• 제목/요약/키워드: Modeling Approach

검색결과 3,532건 처리시간 0.048초

Modeling of an On-Chip Power/Ground Meshed Plane Using Frequency Dependent Parameters

  • Hwang, Chul-Soon;Kim, Ki-Yeong;Pak, Jun-So;Kim, Joung-Ho
    • Journal of electromagnetic engineering and science
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    • 제11권3호
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    • pp.192-200
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    • 2011
  • This paper proposes a new modeling method for estimating the impedance of an on-chip power/ground meshed plane. Frequency dependent R, L, and C parameters are extracted based on the proposed method so that the model can be applied from DC to high frequencies. The meshed plane model is composed of two parts: coplanar multi strip (CMS) and conductor-backed CMS. The conformal mapping technique and the scaled conductivity concept are used for accurate modeling of the CMS. The developed microstrip approach is applied to model the conductor-backed CMS. The proposed modeling method has been successfully verified by comparing the impedance of RLC circuit based on extracted parameters and the simulated impedance using a 3D-field solver.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권4호
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    • pp.254-259
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    • 2008
  • Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Quantitative Analysis for Plasma Etch Modeling Using Optical Emission Spectroscopy: Prediction of Plasma Etch Responses

  • Jeong, Young-Seon;Hwang, Sangheum;Ko, Young-Don
    • Industrial Engineering and Management Systems
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    • 제14권4호
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    • pp.392-400
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    • 2015
  • Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

시간지체 순환신경망모형을 이용한 수문학적 모형화기법 (Hydrologic Modeling Approach using Time-Lag Recurrent Neural Networks Model)

  • 김성원
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2010년도 학술발표회
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    • pp.1439-1442
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    • 2010
  • Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

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Sintering Multi-scale Virtual Reality

  • Olevsky, Eugene A.
    • 한국분말야금학회:학술대회논문집
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    • 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part 1
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    • pp.264-265
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    • 2006
  • The directions of further developments in the modeling of sintering are pointed out, including multi-scale modeling of sintering, on-line sintering damage criteria, particle agglomeration, sintering with phase transformations. A true multi-scale approach is applied for the development of a new meso-macro methodology for modeling of sintering. The developed macroscopic level computational framework envelopes the mesoscopic simulators. No closed forms of constitutive relationships are assumed for the parameters of the material. The model framework is able to predict the final dimensions of the sintered specimen on a global scale and identify the granular structure in any localized area for prediction of the material properties.

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New insights in piezoelectric free-vibrations using simplified modeling and analyses

  • Benjeddou, Ayech
    • Smart Structures and Systems
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    • 제5권6호
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    • pp.591-612
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    • 2009
  • New insights are presented in simplified modeling and analysis of free vibrations of piezoelectric - based smart structures and systems. These consist, first, in extending the wide used piezoelectric-thermal analogy (TA) simplified modeling approach in currently static actuation to piezoelectric free-vibrations under short-circuit (SC) and approximate open-circuit (OC) electric conditions; second, the popular piezoelectric strain induced - potential (IP) simplified modeling concept is revisited. It is shown that the IP resulting frequencies are insensitive to the electric SC/OC conditions; in particular, SC frequencies are found to be the same as those resulting from the newly proposed OC TA. Two-dimensional plane strain (PStrain) and plane stress (PStress) free-vibrations problems are then analyzed for above used SC and approximate OC electric conditions. It is shown theoretically and validated numerically that, for both SC and OC electric conditions, PStress frequencies are lower than PStrain ones, and that 3D frequencies are bounded from below by the former and from above by the latter. The same holds for the modal electro-mechanical coupling coefficient that is retained as a comparator of presented models and analyses.

해석모델을 이용한 태양광모듈의 성능결과 비교분석 (Comparison Results of Photovoltaic Module Performance using Simulation Model)

  • 소정훈;유병규;황혜미;유권종
    • 한국태양에너지학회 논문집
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    • 제28권4호
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    • pp.56-61
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    • 2008
  • The modeling of PV (Photovoltaic) module is useful to perform detailed analysis of PV system performance for changing meteorological conditions, verify actual rated power of PV system sizing and determine the optimal design of PV system and components. This paper indicates a modeling approach of PV module performance in terms of meteorological conditions and identifies validity of this modeling method by comparing measured with simulated value of various PV modules using simulation model.

Hierarchical multiscale modeling for predicting the physicochemical characteristics of construction materials: A review

  • Jin-Ho Bae;Taegeon Kil;Giljae Cho;Jeong Gook Jang;Beomjoo Yang
    • Computers and Concrete
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    • 제33권3호
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    • pp.325-340
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    • 2024
  • The growing demands for sustainable and high-performance construction materials necessitate a deep understanding of their physicochemical properties by that of these heterogeneities. This paper presents a comprehensive review of the state-of-the-art hierarchical multiscale modeling approach aimed at predicting the intricate physicochemical characteristics of construction materials. Emphasizing the heterogeneity inherent in these materials, the review briefly introduces single-scale analyses, including the ab initio method, molecular dynamics, and micromechanics, through a scale-bridging technique. Herein, the limitations of these models are also overviewed by that of effectively scale-bridging methods of length or time scales. The hierarchical multiscale model demonstrates these physicochemical properties considering chemical reactions, material defects from nano to macro scale, microscopic properties, and their influence on macroscopic events. Thereby, hierarchical multiscale modeling can facilitate the efficient design and development of next-generation construction.