• 제목/요약/키워드: field gradient force

검색결과 59건 처리시간 0.022초

Snake 모델에서의 개선된 Gradient Vector Flow: 캡쳐 영역의 확장과 요면으로의 빠른 진행 (Enhanced Gradient Vector Flow in the Snake Model: Extension of Capture Range and Fast Progress into Concavity)

  • 조익환;송인찬;오정수;엄경식;김종효;정동석
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제33권1호
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    • pp.95-104
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    • 2006
  • Gradient vector flow(GVF) snake 또는 active contour 모델은 영상 분할에서 훌륭한 성능을 보여준다. 그러나 기존의 snake 모델에는 제한된 캡쳐 영역과 요면으로의 느린 진행과 같은 문제점들이 존재한다. 본 논문은 주변의 필드로부터 외부장(external force field)을 확장시키고 변형된 평탄화기법을 이용하여 확장된 필드를 정규화 함으로서 GVF snake 모델의 성능을 개선시키는 새로운 방법을 제시한다. 시뮬레이션을 위해 사용된 U자 모양 이미지에서의 결과는 제안된 방법이 좀 더 큰 캡쳐 영역을 갖고 기존의 GVF snake 모델에 비하여 요면으로 빠르게 진행하는 것이 가능함을 보여준다.

Field-Induced Translation of Single Ferromagnetic and Ferrimagnetic Grain as Observed in the Chamber-type μG System

  • Kuwada, Kento;Uyeda, Chiaki;Hisayoshi, Keiji;Nagai, Hideaki;Mamiya, Mikito
    • Journal of Magnetics
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    • 제18권3호
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    • pp.308-310
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    • 2013
  • Translation induced by the field-gradient force is being observed for a single ferromagnetic iron grain and a ferrimagnetic grain of a ferrite sample ($CuFe_2O_4$). From measurements on the translation, precise saturated magnetization of $M_S$ is possible for a single grain. The method is based on the energy conservation rule assumed for the grain during its translation and the grain is translated through a diffuse area under microgravity conditions. The results of the two materials indicate that a field-induced translation of grain bearing spontaneous moment is generally determined by a field-induced potential $-mM_SH(x)$ where m denotes the mass of sample. According to the above translations, the detection of $M_S$ is not interfered by any signals from the sample holder. The $M_S$ measurement does not require m value. By observing translations resulting from fieldinduced volume forces, the magnetization of a single grain is measurable irrespective of its size; the principle is also applicable to measuring susceptibility of diamagnetic and paramagnetic materials.

A Computational Method to Consider the Saturation of Magnetic Field In a High Density Recording Head

  • Park, Gwan-Soo
    • Journal of Magnetics
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    • 제8권4호
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    • pp.164-168
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    • 2003
  • In high density recording system, the recording head field on a medium should be focused in small bit area and should have a sufficient value to overcome the medium coercivity, which resulted in head saturation. In this paper, an efficient method to access the head field and field gradient considering head saturation is presented. The magnetic vector potential on the head surface is pre-calculated considering head saturation in several cases and accumulated into database. The head field on the recording media is easily produced solving Laplace equation using accessed magnetic vector potential boundaries. The computed head field is compared with a quantified magnetic force microscopy measurement.

Dynamic vibration response of functionally graded porous nanoplates in thermal and magnetic fields under moving load

  • Ismail Esen;Mashhour A. Alazwari;Khalid H. Almitani;Mohamed A Eltaher;A. Abdelrahman
    • Advances in nano research
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    • 제14권5호
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    • pp.475-493
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    • 2023
  • In the context of nonclassical nonlocal strain gradient elasticity, this article studies the free and forced responses of functionally graded material (FGM) porous nanoplates exposed to thermal and magnetic fields under a moving load. The developed mathematical model includes shear deformation, size-scale, miscorstructure influences in the framework of higher order shear deformation theory (HSDT) and nonlocal strain gradient theory (NSGT), respectively. To explore the porosity effect, the study considers four different porosity models across the thickness: uniform, symmetrical, asymmetric bottom, and asymmetric top distributions. The system of quations of motion of the FGM porous nanoplate, including the effects of thermal load, Lorentz force, due to the magnetic field and moving load, are derived using the Hamilton's principle, and then solved analytically by employing the Navier method. For the free and forced responses of the nanoplate, the effects of nonlocal elasticity, strain gradient elasticity, temperature rise, magnetic field intensity, porosity volume fraction, and porosity distribution are analyzed. It is found that the forced vibrations of FGM porous nanoplates under thermal and live loads can be damped by applying a directed magnetic field.

