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Online since: February 2022
Authors: Hong Zhou, Cheng Peng
Page Numbers.
not number your paper: Tables.
The equations have to be numbered sequentially, and the number put in parentheses at the right-hand edge of the text.
Punctuation appears after the equation but before the equation number, e.g.
The broadening widths of the peaks in the as-sprayed titanium coating’s pattern suggests that a microstructure with finer grains in the shrouded plasma-sprayed titanium coating was obtained.
not number your paper: Tables.
The equations have to be numbered sequentially, and the number put in parentheses at the right-hand edge of the text.
Punctuation appears after the equation but before the equation number, e.g.
The broadening widths of the peaks in the as-sprayed titanium coating’s pattern suggests that a microstructure with finer grains in the shrouded plasma-sprayed titanium coating was obtained.
Online since: March 2007
Authors: Kazutoshi Kunishige, Masaharu Hatano
In order to simulate a
conventional slab heating rate, a number of tensile specimens were heated slowly, taking 2h from
1050ºC to 1250ºC and oxidized in air at 1250ºC for 30 min.
For 1100ºC specimens, the number of surface cracks increased with holding time from 5 min to 30 min.
On the other hand, for 1150ºC and 1200ºC specimens, the number of surface cracks decreased with keeping time.
Fe-Cu diagram indicates that the solubility of Cu in austenite is less at 1100ºC (7.5%Cu) than at 1250ºC (10.5%Cu) [7] and a liquid film of Cu (Sn) could be precipitated at prior austenite grain boundaries in this layer and grow on cooling by diffusion of Cu (Sn) atoms into the gain boundaries.
Therefore, Cu atoms in the liquid films at 1200ºC could far more easily diffuse back into steel, decreasing the number of surface cracks with the holding time at 1200ºC.
For 1100ºC specimens, the number of surface cracks increased with holding time from 5 min to 30 min.
On the other hand, for 1150ºC and 1200ºC specimens, the number of surface cracks decreased with keeping time.
Fe-Cu diagram indicates that the solubility of Cu in austenite is less at 1100ºC (7.5%Cu) than at 1250ºC (10.5%Cu) [7] and a liquid film of Cu (Sn) could be precipitated at prior austenite grain boundaries in this layer and grow on cooling by diffusion of Cu (Sn) atoms into the gain boundaries.
Therefore, Cu atoms in the liquid films at 1200ºC could far more easily diffuse back into steel, decreasing the number of surface cracks with the holding time at 1200ºC.
Online since: March 2008
Authors: Mamtimin Gheni, Zhi Chun Yang, A Fang Jin
The airflow field is a two-phase flow of air and sand, it can be
described using the Navier-Stokes equation as follows [16,17]:
( ) ()
()
() () () g
vupuu
t u
u
t
g
g
g
g
g
v
vv
vv
v
v
ερτε
βε
ερ
ερ
ερ
ερ
+•∇−−−∇−=•∇+
∂
∂
=•∇+
∂
∂
0
(6)
where gρ is airflow density, p is pressure, u is the velocity of air phase; v is the velocity of sand
particle; τis strain tensor of air phase, β is momentum commutation coefficient between phase, g
is the gravitational acceleration, ε is volume fraction of the sand particle,
0 szpε= (7)
Fig.1 the district distributing of sandflow field
Layer of airflow near land
Earth's surface layer
Shield layer where z0 is the close-grained degree of bed , the Ps is the probability of jump-start can can be
expressed as
D
u
p
g
s
2
*ρ
∝ , then, Eq.(7) can be rewritten as
D
u
Gz
g
2
*
0
ρ
ε •
For sand particle i, its influence area is to be obtained at first, then to get the total number of particle in this influence area, and suppose that sand particle i only impact with particles in this influence area.
Let R is a random number, based on the inequality: 1 11 KK R NN − << − − , we can get the ordinal number k of the sand particle that maybe impact with sand particle i in the influence area.
The physical model Sand particle Airflow Calculational parameter diameter: D=1mm density: ρs=2650kg/m -3 instauration coefficient: e=0.80 friction constant: µ=0.12 number: 4000 density: ρg=1.29kg/m-3 kinetic viscosity: µg=1.8·105Ns/m2 beginning velocity of wind: 1.0m/s,3.0m/s smooth length: 1mm time step: ∆ t=10-6s Fig.2 The model of calculation area Boundary Conditions. (1) Fixed boundary: at the fixed boundary of calculating area, one group of virtual particles are used for a strong push force to the particle near the boundary, thus these particles near boundary are protected from penetrating through the boundary.
