• Smart Structures and Systems
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• v.17 no.2
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• pp.347-361
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• 2016

A two-stage method for damage detection in truss systems is proposed. In the first stage, a modal residual vector based indicator (MRVBI) is introduced to locate the potentially damaged elements and reduce the damage variables of a truss structure. Then, in the second stage, a differential evolution (DE) based optimization method is implemented to find the actual site and extent of damage in the structure. In order to assess the efficiency of the proposed damage detection method, two numerical examples including a 2D-truss and 3D-truss are considered. Simulation results reveal the high performance of the method for accurately identifying the damage location and severity of trusses with considering the measurement noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.212-213
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• 2012

• Journal of Korean Association for Spatial Structures
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• v.5 no.3 s.17
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• pp.117-122
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• 2005

This paper investigated the optimum design of truss structures based on Genetic Algorithms (GA's). With GA's characteristic of running side by side, the overall optimization and feasible operation, the optimum design model of truss structures was established. Elite models were used to assure that the best units of the previous generation had access to the evolution of current generation. Using of non-uniformity mutation brought the obvious mutation at earlier stage and stable mutation in the later stage; this benefited the convergence of units to the best result. In addition, to avoid GA's drawback of converging to local optimization easily, by the limit value of each variable was changed respectively and the genetic operation was performed two times, so the program could work more efficiently and obtained more precise results. Finally, by simulating evolution process of nature biology of a kind self-organize, self-organize, artificial intelligence, this paper established continuous structural optimization model for ten bars cantilever truss, and obtained satisfactory result of optimum design. This paper further explained that structural optimization is practicable with GA's, and provided the theoretic basis for the GA's optimum design of structural engineering.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.2
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• pp.163-174
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• 2011

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3106-3111
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• 2010

In this study, a comparative study was performed between one- and two-stage refrigeration system to cool the natural gas temperature down to $-40^{\circ}C$ using propane as a chilling medium. As a thermodynamic model, Peng-Robinson equation of state equation was applied and PRO/II with PROVISION release 8.3 at Invensys company was utilized for the simulation of the refrigeration system. Through this study, optimization work showed that two-stage refrigeration system was proven to save about 33.5% refrigeration power consumption compared to the one-stage refrigeration cycle.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.1097-1103
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• 2010

Injection pressure, an important factor in the filling procedure, should be minimized to enhance injection molding quality. In addition, warping deformation and weld lines, which are representative failures, should be avoided to enhance injection molding quality. To improve injection molding quality, the design procedure for an automotive fog blank cover is divided into two stages. In the first stage, we optimally obtain injection molding process variables that minimize injection pressure and warping deformation by using design of experiments, approximation and optimization techniques equipped in PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration and Design Optimization) tool. Then, we determine the thickness of the automotive fog blank cover that enables us to avoid generating weld lines. The design results we obtain in this study are found far better than those of the initial design, which demonstrates the effectiveness of our design method.

• Korean Journal of Food Science and Technology
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• v.21 no.5
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• pp.655-661
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• 1989

Optimal drying conditions consisting of air temperature and relative humidity were searched by the simulation-optimization technique for minimizing quality changes in red pepper drying. Optimized drying conditions were analysed in the viewpoint of quality change kinetics and effects of control variables on the state variables. Optimal drying conditions were nearly same in both cases for carotenoid maximization and browning minimization. In two staged optimized drying, relative humidity took a lower search limit of about 10%, and air temperature in the first stage was near the lower limit of $50^{\circ}C$ and in second stage increased to a higher temperature varying with total drying time and stage changing time. Response surface analysis of time invariable drying confirmed the location of the optimal point lying on the vertex of lower limit humidity and a lowest drying temperature which ensures to attain target moisture of 0.2g water/g dry solid. Two stage drying can attain the higher objective function of quality by 3-5% than time invariable drying for shorter total drying times.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.164-175
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• 1999

If the camera plane is nearly parallel to the calibration board on which objects are defined, most of existing calibration approaches such as Tsai's radial-alignment-constraint method cannot be applied. Recently, for such an ill-conditioned case, Zhuang & Wu suggested the linear two-stage calibration algorithm assuming that the exact values of focal length and scale factor are known a priori. In this paper, we developed an iterative two-stage algorithm starts with initial guess fo the two parameters to determine the value of the others using Zhuang & Wu's method. In the second stage, the two parameters are locally optimized. This process is repeated until any improvement cannot be expected any more. The performance comparison between Zhuang & Wu's method and our algorithm shows the superiority of ours. Also included are the computational results for the effects of the distribution and the number of calibration points on the calibration performance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1118-1127
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• 2008

The position and size of holes in the partition of a double cavity are known to strongly affect the eigenfrequency of the longitudinal eigenmodes of the double cavity. To maximize or minimize the eigenfrequency of the hole-partitioned double cavity, two acoustical topology optimization problems are formulated and solved. While two sub-cavities are filled with air, a partition between them is assumed to consist of sub-partitions of variable acoustical properties. One design variable is assigned to each sub-partition, whose material properties are interpolated as those of an intermediate material between air and a rigid body. The penalty parameter of the used interpolation function is adjusted to obtain a distinct air and rigid body distribution at the converged stage in each acoustical topology optimization problem. A special attention is paid to the selection of initial values of design variables to obtain solutions as close to global optimum and symmetric as possible. To show numerical characteristics of these optimization problems, the formulated problems are first solved for the one-dimensional partition design domain and then for the two-dimensional partition design domain.