• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.1-8
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• 2015

In transportation networks, searching speed and result accuracy are becoming more critical on searching minimum path algorithm. Current $A^*$ algorithm has a big advantage of high searching speed. However, it has disadvantage of complicated searching network and low accuracy rate of finding the minimum path algorithm. Therefore, this study developed $A^*$ algorithm's heuristic function and focused on improving it's disadvantages. Newly developed function in this study contains the area concept, not the line concept. During the progress, this study adopts the idea of a heavier node that remains lighter to the target node is better that the lighter node that becomes heavier when it is connected to the other. Lastly, newly developed algorithm has the feedback function, which allows the larger accuracy value of heuristic than before. This developed algorithm tested on real network, and proved that developed algorithm is useful.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.276-284
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• 2000

Usual practice of the transformation of a B-spline curve into a set of piecewise polynomial curves in a power form is done by either a knot refinement followed by basis conversions or applying a Taylor expansion on the B-spline curve for each knot span. Presented in this paper is a new algorithm, called a direct expansion algorithm, for the problem. The algorithm first locates the coefficients of all the linear terms that make up the basis functions in a knot span, and then the algorithm directly obtains the power form representation of basis functions by expanding the summation of products of appropriate linear terms. Then, a polynomial segment of a knot span can be easily obtained by the summation of products of the basis functions within the knot span with corresponding control points. Repeating this operation for each knot span, all of the polynomials of the B-spline curve can be transformed into a power form. The algorithm has been applied to both static and dynamic curves. It turns out that the proposed algorithm outperforms the existing algorithms for the conversion for both types of curves. Especially, the proposed algorithm shows significantly fast performance for the dynamic curves.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.289-291
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• 2005

Even though a lot of routing algorithms have been proposed, an omnipotent algorithm of routing technique, which has optimal efficiency, does not exist. Therefore, A routing algorithm in a sensor network is an application oriented; the best effective routing algorithm depends on which application it is used to. In this paper, the routing algorithm is proposed for the purpose of monitoring a movement of Assets in office. This Paper proposes a new multi-hop routing algorithm, that is, RSS(Received Signal Strength) value which was used in a localization of sensor network is applied to routing algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.275-280
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• 2009

A Genetic Algorithm (GA) is a kind of search techniques used to find exact or approximate solutions to optimization and searching problems. This paper discusses the design of a genetic algorithm-based intelligent parking system. This is a search strategy based on the model of evolution to solve the problem of parking systems. A genetic algorithm for an optimal solution is used to find a series of optimal angles of the moving vehicle at a parking space autonomously. This algorithm makes the planning simpler and the movement more effective. At last we present some simulation results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.1
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• pp.25-30
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• 2005

An accurate digital distance relaying algorithm which is immune to mutual coupling effect and reactance effect of the fault resistance and the load current for the line faults in 765kV untransposed transmission lines is proposed. The algorithm can estimate adaptively the impedance to a fault point independent of the fault resistance. To compensate the magnitude and phase of the apparent impedance, this algorithm uses the angle of an impedance deviation vector. The impedance correction algorithm for phase-to-ground fault and phase-to-phase short fault use a voltage equation at fault point to compensate the fault current at fault point. A series of tests using EMTP output data in a 765kV untransposed transmission lines have proved the accuracy and effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1405-1412
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• 2000

In this paper, we propose an efficient dynamic wavelength assignment algorithm in distributed WDM (Wavelength-Division Multiplexing) networks without wavelength conversion. The algorithm tries to assign a locally-most-used wavelength distributedly on a fixed routing path. We first formulate our algorithm by using the concept of a sample space which consists of optical fibers connected to nodes on a routing path of a lightpath to be assigned a wavelength. In particular, we analyze the blocking performance mathematically as compared with that of the most-used (MU) wavelength assignment algorithm previously proposed for WDM networks under centralized control. We also obtain numerical results by simulation on the blocking performance of other centralized/distributed wavelength assignment algorithms as well as our algorithm using the M/M/c/c dynamic traffic model. Consequently, we show that analytical results match simulation results and that our algorithm is efficient in distributed WDM networks in terms of blocking performance, control traffic overhead and computation complexity.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.392-400
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• 2008

This paper proposes a novel optimization algorithm inspired by bacteria behavior patterns for foraging. Most bacteria can trace attractant chemical molecules for foraging. This tracing capability of bacteria called chemotaxis might be optimized for foraging because it has been evolved for few millenniums. From this observation, we developed a new optimization algorithm based on the chemotaxis of bacteria in this paper. We first define behavior and decision rules based on the behavior patterns of bacteria and then devise an optimization algorithm with these behavior and decision rules. Generally bacteria have a quorum sensing mechanism that makes it possible to effectively forage, but we leave its implementation as a further work for simplicity. Thereby, we call our algorithm a simple bacteria cooperative optimization (BCO) algorithm. Our simple BCO is tested with four function optimization problems on various' parameters of the algorithm. It was found from experiments that the simple BCO can be a good framework for optimization.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.435-446
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• 2020

The use of groundwater in Korea has increased in recent years to the point where its extraction is restricted in times of drought. This work models the groundwater pumping field as a confined aquifer in a simplified simulation of groundwater flow. It proposes a genetic algorithm to maximize groundwater development using a conceptual model of a steady-state confined aquifer. Solving the groundwater flow equation numerically calculates the hydraulic head along the domain of the problem; the algorithm subsequently offers optimized pumping strategies. The algorithm proposed here is designed to improve a prior initial groundwater management model. The best solution is obtained after 200 iterations. The results compare the computing time for five simulation cases. This study shows that the proposed algorithm can facilitate better groundwater development compared with a basic genetic algorithm.