Besides, the velocity of wind has a great impact on the sand cover phenomenon, and the higher the former, the more serious the latter. 0 500 1000 1500 2000 2500 3000 3500 4000 4500 t =0s t =5. 5s t =11s t =22s time number of sand par t i cl e 0- 2m 2- 3m 3- 7m 7- 8m 8- 9m (a) Beginning velocity of wind is 1.0m/s (b) 0 500 1000 1500 2000 2500 3000 3500 4000 4500 t =0s t =5. 5s t =11s t =22s time number of sand par t i cl e 0- 2m 2- 3m 3- 7m 7- 8m 8- 9m (c) Beginning velocity of wind is 3.0m/s Fig.4 The result of numerical imitates There are also many factors that can cause the highway sand cover disaster, the influence of wind blow has been considered in the research.
For sand particle i, its influence area is to be obtained at first, then to get the total number of particle in this influence area, and suppose that sand particle i only impact with particles in this influence area.
Let R is a random number, based on the inequality: 1 11 KK R NN − << − − , we can get the ordinal number k of the sand particle that maybe impact with sand particle i in the influence area.
The physical model Sand particle Airflow Calculational parameter diameter: D=1mm density: ρs=2650kg/m -3 instauration coefficient: e=0.80 friction constant: µ=0.12 number: 4000 density: ρg=1.29kg/m-3 kinetic viscosity: µg=1.8·105Ns/m2 beginning velocity of wind: 1.0m/s,3.0m/s smooth length: 1mm time step: ∆ t=10-6s Fig.2 The model of calculation area Boundary Conditions. (1) Fixed boundary: at the fixed boundary of calculating area, one group of virtual particles are used for a strong push force to the particle near the boundary, thus these particles near boundary are protected from penetrating through the boundary.
Besides, the velocity of wind has a great impact on the sand cover phenomenon, and the higher the former, the more serious the latter. 0 500 1000 1500 2000 2500 3000 3500 4000 4500 t =0s t =5. 5s t =11s t =22s time number of sand par t i cl e 0- 2m 2- 3m 3- 7m 7- 8m 8- 9m (a) Beginning velocity of wind is 1.0m/s (b) 0 500 1000 1500 2000 2500 3000 3500 4000 4500 t =0s t =5. 5s t =11s t =22s time number of sand par t i cl e 0- 2m 2- 3m 3- 7m 7- 8m 8- 9m (c) Beginning velocity of wind is 3.0m/s Fig.4 The result of numerical imitates There are also many factors that can cause the highway sand cover disaster, the influence of wind blow has been considered in the research.
Online since: June 2017
Authors: Azwan Iskandar Azmi, Chang Chuan Lee, M.M.W. Irina
A 2k factorial designs have been utilized in the experiment to study the joint effect of parameter factors on output, where k represent the number of factors.
A total number of 20 experimental runs (sixteen factorial points - 24 and four center points) have been listed and carried out using Design Expert software (Version 8.0.6).
This is due to the fact that an increase in the number of abrasive tends to increase the number of impacts per unit area.
A large number of abrasive particles tends to increase the momentum of collision to penetrate targeted workpiece area.
The coarse-grained abrasive particles trim and worn away uncut fiber neatly [8].
A total number of 20 experimental runs (sixteen factorial points - 24 and four center points) have been listed and carried out using Design Expert software (Version 8.0.6).
This is due to the fact that an increase in the number of abrasive tends to increase the number of impacts per unit area.
A large number of abrasive particles tends to increase the momentum of collision to penetrate targeted workpiece area.
The coarse-grained abrasive particles trim and worn away uncut fiber neatly [8].
Online since: April 2008
Authors: Igor Mazur
The Lipetsk State Technical University (LSTU) jointly with the NLMK Information Technologies
Department has developed a number of PC applications which have been successfully introduced at
2000 Wide Strip Continuous Mill [1].
Transformation of the Grain Structure of Austenite within the Cycle "deformation - Initial recrystallization " //Physics of Metals and Physical Metallurgy. -1996.
