• 제목/요약/키워드: limited model

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SEI 성장 모델을 이용한 리튬 이온 배터리의 캘린더 노화 연구 (Study of the Calendar Aging of Lithium-Ion Batteries Using SEI Growth Models)

  • 전동협;채병만;이상우
    • 공업화학
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    • 제35권1호
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    • pp.48-53
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    • 2024
  • 전기화학 기반의 SEI 성장 모델을 이용하여 리튬이온 배터리의 캘린더 노화 및 장기 수명을 예측하였다. 네 가지 유형의 장기 SEI 성장 모델(용매 확산 제한 모델, 전자 이동 제한 모델, 리튬-간극 확산 제한 모델, 반응 제한 모델)을 적용하여 수치해석이 이루어졌고, 캘린더 에이징 동안의 용량 감소와 리튬 재고 손실을 계산하였다. 수치해석 결과, 전자 이동 제한 모델과 리튬-간극 확산 제한 모델이 낮은 용량 감소를 보였으며, 용매 확산 제한 모델과 반응 제한 모델은 10년이내에 80%의 용량 감소를 보였다. 캘린더 노화 중 저온 보관 시 SEI의 성장을 저하시켜 용량 감소가 적었다. 사이클링 중 C-rate가 증가할수록 SEI 두께 증가로 수명 하락이 크게 나타났으나 그 차이는 크지 않았다.

한정된 연산유닛에서 명령어 종속성을 이용하는 수퍼스칼라 프로세서의 이론적 성능 모델 (A Theoretical Superscalar Microprocessor Performance Model with Limited Functional Units Using Instruction Dependencies)

  • 이종복
    • 전기학회논문지
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    • 제59권2호
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    • pp.423-428
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    • 2010
  • In the initial design phase of superscalar microprocessors, a performance model is necessary. A theoretic performance model is very useful since performance for various architecture parameters can be obtained by simply computing equations, without repeating simulations, Previous studies established theoretic performance models using the relation between the instruction window size and the issue width, with the penalties due to branch mispredictions and cache misses. However, the study was intended for unlimited number of functional units, which is insufficient for the real case application. This paper proposes a superscalar microprocessor theoretical performance model which also works for the limited functional units. To enhance the accuracy of our limited functional unit model, instruction dependency rates are employed. By using trace-driven data of SPEC 2000 integer programs as input, this paper shows that the theoretically computed performance of superscalar microprocessor with limited number of functional units is quite similar to the measured performance.

Optimized finite element model updating method for damage detection using limited sensor information

  • Cheng, L.;Xie, H.C.;Spencer, B.F. Jr.;Giles, R.K.
    • Smart Structures and Systems
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    • 제5권6호
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    • pp.681-697
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    • 2009
  • Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.

Estimation on Exponential Model with Limited Replacements

  • Cho, Kil-Ho;Cho, Jang-Sik;Jeong, Seong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • 제16권2호
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    • pp.457-465
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    • 2005
  • We consider the estimation of parameter in the exponential model in the case that the number of replacements of failed items is limited. And the desirable number of replacements to give the similar effect as unlimited case in terms of the mean square errors is proposed.

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adaptive neuro-fuzzy inference system;daily solar radiation;Illinois;limited weather variables;

  • Kim, Sungwon
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.483-486
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    • 2015
  • The objective of this study is to develop generalized regression neural networks (GRNN) model for estimating daily solar radiation using limited weather variables at Champaign and Springfield stations in Illinois. The best input combinations (one, two, and three inputs) can be identified using GRNN model. From the performance evaluation and scatter diagrams of GRNN model, GRNN 3 (three input) model produces the best results for both stations. Results obtained indicate that GRNN model can successfully be used for the estimation of daily global solar radiation at Champaign and Springfield stations in Illinois. These results testify the generation capability of GRNN model and its ability to produce accurate estimates in Illinois.

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Current Density Equations Representing the Transition between the Injection- and Bulk-limited Currents for Organic Semiconductors

  • Lee, Sang-Gun;Hattori, Reiji
    • Journal of Information Display
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    • 제10권4호
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    • pp.143-148
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    • 2009
  • The theoretical current density equations for organic semiconductors was derived according to the internal carrier emission equation based on the diffusion model at the Schottky barrier contact and the mobility equation based on the field dependence model, the so-called "Poole-Frenkel mobility model." The electric field becomes constant because of the absence of a space charge effect in the case of a higher injection barrier height and a lower sample thickness, but there is distribution in the electric field because of the space charge effect in the case of a lower injection barrier height and a higher sample thickness. The transition between the injection- and bulk-limited currents was presented according to the Schottky barrier height and the sample thickness change.

기상청 고해상도 국지 앙상블 예측 시스템 구축 및 성능 검증 (Development and Evaluation of the High Resolution Limited Area Ensemble Prediction System in the Korea Meteorological Administration)

  • 김세현;김현미;계준경;이승우
    • 대기
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    • 제25권1호
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    • pp.67-83
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    • 2015
  • Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

A New Ship Scheduling Set Packing Model Considering Limited Risk

  • Kim, Si-Hwa;Hwang, Hee-Su
    • 한국항해항만학회지
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    • 제30권7호
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    • pp.561-566
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    • 2006
  • In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

Speaker Verification with the Constraint of Limited Data

  • Kumari, Thyamagondlu Renukamurthy Jayanthi;Jayanna, Haradagere Siddaramaiah
    • Journal of Information Processing Systems
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    • 제14권4호
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    • pp.807-823
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    • 2018
  • Speaker verification system performance depends on the utterance of each speaker. To verify the speaker, important information has to be captured from the utterance. Nowadays under the constraints of limited data, speaker verification has become a challenging task. The testing and training data are in terms of few seconds in limited data. The feature vectors extracted from single frame size and rate (SFSR) analysis is not sufficient for training and testing speakers in speaker verification. This leads to poor speaker modeling during training and may not provide good decision during testing. The problem is to be resolved by increasing feature vectors of training and testing data to the same duration. For that we are using multiple frame size (MFS), multiple frame rate (MFR), and multiple frame size and rate (MFSR) analysis techniques for speaker verification under limited data condition. These analysis techniques relatively extract more feature vector during training and testing and develop improved modeling and testing for limited data. To demonstrate this we have used mel-frequency cepstral coefficients (MFCC) and linear prediction cepstral coefficients (LPCC) as feature. Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) are used for modeling the speaker. The database used is NIST-2003. The experimental results indicate that, improved performance of MFS, MFR, and MFSR analysis radically better compared with SFSR analysis. The experimental results show that LPCC based MFSR analysis perform better compared to other analysis techniques and feature extraction techniques.

계곡 추적 Deformable Model을 이용한 반자동 척추뼈 분할 도구의 개발 (Developments of Semi-Automatic Vertebra Bone Segmentation Tool using Valley Tracking Deformable Model)

  • 김예빈;김동성
    • 대한의용생체공학회:의공학회지
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    • 제28권6호
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    • pp.791-797
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    • 2007
  • This paper proposes a semiautomatic vertebra segmentation method that overcomes limitations of both manual segmentation requiring tedious user interactions and fully automatic segmentation that is sensitive to initial conditions. The proposed method extracts fence surfaces between vertebrae, and segments a vertebra using fence-limited region growing. A fence surface is generated by a deformable model utilizing valley information in a valley emphasized Gaussian image. Fence-limited region growing segments a vertebra using gray value homogeneity and fence surfaces acting as barriers. The proposed method has been applied to ten patient data sets, and produced promising results accurately and efficiently with minimal user interaction.