• Title/Summary/Keyword: Fitting Model

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The development of On-line Model for the Prediction of Effective Strain Distribution by Non-dimensionalization on FEM Basis (유한요소법 기반의 무차원화를 이용한 판 유효 변형률 분포 예측 온라인 모델 개발)

  • Kim S. H.;Lee J. H.;Hwang S. M.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2004.08a
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    • pp.359-367
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    • 2004
  • In this research on-line model for the prediction of the effective strain distribution in strip on finishing mill process is presented. To describe the effective strain distribution in strip, three guide points and a distribution fitting variable are used. On-line models to get these points and fitting variable non-dimensionalization method and least square method were used with FEM simulation results. The model is developed using strip only FEM simulation as reference sets and compared with roll coupled FEM simulation results as perturbed sets. The on-line model to describe effective strain distribution shows good agreement with coupled FEM analysis results.

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Application of Bootstrap Method to Primary Model of Microbial Food Quality Change

  • Lee, Dong-Sun;Park, Jin-Pyo
    • Food Science and Biotechnology
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    • v.17 no.6
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    • pp.1352-1356
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    • 2008
  • Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

Investigation of 1D sand compression response using enhanced compressibility model

  • Chong, Song-Hun
    • Geomechanics and Engineering
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    • v.25 no.4
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    • pp.341-345
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    • 2021
  • 1D sand compression response to ko-loading experiences volume contraction from low to high effective stress regimes. Previous study suggested compressibility model with physically correct asymptotic void ratios at low and high stress levels and examined only for both remolded clays and natural clays. This study extends the validity of Enhanced Terzaghi model for different sand types complied from 1D compression data. The model involved with four parameters can adequately fit 1D sand compression data for a wide stress range. The low stress obtained from fitting parameters helps to identify the initial fabric conditions. In addition, strong correlation between compressibility and the void ratio at low stress facilitates determination of self-consistent fitting parameters. The computed tangent constrained modulus can capture monotonic stiffening effect induced by an increase in effective stress. The magnitude of tangent stiffness during large strain test should not be associated with small strain stiffness values. The use of a single continuous function to capture 1D stress-strain sand response to ko-loading can improve numerical efficiency and systematically quantify the yield stress instead of ad hoc methods.

Development of Hyperelastic Model for Butadiene Rubber Using a Neural Network

  • Pham, Truong Thang;Woo, Changsu;Choi, Sanghyun;Min, Juwon;Kim, Beomkeun
    • Elastomers and Composites
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    • v.56 no.2
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    • pp.79-84
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    • 2021
  • A strain energy density function is used to characterize the hyperelasticity of rubber-like materials. Conventional models, such as the Neo-Hookean, Mooney-Rivlin, and Ogden models, are widely used in automotive industries, in which the strain potential is derived from strain invariants or principal stretch ratios. A fitting procedure for experimental data is required to determine material constants for each model. However, due to the complexities of the mathematical expression, these models can only produce an accurate curve fitting in a specified strain range of the material. In this study, a hyperelastic model for Neodymium Butadiene rubber is developed by using the Artificial Neural Network. Comparing the analytical results to those obtained by conventional models revealed that the proposed model shows better agreement for both uniaxial and equibiaxial test data of the rubber.

A Comparative Analysis of 3D Circle Fitting Algorithms for Determination of VLBI Antenna Reference Point (VLBI 안테나 기준점 결정을 위한 3D Circle Fitting 알고리즘의 비교 분석)

  • Hyuk Gil, Kim;Jin Sang, Hwang;Hong Sik, Yun;Tae Jun, Jeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.231-244
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    • 2015
  • The accuracy of reference point of VLBI antenna is mandatory to perform collocation of different space geodetic techniques. In this study, we evaluated the optimal methods for the 3D circle fitting to enhance the accuracy of the reference point of VLBI antenna. Two kinds of methodologies for the orthonormal coordinate system with translation of planar observation point and the unitary coordinate transforamation were suggested and their fitting accuracies were evaluated where the orthogonal distance was calculated by residual between observation point and fitting model and the recursive calculation was performed to improve the accuracy of 3D circle fitting. Finally, we found that the methodology for the unitary coordinate transformation is highly appropriate to determine the optimal equation for azimuth-axis and elevation-axis of VLBI antenna. Therefore, the reference point of VLBI antenna with high accuracy can be determined by the intersection of the above two axises (azimuth-axis and elevation-axis). This result is expected to be utilized for a variety of researches for connection between VLBI observation results and the national control point.

Voxel-wise Mapping of Functional Magnetic Resonance Imaging in Impression Formation

