• 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.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.773-777
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• 2006

Growth of Bacillus cereus was assessed during the storage of seasoned soybean sprouts at 0,5, 10, and $15^{\circ}C$. No lag time in its growth curve was observed and thus the specific growth rate of B. cereus in the exponential growth phase was estimated for bootstrapped microbial count data. The distribution of the specific growth rate could be explained by the BetaGeneral distribution function, and temperature dependence was described by the Ratkowsky square root model. The temperature dependence of the growth could be successfully incorporated into the differential equation of microbial growth to predict the B. cereus count on the seasoned soybean sprouts under fluctuating temperature conditions. Safe shelf lives with different probabilities to reach $10^5\;CFU/g$ were presented at four different temperatures, considering the variation in initial contamination and specific growth rate by the Monte Carlo method and 2-step bootstrapping, respectively. Safe shelf lives defined as the time with a probability of less than 0.1% of reaching the critical limit, were 13.4, 5.2, 3.6, and 2.8 days at 0, 5, 10, and $15^{\circ}C$, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.987-992
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• 2002

In an attempt to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Pareto-optimal points, instead of a single point. In this paper, pareto-based Continuous Evolutionary Algorithms for Multiobjective Optimization problems having continuous search space are introduced. This algorithm is based on Continuous Evolutionary Algorithms to solve single objective optimization problems with a continuous function and continuous search space efficiently. For multiobjective optimization, a progressive reproduction operator and a niche-formation method fur fitness sharing and a storing process for elitism are implemented in the algorithm. The operator and the niche formulation allow the solution set to be distributed widely over the Pareto-optimal tradeoff surface. Finally, the validity of this method has been demonstrated through a numerical example.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.301-316
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• 2002

An important goal of computational wind engineering is to impact the design process with simulations of flow around buildings and bridges. One challenging aspect of this goal is to solve the Navier-Stokes (NS) equations accurately. For the unsteady computations, an adaptive finite element technique may reduce the computer time and storage. The preliminary application of a p-version as well as an h-version adaptive technique to computational wind engineering has been reported in previous paper. The details on the implementation of p-adaptive technique will be discussed in this paper. In this technique, two posteriori error estimations, which are based on the velocity and vorticity, are first presented. Then, the polynomial order of the interpolation function is increased continuously element by element until the estimated error is less than the accepted. The second through sixth orders of hierarchical functions are used as the interpolation polynomials. Unequal order interpolations are used for velocity and pressure. Using the flow around a circular cylinder with Reynolds number of 1000 the two error estimators are compared. The result show that the estimated error based on the velocity is lower than that based on the vorticity.

• Progress in Superconductivity and Cryogenics
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• v.7 no.4
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• pp.24-27
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• 2005

Development of a 600 kJ class Superconducting Magnetic Energy Storage (SMES) system is being in progress by Korea Electrotechnology Research Institute(KERI). High temperature superconducting (HTS) wires are going to be used for the windings for the SMES system is presented in this paper. We considered BSCCO-2223 wire for the HTS windings and the operating temperature of the winding was decided to be 20 K which will be accomplished by conduction cooling method using cyro-coolers. Auto-Tuning Niching Genetic Algorithm was adopted for an optimization method of the HTS magnets in the SMES system. The objective function of the optimal process was minimizing total amount of the HTS wire. As a result, we obtained output parameters for optimization design of 600 kJ class SMES under several constrained conditions. These HTS windings are going to be applied to the SMES system whose purpose is stabilization of the power grid.

