• Title/Summary/Keyword: Size Prediction

Search Result 1,447, Processing Time 0.027 seconds

Microstructure Prediction Technology of Ni-Base Superalloy (단조용 니켈기지 초내열합금의 조직예측기술)

  • Yeom, J.T.;Kim, J.H.;Hong, J.K.;Park, N.K.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
    • /
    • 2009.10a
    • /
    • pp.89-92
    • /
    • 2009
  • As a class of materials, Ni-base superalloys are among the most difficult metal alloys to forge together with refractory metals and cobalt-base superalloys. The mechanical properties of Ni-base superalloys depend very much on grain size and the strengthening phases, $\gamma$' ($Ni_3$(Al,Ti)-type) and $\gamma$".($Ni_3$Nb-type). Especially, the control of grain size remains as a sole means for the control of mechanical properties. The grain size and distribution changes of the wrought superalloys during hot working and heat treatment are mainly controlled by the recrystallization and grain growth behaviors. In this presentation, prediction technology of grain size through the computer-aided process design, and numerical modeling for predicting the microstructure evolution of Ni-base superalloy during hot working were introduced. Also, some case studies were dealt with actual forming processes of Ni-base superalloys.

  • PDF

Prediction of Crack Growth Retardation Behavior by Single Overload (단일 과대 하중에 의한 균열 성장 지연 거동 예측)

  • 송삼흥;최진호;김기석
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • 1996.11a
    • /
    • pp.928-932
    • /
    • 1996
  • Single overload fatigue tests with overload sizes ranging from 50% and 100% have been performed to investing ate the fatigue crack growth retardation behavior. A modified and experimental method of Willenborg's model for prediction of crack growth retardation behavior has been developed, based on evaluations of equivalent plastic zone size (EPZS) changing its size along the overload plastic zone boundary. The minimum crack growth rates of each overload size are linearly decreased with overload size increasing, but fatigue lives extended by single overload are increasing much more unlike the crack growth rates. Comparisons of crack growth behavior predicted by EPZS model and Willenborg model have shown that the EPZS model accounts for overload effects better than Willenborg model. These effects include delayed retardation, large retardation region, minimum crack growth rate, and the increase rate of crack growth rate in the region crack growth rate recovered.

  • PDF

Enhanced Prediction for Low Complexity Near-lossless Compression (낮은 복잡도의 준무손실 압축을 위한 향상된 예측 기법)

  • Son, Ji Deok;Song, Byung Cheol
    • Journal of Broadcast Engineering
    • /
    • v.19 no.2
    • /
    • pp.227-239
    • /
    • 2014
  • This paper proposes an enhance prediction for conventional near-lossless coder to effectively lower external memory bandwidth in image processing SoC. First, we utilize an already reconstructed green component as a base of predictor of the other color component because high correlation between RGB color components usually exists. Next, we can improve prediction performance by applying variable block size prediction. Lastly, we use minimum internal memory and improve a temporal prediction performance by using a template dictionary that is sampled in previous frame. Experimental results show that the proposed algorithm shows better performance than the previous works. Natural images have approximately 30% improvement in coding efficiency and CG images have 60% improvement on average.

Reviving GOR method in protein secondary structure prediction: Effective usage of evolutionary information

  • Lee, Byung-Chul;Lee, Chang-Jun;Kim, Dong-Sup
    • Proceedings of the Korean Society for Bioinformatics Conference
    • /
    • 2003.10a
    • /
    • pp.133-138
    • /
    • 2003
  • The prediction of protein secondary structure has been an important bioinformatics tool that is an essential component of the template-based protein tertiary structure prediction process. It has been known that the predicted secondary structure information improves both the fold recognition performance and the alignment accuracy. In this paper, we describe several novel ideas that may improve the prediction accuracy. The main idea is motivated by an observation that the protein's structural information, especially when it is combined with the evolutionary information, significantly improves the accuracy of the predicted tertiary structure. From the non-redundant set of protein structures, we derive the 'potential' parameters for the protein secondary structure prediction that contains the structural information of proteins, by following the procedure similar to the way to derive the directional information table of GOR method. Those potential parameters are combined with the frequency matrices obtained by running PSI-BLAST to construct the feature vectors that are used to train the support vector machines (SVM) to build the secondary structure classifiers. Moreover, the problem of huge model file size, which is one of the known shortcomings of SVM, is partially overcome by reducing the size of training data by filtering out the redundancy not only at the protein level but also at the feature vector level. A preliminary result measured by the average three-state prediction accuracy is encouraging.

  • PDF

Evaluation of Bubble Size Models for the Prediction of Bubbly Flow with CFD Code (CFD 코드의 기포류 유동 예측을 위한 기포크기모델 평가)

  • Bak, Jin-yeong;Yun, Byong-jo
    • Journal of Energy Engineering
    • /
    • v.25 no.1
    • /
    • pp.69-75
    • /
    • 2016
  • Bubble size is a key parameter for an accurate prediction of bubble behaviours in the multi-dimensional two-phase flow. In the current STAR CCM+ CFD code, a mechanistic bubble size model $S{\gamma}$ is available for the prediction of bubble size in the flow channel. As another model, Yun model is developed based on DEBORA that is subcooled boiling data in high pressure. In this study, numerical simulation for the gas-liquid two-phase flow was conducted to validate and confirm the performance of $S{\gamma}$ model and Yun model, using the commercial CFD code STAR CCM+ ver. 10.02. For this, local bubble models was evaluated against the air-water data from DEDALE experiments (1995) and Hibiki et al. (2001) in the vertical pipe. All numerical results of $S{\gamma}$ model predicted reasonably the two-phase flow parameters and Yun model is needed to be improved for the prediction of air-water flow under low pressure condition.

