Differentiation of Gliomas Using Tissue Parameters and a Three-dimensional Density Distribution Model

1990 ◽  
pp. 294-298
Author(s):  
P. Pedrosa ◽  
M. Jungke ◽  
M. Grigat ◽  
H. P. Higer ◽  
S. Meindl ◽  
...  
Keyword(s):  
Density Distribution ◽  
Three Dimensional ◽  
Distribution Model

Criteria and Methods for Reliable Three-Dimensional Image Reconstruction

1974 ◽  
Vol 32 ◽  
pp. 330-331
Author(s):  
R. A. Crowther
Keyword(s):  
Image Reconstruction ◽  
Finite Number ◽  
Density Distribution ◽  
Electron Micrographs ◽  
Mathematical Problem ◽  
Three Dimensional ◽  
Ideal Case ◽  
Dimensional Image ◽  
General Object ◽  
The Ideal

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.

An improved flux density distribution model for a flat heliostat (iHFLCAL) compared with HFLCAL

Energy ◽  
2019 ◽  
Vol 189 ◽  
pp. 116239
Author(s):  
Caitou He ◽  
Yuhong Zhao ◽  
Jieqing Feng
Keyword(s):  
Density Distribution ◽  
Flux Density ◽  
Distribution Model ◽  
Flux Density Distribution

Simulation of Three-Dimensional Stress Distribution in Compression Dies

2008 ◽  
Vol 575-578 ◽  
pp. 449-454
Author(s):  
Chu Yun Huang ◽  
Sai Yu Wang ◽  
Tao Yang ◽  
Xu Dong Yan
Keyword(s):  
Stress Distribution ◽  
Computer Aided Design ◽  
Three Dimensional ◽  
Distribution Model ◽  
Extrusion Dies ◽  
Maximum Value ◽  
Multiple Unit ◽  
Stress Freezing Method ◽  
Experimental Values ◽  
Aided Design

The stress fields of rectangular and T shape compression dies were simulated by three dimensional photo-elasticity of stress freezing method. The rules of stress distribution of σx, σy, σz on the surface of rectangular and T-shaped dies were discovered, and the rules were also found inside the dies. The results indicate that the stress distribution of rectangular die is similar to that of T shape die. Obvious stress concentration in corner of die hole was observed. σz rises from die hole to periphery until it achieves maximum value then it diminishes gradually, and σz between die hole and fix diameter zone is higher than it is in other position. At the same time, the equations of stress field of extrusion dies were obtained by curved surface fitting experimental values in every observed point with multiple-unit regression analysis method and orthogonal transforms. These works can provide stress distribution model for die computer aided design and make.

scholarly journals Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm

2017 ◽  
Vol 23 (3) ◽  
pp. 661-667 ◽  
Author(s):  
Yue Li ◽  
Di Zhang ◽  
Ilker Capoglu ◽  
Karl A. Hujsak ◽  
Dhwanil Damania ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Density Distribution ◽  
Scanning Transmission Electron Microscopy ◽  
Mass Density ◽  
Three Dimensional ◽  
Force Microscopy ◽  
Statistical Measures ◽  
Atomic Force ◽  
Transmission Electron ◽  
Scanning Transmission

AbstractEssentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass–density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass–density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass–density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass–density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass–density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.

A Small PWR-Core Physical Calculation Based on PWR-Core Analysis Code CORAL

2021 ◽  
Author(s):  
Wen Yang ◽  
Lun Zhou ◽  
Junrong Qiu ◽  
Yun Tai
Keyword(s):  
Density Distribution ◽  
Power Distribution ◽  
Channel Model ◽  
Three Dimensional ◽  
Least Square ◽  
Object Oriented Programming ◽  
Core Analysis ◽  
Fuel Temperature ◽  
Fuel Assemblies ◽  
Calculation Results

Abstract Three dimensional PWR-core analysis code CORAL is developed by Wuhan Second Ship Design and Research Institute. This code provides basic functions including three-dimensional power distribution, fine power reconstruction, fuel temperature distribution, critical search, control rod worth, reactivity coefficients, burnup and nuclide density distribution, etc. CORAL employ nodal expansion method to solve neutron diffusion equation, and the least square method is used to achieve few group constants, and sub-channel model and one-dimensional heat transfer is used to calculate fuel temperature and coolant density distribution, and burnup distribution and nuclide nuclear density could be obtained by solving macro-depletion and micro-depletion equation. The CORAL code is convenient to update and maintain in consider of modular, object-oriented programming technology. In order to analyze the computational accuracy of the CORAL code in small PWR-core and its capability to deal with heterogeneous, calculation analysis are carried out based on the material and geometry parameters of the SMART core. The core has 57 fuel assemblies, with 8, 20 or 24 gadolinium rods arranged in the fuel assemblies. In this paper, a quantitative comparison and analysis of the small PWR problem calculation results are carried out. Numerical results, including effective multiplication factor, assembly power distribution and pin power distribution, all agree well with the calculation results of OpenMC or Bamboo at both hot zero-power (HZP) and hot full-power (HFP) conditions.

A Three-Dimensional Load Sharing Model of Planetary Gear Sets Having Manufacturing Errors

2015 ◽  
Author(s):  
Nicholas D. Leque ◽  
Ahmet Kahraman
Keyword(s):  
Three Dimensional ◽  
Planetary Gear ◽  
Load Sharing ◽  
Distribution Model ◽  
Gear Mesh ◽  
Position Errors ◽  
Proposed Model ◽  
Manufacturing Errors ◽  
Manufacturing Tolerancing ◽  
Planetary Gear Sets

Planet-to-planet load sharing is a major design and manufacturing tolerancing issue in planetary gear sets. Planetary gear sets are advantageous over their countershaft alternatives in many aspects, provided that each planet branch carries a reasonable, preferably equal, share of the torque transmitted. In practice, the load shared among the planets is typically not equal due to the presence of various manufacturing errors. This study aims at enhancing the models for planet load sharing through a three-dimensional formulation of N-planet helical planetary gear sets. Apart from previous models, the proposed model employs a gear mesh load distribution model to capture load and time dependency of the gear meshes iteratively. It includes all three types of manufacturing errors, namely constant errors such as planet pinhole position errors and pinhole diameter errors, constant but assembly dependent errors such as nominal planet tooth thickness errors, planet bore diameter errors, and rotation and assembly dependent errors such as gear eccentricities and run-outs. At the end, the model is used to show combined influence of these errors on planet load sharing to aid designers on how to account for manufacturing tolerances in the design of the gears of a planetary gear set.

The experimental determination and evaluation of the three-dimensional fission density distribution of the IPEN/MB-01 research reactor facility for the IRPhE project

2011 ◽  
Vol 38 (2-3) ◽  
pp. 418-430 ◽  
Author(s):  
Adimir dos Santos ◽  
Leda C.C.B. Fanaro ◽  
Graciete S. de Andrade e Silva ◽  
Arlindo G. Mendonça
Keyword(s):  
Density Distribution ◽  
Experimental Determination ◽  
Research Reactor ◽  
Three Dimensional ◽  
Reactor Facility

scholarly journals Population Distribution in the Wake of a Sphere

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1498 ◽  
Author(s):  
Taraprasad Bhowmick ◽  
Yong Wang ◽  
Michele Iovieno ◽  
Gholamhossein Bagheri ◽  
Eberhard Bodenschatz
Keyword(s):  
Reynolds Number ◽  
Spatial Distribution ◽  
Population Density ◽  
Density Distribution ◽  
Population Distribution ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Wake Flow ◽  
Sample Number ◽  
Scalar Fluxes

The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

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