Si/Al$ spent nuclear fuel, unirradiated $U_3Si/Al$ whose composition consists of small $U_3Si$ particle dispersed in an Al matrix with Al cladding was dissolved with a mixture of 4 M HCl and 10 M $HNO_3$ and 8 or 15 fission product elements were added to the dissolved solution. The trace amount of silica in the solutions was removed by evaporating to dryness with HF and the U was adsorbed on the first anion exchange resin. Neodymium can be purely isolated from the fission product elements with a methanol-nitric acid eluent using the second anion exchange resin. A large excess of Al didn't influence on the elution velocity of Nd, but reduced the eluted contents of Nd, Al, Eu, Gd, Sm and Sr, A large amount of Al was removed first from the column with 3 mL of loading solution (0.8 M $HNO_3$/99.8% MeOH) before Nd elution by the eluent [0.04 M $HNO_3$-99.8% MeOH(1:9)]. The recovery of Nd was more than 94%, regardless of Al contents. Taking the 9 to 13 mL fraction of eluate was effective to purely isolate Nd.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.1
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• pp.24-34
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• 2020

This research is a study on the characteristics of OPC-slag cement using nano-silica solution (NSS) with water-weight substitution method. The new replacement method is a fundamental step to study the behavior of cement with higher NSS replacement rates than previous studies. NSS was replaced by 10%, 20%, 30%, 40%, and 50% of the mixing water weight. As a result, the mechanical and microstructural characteristics were improved. This can be summarized in two ways. First, when the NSS is replaced with mixing water, the homogeneous dispersion action of the nano-silica particles is improved. This promotes initial hydration. Second, substitution of NSS with higher density than mixing water reduces w / b. This forms a dense hydration reaction material. The new substitution method did not show any degradation of mechanical and microstructural properties as compared with the results using the powdered nano-silica particles revealed in the previous study. Therefore, it is considered that the method of weight substitution of NSS used in this study can be applied to the formulation of OPC-slag cement.