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However, in the case of the CBN grain tool, the glass plate is broken and the tool often fractures at drilling number of 1 hole.
The diamond grain tool is 100 times as drilling number as the CBN grain tool.
Figure 4 shows the relationship between the number of grain and the grain density.
The number of grain counts all grain in the circle of a diameter of 1mm.
The number of grain increases with decreasing average grain diameter.

Y X O O‘ x y particle scale (sub-coordinate system) pore network dryer scale (macro-coordinate system) hot wind outlet wire mesh container wall corn hot wind inlet (a) (b) constructed enlarged (c) throat corn particle pore (node) Fig.1 Drying container (a), pore network physical model (b) and enlarged pore network (c) Pore Network Physical Model Generally, the parameters for describing the structure characteristics of grain materials included the porosity, area density of pore and grain number, particle size distribution and the pore size distribution.
A two-dimension pore network physical model could be described by the parameters of pore and particle size distribution, distance between two nodes, the number of model scale, and coordination number [3-4].
As said above, the grain materials included two kinds of different scale pore system at least.
Then, the mass and heat transfer equation at the particle scale can be obtained: (4) (5) where D is the moisture diffusion coefficient in the skeleton grain (m2/s), r is the spherical coordinate variable (m), M is the local moisture content at certain moment and place inside the grain(d. b.), is the heat consumed by vaporizing the grain water during unit time (J/s), is the heat received from heat convection between the vapor-phase and grain surface during unit time (J/s), R is the grain radius (m), is the grain density (kg/m3), and Cg is the specific heat capacity of the grain (J/(kg·K)).
Table 1 Main parameters for pore network model node number corn grain density [kg/m3] mean grain diameter [mm] pore number density [unit/m2] grain number density [unit/m2] pore coordination number 1801 1004 8.8 17504 17289 4 Results and Discussion Drying and Temperature Curves Compared Experiment with Simulation.

We postulated a softening model involving grain rotation that results in diffusion-accommodated grain-boundary sliding.
Shan et al. [10] also confirmed the presence of visible grain orientation and deteceted that grains grew into an elongated equiaxed shape as a result of grain orientation.
Here we consider a two-dimensional hexagon ranged structure element that contains a large number of grains.
Then denotes as the number fraction of grains having the soft orientation aligned with the shear direction, where is the number of grains that have the soft orientation aligned with the shearing direction.
Homogenized representation of grain rotation.

Based on the studies of superplastic grain growth mechanism, the superplastic grain growth rate equation are derived in this paper by coupling static state anneal grain growth mechanism and deformation stimulated grain growth mechanism.
Static state anneal grain growth mechanism and dynamic grain growth mechanism or forming stimulate grain growth mechanism are mainly ways in grain growth of superplastic forming, and the forming stimulate grain growth is the mostly form in superplastic deformation [2].
For each cell, we can select randomly an integer as microcosmic tropism in Q�Q>1�number.
Therefore the total energy of the whole system is ( )11 1 1 2 i j i n m n s s s i j i J E Hδ = = = = − +∑∑ ∑ �3-8� where the first item is the general crystal boundary energy, the secondly is the general shaping energy, isH is the shaping energy of Si crystal lattice, E is the system energy, n is crystal lattice numbers in system and m is the number of vicinity nodes.
The images indicate that the grain grow up with the forming process, some grain was reduced and swallowed up finally by surrounding grains.

The second area of study is the inhibition of grain growth due to second phase particles pinning the grain boundaries so as to stagnate the grain size from growing any further.
A square matrix of size ‘N’ is then generated, which contains all its elements as random numbers ranging from 1 to Q, where Q stands for the number of grain orientations. 3.
If ΔE ≤ = 0, the change is accepted else if ΔE > 0, compute probability, p = exp(-ΔE/kT) (4) where k = Boltzmann constant, and, T = temperature if r < p where r is a random number generated and uniformly distributed between 0 & 1, the change is still accepted, else, rejected.
No Author(s) Year Equation for Limiting Grain Size 1.
The number of nearest neighbors considered was 26 and the size of second phase particles was kept at one voxel, or one cube, when studying the effects of static particles on grain growth parameters.

The color represents the grain number gi.
This number is given at random between 1 and 50 for each grain on nucleation, and remains while growing.
The value of R is calculated as follows: there are Nx grids on a constant-y line, and the number of grids where Si fi 2 < 0.5 is counted as grain boundary site.
The total number divided by Nx is defined as R.
Large value in R indicates that many fine grains distribute, whereas small R indicates small number of coarse grain exists.

Both, chemical (precipitations, phases) and physical (dislocations, high-angle grain boundaries, grain size, low-angle grain boundaries) inhomogeneities characterize the microstructure of this commercially used Al-Mg-Si alloy.
This is caused by the introduction of physical (high-angle grain boundaries, low-angle grain boundaries, dislocations) and/or chemical (phases) inhomogeneities leading to local differences in the potentials.
After the deformation, the material state is referred to "as UFG" combined with the used processing route and number of extrusions (e.g.
Although almost at the border between the standard deviation (≤ 26 %), the slight increase of the polarization resistance by the number of ECA-extrusions can be stated.
Compared to the CG counterpart, the corrosion damage of the UFG microstructure exhibits significantly weaker attacks (~ 50 % less deep pits) with increasing numbers of ECAextrusions.

After five and ten turns, as shown in Fig. 2(b) and (c), the distributions of the number fractions of the misorientation angles have a similar tendency.
Detailed inspection shows the number fractions of high-angle grain boundaries increase at the center and the peak of low-angle boundaries is reduced significantly by comparison with those of a quarter turn.
Fig. 2 Distributions of the number fractions of the grain boundary misorientations at the centers and edges of the disks processed by HPT through (a) 1/4 turn, (b) 5 turns and (c) 10 turns.
Moreover, the gradual evolution towards homogeneity with increasing numbers of turns was visible in this Cu-0.1% Zr alloy in which the results were presented in the form of the microhardness evolution [7].
These low-angle miorientations are formed because large numbers of dislocations begin to arrange into low-energy configurations in the form of low-angle grain boundaries.

When the grain boundaries are sufficiently weak, the CM lies entirely on grain boundaries, while when the grain boundaries are strong, cleavage occurs.
Although the CM algorithm can operate on digitized experimental microstructures, simulated Journal Title and Volume Number (to be inserted by the publisher) 3 microstructures were used to allow a consistent 3D representation and to ensure equivalence between specimens.
(b) For ε = 0.4, the CM cleaves large grains and follows the boundaries of small grains.
Journal Title and Volume Number (to be inserted by the publisher) 5 In the mixed regime, the CM cleaves unfavorably oriented grains and goes around favorably oriented grains.
Conclusions A number of material properties depend on the characteristics of the three-dimensional grain boundary network.

The total number of order parameters is , and .
The area fraction of the particles is fixed at 1.5%, while the number of particles varies from 2 to 8.
When the number of particles increases, the reduction speed of the grain 2 area fraction is lowered.
Fig. 7 Effect of particle size on pinning effect: (a) area variations of grain 2 with different number of particles; (b) 8 particles, = 50.
Yang, Computer simulation of the domain dynamics of a quenched system with a large number of nonconserved order parameters: The grain-growth kinetics, Phys.