Transformation of the Grain Structure of Austenite within the Cycle "deformation - Initial recrystallization " //Physics of Metals and Physical Metallurgy. -1996.
Online since: June 2013
Authors: Razvan Păcurar, Petru Berce
It is well known the Selective Laser Melting basic principle of manufacturing metallic parts that uses a laser source directed through an optical system onto a base plate, in order to melt the powder and weld the metallic grains together according to the cross section of the 3D model, process that it is repeated layer by layer, until the part is finished [2, 3].
The minimum value of the porosity as calculated was 1,27 [%], in the case of sample number 12.
The maximum value of density was obtained (as calculated) in the case of sample number 12 (ρ=7.90 [g/cm3]), compared with a minimum value that has been obtained in the case of sample number 3 (ρ=7.20 [g/cm3].
Two cases were analyzed within the numerical simulation, one case being considered as for the sample having a density of 7,20 [g/cm3]) (sample 3, manufactured with a Hatch Solid and Fill Contour Lens Position of -50 [µm]), and a second one, the case of sample number 12, that was manufactured with a Hatch Solid and Fill Contour Lens Position of 40 [µm], having as experimentally determined, the maximum density value of 7,90 [g/cm3].
From the set of 15 samples that were manufactured, by using the SLM machine, the sample number 12 has corresponded by the mechanical resistance point of view, so the lens position has finally been adjusted with a value of +40 [µm], as compared to the starting position (the initial position that has been considered as reference at starting point of the experiment).
The minimum value of the porosity as calculated was 1,27 [%], in the case of sample number 12.
The maximum value of density was obtained (as calculated) in the case of sample number 12 (ρ=7.90 [g/cm3]), compared with a minimum value that has been obtained in the case of sample number 3 (ρ=7.20 [g/cm3].
Two cases were analyzed within the numerical simulation, one case being considered as for the sample having a density of 7,20 [g/cm3]) (sample 3, manufactured with a Hatch Solid and Fill Contour Lens Position of -50 [µm]), and a second one, the case of sample number 12, that was manufactured with a Hatch Solid and Fill Contour Lens Position of 40 [µm], having as experimentally determined, the maximum density value of 7,90 [g/cm3].
From the set of 15 samples that were manufactured, by using the SLM machine, the sample number 12 has corresponded by the mechanical resistance point of view, so the lens position has finally been adjusted with a value of +40 [µm], as compared to the starting position (the initial position that has been considered as reference at starting point of the experiment).
Online since: December 2014
Authors: Hong Fang Ma, Ming Zhu, Qing Zhu, Yan Li
The mass of the samples were measured by using an electric balance with the sensitivity of 10-5g.Then the samples were numbered, recorded and set aside.
Besides, there are a large number of molten salt crystals stick on the sample surface.
Layer surface have a small number of holes, in a,b,c and d part of layer on the samples surface have fallen off, but it was not very serious.
The samples of a and b have corrosion holes and easily peeling off, Corrosion products layer were more serious and relatively loose .Compared with a and b samples, c, d, e and f were taken place corrosion along the grain boundary ,but the corrosion products were denser.
But with respect to the relationship between the different mixing molten salt alkalinity, mixed molten salt melting point and the mass ratio have no certain rules, since this experiment involved a relatively small number of binary molten salt ratio group.
Besides, there are a large number of molten salt crystals stick on the sample surface.
Layer surface have a small number of holes, in a,b,c and d part of layer on the samples surface have fallen off, but it was not very serious.
The samples of a and b have corrosion holes and easily peeling off, Corrosion products layer were more serious and relatively loose .Compared with a and b samples, c, d, e and f were taken place corrosion along the grain boundary ,but the corrosion products were denser.
But with respect to the relationship between the different mixing molten salt alkalinity, mixed molten salt melting point and the mass ratio have no certain rules, since this experiment involved a relatively small number of binary molten salt ratio group.
Online since: December 2013
Authors: Mônica C. Andrade, Gloria D. Soares, Marcia Sader, Gustavo M. Platt, Ivan N. Bastos, Denisar Ismério
Reynolds number is a ratio of inertial and viscous forces and is used to classify a flow regime
as laminar or turbulent.
