Search results

A greater step size would give rise to only very few data points for each retained austenite grain, since they had an average grain size of about 1 µm and this would risk erasing the grain when performing data clean-up procedures.
A third reason is found in the relationship that is observed between the number of neighbouring BCC grains a retained austenite grain has and the smallest misorientation from an ideal transformation product.
It is found that grains that have the lowest misorientation have an average number of neighbours between three and four, while grains with the highest misorientation have on average between two and three neighbours.
This finding, combined with the small orientation differences between the different orientation relationships, may lead to the conclusion that the local environment of the grain, i.e. the interaction of the grain with its neighbours, plays a decisive role in which orientation relationship prevails. 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 10 (a) Frequency, % Variant number Figure 3: Histogram showing the frequency of the different variants: (a) Kurdjumov-Sachs, (b) Nishiyama-Wassermann, (c) Pitsch orientation relationships.
The horizontal line shows the expected number of variants in case of no variant selection. 1 2 3 4 5 6 7 8 9 10 11 12 0 2 4 6 8 10 12 14 16 (b) Frequency, % Variant number 1 2 3 4 5 6 7 8 9 10 11 12 0 2 4 6 8 10 12 14 16 (c) Frequency, % Variant number Fig. 3 shows the distribution of the different variants for the KS, NW and Pitsch orientation relationship.

Cracks on a broken section of DWTT samples can (a) penetrate the coarse grains directly, (b) propagate in Zig-Zaga way in the fine grains, and (c) be around the boundary of original austenite grains.
In order to establish the steel processing for stable and high quality steel plates, especially to guarantee the DWTT property, a number of industrial trials were carried out for developing OHTP technology in Shagang.
A lot of continuous coarse austenite grains present on the middle of 1#sample, in comparison of small austenite grains in 2# sample.
In the case of X80 pipeline steel with acicular ferrite, the original austenite grain plays a key role for the fracture toughness because these grains are the effective grains when a fracture is taken place [5,6].
Fig.13 shows some crack propagations between coarse and fine austenite grains of 1# DWTT sample, in which (a) cracks penetrate the coarse grains directly, (b) cracks propagate in Zig-Zaga way in the fine grains, and (c) cracks are around the boundary of original austenite grains.

Moreover, with a large number of CO2 oil displacement technology used in the development of deep well and super deep well, massive costs are directed annually to alleviating and managing corrosion.
But, Sn element will weaken the adhesion of grain boundaries, reduce grain boundary energy and decrease the diffusion coefficient of grain boundaries, thereby influencing the corrosivity of steel.
A great number of dislocation produced because of volume difference occurred in quenching extremely cold condition.
Compared with A steel, B steel have less number of large-angle grain boundary to hinder crack propagation while being in the process of stress, so the elongation and impact energy of B steel decline remarkably.
Uneven Surface textures such as grain boundaries and dislocation were susceptible to corrosion, whereas large angle grain boundaries had the worst resistant corrosion in all types of grain boundaries.

Additional to what Beck could see, the 3DXRD approach allows complete 3D in-situ monitoring of the growing grains.
Figure 2: The initial, A and C, and final, B and D, 3D shape of the grain as observed by the 3DXRD microscope.
The Journal Title and Volume Number (to be inserted by the publisher) 3 shape of the grain measured was reconstructed by simply stacking the cross sections of the grain as seen on the images, i.e. stacking the diffraction spots obtained after background subtraction and normalization to the synchrotron current.
Since the grain had already migrated to the surface of the sample growth was observed in all regions except the top region.
Complete 3D maps of growing grains are obtained with a time resolution in the order of minutes. 2.

The effect of grain composition, replacement ratios and chemical activator of recycled aggregate on compressive strength of concrete small hollow block was studied.
Results and Discussions The effect of grain composition of recycled aggregate on compressive strength.
Table 3 The effect of grain composition of recycled aggregate on compressive strength of samples No.
The main reason for this trend was that on one hand, there were a large number of microcracks in the surface and interior of recycled aggregate.
In addition, there were a large number of microcracks in recycled aggregate.

