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Fig. 2 shows the distribution of rotating particles which marked black color under the condition of different that the number of rotating particles decreases with increases and the shear plane becomes misty.
(a) 0.5mm/min (b) 25mm/min (c) 75mm/min Fig. 4 Particle rotation velocity field under different shear rate Fig. 4 shows that with the increase of shearing rate, sample destruction is no longer along the shear plane, but a large number of failure areas appear in internal sample when the shearing rate is 75 mm/min based on particle rotation velocity field, and the number of rotating particles increases which resulted from large cracks generate in internal sample.
Micro-simulation of triaxial test of coarse grained material.
The influence of mesoscopic parameters in particle flow model on macro-reaction of coarse grained material.
The Shear Dilation and Shear Band of Coarse Grained Material Based on Discrete Element Method.

The analysis shows that the chilling effect of the inner channel wall precipitates a large number of primary silicon nuclei, and so the primary silicon grains are refined greatly.
As a result, a large number of primary silicon nuclei can be formed and a part of them may grow up along the inner wall surface.
Therefore, a large number of small primary silicon crystal nuclei or grains can survive in this melt.
If a large number of primary silicon grains appear in the A390 alloy slurry, the distance among the grains may be very much small and the mutual interference in the solute field and the temperature field can inhibit the excessive growth of the primary silicon grains, which makes the primary silicon grains significantly fine, as shown in Figure 1.
The chilling effect of the channel wall will become weaker and the number of primary silicon nuclei in the undercooled liquid area will decrease.

Ferrite Grain Refinement during Hot Rolling of Seamless Tubes R.
The composition of the steel was 0.2C, 1.44Mn, 0.24Si and 0.12Cr, all numbers in % weight.
The starting grain size for the torsion experiments were certainly higher than 100µm, as there was no pinning effect limiting grain growth during heating.
The grain size of torsion sample quenched at a point simulating withdrawal of the tube from TF shows that the austenite grain size leaving TF is about the same size as for the grain which left CMM.
This in turns determines final ferrite grain sizes bring refinement of these grains by a factor of almost 2, that is, from 20.8 to 12.4µm.

With the roles of above two interactions, some EBSD characteristics such as the packet size and the number fraction of high angle grain boundaries all have a peak present at 740℃ Introduction HSLA100 steel has been developed widely in recent years owing to an excellent combination of high strength, good toughness and excellent welding performance.
Fig.3f shows the number fraction of HAGBs (≥15°) in the test samples quenched at different temperature in the 2-phase region.
With the quenching temperature increasing, the number fraction of HAGBs increase gradually to peak at 740℃ and then decrease gradually, and finally the fraction of HAGBs fluctuate slightly above 800℃.
With the roles of above two interactions, some EBSD characteristics such as the packet size and the number fraction of high angle grain boundaries all have a peak present at 740℃ (Fig.5).
With the roles of above two interactions, some EBSD characteristics such as the packet size and the number fraction of high angle grain boundaries all have a peak present at 740℃ References [1] E.J.

The number of the acicular ferrite significantly increases in the cast microstructure, and the grains become more fine and uniform.
The number of bainite is largest in the cast microstructure, most of which is distributed at the boundary of the ferrite grains, when the 0.02 wt% CaO is added.
The number of bainite, which is mostly distributed at the boundary of the ferrite grains, increase in the cast microstructure.
The number of the acicular ferrite significantly increases in the cast microstructure, and the grains become more fine and uniform.
The number of the acicular ferrite significantly increases in the cast microstructure, and the grains become more fine and uniform.

Different ORs exist between the γ-fcc and the α'-bcc crystal lattices and each OR determines the maximum number of the possible α' variants inherited from a parent grain.
However, when the number of variants Viα' available per parent grain is too small, more than one potential parent can be derived from all considered variants.
The γ orientations of the resulting cells (the γ grains) were randomly tossed.
The number of these variants was variable.
One limit for the reconstruction is the number of differently oriented variants available per parent grain.

The studies demonstrated, that overestimated recrystallization driving force not only results in erroneous kinetics estimation, but also gives excessive number of recrystallization centers and undersized grain structure.
The grains present conglomerate of recrystallized grains with 10 microns average size and residual 300 microns dendritic grains.
This is explained by a larger number of formed recrystallization nucleation centers in the model.
The driving force for recrystallization influences not only its kinetics, but also the number of new grain nuclei.
The overestimation of the driving force for recrystallization skews the number of new grains nuclei upward, hence the grain size after recrystallization is complete.

According to the architecture characteristics of the grain storage system and the main factors influencing the safety of the grain storage, this paper has proposed a two layers data fusion system based on multi-sensors grain storage monitoring technique, which is used to identify the safety of the storage.
During the grain storage procedure, the factors influencing the grain most are temperature, moisture, insect pests and micro-organism, these factors correlate and interact with each other, causing influencing elements such as moisture condensation, stack fever, stack mildew and insects, which result in grain store stability and safety varying, grain storage quality descends.
In this way, make judgment to current grain state according to the recognition frame.
Summaries and Prospect This paper has collected data relevant to the grain storage safety based on current grain information monitoring system.
The proposed method could effectively evaluate grain storage safety state of a certain time, thus judge out grain storage state quality.

It is mainly observed in metals and alloys with cubic face-centered lattice, characterized by a high number of slip systems (Al, Cu, Ni) [4].
At this temperature the total number of 3 passes was applied.
The mean grain size is about 1.9 mm, what indicates that two additional passes of ECAP caused almost 2.5 times reduction of grain size.
The microstructure is mostly composed of small equiaxed grains and only few larger grains with a high density of low angle boundaries can be detected.
The average grain size is about 1.9 mm.

BEHAVIOR OF GRAIN BOUNDARIES UNDER DEFORMATION Grain boundaries can respond to stress in a number of ways. [2] They can act as dislocation sources by emitting dislocations into the neighboring grains.
In addition to transferring stresses and strains, the boundary itself can deform by a number of processes.
Slip continuity, expressed as percent in Fig. 1, was defined as the ratio of the number of slip traces across a boundary divided by the total number of slip lines impinging at the interface.
The localization of strain leads to a mismatch at the grain boundary; called a “deformation ledge.” [11] Das and Marcinkowski characterized the deformation ledge by an “effective” Burgers vector B, given by: (1) B = n(b1-Qb2), where b1 and b2 are the Burgers vectors in grains 1 and 2, respectively, Q is a rotation matrix, and n is the number of dislocations that enter the boundary.
In the case of localized deformation and channeling, dislocations pile-up at the grain boundary in only a small number of widely spaced locations, increasing n and therefore, B.