• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.10
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• pp.853-861
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• 2012

This paper considers one of the explicit guidance algorithms, which has been proposed by Jaggers, to determine the closed-loop guidance algorithm for upper stages of a 3-staged space launch vehicle. Its commanded thrust vector is closer to the optimal solution when compared with that obtained by using the well-known Powered Explicit Guidance (PEG), which has been developed through the Space Shuttle program. Its performance is evaluated here by applying for guidance of the launcher during the second and third stages. Furthermore, to generate more precise guidance commands, it is attempted not to use the approximate formulas for the derivation of the original guidance law, and it is shown that performance is improved in comparison with the original.

• Structural Engineering and Mechanics
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• v.37 no.5
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• pp.475-487
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• 2011

In a flexible multi-body dynamic system the typical topological optimization method for structures cannot be directly applied, as the stiffness varies with position. In this paper, the topological optimization of the flexible multi-body dynamic system is converted into structural optimization using the equivalent static load method. First, the actual boundary conditions of the control system and the approximate stiffness curve of the mechanism are obtained from a flexible multi-body dynamical simulation. Second, the finite element models are built using the absolute nodal coordination for different positions according to the stiffness curve. For efficiency, the static reanalysis method is utilized to solve these finite element equilibrium equations. Specifically, the finite element equilibrium equations of key points in the stiffness curve are fully solved as the initial solution, and the following equilibrium equations are solved using a reanalysis method with an error controlled epsilon algorithm. In order to identify the efficiency of the elements, a non-dimensional measurement is introduced. Finally, an improved evolutional structural optimization (ESO) method is used to solve the optimization problem. The presented method is applied to the optimal design of a die bonder. The numerical results show that the presented method is practical and efficient when optimizing the design of the mechanism.

• Culinary science and hospitality research
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• v.7 no.3
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• pp.145-161
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• 2001

In odor to develop fillet-type seasoner and mixed powder-type seasoner using smoked mackerel as primary material, processing conditions of the mackerel meat and flavoring extract from various materials were examined. The approximate composition of mackerel meat and mixed powde-type seasoner using mackerel as primary material were 10.9 and 11.7%, for moisture 79.1 and 57.2% for crude protein, 5.3 and 2.9% for crude lipid, and 4.3 and 24.6% for crude ash, respectively. It was suitable to simmer raw mackerel in 3% chitooligosaccaride solution at 8$0^{\circ}C$ for 10 min., for the enhancement of reaction their meat and chitooligosaccharide. Considering effect of type of woodsmoke on organoletic properties of mackerel after smoking, oak and mixture(oak wood ＋ citrus wood = 1 : 1) were superior to another woodsmoke, the smoking conditions favoring the most overall preference were 8$0^{\circ}C$, 25min. for smoking time, 20$0^{\circ}C$, 20min. for baking, and 10$0^{\circ}C$. 4hrs. for drying. The optimal material mixing ratio for mixed powder-type seasoner was powder of smoked mackerel 60%, dried anchovy 15%, dried sea tangle 10%. The most appropriate extraction condition of mixed powder seasoner with packing tea bag(10g/bag) was 98$^{\circ}C$ for 5min. in the boiling water.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1333-1353
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• 2012

The robustness of a network is usually measured by error tolerance and attack vulnerability. Significant research effort has been devoted to determining the network design with optimal robustness. However, little attention has been paid to the problem of how to improve the robustness of existing networks. In this paper, we investigate how to optimize attack tolerance and communication efficiency of an existing network under the limited link addition. A survival fitness metric is defined to measure both the attack tolerance and the communication efficiency of the network. We show that network topology reconfiguration optimization with limited link addition (NTRLA) problem is NP-hard. Two approximate solution methods are developed. First, we present a degree-fitness parameter to guide degree-based link addition method. Second, a preferential configuration node-protecting cycle (PCNC) method is developed to do trade-off between network robustness and efficiency. The performance of PCNC method is demonstrated by numerical experiments.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.6 s.144
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• pp.654-665
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• 2005

In this paper, we present a non-linear integer programming by genetic algorithm (GA) for available sizes of stiffener or thickness of plate in a job site. GA can rapidly search for the approximate global optimum under complicated design environment such as ship. Meanwhile it can handle the optimization problem involving discrete design variable. However, there are many parameters have to be set for GA, which greatly affect the accuracy and calculation time of optimum solution. The setting process is hard for users, and there are no rules to decide these parameters. In order to overcome these demerits, the optimization for these parameters has been also conducted using GA itself. Also it is proved that the parameters are optimal values by the trial function. Finally, we applied this method to compass deck of ship where the vibration problem is frequently occurred to verify the validity and usefulness of nonlinear integer programming.

