• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.115-120
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• 2003

In this work, a continuous-flow micro-PCR system is systematically designed. From the numerical simulation based on the finite volume method, adapting oneself to a new environmental temperature without an external temperature controller is shown to be possible and a cooler as well as a heater is shown to be necessary to obtain three individual temperature zones for polymerase chain reaction. In addition, appropriate geometry of a heat sink for the cooler is determined by using a compact modeling method, the porous medium approach.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.149-150
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• 2005

• Journal of Mechanical Science and Technology
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• v.17 no.9
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• pp.1268-1275
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• 2003

In this paper, a compact 3-DOF mobile microrobot with sub-micron resolution is presented. It has many outstanding features : it is as small as a coin ; its precision is of sub-micrometer resolution on the plane ; it has an unlimited travel range ; and it has simple and compact mechanisms and structures which can be realized at low cost. With the impact actuating mechanism, this system enable both fast coarse motion and highly precise fine motion with a pulse wave input voltage controlled. The 1 -DOF impact actuating mechanism is modeled by taking into consideration the friction between the piezoelectric actuator and base. This modeling technique is extended to simulate the motion of the 3-DOF mobile robot. In addition, experiments are conducted to verify that the simulations accurately represent the real system. The modeling and simulation results will be used to design the model-based controller for the target system. The developed system can be used as a robotic positioning device in the micromanipulation system that determines the position of micro-sized components or particles in a small space, or assemble them in the meso-scale structure.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.1
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• pp.33-41
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• 2015

Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

• International Journal of Contents
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• v.5 no.4
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• pp.88-93
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• 2009

It is important for communication networks to possess the capability to overcome failures and provide survivable services. We address modeling and analysis of performability affected by both performance and availability of system components for a token ring network under failure and repair conditions. Stochastic reward nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, hierarchical SRN modeling techniques are used to overcome state largeness problem. The upper level model is used to compute availability and the lower level model captures the performance. And Normalized Throughput Loss (NTL) is obtained for the composite ring network for each node failures occurrence as a performability measure. One of the key contributions of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performability analysis for a token ring network under SRN reward concepts.

• Advances in Energy Research
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• v.1 no.1
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• pp.53-78
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• 2013

Methane carbon dioxide reforming (MCDR) is a promising way of utilizing greenhouse gas for hydrogen-rich fuel production. Compared with other types of reactors, Compact Reformers (CRs) are efficient for fuel processing. In a CR, a thin solid plate is placed between two porous catalyst layers to enable efficient heat transfer between the two catalyst layers. In this study, the physical and chemical processes of MCDR in a CR are studied numerically with a 2D numerical model. The model considers the multi-component gas transport and heat transfer in the fuel channel and the porous catalyst layer, and the MCDR reaction kinetics in the catalyst layer. The finite volume method (FVM) is used for discretizing the governing equations. The SIMPLEC algorithm is used to couple the pressure and the velocity. Parametrical simulations are conducted to analyze in detail the effects of various operating/structural parameters on the fuel processing behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• Korean Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.1-19
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• 1996

Non-manifold topological representations can provide a single unified representation for mixed dimensional models or cellular models and thus have a great potential to be applied in many application areas. Various boundary representations for non-manifold topology have been proposed in recent years. These representations are mainly interested in describing the sufficient adjacency relationships and too redundant as a result. A model stored in these representations occupies too much storage space and is hard to be manipulated. In this paper, we proposed a compact hierarchical non-manifold boundary representation that is extended from the half-edge data structure for solid models by introducing the partial topological entities to represent some non-manifold conditions around a vertex, edge or face. This representation allows to reduce the redundancy of the existing schemes while full topological adjacencies are still derived without the loss of efficiency. To verify the statement above, the storage size requirement of the representation is compared with other existing representations and present some main procedures for querying and traversing the representation. We have also implemented a set of the generalized Euler operators that satisfy the Euler-Poincare formula for non-manifold geometric models.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.109-124
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• 2016

In this paper, process of dynamic powder compaction is investigated experimentally using impact of drop hammer and die tube. A series of test is performed using aluminum powder with different grain size. The energy of compaction of powder is determined by measuring height of hammer and the results presented in term of compact density and rupture stress. This paper also presents a mathematical modeling using experimental data and neural network. The purpose of this modeling is to display how the variations of the significant parameters changes with the compact density and rupture stress. The closed-form obtained model shows very good agreement with experimental results and it provides a way of studying and understanding the mechanics of dynamic powder compaction process. In the considered energy level (from 733 to 3580 J), the relative density is varied from 63.89% to 87.41%, 63.93% to 91.52%, 64.15% to 95.11% for powder A, B and C respectively. Also, the maximum rupture stress are obtained for different types of powder and the results shown that the rupture stress increases with increasing energy level and grain size.

• Journal of IKEEE
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• v.25 no.4
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• pp.778-781
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• 2021

In this paper, we propose the 16-layer 3D NAND Flash memory compact modeling using SPICE. In the same structure and simulation conditions, the channel potential about Down Coupling Phenomenon(DCP) and Natural Local Self Boosting (NLSB) were simulated and analyzed with Technology Computer Aided Design(TCAD) tool Atlas(Silvaco^TM) and SPICE, respectively. As a result, it was confirmed that the channel potential of TCAD and SPICE for the two phenomena were almost same. The SPICE can be checked the device structure intuitively by using netlist. Also, its simulation time is shorter than TCAD. Therefore, using SPICE can be expected to efficient research on 3D NAND Flash memory.