New Intra Coding Scheme for High-definition Video Coding (고화질 비디오 부호화를 위한 새로운 화면내 부호화 방법)

  • Heo, Jin;Ho, Yo-Sung
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.45 no.5
    • /
    • pp.72-78
    • /
    • 2008
  • Although the H.264 video coding scheme is popular, it is not efficient for high-definition (HD) video coding because the size of its macroblock is relatively small for the HD video resolution. In this paper, we propose a new intra coding scheme based on the enlarged macroblock size. For the luminance component, intra $4{\times}4$ prediction and intra $16{\times}16$ prediction in H.264 are scaled into intra $8{\times}8$ prediction and intra $32{\times}32$ prediction, respectively. For the chrominance components, intra $8{\times}8$ prediction is extended to intra $16{\times}16$ prediction. Along with the $8{\times}8$ basic coding block size, an $8{\times}8$ integer discrete cosine transform (DCT) is used. Experimental results show that the proposed algorithm improves coding efficiency of the intra coding for HD video: PSNR gain by 0.23dB and bit-rate reduction by 5.32% on average.

A Study on Stock Trend Determination in Stock Trend Prediction

  • Lim, Chungsoo
    • Journal of the Korea Society of Computer and Information
    • /
    • v.25 no.12
    • /
    • pp.35-44
    • /
    • 2020
  • In this study, we analyze how stock trend determination affects trend prediction accuracy. In stock markets, successful investment requires accurate stock price trend prediction. Therefore, a volume of research has been conducted to improve the trend prediction accuracy. For example, information extracted from SNS (social networking service) and news articles by text mining algorithms is used to enhance the prediction accuracy. Moreover, various machine learning algorithms have been utilized. However, stock trend determination has not been properly analyzed, and conventionally used methods have been employed repeatedly. For this reason, we formulate the trend determination as a moving average-based procedure and analyze its impact on stock trend prediction accuracy. The analysis reveals that trend determination makes prediction accuracy vary as much as 47% and that prediction accuracy is proportional to and inversely proportional to reference window size and target window size, respectively.

Long-Term Performance of High Strength Concrete

  • Choi Yeol;Kang Moon-Myung
    • Journal of the Korea Concrete Institute
    • /
    • v.16 no.3 s.81
    • /
    • pp.425-431
    • /
    • 2004
  • This paper describes an experimental investigation of how time-dependent deformations of high strength concretes are affected by maximum size of coarse aggregate, curing time, and relatively low sustained stress level. A set of high strength concrete mixes, mainly containing two different maximum sizes of coarse aggregate, have been used to investigate drying shrinkage and creep strain of high strength concrete for 7 and 28-day moist cured cylinder specimens. Based upon one-year experimental results, drying shrinkage of high strength concrete was significantly affected by the maximum size of coarse aggregate at early age, and become gradually decreased at late age. The larger the maximum size of coarse aggregate in high strength concrete shows the lower the creep strain. The prediction equations for drying shrinkage and creep coefficient were developed on the basis of the experimental results, and compared with existing prediction models.

Average Particle Size Prediction of Rubber Dispersed Phase in High Impact Polystyrene (내충격성 폴리스티렌의 고무상 입자경 예측)

  • Lee, Seong-Jae;Chung, Kyung-Ho
    • Elastomers and Composites
    • /
    • v.31 no.5
    • /
    • pp.327-334
    • /
    • 1996
  • A correlative analysis has been carried out to predict the average particle size of rubber dispersed phase In high impact polystyrene manufactured by bulk polymerization. To do the correlation, a mechanistic model suggested previously by the author was used for describing the size of stabilizing particles agitated under the turbulent viscous shear subranges in a prepolymerization reactor, where the rubber particles were assumed to be formed at the time of phase inversion in the reactor. Viscosities required for the model were postulated to describe the overall behavior of butadiene rubber and polystyrene mixture along the wide range of conversion. The good agreement between the model and the experimental data from a plant was quite satisfactory for the prediction of the average rubber particle size of high impact polystyrene.

  • PDF

A Fast Intra-Prediction Method in HEVC Using Rate-Distortion Estimation Based on Hadamard Transform

  • Kim, Younhee;Jun, DongSan;Jung, Soon-Heung;Choi, Jin Soo;Kim, Jinwoong
    • ETRI Journal
    • /
    • v.35 no.2
    • /
    • pp.270-280
    • /
    • 2013
  • A fast intra-prediction method is proposed for High Efficiency Video Coding (HEVC) using a fast intra-mode decision and fast coding unit (CU) size decision. HEVC supports very sophisticated intra modes and a recursive quadtree-based CU structure. To provide a high coding efficiency, the mode and CU size are selected in a rate-distortion optimized manner. This causes a high computational complexity in the encoder, and, for practical applications, the complexity should be significantly reduced. In this paper, among the many predefined modes, the intra-prediction mode is chosen without rate-distortion optimization processes, instead using the difference between the minimum and second minimum of the rate-distortion cost estimation based on the Hadamard transform. The experiment results show that the proposed method achieves a 49.04% reduction in the intra-prediction time and a 32.74% reduction in the total encoding time with a nearly similar coding performance to that of HEVC test model 2.1.