• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.6
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• pp.641-654
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• 2017

The KVLCC2 and its modified hull form were investigated in regular head waves using Unsteady Reynolds Averaged Navier-Stokes (URANS) methods. The modified KVLCC2 (named KWP-bow KVLCC2) is designed for reducing wave reflection from the bow. Firstly, the original KVLCC2 is studied for verification of the present code and methodology and the computed time history of total resistance and 2DOF motions (heave and pitch) for the selected two wave length conditions are directly compared with the results obtained from KRISO towing tank experiment under the identical condition. The predicted added resistance, heave and pitch motion RAOs show relatively good agreement with the experimental results. Secondly, the comparison of performance in waves between KVLCC2 and KWP-bow KVLCC2 is carried out. We confirmed that newly designed hull form shows better performances in all the range of wave length conditions through both the computation and the experiment. The present URANS method can capture the difference of performance in waves of the two hull forms without any special treatment for short wave length conditions. It can be identified that KWP-bow KVLCC2 gives about 8% of energy saving in sea state 5 condition.

• Journal of Welding and Joining
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• v.11 no.2
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.713-724
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• 2001

Hydrologists have tried to develop monthly runoff simulation models which are important factor in wafer resources planning. One of the models called Kajiyama formu]a is widely used for monthly runoff simulation in Korea. In recent work by Xiong and Guo (1999), they suggested Two-parameter monthly water balance model to simulate the runoff and showed that the model can be used for the water resources planning program and the climate impact studies. However, they estimated two parameters of transformation of time scale, c and of the field capacity, SC by the trial and error method. Therefore, the purpose of this study is to suggest the estimation methodologies of c and SC, and compare Kajiyama formula with a Two-parameter monthly water balance model to simulate the runoff in Han river and IHP representative basins in Korea. The c is estimated by using the relationship of actual and potential evaporations, and SC is estimated from association with CN. We show that the estimated c and SC can be used as the initial or optimal values in the model.

• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.3-17
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• 2013

The purpose of this study is to develop a traffic assignment model where the variable of signal intersection delay is taken into account in assigning traffic in large-scale network settings. Indeed, despite the fact that the majority of the increase in travel time or cost involving congested urban network or interrupted flow are accounted for by stop delays or congested delays at signal intersections, the existing traffic assignment models did not reflect this. The traffic assignment model considering intersection delays presented in this study was built based on the existing traffic assignment models, which were added to by the analysis technique for the computation of intersection delay provided in Korea Highway Capacity Manual. We can conclude that a multiple variety of simulation tests prove that this model can be applied to real network settings. Accordingly, this model shows the possibility of utilizing a model considering intersection delay for traffic policy decisions through analysis of effects of changes in traffic facilities on large urban areas.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.280-287
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• 2010

The first Korean satellite launch vehicle, KSLV-I(Korea Space Launch Vehicle-I), was launched for its first flight test on Aug. 25, 2009 from Naro Space Center located in south Jolla province. Because launch vehicles usually fly long range with large amount of propellants aboard, preparation of countermeasures against potential malfunctions during flight is essential in launch operation. In this paper, the flight safety operation, prepared to guarantee flight safety during launch operation of KSLV-I, is presented. Prior to flight test, flight safety analysis is performed to estimate associated risk levels quantitatively, and during flight, flight safety systems are operated to cope with any risky situations. Real-time flight monitoring including computation of instantaneous impact point using tracking data is executed normally and the flight test is completed without activation of flight termination system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.237-247
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• 2003

The Motion Estimation (ME) process is an important part of a video encoding systems since they can significantly reduce bitrate with keeping the output quality of an encoded sequence. Unfortunately this process may dominate the encoding time using straightforward full search algorithm (FS). Up to now, many fast algorithms can reduce the computation complexity by limiting the number of searching locations. This is accomplished at the expense of less accuracy of motion estimation. In this paper, we introduce a new fast motion estimation method based on the spatio-temporal correlation of adjacent blocks. A reliable predicted motion vector (RPMV) is defined. The reliability of RPMV is shown on the basis of motion vectors achieved by FS. The scalar and the direction of RPMV are used in our proposed scheme. The experimental results show that the proposed method Is about l1~14% faster than the nearest neighbor method which is a wellknown conventional fast scheme.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.2
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• pp.55-64
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• 2000

In this paper, we propose an efficient datapath placement algorithm to minimize track density. Here, we consider each datapath element as a cluster, and merge the most strongly connected two clusters to a new cluster until only one cluster remains. As nodes in the two clusters to be merged are already linearly ordered respectively, we can merge two clusters with connecting them. The proposed algorithm produces circular linear ordering by connecting starting point and end point of the final cluster, and n different linear ordering by cutting between two contiguous elements of the circular linear ordering. Among the n different linear ordering, the linear ordering to minimize track density is final solution. In this paper, we show and utilize that if two clusters are strongly connected in a graph, the inner product of the corresponding vectors mapped in d-dimensional space using spectral method is maximum. Compared with previous datapath placement algorithm GA/S $A^{［2］}$, the proposed algorithm gives similar results with much less computation time.

• Korean Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.195-210
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• 1997

In Rapid Prototyping process, the time required to build multiple prototype parts can be reduced by packing several parts optimally in a work volume. Interactive arrangement of the multiple parts is a tedious process and does not guarantee the optimal placement of all the parts. In this case, packing is a kind of 3-D nesting problem because parts are represented by STL files with 3-D information. 3-D nesting is well known to be a problem requiring an intense computation and an efficient algorithm to solve the problem is still under investigation. This paper proposes that packing 3-D parts can be simplified into a 2-D irregular polygon nesting problem by using the characteristic of rapid prototyping process that the process uses 2-dimensional slicing data of the parts and that slice of the STL parts are composed of polygons. Our algorithm uses no-fit-polygon (NFP) to place each slice without overlapping other slices in the same z-level. The allowable position of one part at a fixed orientation for given parts already packed can be determined by obtaining the union of all NFP's that are obtained from each slice of the part. Genetic algorithm is used to determine the order of parts to be placed and orientations of each part for the optimal packing. Optimal orientation of a part is determined while rotating it about the axis normal to the slice by finite angles and flipping upside down. This algorithm can be applied to any rapid prototyping process that does not need support structures.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.363-366
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• 2006

The effectiveness of two passive control techniques for alleviating the pressure oscillation generated in a supersonic cavity flow is investigated numerically. The passive devices suggested in the present research include a triangular bump and a sub-cavity installed near the upstream edge of a rectangular cavity. The supersonic cavity flow characteristics are examined by using the three-dimensional, unsteady Wavier-Stokes computation based on a finite volume scheme. Large eddy simulation (LES) is carried out to properly predict the turbulent features of cavity flow. The results show that the pressure oscillation near the downstream edge dominates overall time-dependent cavity pressure variations. Such an oscillation is attenuated more considerably using the sub-cavity compared with other methods, and a larger sub-cavity leads to better control performance.