Search results

Low cycle fatigue strength of the maraging steel depends on grain size in number of cycles up to 103.The smaller the grain size, the higher the low cycle fatigue strength was.
Quasci-cleavage fracture surfaces were predominant for material with grain size of 20µm,while intergranular fracture surfaces were predominant for materials with larger grain size in number of cycles lower than 60.
Striation was predominant for all tested materials in number of cycles higher than 60.Low cycle fatigue strength of Ti-6Al-4V alloy also depends on grain size in number of cycles up to 104.
Fracture surface was observed by scanning electronmicroscopy.At failed number of cycles lower than 60 intergranular fracture was predominant on fracture surface of the specimens with grain size of 60 and 100µm, while quasiclevage fracture surface was predominant on the fracture surface of the specimen with grain size of 20µm.At failed number of cycles higher than 60 striation was predominant for all tested specimens with grain size of 20,60 and 100µm.The wider striation spacing was observed on fracture surface of the specimen with larger grain size.
The smaller the grain size the higher the fatigue strength is at number of cycles lower than 104.

A large number of grains is therefore necessary for statistically reasonable results.
We have found that the number of boundary types not represented in the simulation becomes nonzero when the total number of grains drops below approximately 10000 and increases steadily thereafter.
It is clear from these plots that a steady state distribution of boundary planes is reached after the number of grains in the sample has decreased by more than about 25-40% (loss of approximately 10000-16000 grains) or, equivalently, after a reduction of total boundary area of more than 10-20%.
There is a clear Journal Title and Volume Number (to be inserted by the publisher) 3 Fig. 1.
Relative grain number and boundary area as a function of simulation output time. 0000 0002 0005 0010 0015 0020 Fig. 2.

Except of a short description the Gibbs method of surface excesses and grain boundary segregation isotherms with the limited number of segregation sites in grain boundary, the paper concentrates on the effects of complexes formation, including thermodynamic and computer modeling, and concentration phase transition in the grain boundaries in systems with restricted solubility and intermediate compounds.
McLean [1] proposed that the maximal part of available sites for solute atoms in the GB: X0bmax=zbNb (8) where Nb is the whole number of sites and zb is the number of available sites.
The number of free M atoms (open circle) and number of M atoms in complexes (closed circle) for: a) Epair=-0.2 eV/atom, T= 1000 K; b) Epair=-0,5 eV/atom, T=1200K.
Rodin, Grain Boundary Diffusion and Grain Boundary Segregation in Metals and Alloys.
Rodin, A new model of grain boundary segregation with the formation of atomic complexes in grain boundary Phys.

This shows that there is only a small increase in latency time to reach the maximum number of abnormal grains as the particle fraction increases.
Also, since this effect is so small, the material will still contain a considerable fraction of abnormal grains, i.e. adding particles will not inhibit abnormal grain growth but only reduce the number of abnormal grains and delay their growth.
The time when the maximum number fraction of abnormal grains is reached as a function of the vol% of particles.
Number fraction of abnormal grains versus the vol% of particles together with the standard deviation.
Dotted line: Linear trend; dashed line: Cut-off in number fraction below 5 vol%.

The results show that simulations at zero temperature or on a small scale lattice (say, the number of sites on one edge of the square lattice L=1000) cannot reach the steady-state period of grain growth, while large-scale simulations (say, L=2000) at a much higher simulation temperature can.
The initial microstructure was generated by assigning a random number grom 1 to Q to each site in the lattice.
The grain radius R is usually defined as the radius of the equal-area circle of a grain, the grain area A is the number of sites in a grain.
Lattice size L is the number of sites on one edge of the square lattice, set as 400, 1000, and 2000 in this work for evaluating its effect on simulation results.
The effect of lattice size on simulation results comes from that a too small grain number in the steady state period may lead to unreliable statistical analysis.

Beware of Grain Refinement Boris V.
However, introduction of grain refining additives results in a number of negative effects.
The use of grain refiners has a number of issues.
This effect was found during extrusion of heat-treatable alloys, such as 6061, 2014, 2017 and a number of others.
Solidification with a large number of intermetallic particles may result in the growth of stresses in a solidified ingot and a high probability of cold crack formation. 3.

As proposed by Cahn and Taylor in their model describing the grain boundary migration, grain translation and grain rotation [12,30], a rotation of grains caused by boundary migration-shear coupling is characterized by the constant number of dislocations which accommodate the grain misorientation.
As seen in Fig. 4, this rule of invariant dislocation number was not ideally held in the simulations.
For the shrinking embedded grain the solely possible reaction between dislocations, which can results in a reduction of their number, is the annihilation of dislocations with antiparallel Burgers vectors located on opposite sides of the cylindrical grain [29].
Figure 7 shows the typical chain of dislocation reactions resulting in a reduction of the dislocation number in the boundary, as found in the simulations.
As seen in Fig. 6, the number of dislocations after annealing for 0.42 ns decreased to 11 from 15 ones observed after annealing for 0.11 ns.

However, strengthening at large number of passes is due to the grain refinement alone.
Refinement in grain size takes place by subjecting the billet to a repeated number of passes.
The microstructure after large number of passes has a lower dislocation density in the interior of grains/subgrains in comparison to the microstructure obtained in the initial passes [6].
Vickers hardness number is lowest for Al99.9, followed by Al99.5.
However, such a difference ceases to exist with increasing number of passes when grain size reaches ultra fine level.

The way in which the curvature is distributed along the perimeter of a grain only gives rise only to second order corrections to the rate of change of area as a function of grain topology (number of sides).
For grain growth V m K A K b b b γ= ≡ (2) where mb is grain boundary mobility, bγ is the grain boundary surface tension, Κ is the local curvature of the grain boundary: /K d dlϕ= , where ϕ is the tangential angle at any given point of the grain boundary.
Consequently ( ) 2 6 33 dS An b A n bdt ππ  = − π− = −     (4) where n is the number of triple junctions for each respective grain, i.e. the topological class of the grain.
The result expressed in Eq. (4) does not depend on the shape of moving boundaries: the rate of grain area change along with the sign of the right-hand side of Eq. (4) is determined only by the number of adjacent (neighbouring) grains, or, what is same, by the topological class of the Journal Title and Volume Number (to be inserted by the publisher) 3 grain - the number of triple junctions of the grain.
Although an nsided convex grain is considered it is easy to see that the same result would be obtained for a grain Journal Title and Volume Number (to be inserted by the publisher) 5 with concave boundaries.

The results show that the fertilizer consumption, large cattle head number, end grain sowing area, effective irrigation area and rural per capita living space are the main effect factor on grain yield.
The number of input nodes of the network is determined.
The second is to select m (mnumber of samples and p is the number of variables.
The number of nodes in the input layer is the number of influence factor of grain yield.
Through principal component analysis, the main impact factors such as chemical fertilizer, large cattle head number, end grain sowing area, effective irrigation area, grain production and rural per capita residential area  have significant relationship with the grain yield of  Jilin province, therefore it may be concluded that input layer has 5 nodes.