The morphological evaluation of the sintered β-TCP and β-TCMP grains was carried out by scanning electron microscopy SEM (JEOL, JSM6460LV).
The Reynolds number correspondent to disk of 13 mm varies from 700 to 25321, respectively to 100 and 3600 rpm (10.47 and 377.0 rad.s−1).
The first number represents the average and the second one indicates the standard deviation.
This observation is confirmed by the lower number of pores found when compared with β-TCP disks.
The morphological evaluation of the sintered β-TCP and β-TCMP grains was carried out by scanning electron microscopy SEM (JEOL, JSM6460LV).
The Reynolds number correspondent to disk of 13 mm varies from 700 to 25321, respectively to 100 and 3600 rpm (10.47 and 377.0 rad.s−1).
The first number represents the average and the second one indicates the standard deviation.
This observation is confirmed by the lower number of pores found when compared with β-TCP disks.
Online since: November 2007
Authors: David H. StJohn
The best indicator of the increased interest in magnesium is provided by the number of
papers submitted to International Conferences which has increased each year for all magnesium
conferences.
CANMET is a key collaborator in a number of the USAMP projects.
Associated with AM-SC1 is AM-cast [9], a zirconium grain refiner suitable for magnesium sand cast alloys such as AM-SC1.
To ensure that significant growth occurs and that there is sustained use of magnesium as the lightweight material of choice, there are a number of advances that need to be made.
If alloy design can deliver significantly improved corrosion resistance then the number of applications for magnesium alloys will also significantly increase.
CANMET is a key collaborator in a number of the USAMP projects.
Associated with AM-SC1 is AM-cast [9], a zirconium grain refiner suitable for magnesium sand cast alloys such as AM-SC1.
To ensure that significant growth occurs and that there is sustained use of magnesium as the lightweight material of choice, there are a number of advances that need to be made.
If alloy design can deliver significantly improved corrosion resistance then the number of applications for magnesium alloys will also significantly increase.
Online since: June 2012
Authors: Zhi Wei Han, Ke Feng, Jian Feng Cao, Yi Wen Kong, Shui Gen Wang
Introduction
During continuous casting process of slab, molten steel experiences the multiple cooling zones to solidify into slabs continuously, with various macroscopic transport phenomena (heat transfer, mass transport, momentum transfer), solidification (solute segregation, nucleation, component undercooling, evolution of equiaxed grain and columnar crystal), forced deformation (ferrostatic pressure, withdrawal resistance, bulging deformation and stress, straightening force, bending force, thermal stress) and phase transition(peritectic transformation, eutectic transformation)[1].
Most of the existing prediction systems[4-6] are based on pure expert system, neural network or database query and so on, which process according to a large number of collected samples.
Where Nact is slab number for each grade of actual quality, Npre is slab number for each grade when the model predictions agree with actual.
The qualities of collected 2162 slabs Grades of slab quality Nact Npre Nonoccurrence, Lower than 1.0 1732 1491 Possible, Between 1.0 and 1.2 207 176 Slight, Between 1.2 and 1.5 114 99 General, Between 1.5 and 2.0 67 58 Serious, Higher than 2.0 42 36 Total slab number 2162 1860 Prediction accuracy 86.03% The slab numbers for each grade of actual quality are 1732, 207, 114, 67 and 42 respectively.
The slab numbers for each grade when the model predictions agree with actual are 1491, 176, 99, 58 and 36 respectively.
Most of the existing prediction systems[4-6] are based on pure expert system, neural network or database query and so on, which process according to a large number of collected samples.
Where Nact is slab number for each grade of actual quality, Npre is slab number for each grade when the model predictions agree with actual.
The qualities of collected 2162 slabs Grades of slab quality Nact Npre Nonoccurrence, Lower than 1.0 1732 1491 Possible, Between 1.0 and 1.2 207 176 Slight, Between 1.2 and 1.5 114 99 General, Between 1.5 and 2.0 67 58 Serious, Higher than 2.0 42 36 Total slab number 2162 1860 Prediction accuracy 86.03% The slab numbers for each grade of actual quality are 1732, 207, 114, 67 and 42 respectively.
The slab numbers for each grade when the model predictions agree with actual are 1491, 176, 99, 58 and 36 respectively.