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The laser processing variables were pulse energy and and number of pulses.
With the increasing number of pulses was increased material loss by laser ablation mechanism.
Laser spots are affected by the specific heat and vaporization, but the crater depth is dependent on the number of pulses.
The pulse number dependent effect is clearly seen in Fig. 2.
Murakami, Recent development of low-loss grain-oriented silicon steel, J Magn.

In their model recrystallisation, recovery and precipitation are described by sub-models with dislocation density, precipitate number density and average precipitate size as the internal variables coupling them together.
Grain growth.
Such an approach, however, has a number of complications.
To determine the migration factor (i.e. the proportional factor between the migration rate and the driving force) from recrystallisation data (i.e. the volume fraction recrystallised as a function of time) it is necessary to know the size of the driving force, namely the stored energy, and the number density of recrystallizing grains, both quantities as a function of time.
This research was carried out under the project number K41.2.09354 in the framework of the Research Programme of the Materials innovation institute (M2i) (www.m2i.nl).

Under hot deformation conditions, the flow stresses can be related to the DRX grain sizes with a grain size exponent of about 0.7 [2].
The new grains are characterized by a number of dislocations within their interiors (e.g.
A number of LAGBs with misorientations less than 15° are evolved in vicinity of initial HAGBs (Fig. 3a).
"ew grain formation at T = 500°°°°C (∼∼∼∼0.45 Tm).
The numbers in (b) indicate the misorientations in degrees.

Development of models to predict drying process has assisted in understanding the factors affecting drying process such as temperature, relative humidity and velocity of drying air and optimizes them for reducing drying time and saving energy without performing a large number of experiments [8].
Applications in grains.
The equation used to obtain the heat and mass transfer coefficients are given by [13]: (8) (9) where DAB is the vapor diffusivity in the air, hm is the mass transfer coefficient, hc is the heat transfer coefficient, dp = 2.50 mm is the particle diameter, J/kg K is universal constant for air, Re is the Reynolds number, Pr is the Prandtl number, and Sc is the Schmidt number, obtained by the following expressions: (10) (11) (12) being m the fluid viscosity that past over the grain The value of temperature, relative humidity and velocity of the drying air, and convective mass transfer coefficient, convective heat transfer coefficient, initial and equilibrium moisture content, initial temperature and dimensions of the rough rice used in the simulations are shown Table 1.
Bean grain drying analysis.
Hall, Thermal properties of grain, Trans.

In the bicrystals, the observed independence of the peak strain can be ascribed to the limited number of nucleation sites along the grain boundaries, so that this feature of the flow curve is largely determined by the orientations of the component grains of the bicrystals.
DRX nucleation took place at the grain boundary at a strain as low as 0.05, although the number of new grains was quite limited.
Only the number of primary slip traces was counted.
Concurrently, the number of new grains at grain boundary increases.
The new grains appeared behind migrating grain boundaries and were all first-order twins of the parent grains.

The production of fine grained materials by SPD, led to a large number of investigations focusing on the microstructure development and related to mechanical properties.
Compared to other SPD processes the HPT technique offers a large number of advantages, as stated in [4].
Transmission electron microscopy (TEM) was used to evaluate the ultrafine grain microstructure evolution with respect to site on deformed disc and the number of turns at corresponding εeq.
The ufg grain substructural features in disc edge support this selective growth of fine grains, as e seen Fig. 4.
Specific behaviour resulted as strain was increasing with number of turn.

Two nodes numbered 1857 and 23950 located on the fringe of protruding column and bottom of casting, where the heat dissipates quickly.
Fig.5 Temperature field distribution of casting system 1800s after pouring Simulation of Grain Structure Mathematical Model of Grain Structural Feature Values.
Rappaz firstly suggested that nuclei of crystal arise at different positions during heterogeneous nucleation which accord with statistic laws, and that a number of nucleation position should be activated under each supercooling degree ∆T.
The grain feature values of measured and simulated are listed in Table 1.
Fig.6 The factual grain structure and simulation result around node 1857 Fig.7 The factual grain structure and simulation results around node 23950

The inhibition of grain boundary migration caused by the dispersed particles is of great practice importance in controlling the grain size of material.
Yu[10] applied the CA method to simulate the processes of normal grain growth and abnormal grain growth in steel.
The models mentioned above successfully describe the dynamic behavior of grain growth and the distribution of grain size.
Obviously, the reasons why the phenomena mentioned above take place are that under the same volume fraction of second phase particles, the smaller is the average size of second phase particles, the more is their number, and the greater is the degree of their dispersion, and the higher is the chance that they locate at the grain interfaces, edges and corners, so that grain boundary may be pinned by more second phase particles, and then the grain growth slows down.
This means that n is not a constant number and decreases with the increase of simulation time when the matrix contains second phase particles.

The number steps of one sign is determined by a misorientation of crystals and the number of pairs steps of various signs depends on the temperature according to the exponential law.
Consequently the number of the excited atomic configurations in the grain boundary arises.
Figure 12 represents the examples of such dependencies at some values of parameter κ ( )25,13,12 −−−=κ signed accordingly by numbers {2, 3, and 5}.
At low temperatures the number of such excitations is not enough and their sizes are rather small against distance between them.
With growth of temperature the number of clusters as well as the number of atoms included in them grows.

Abnormal grain growth (AGG) proceeds in case that normal grain growth is inhibited.
Then how the overall grain structure evolves during grain growth in this situation?
This means that we can put a restriction on the maximum number of positive phase-fields coexisting on a grid, with negligible affect on the grain growth dynamics, but with significant saving of the required memory space.
As can be cleary seen in Fig. 3, the grain growth is undergoing abnormally; a number of grains are abnormally growing by sweeping away the matrix grains.
In fact the crucial one determining a grain's destiny at the initial stage of grain growth is its nearest neighbor grains.