• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.129-143
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• 2012

This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

• Journal of Power Electronics
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• v.17 no.2
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• pp.442-452
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• 2017

This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.923-931
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• 1999

In this paper, a modeling and a robust time-delay control for the reclaimer are investigated. Supplying the same amount of a raw material throughout the reclamation process from the raw yard to a sinter plant is important to keep the quality of the molten steel uniform in blast furnaces. As the actual parameter values of the reclaimer are not available, the boom rotational dynamics are modeled as a second order differential equation with unknown coefficients. The unknown parameters in the nominal model are estimated using a recursive estimation method. Another important factor in the control design of the reclaimer is the large time-delay in output measurement. Assuming a multiplicative uncertainty, that accounts for both the unstructured uncertainty neglected in the modeling and the structured uncertainty contained in the parameter estimation, a robust Smith predictor is designed. A robust stability criterion for the multiplicative uncertainty is also derived. Following the work of Goodwin et al. [4], a quantifying procedure of the multiplicative uncertainty bound, through experiments , is described. Experimental and simulation results are provided.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.220-221
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• 2005

Sub-bottom profiler(SBP) has been used extensively for the mapping of basement in the foundation design of offshore structure, for pre- and post-dredging operations within harbors and channels, for selection of pipeline routes, sitting of drilling platforms, and in the exploration for an aggregates such as sands and gravels. During the construction of Siwha embankment for irrigation water and the expansion of arable land, the breaking of an embankment unfortunately occurred so that a lot of riprap was swept away and widely dispersed by the tide and strong current. The feasibility study for the construction of the tidal-powered electric plant in Siwha embankment was performed quite recently. Therefore we made use of SBP survey to investigate the distribution of the lost riprap. We could successfully map out the distribution of the lost riprap from the reflection amplitude characteristics of the sediments in SBP data set. We demonstrated the variation of reflection amplitude versus the sediments with and/or without riprap by means of the numerical modeling of acoustic wave equation using finite difference method. Also we examined an amplitude anomaly of the ripraped area through the physical modeling using ultrasonic.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.295-305
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• 2017

This paper reviews current status of the unified approach known as integrated safety assessment (ISA), as well as the associated SCAIS (simulation codes system for ISA) computer platform. These constitute a proposal, which is the result of collaborative action among the Nuclear Safety Council (CSN), University of Madrid (UPM), and NFQ Solutions S.L, aiming to allow independent regulatory verification of industry quantitative risk assessments. The content elaborates on discussions of the classical treatment of time in conventional probabilistic safety assessment (PSA) sequences and states important conclusions that can be used to avoid systematic and unacceptable underestimation of the failure exceedance frequencies. The unified ISA method meets this challenge by coupling deterministic and probabilistic mutual influences. The feasibility of the approach is illustrated with some examples of its application to a real size plant.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06b
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• pp.365-372
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• 2006

In this paper, the possibility of statistical modeling from the pulp and peroxide bleaching condition variables to predict optical properties of a bleached chemimechanical pulp used in a newsprint paper machine at Mazandaran Wood and Paper Industries Company (MWPI) was studied. Due to the variations in the opacity and the brightness of the bleached pulp at MWPI and to tackle this problem, it was decided to study the possibility of modeling the bleaching process. To achieve this purpose, Multi-variate Regression Analysis was used for model building and it was found that there is a relationship between independent variables and pulp brightness as well as pulp opacity, consequently, two models were constructed. Then, model validation was carried out using new data set in the bleaching plant at MWPI to test model predictive ability and its performance.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1192-1205
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• 2016

Field programmable gate array (FPGA)-based systems are thought to be a practical option to replace certain obsolete instrumentation and control systems in nuclear power plants. An FPGA is a type of integrated circuit, which is programmed after being manufactured. FPGAs have some advantages over other electronic technologies, such as analog circuits, microprocessors, and Programmable Logic Controllers (PLCs), for nuclear instrumentation and control, and safety system applications. However, safety-related issues for FPGA-based systems remain to be verified. Owing to this, modeling FPGA-based systems for safety assessment has now become an important point of research. One potential methodology is the dynamic flowgraph methodology (DFM). It has been used for modeling software/hardware interactions in modern control systems. In this paper, FPGA logic was analyzed using DFM. Four aspects of FPGAs are investigated: the "IEEE 1164 standard," registers (D flip-flops), configurable logic blocks, and an FPGA-based signal compensator. The ModelSim simulations confirmed that DFM was able to accurately model those four FPGA properties, proving that DFM has the potential to be used in the modeling of FPGA-based systems. Furthermore, advantages of DFM over traditional reliability analysis methods and FPGA simulators are presented, along with a discussion of potential issues with using DFM for FPGA-based system modeling.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.265-272
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• 2005

Severe accidents in nuclear power plants can cause hydrogen-generating chemical reactions, which create the danger of hydrogen combustion and thus threaten containment integrity. For containment analyses, a three-dimensional mechanistic code, GOTHIC-3D has been applied near source compartments to predict whether or not highly reactive gas mixtures can form during an accident with the hydrogen mitigation system working. To assess the code applicability to hydrogen combustion analysis, this paper presents the numerical calculation results of GOTHIC-3D for various hydrogen combustion experiments, including FLAME, LSVCTF, and SNU-2D. In this study, a technical base for the modeling oflarge- and small-scale facilities was introduced through sensitivity studies on cell size and bum modeling parameters. Use of a turbulent bum option of the eddy dissipation concept enabled scale-free applications. Lowering the bum parameter values for the flame thickness and the bum temperature limit resulted in a larger flame velocity. When applied to hydrogen combustion analysis, this study revealed that the GOTHIC-3D code is generally able to predict the combustion phenomena with its default bum modeling parameters for large-scale facilities. However, the code needs further modifications of its bum modeling parameters to be applied to either small-scale facilities or extremely fast transients.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.386-403
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• 2016

The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant.