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The precipitates are found to homogeneously distribute in grains (Fig.4a) and nucleate at dislocations (Fig.4b).
It reveals that ageing behavior of the precipitation of g1 in Ti-48Al-10Nb alloy has the feature of non-precipitated area near both sides of grain boundaries and precipitated area inner grains.
The precipitates are found to homogeneously distribute in grains (a) and nucleate at dislocations(b).
Acknowledgement This work was financially supported by the project sponsored by (1) National Natural Science Foundation of China under the grant numbers 50971047 and 50571101, (2) The Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry and（3）the Initial Research Fund for Doctoral scholars Sponsored by Guangxi University, China under grant numbers DD010010 References

The observation of microstructure revealed randomly oriented equiaxed grains of austenite having an average grain size of 40 μm.
Results and Discussion The fatigue hardening/softening curves plotted as a dependence of equivalent stress amplitude on the number of cycles are shown in Fig. 3a-c.
Fatigue life curves plotted as a dependence of equivalent stress amplitude at half-life versus number of cycles to fracture are shown for all loading modes in Fig. 3d.
In torsion predominantly one slip system is activated in each grain.
Contrary to the pure axial or pure torsional loading where predominantly one slip system is activated in a grain, biaxial loading resulted in activation of several slip systems.

In this case, the phase and structural states of the films are characterized by the presence of the ferromagnetic α-Fe-based nanocrystalline phase with a grain size of ~ 10nm and nano-sized particles of a thermodynamically stable nonmagnetic MeX phase (either carbide, or nitride, etc.)
An important result of this model is the analytical correlation between of coercive force and the basic magnetic constants and nanostructure parameters: Hc ~ L ~ K4D 6/(MA 3), where K=HaM/2 is the effective local magnetic anisotropy energy; A is the exchange interaction constant; D = 2Rc is the grain size (Rc is the random magnetic anisotropy correlation radius); M is the saturation magnetization, Ha is the local magnetic anisotropy field.
So the coercive force can not be controlled unambiguously and only by the grain size.
In the fields being less than HR, the magnetization deviation from the saturation for the nanocrystalline alloy is written as: ( ) ( ) 1/ 2 4 3 ( ) / / S S a L M M H M a H Hε − = , (2) where /aL aH H � 〈 〉 = is the averaged effective magnetic anisotropy field (� is the number of nanograins in a stochastic domain); the constant ε is determined by the ratio of the exchange energy of the stochastic domain to its anisotropy energy and defines the nanostructural ferromagnet by the inequality ( ) 1/2 1/ 2 / cR A Kε − < ⋅ [9].
It is spontaneously formed by a large number of nanograins, since their macroscopic magnetic characteristics are due to the size and anisotropy of these domains [8, 9].

Increasing the Pr content, a better insulation between the hard magnetic grains of the matrix phase is achieved due to a larger amount of the intergranular Pr-rich phase and, consequently, higher values of µ0iHc are expected.
Smaller mean grain sizes (MGS) have been obtained with PBM for all compositions prepared, as also listed in Table 2.
In the boundary grains of the etched samples, the secondary phase is Pr1+ε(Fe, Co)4B4.
Table 2 - Mean grain size, standard deviation and composition of the Pr2(Fe, Co)14B phase.
Périgo, contract number 2005/04711-2).

Shields condition for incipient motion shows that the shear stress on coarse sediment only depends on the particle size and bulk density, and does not depend on the grain Reynolds number.
The relationship between the model block resistance coefficient and grain Reynolds number () [3] indicates that resistance coefficient is approximately a constant value when Reynolds number is large.
For the model block of height 1cm, the grain Reynolds number is greater than 1000 if the bottom velocity is greater than 10cm/s.
When the prototype and model grain Reynolds number are in the range from 103 to 106, the drag coefficient is basically the same; The lift coefficient is in the same order of magnitude with , and also is approaching a constant value.

In addition, an increase in this parameter leads to a decrease in grain size during severe plastic deformations [4].
It should be noted, that the parameter above mentioned can be considered as characteristics of matrix phase materials, since it depends on the grain size.
With an increase in the number of process passes, the overall level of accumulated deformation increases significantly (Fig. 1).
At the same time, the presence of hard inclusions introduces a number of features.
In particular it promotes the milling of grain.

Compositions and mechanical properties of Ti(C,N)-based cermet die materials Cermet number WTiC [wt%] WTiN [wt%] WZrO2 [wt%] WWC [wt%] WMo [wt%] WNi [wt%] σ [MPa] Hv [GPa] KIC [MPa·m1/2] 1 44.4 19.6 0 14.4 7.0 13.0 584.83 16.23 6.49 2 40.9 18.1 5.0 14.4 7.0 13.0 579.85 12.08 7.11 3 37.4 16.6 10.0 14.4 7.0 13.0 967.09 14.24 13.62 4 34.0 15.0 15.0 14.4 7.0 13.0 691.53 12.65 13.65 5 30.5 13.5 20.0 14.4 7.0 13.0 414.57 12.66 13.78 6 27.0 12.0 25.0 14.4 7.0 13.0 411.25 11.67 13.59 The mixtures were subsequently homogenized with absolute alcohol media and PEG in a ball mill for 48h with cemented carbide ball.
It is found that a grain-refining trend happens with the increase nano-ZrO2 content.
The finer the grain, the higher the strength is.
According to the Hall-Petch formula [6], the strength of Ti(C,N)-based cermet die material is in reverse proportion with the square root of grain size.
Therefore, the reduction in grain size of the Ti(C,N)-based cermet die material will certainly result in the enhancement of the flexural strength.

Introduction Moisture content is considered as one of the most important factors to maintain grain quality during storage.
The survival and reproduction of biological agents in grain are dependent to a great extent on the temperature and moisture levels.
Many researchers have studied the movement of moisture in stored grain.
In this work, we consider that the water vapour transfer in the intergranular spaces of the grain mass is governed by molecular diffusion.
The space between nodes in the pile is equal to the diameter of popcorns particles and it was estimated the number of particles in each layer, by a relationship between the cylinder diameter and the diameter of the particles.

For the fully spectral formulation the bottom dissipation source function is based on linear theory and can be generalised into Eq. (1) below [2]: Sbot（σ，θ）= -Cf E（σ，θ） (1) where Cf is a dissipation coefficient (=fwUbm), fw is the wave friction factor, is the wave number, Ubm is the maximum near-bed particle velocity given by Eq. (2): Ubm=[]1/2 (2) The bottom friction can be specified in five different ways: 1.
Sand grain size, d50.
The default value is 0.00025 m (median sediment grain size).
The bottom friction in areas dominated by sand depends on the grain size of the sediment and the presence of bed forms.
For the case where there is no bed form, the Nikuradse roughness parameter kN can be estimated by kN=2 d50, where d50 is the median grain size.

It can be seen from figure 4, there are needle-like and column-like crystalline grains exist in the sample.
So, the use of ceramic waste could increase the number of crystalline of foam glass.
The external surface of the crystalline grain is complete, the length of which is 8-10 µm and the diameter is 2µm.
The high compressive strength of foam glass is constituted by the closely connected by the grains.[9] Figure 4.
(3) From the analysis of SEM, there are Independent holes and needle-like and column-like crystalline grains exist in foam glass, which increase the thermal insulation property and compressive strength of foam glass.