• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.64-71
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• 2017

A damage estimation method is presented for jacket-type support structure of offshore wind turbine using a change of modal properties due to damage and committee of neural networks for effective structural health monitoring. For more practical monitoring, it is necessary to monitor the critical and prospective damaged members with a limited number of measurement locations. That is, many data channels and sensors are needed to identify all the members appropriately because the jacket-type support structure has many members. This is inappropriate considering economical and practical health monitoring. Therefore, intensive damage estimation for the critical members using a limited number of the measurement locations is carried out in this study. An analytical model for a jacket-type support structure which can be applied for a 5 MW offshore wind turbine is established, and a training pattern is generated using the numerical simulations. Twenty damage cases are estimated using the proposed method. The identified damage locations and severities agree reasonably well with the exact values and the accuracy of the estimation can be improved by applying the committee of neural networks. A verification experiment is carried out, and the damage arising in 3 damage cases is reasonably identified.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.704-715
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• 2004

Recently, a single or multi processor system uses the hierarchical memory structure to reduce the time gap between processor clock rate and memory access time. A cache memory system includes especially two or three levels of caches to reduce this time gap. Moreover, one of the most important things In the hierarchical memory system is the hit rate in level 1 cache, because level 1 cache interfaces directly with the processor. Therefore, the high hit rate in level 1 cache is critical for system performance. A victim cache, another high level cache, is also important to assist level 1 cache by reducing the conflict miss in high level cache. In this paper, we propose the advanced high level cache management scheme based on the processor reuse information. This technique is a kind of cache replacement policy which uses the frequency of processor's memory accesses and makes the higher frequency address of the cache location reside longer in cache than the lower one. With this scheme, we simulate our policy using Augmint, the event-driven simulator, and analyze the simulation results. The simulation results show that the modified processor reuse information scheme(LIVMR) outperforms the level 1 with the simple victim cache(LIV), 6.7% in maximum and 0.5% in average, and performance benefits become larger as the number of processors increases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3071-3080
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• 2015

The increased demand on the transport of both passengers and goods through rail systems implies higher traffic intensity and congestion on the railways, resulting in greater likelihood of accidents and also degraded passenger services. To cope with the issues, development of an integrated communication network for rails has attracted great deal of attention lately. GSM-R is such an example developed in Europe, which seems to have restrictions in providing various communication services due to network speed limit. For the reason, an LTE-based approach is under study in Korea. After the network development, operation management of the network is necessary. Design of operation management systems has been studied little and thus is the objective of this paper. To do so, a conceptual design has been carried out based on model-based approach. Specifically, a context model has first been created using the use case diagram. Then, SysML models of operational scenarios were developed for the management system. The SysML models have alternatively been expressed as EFFBD models to simulate and verify them. Consequently, the result of the conceptual system design for the operation management of the integrated wireless network is expected to be used as a basis for the detailed design later.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.274-279
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• 2009

The flow of a universal system-level design methodology consists of system specification, system-level hardware/software partitioning, co-design, co-verification using virtual or physical prototype, and system integration. In this paper, verification environments based-on SystemVerilog and SystemC, one is native-code co-verification environment which makes prompt functional verification possible and another is SystemVerilog layered testbench which makes clock-level verification possible, are implemented. In native-code co-verification, HW and SW parts of SoC are respectively designed with SystemVerilog and SystemC after HW/SW partitioning using SystemC, then the functional interaction between HW and SW parts is carried out as one simulation process. SystemVerilog layered testbench is a verification environment including corner case test of DUT through the randomly generated test-vector. We adopt SystemC to design a component of verification environment which has multiple inheritance, and we combine SystemC design unit with the SystemVerilog layered testbench using SystemVerilog DPI and ModelSim macro. As multiple inheritance is useful for creating class types that combine the properties of two or more class types, the design of verification environment adopting SystemC in this paper can increase the code reusability.