• Earthquakes and Structures
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• v.23 no.4
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• pp.363-371
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• 2022

Traditional metal dampers have disadvantages such as a higher yield point and inadequate adjustability. The experimental results show that the low yield point steel has superior energy dissipation hysteretic capacity and can be applied to seismic structures. To overcome these deficiencies, a novel compound metal damper comprising both low yield point steel plates and common steel plates is presented. The optimization objectives, including "maximum rigidity" and "full stress state", are proposed to obtain the optimal edge shape of a compound metal damper. The numerical results show that the optimized composite metal damper has the advantages such as full hysteresis curve, uniform stress distribution, more sufficient energy consumption, and it can adjust the yield strength of the damper according to the engineering requirements. In view of the mechanical characteristics of the compound metal damper, the equivalent model of eccentric cross bracing is established, and the approximate analytical solution of the yield strength and the yield displacement is proposed. A nonlinear simulation analysis is carried out for the overall aseismic capacity of three-layer-frame structures with a compound metal damper. It is verified that a compound metal damper has better energy dissipation capacity and superior seismic performance, especially for a damper with double-objective optimized shape.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.105-111
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• 2024

This paper deals with the minimum linear arrangement(MinLA) of a lattice graph, to which an approximate algorithm of linear complexity O(n) remains as a viable solution, deriving the optimal MinLA of 31,680 for 33×33 lattice. This paper proposes a partitioning arrangement algorithm of complexity O(1) that delivers exact solution to the minimum linear arrangement. The proposed partitioning arrangement algorithm could be seen as loading boxes into a container. It firstly partitions m rows into r₁,r₂,r₃ and n columns into c₁,c₂,c₃, only to obtain 7 containers. Containers are partitioning with a rule. It finally assigns numbers to vertices in each of the partitioned boxes location-wise so as to obtain the MinLA. Given m,n≥11, the size of boxes C₂,C₄,C₆ is increased by 2 until an increase in the MinLA is detected. This process repeats itself 4 times at maximum given m,n≤100. When tested to lattice in the range of 2≤n≤100, the proposed algorithm has proved its universal applicability to lattices of both m=n and m≠n. It has also obtained optimal results for 33×33 and 100×100 lattices superior to those obtained by existing algorithms. The minimum linear arrangement algorithm proposed in this paper, with its simplicity and outstanding performance, could therefore be also applied to the field of Very Large Scale Integration circuit where m,n are infinitely large.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.42-48
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• 2006

In this study, a repetitive response surface enhancement technique (RRSET) is proposed as a new system approximation method for the efficient multidisciplinary design and optimization (MDO). In order to represent the highly nonlinear behavior of the response with second order polynomials, RRSET introduces a design space transformation using stretching functions and repetitive response surface improvement. The tentative optimal point is repetitively included to the set of experimental points to better approximate the response surface of the system especially near the optimal point, hence a response surface with significantly improved accuracy can be generated with very small experimental points and system iterations. As a system optimizer, the simulated annealing, which generates a global design solution is utilized. The proposed technique is applied to several numerical examples, and demonstrates the validity and efficiency of the method. With its improved approximation accuracy, the RRSET can contribute to resolve large and complex system design problems under MDO environment.

• Journal of Korean Institute of Industrial Engineers
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• v.6 no.2
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• pp.21-29
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• 1980

This paper deals with the capital budgeting problem of a firm where investments are risky and interrelated. The established models might be classified into two categories; One is the chance-constrained programming model and the other is the expected utility maximization model. The former has a rather limited objective function and does not consider the risk in direct manner. The latter, on the other hand, might lead to a wrong decision because it uses an approximate value of expected utility. This paper attempts to extend the applicability of the chance-constrained programming model by modifying its objective function into a more general form. The capital budgeting problem is formulated as a nonlinear 0-1 integer programming problem first, and is formulated into a linear 0-1 integer programming problem for finding a lower-bound solution of the original problem. The optimal solution of the original problem is then obtained by branch & bound algorithm.