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The cellular automaton (CA) method is an effective technique used to simulate the grain evolution of materials.
To apply the CA method, a continuous structure is first discretized into finite number of small cells, the state of each cell is associated with local neighborhood cells and dependent upon evolution of its neighborhood cells only.
He Yan etc. [5] conducted researches on the mean DRX grain volume affected by dynamic recovery.
At the second step, the nucleation rate for loading case (a) is lower than loading case (b), but the number of new grains will not be obviously smaller due to the larger number of boundary cells.
The new grains would grow up and become bigger grains since the dislocation density is increased slowly for loading case (a).

The local strain in analysed place of probes on their sections was obtained by stereological measurement of degree of grain boundaries orientation, which is proportional to grain boundaries deformation degree.
From the relative number (number to unit of length) of parallel test lines intersections with grain boundaries (PL)P and perpendicular lines ones (PL)O was total relative surface area (SV)TOT of grains estimated according to Eq. 1.
Planar oriented part of relative surface area (SV)OR of grains was estimated according to Eq. 2.
From this values degree of orientation of grain boundaries O was estimated as ratio of (SV)OR and (SV)TOT
The higher number of holes was drilled to the same wear by coated drill.

Original grain distribution, grain size is 119μm 2μm 2μm Fig.1.
If a R-grain impinges upon another, both grains stop growing at the point of impingement.
(3) The nucleation of DRX will occur on grain boundaries (including primary grain boundaries and R-grain boundaries) or some other high-energy defects inside grains[7,8] 1.3 Recovery model.
There are a certain number of cells, N, which is chosen randomly from all the cells.
The number N is decided by the formula below: (3) Where M is total cells in CA model, K is a constant with 6030, is the increasing rate of dislocation density, and m is the sensitivity of stain rate.

From this clarification, it turned out to be clear that the number of blocks and packets per 100µm length of prior austenite grain boundary is larger at the RZ than the AWZ.
The numbers of blocks and packets were 5.3 and 2.4 at the RZ respectively.
In contrast, the numbers were 5.1 and 1.6 at the AWZ.
Since the nucleation rate from the prior austenite grain boundaries is considered to be related to the segregation of the solute elements near and at the austenite grain boundaries, Ni concentration was measured across prior austenite grain boundaries at the AWZ and the RZ by energy-dispersive X-ray spectroscopy (EDS).
It is considered that the lower Ni segregation concentration at the prior austenite grain boundaries of the RZ caused higher grain boundary energy β.

In some cases, this network consists of a glassy phase present as thin grain boundary films merging into pockets at multi-grain junctions.
Secondary samarium melilite (Sm2Si3-xAlxO3+xN4-x) had formed in a number of the intergranular pockets (arrowed).
Imaging and chemical analysis Grain size and shape.
Oxynitride glass network modifiers also promote grain growth.
A grain growth exponent of 3 was determined, which indicates diffusion controlled grain growth [11].

China Keywords: Titanium Silicon Carbide, spark plasma sintering, fine grain, layered structure Abstract.
Fine Plate-like grains of the samples with sizes of 2~6µm could be identified by scanning electronic microscope (SEM).
Since the Ti3SiC2 phase was first identified by Jeitschko and Nowotny [1] in 1967, a large number of works on the synthesis of this material have been reported [2-8].
Ti3SiC2 phase with plate-like grains can be observed around the dark speckles.
Fine grain polycrystalline Ti3SiC2 with a purity over 98vol.% can be synthesised by SPS sintering at temperature range of 1100~1300 o C for 5min.

However, rapid solidification/powder metallurgy (RS/PM) processing of magnesium alloys poses critical challenges due to the very high chemical reactivity of magnesium metal itself and a number of its important alloying elements.
The grain size ranged from 10-30µm, and the average grain size was about 20µm.
The dynamic recrystallization grain sizes depend on the initial grain sizes, and tend to decrease as the initial grain size decreases.
It's benefit for the dynamic recrystallization grain nuclear in primary grain boundary[7].
The fine dimple numbers are quite large.

It suggested that these particles might stimulate the recrystallization nucleation of the {110} oriented grains and restrain the development of {111} oriented grains in the sheet of non-oriented electrical steel.
Grain structures of the specimens were examined by optical microscopy.
The grain size was measured by the intercept method.
Results and Discussion Effects of precipitates on the final texture. 0 20 40 60 80 100 120 140 160 1# 2# 3# 4# 5# Specimen number Diameter,μm 3.6 3.8 4 4.2 4.4 10# 20# 30# 40# 50# Specimen number Core loss, W/Kg 1.5 1.6 1.7 1.8 1.9 2 Magnetic induction, T Core loss Magnetic induction Fig 1 Grain size of Fig 2 Magnetic properties ( Core loss and the normalized specimens magnetic induction ) of the final products Fig.1 shows the grain size of the specimens before cold rolling.
In some circumstances, when the grain size was larger than a certain value, the precipitates would take the place of the grain size to become the dominant factor of the final texture.

Table 1: Constants for copper grains ([27]).
It is seen in Fig. 3 that the nonhomogeneous part for the coarse grain size is small but when the grain size approaches to nonometer ranges, this part becomes dominant.
However, for simplicity, the strain gradient are computed here based on the directional derivative as: Dnf = ▽f.n (15) where n is the unit direction between the points and ▽f is: ▽ f = ∂f ∂xi + ∂f ∂y j (16) In Eq. 15, for the N number of nearest points around the interest point i, strain gradients are calculated.
It is demonstrated that for micro size grains, this effect is too low.
However, for 49 nm grain size, the difference is noticeable.

The influence of ram speed on grain structure evolution was analyzed.
A number of models, such as the Laasraoui-Jonas model (LJ model) [7], the KM model [8] and the two-parameter model [9], have been used to describe the evolution of dislocation density in grains.
Different shades represent different orientations of grains.
The black lines represent grain boundaries.
Most of grain misorientation angles are larger than 150.