• Journal of the Korean Institute of Gas
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• v.20 no.1
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• pp.13-22
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• 2016

This paper presents development of an appropriate procedure and flow chart to analyze shale gas production data obtained from a multi-fractured horizontal well according to flow characteristics in order to calculate an estimated ultimate recovery. Also, the technical considerations were proposed when a rate transient analysis was performed with field production data occurred to only $1^{st}$ transient flow. If production data show the $1^{st}$ transient flow from log-log and square root time plot analysis, production forecasting must be performed by applying different method as before and after of the end of $1^{st}$ linear flow. It is estimated by an area of stimulated reservoir volume which can be calculated from analysis results of micro-seismic data. If there are no bottomhole pressure data or micro-seismic data, an empirical decline curve method can be used to forecast production performance. If production period is relatively short, an accuracy of production data analysis could be improved by analyzing except the early production data, if it is necessary, after evaluating appropriation with near well data. Also, because over- or under-estimation for stimulated reservoir volume could take place according to analysis method or analyzer's own mind, it is necessary to recalculate it with fracture modeling, reservoir simulation and rate transient analysis, if it is necessary, after adequacy evaluation for fracture stage, injection volume of fracture fluid and productivity of producers.

• Tunnel and Underground Space
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• v.26 no.3
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• pp.235-252
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• 2016

This study presents a methodology to reproduce the mechanical behavior of isotropic or transversely isotropic rock using the polygonal grain-based distinct element model. A numerical technique to monitor the evolution of micro-cracks during the simulation was developed in the present study, which enabled us to examine the contribution of tensile cracking and shear cracking to the progressive process of the failure. The numerical results demonstrated good agreement with general observations from rock specimens in terms of the behavior and the evolution of micro-cracks, suggesting the capability of the model to represent the mechanical behavior of rock. We also carried out a parametric study as a fundamental work to examine the relationships between the microscopic properties of the constituents and the macroscopic behavior of the model. Depending on the micro-properties, the model exhibited a variety of responses to the external load in terms of the strength and deformation characteristics. In addition, a numerical technique to reproduce the transversely isotropic rock was suggested and applied to Asan gneiss from Korea. The behavior of the numerical model was in good agreement with the results obtained in the laboratory-scale experiments of the rock.

• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.459-464
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• 2008

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.1-30
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• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.165-178
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• 2021

We studied driftwood behaviors including generation and deposition in a tsunami using a numerical simulation. We used an integrated two-dimensional numerical model, which included a driftwood dynamics model. The study area was Sendai, Japan. Observation data collected by Inagaki et al. (2012) were used to verify the simulation results by comparing them with driftwood deposition patterns. A simplified model was developed to consider the threshold of driftwood generation by the drag force of water flows. To consider the volume of driftwood generated, we estimated the total wood number in the study area using Google Earth. Therefore, we simulated more than 13,000 pieces of driftwood that were generated and transported inland from approximately 300,000 trees that were growing in the forest. The final distribution of the driftwood was similar to the observation data. The reproducibility of the generation and deposition patterns of driftwood showed good agreement in terms of longitudinal deposition pattern. In the future, a sensitivity analysis on driftwood parameters, such as the size of the wood, boundary conditions, and grid size, will be implemented to predict the travel patterns of driftwood. Such modeling will be a useful methodology for disaster prediction based on water flow and driftwood.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.611-620
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• 2021

The maintenance industry is mainly progressing based on condition-based maintenance after corrective maintenance and preventive maintenance. In condition-based maintenance, maintenance is performed at the optimum time based on the condition of equipment. In order to find the optimal maintenance point, it is important to accurately understand the condition of the equipment, especially the remaining useful life. Thus, using simulation data (C-MAPSS), a prediction model is proposed to predict the remaining useful life of a turbofan engine. For the modeling process, a C-MAPSS dataset was preprocessed, transformed, and predicted. Data pre-processing was performed through piecewise RUL, moving average filters, and standardization. The remaining useful life was predicted using principal component analysis and the k-NN method. In order to derive the optimal performance, the number of principal components and the number of neighbor data for the k-NN method were determined through 5-fold cross validation. The validity of the prediction results was analyzed through a scoring function while considering the usefulness of prior prediction and the incompatibility of post prediction. In addition, the usefulness of the RUL prediction model was proven through comparison with the prediction performance of other neural network-based algorithms.