• 정보저장시스템학회:학술대회논문집
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• 2005.10a
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• pp.32-37
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• 2005

We developed a numerical simulator in order to study the Super-RENS/ROM (Super REsolution Near-Field Structure, Read Only Memory) using 3-dimensional FDTD (finite difference time domain) method. The simulation can be performed by three steps. In the first step, we utilized the vector-diffraction theory to calculate the characteristics of incident laser beam from the object-lens to the surface of the disk. At the second step, we fed the calculated result as an input for the main FDTD simulations on the optical layers in the disk structure. After performed the FDTD simulations, we took near-to-far field transformation for the reflected signal, from the surface of the disk to the detector. Finally, we can get reflected signal at the photo-diode. Using this developed simulator, we were able to study about the reading signal from various disk structures as a function of a laser beam position. We calculated reading signals for various pit sizes for Super-ROM structure, and it is found that the simple optical diffraction theory can not explain the reading mechanism of Super-ROM, and more complicated temperature dependent physics must be involved.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• Geomechanics and Engineering
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• v.33 no.2
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• pp.133-140
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• 2023

Soil erosion can cause scouring and failures of underwater structures, therefore, various soil improvement techniques are used to increase the soil erosion resistance. The microbially induced calcium carbonate precipitation (MICP) method is proposed to increase the erosion resistance, however, there are only limited experimental and numerical studies on the use of MICP treatment for improvement of surface erosion resistance. Therefore, this study investigates the improvement in surface erosion resistance of sands by MICP through laboratory experiments and numerical modeling. The surface erosion behaviors of coarse sands with various calcium carbonate contents were first investigated via the erosion function apparatus (EFA). The test results showed that MICP treatment increased the overall erosion resistance, and the contribution of the precipitated calcium carbonate to the erosion resistance and critical shear stress was quantified in relation to the calcium carbonate contents. Further, these surface erosion processes occurring in the EFA test were simulated through the coupled computational fluid dynamics (CFD) and discrete element method (DEM) with the cohesion bonding model to reflect the mineral precipitation effect. The simulation results were compared with the experimental results, and the developed CFD-DEM model with the cohesion bonding model well predicted the critical shear stress of MICP-treated sand. This work demonstrates that the MICP treatment is effective in improving soil erosion resistance, and the coupled CFD-DEM with a bonding model is a useful and promising tool to analyze the soil erosion behavior for MICP-treated sand at a particle scale.

• Journal of the Korean Society of Costume
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• v.63 no.7
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• pp.1-16
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• 2013

The objective of this study is to analyze the characteristic of a functional design for a commercial outdoor brand jacket based on 3 types of functions : windproof, waterproof, and cold proof. To analyze the design and fabric characteristics of outdoor jackets by function, 903 men's and women's outdoor jacket images were selected from the catalogues during S/S 2009 - F/W 2011 of the 6 brands: The North Face, Columbia Sports Wear, Kolon Sports, K2, Arcteryx and Mont-Bell. These brands were selected based on their high market share and brand awareness of the outdoor brands in Korea. In this study, design elements analysis was conducted as following 8 elements: hood/collar height/central front flap/waistline/pocket location/ventilation for the body part/sleeve patterns/cuff for the sleeve part. Fabrics were analyzed by the frequency of fabric types used in the 3 jacket types. According to the result derived from the analysis of the six brands of outdoor wear jacket design trends by year, detachable hood and a co-use of velcro and elastic bands have been mainly designed for all of windproof, waterproof, and cold proof jacket to all in order to respond quickly to changes in the external environment. For reinforced storage function on trekking, the number of pockets has been gradually growing, and a function was being developed to connect an electronic device to a pocket. The method, result, and collateral observations relevant to each of these phases are described. Outdoor jacket design characteristics were investigated for outdoor brands, which can provide data to suggest more accurate functional design, and satisfy functional design needs. In this regard, this research was significant in the sense that it suggested preliminary data to reconsider competitiveness of the brand products.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.981-984
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• 2005

This study is to realize its threshold voltage shift after programming operation in charge trap type SONOS memory by simulation. SONOS devices are charge trap type nonvolatile memory devices in which charge storage takes place in traps in the nitride-blocking oxide interface and the nitride layer. For simulation of their threshold voltage as a function of the memory states, traps in the nitride layer have to be defined. However, trap models in the nitride layer are not developed in commercial simulator. So, we propose a new method that can simulate their threshold voltage shift by an amount of charges induced to the electrodes as a function of a programming voltages and times as define two electrodes in the tunnel oxide-nitride interface and the nitride-blocking oxide interface of SONOS structures.