  • Jeesung Ahn;Yoonjin Nah;Inwhan Ko;Sanghoon Han
    • Science of Emotion and Sensibility
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    • v.25 no.4
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    • pp.77-94
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    • 2022
  • Social interactions often involve encountering inconsistent information about social others. We conducted a functional magnetic resonance imaging (fMRI) study to comprehensively investigate voxel-wise temporal dynamics showing how impressions are anchored and/or adjusted in response to inconsistent social information. The participants performed a social impression task inside an fMRI scanner in which they were shown a male face, together with a series of four adjectives that described the depicted person's personality traits, successively presented beneath the image of the face. Participants were asked to rate their impressions of the person at the end of each trial on a scale of 1 to 8 (where 1 is most negative and 8 is most positive). We established two hypothetical models that represented two temporal patterns of voxel activity: Model 1 featured decreasing patterns of activity towards the end of each trial, anchoring impressions to initially presented information, and Model 2 showed increasing patterns of activity toward the end of each trial, where impressions were being adjusted using new and inconsistent information. Our data-driven model fitting analyses showed that the temporal activity patterns of voxels within the ventral anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex, amygdala, and fusiform gyrus fit Model 1 (i.e., they were more involved in anchoring first impressions) better than they did Model 2 (i.e., showing impression adjustment). Conversely, voxel-wise neural activity within dorsal ACC and lateral OFC fit Model 2 better than it did Model 1, as it was more likely to be involved in processing new, inconsistent information and adjusting impressions in response. Our novel approach to model fitting analysis replicated previous impression-related neuroscientific findings, furthering the understanding of neural and temporal dynamics of impression processing, particularly with reference to functionally segmenting each region of interest based on relative involvement in impression anchoring as opposed to adjustment.

Effect of Cyclic Soil Model on Seismic Site Response Analysis (지반 동적거동모델에 따른 부지응답해석 영향연구)

  • Lee, Jinsun;Noh, Gyeongdo
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.12
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    • pp.23-35
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    • 2015
  • Nonlinear soil behavior before failure under dynamic loading is often implemented in a numerical analysis code by a mathematical fitting function model with Masing's rule. However, the model may show different behavior with an experimental results obtained from laboratory test in damping ratio corresponding secant shear modulus for a certain shear strain rage. The difference may come from an unique soil characteristics which is unable to implement by using the existing mathematical fitting model. As of now, several fitting models have been suggested to overcome the difference between model and real soil behavior but consequence of the difference in dynamic analysis is not reviewed yet. In this paper, the effect of the difference on site response was examined through nonlinear response history analysis. The analysis was verified and calibrated with well defined dynamic geotechnical centrifuge test. Site response analyses were performed with three mathematical fitting function models and compared with the centrifuge test results in prototype scale. The errors on peak ground acceleration between analysis and experiment getting increased as increasing the intensity of the input motion. In practical point of view, the analysis results of accuracy with the fitting model is not significant in low to mid input motion intensity.

Gaussian Model for Laser Image on Curved Surface

  • Annmarie Grant;Sy-Hung Bach;Soo-Yeong Yi
    • Current Optics and Photonics
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    • v.7 no.6
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    • pp.701-707
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    • 2023
  • In laser imaging, accurate extraction of the laser's center is essential. Several methods exist to extract the laser's center in an image, such as the geometric mean, the parabolic curve fitting, and the Gaussian curve fitting, etc. The Gaussian curve fitting is the most suitable because it is based on the physical properties of the laser. The width of the Gaussian laser beam depends on the distance from the laser source to the target object. It is assumed in general that the distance remains constant at a laser spot resulting in a symmetric Gaussian model for the laser image. However, on a curved surface of the object, the distance is not constant; The laser beam is narrower on the side closer to the focal point of the laser light and wider on the side closer to the laser source, which causes the distribution of the laser beam to skew. This study presents a modified Gaussian model in the laser imaging to incorporate the slant angle of a curved object. The proposed method is verified with simulation and experiments.

A Study on Creation of 3D Facial Model Using Facial Image (임의의 얼굴 이미지를 이용한 3D 얼굴모델 생성에 관한 연구)

  • Lee, Hea-Jung;Joung, Suck-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.21-28
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    • 2007
  • The facial modeling and animation technology had been studied in computer graphics field. The facial modeling technology is utilized much in virtual reality research purpose of MPEG-4 and so on and movie, advertisement, industry field of game and so on. Therefore, the development of 3D facial model that can do interaction with human is essential to little more realistic interface. We developed realistic and convenient 3D facial modeling system that using a optional facial image only. This system allows easily fitting to optional facial image by using the Korean standard facial model (generic model). So it generates intuitively 3D facial model as controling control points elastically after fitting control points on the generic model wire to the optional facial image. We can confirm and modify the 3D facial model by movement, magnify, reduce and turning. We experimented with 30 facial images of $630{\times}630$ sizes to verify usefulness of system that developed.

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Nonlinear creep model based on shear creep test of granite

  • Hu, Bin;Wei, Er-Jian;Li, Jing;Zhu, Xin;Tian, Kun-Yun;Cui, Kai
    • Geomechanics and Engineering
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    • v.27 no.5
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    • pp.527-535
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    • 2021
  • The creep characteristics of rock is of great significance for the study of long-term stability of engineering, so it is necessary to carry out indoor creep test and creep model of rock. First of all, in different water-bearing state and different positive pressure conditions, the granite is graded loaded to conduct indoor shear creep test. Through the test, the shear creep characteristics of granite are obtained. According to the test results, the stress-strain isochronous curve is obtained, and then the long-term strength of granite under different conditions is determined. Then, the fractional-order calculus software element is introduced, and it is connected in series with the spring element and the nonlinear viscoplastic body considering the creep acceleration start time to form a nonlinear viscoplastic creep model with fewer elements and fewer parameters. Finally, based on the shear creep test data of granite, using the nonlinear curve fitting of Origin software and Levenberg-Marquardt optimization algorithm, the parameter fitting and comparative analysis of the nonlinear creep model are carried out. The results show that the test data and the model curve have a high degree of fitting, which further explains the rationality and applicability of the established nonlinear visco-elastoplastic creep model. The research in this paper can provide certain reference significance and reference value for the study of nonlinear creep model of rock in the future.