강화된 자기장 구배 하에서 나노자성입자를 이용한 미세유체 기반의 면역 측정 (Microfluidic immunoassay using superparamagnetic nanoparticles in an enhanced magnetic field gradient)

  • 한영기;강주헌;김규성;박제균
    • 센서학회지
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    • 제15권3호
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    • pp.158-163
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    • 2006
  • This paper reports a novel immunoassay method using superparamagnetic nanoparticles and an enhanced magnetic field gradient for the detection of protein in a microfluidic device. We use superparamagnetic nanoparticles as a label and fluorescent polystyrene beads as a solid support. Based on this platform, magnetic force-based microfluidic immunoassay is successfully applied to analyze the concentration of IgG as model analytes. In addition, we present ferromagnetic microstructure connected with a permanent magnet to increase magnetic flux density gradient (dB/dx, ${\sim}10^{4}$ T/m), which makes limit of detection reduced. The detection limit is reduced to about 1 pg/mL.

Wave dispersion analysis of rotating heterogeneous nanobeams in thermal environment

  • Ebrahimi, Farzad;Haghi, Parisa
    • Advances in nano research
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    • 제6권1호
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    • pp.21-37
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    • 2018
  • In the present article, wave dispersion behavior of a temperature-dependent functionally graded (FG) nanobeam undergoing rotation subjected to thermal loading is investigated according to nonlocal strain gradient theory, in which the stress numerates for both nonlocal stress field and the strain gradient stress field. The small size effects are taken into account by using the nonlocal strain gradient theory which contains two scale parameters. Mori-Tanaka distribution model is considered to express the gradually variation of material properties across the thickness. The governing equations are derived as a function of axial force due to centrifugal stiffening and displacements by applying Hamilton's principle according to Euler-Bernoulli beam theory. By applying an analytical solution, the dispersion relations of rotating FG nanobeam are obtained by solving an eigenvalue problem. Obviously, numerical results indicate that various parameters such as angular velocity, gradient index, temperature change, wave number and nonlocality parameter have significant influences on the wave characteristics of rotating FG nanobeams. Hence, the results of this research can provide useful information for the next generation studies and accurate deigns of nanomachines including nanoscale molecular bearings and nanogears, etc.

Simulation of a solar eruption with a background solar wind

  • 이환희;;강지혜
    • 천문학회보
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    • 제41권1호
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    • pp.46.3-47
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    • 2016
  • We construct a solar eruption model with a background solar wind by performing three-dimensional zero-beta magnetohydrodynamic (MHD) simulation. The initial configuration of a magnetic field is given by nonlinear force-free field (NLFFF) reconstruction applied to a flux emergence simulation. The background solar wind is driven by upflows imposed at the top boundary. We analyzed the temporal development of the Lorentz force at the flux tube axis. Based on the results, we demonstrate that a solar eruption is caused by the imbalance between magnetic pressure gradient force and magnetic tension force. We conclude that this imbalance is produced by a weak but continuously existing solar wind above an active region.

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Machine learning-based prediction of wind forces on CAARC standard tall buildings

  • Yi Li;Jie-Ting Yin;Fu-Bin Chen;Qiu-Sheng Li
    • Wind and Structures
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    • 제36권6호
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    • pp.355-366
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    • 2023
  • Although machine learning (ML) techniques have been widely used in various fields of engineering practice, their applications in the field of wind engineering are still at the initial stage. In order to evaluate the feasibility of machine learning algorithms for prediction of wind loads on high-rise buildings, this study took the exposure category type, wind direction and the height of local wind force as the input features and adopted four different machine learning algorithms including k-nearest neighbor (KNN), support vector machine (SVM), gradient boosting regression tree (GBRT) and extreme gradient (XG) boosting to predict wind force coefficients of CAARC standard tall building model. All the hyper-parameters of four ML algorithms are optimized by tree-structured Parzen estimator (TPE). The result shows that mean drag force coefficients and RMS lift force coefficients can be well predicted by the GBRT algorithm model while the RMS drag force coefficients can be forecasted preferably by the XG boosting algorithm model. The proposed machine learning based algorithms for wind loads prediction can be an alternative of traditional wind tunnel tests and computational fluid dynamic simulations.