The microstructure contains total 2,167 grains with the average grain size of 30 μm.
Note that the fine grains show higher stored energy, compared to the coarse grains.
When vij is greater than a random probability obtained from a random-number generator that produces numbers between 0 and 1, then the recrystallized grain grows at the expense of the deformed site j; as a consequence, the stored energy of site j is reset to zero, and the orientation of site j is changed to that of site i.
For grain growth, curvature-driven grain growth was assumed [8] as is in a conventional MC modeling.
Figure 3 MC-modeling results showing the effect on recrystallization kinetics of: (a) the number of nuclei, (b) average stored energy, (c) the spatial distribution of nuclei, and concurrent recovery under (d) random nucleation and isotropic grain boundary motion, (e) HSEN and isotropic grain boundary motion and (f) HSEN and anisotropic grain boundary motion.

Furthermore, when the strain reaches a value of 4, a significant number of ultrafine grains have formed with the fraction of the HAGBs increasing continuously with strain.
A larger number of ultrafine grains were noticed in the region of higher strain, indicating that these grains are formed by a process of fragmentation/subdivision of initial grains.
It may be noted from Fig. 3(a) that even at a strain of 0.5, ultrafine grains, though few in number, have formed at the original grain boundaries and their volume fraction increases with increasing strain.
(I). purely elongated grains; (II). elongated grains with newly generated grains; and (III). newly generated grains.
Considering the large number of defects in ultrafine grained materials, it is appropriate to consider the grain boundary diffusion as the controlling mechanism of ferrite grain size, we obtain the relationship: ( ) 2/1 tDTH gb=α (3) The constant strain rate (ε& ) deformation at high temperatures can be divided into an amount of instantaneous plastic deformation (ε) and static annealing for a given period ( tt / ; εε=& ).

The goal of relating a local fatigue life approach with different microstructures requires the consideration of the main forging process dependent influence factors and their effect on grain size, grain shape, grain contiguity and others.
Fig. 1 displays the relation between standard ASTM grain size G and microstructural energy e which corresponds in principal to the grain area.
A selected number of independent geometric particle properties are used for further processing [6].
Closed Loop Simulation Chain The fatigue life behavior of hot-forged superalloy 718 is assessed by local stress based SN-curves using parameters like endurance limit; slope and number of cycles to fatigue limit.
Finally, the estimated strain amplitude is given for variations in number of endurable load cycles and test temperature for this demo part.

Intorduction So far, a great number of research activities have been devoted to modeling and predicting surface roughness for the grinding process[1].
In order to simplify the grinding kinematic analysis, the assumptions adopted in the present work for predicting the cross-sectional surface roughness are as follows: 1) the abrasive grains are conical in shape; 2) the distribution of the grain intervals is uniform, and the grain interval can be determined as [6], where is the grit number and is the structure number of the wheel; 3) the grain protrusion height is distributed with mean value and standard deviation .
Set as the depth of cut and as the minimum radius in one row, and then the limit value of the intersection of the grain with the cross-section can be expressed as (5) The parameter can be solved from Eq. (5) as (6) The range of the engaged grains through the cross-section can be determined as (7) Along each row, number the grains engaged with the cross-section as, and then the grain in row which will leave marks on the cross-section can be determined as (8) 1.2 Prediction of surface roughness.
The grain mesh size is 180, the structure number is 8, the wheel spindle speed is 4500 rpm and the table speed is 0.06 m/s.
In practice, the grain interval is random and the grain shapes are complex basic geometries, such as ellipsoid, tetrahedron, cuboids and octahedron.

(a) Parallel arrangement of grains (shaded) and grain boundaries in the diffusion direction; (b) Series arrangement of grains (shaded) and grain boundaries in the diffusion direction; (c) Grains represented as cubes (shaded).
For other arrangements and shapes of the grains, there have been a large number of different formalisms that have been developed that attempt to describe the effective diffusivity.
Substituting the electrical conductivity with the diffusivity assumes, in effect, that the numbers of charge carriers per unit volume in each ‘phase’ are equal.
The extent of this access depends on the concentration of grain boundaries, the relative values of Dgb and Dl and the solubility limits of the solute between the grains and grain boundaries.
In other words, an average tracer atom will explore a number of grains in the diffusion time.