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Online since: January 2005
Authors: Zoltán Dudás
- crystallization:
- treatment of liquid and solid structures (considering grain size growth)
- treatment of processes of the hot crack formation
- treatment of formation of amorf - crystal structures
- recrystallization and grain growth processes
- thermomechanical processes.
The numbers of the names are equal with the number of the treatable phases in the diagram.
The first number belongs to the phase having the first name.
The following numbers are separated by spaces and belong to the phase names listed below.
The numbers of the names are equal with the number of the treatable phases in the diagram.
The first number belongs to the phase having the first name.
The following numbers are separated by spaces and belong to the phase names listed below.
Online since: January 2012
Authors: Hai Feng Zhang, Yan Chen, Jin Ping Pei
(refere to table 1)
Table 1 The evaluation index system of economic cooperation harbor city competitiveness in Beibu Gulf Rim
A layer
B layer
C layer
Unit
Economic cooperation harbor city competitiveness in Beibu Gulf Rim
B1 Comprehensive economic strength
C1 GDP
¥ one hundred million
C2 investment in fixed assets in the whole society
¥ one hundred million
C3 foreign direct investment
$ ten thousand
B2Fiscal and financial strength
C4 the residents' deposits
¥ ten thousand
C5 local financial general budget income
¥ one hundred million
C6 local financial general budgetary expenditures
¥ one hundred million
B3 Science and cultural strength
C7 the number of students learning in thehigher regular schools
person
C8 the added value of information transmission, computer service and the software industry
¥ ten thousand
C9 the number of health institutions
singleton
B4 Industry development strength
C10 proportion of the first industry in GDP
%
C11 proportion of the second industry in
GDP % C12 proportion of the third industry in GDP % B5 Consumer strength C13 Social total retail sales of consumer goods ¥ ten thousand C14 commodity house sales area Ten thousand square meters C15 Grain consumption Ten thousand tons In the source of data, each urban index data mainly comes from two aspects: most of the index data from 《Guangxi statistical yearbook》,《Guangdong statistical yearbook》 and《Hainan statistical yearbook》in 2010; Only a small part of data get through a simple calculation.
(Results is referd to table 2) (4) Table 2 The grey correlation coefficient of each index and its weight in comprehensive evaluation of economic cooperation harbor city competitiveness in Beibu Gulf Rim (2009) index Grey correlation degree weight C1 GDP 0.553 0.060 C2 investment in fixed assets in the whole society 0.581 0.063 C3 foreign direct investment 0.652 0.070 C4 the residents' deposits 0.597 0.064 C5 local financial general budget income 0.597 0.064 C6 local financial general budgetary expenditures 0.562 0.061 C7 the number of students learning in thehigher regular schools 0.579 0.063 C8 the added value of information transmission, computer service and the software industry 0.643 0.069 C9 the number of health institutions 0.671 0.072 C10 proportion of the first industry in GDP 0.734 0.079 C11 proportion of the second industry in GDP 0.641 0.069 C12 proportion of the third industry in GDP 0.565 0.061 C13 Social total retail sales of consumer goods
0.674 0.073 C14 commodity house sales area 0.556 0.060 C15 Grain consumption 0.657 0.071 Fifth, through the formula (5) the score of urban competitiveness development level is calculated and sorted. [[] Zhang Xianchun, Zeng Peng, Yang Shasha.
GDP % C12 proportion of the third industry in GDP % B5 Consumer strength C13 Social total retail sales of consumer goods ¥ ten thousand C14 commodity house sales area Ten thousand square meters C15 Grain consumption Ten thousand tons In the source of data, each urban index data mainly comes from two aspects: most of the index data from 《Guangxi statistical yearbook》,《Guangdong statistical yearbook》 and《Hainan statistical yearbook》in 2010; Only a small part of data get through a simple calculation.
(Results is referd to table 2) (4) Table 2 The grey correlation coefficient of each index and its weight in comprehensive evaluation of economic cooperation harbor city competitiveness in Beibu Gulf Rim (2009) index Grey correlation degree weight C1 GDP 0.553 0.060 C2 investment in fixed assets in the whole society 0.581 0.063 C3 foreign direct investment 0.652 0.070 C4 the residents' deposits 0.597 0.064 C5 local financial general budget income 0.597 0.064 C6 local financial general budgetary expenditures 0.562 0.061 C7 the number of students learning in thehigher regular schools 0.579 0.063 C8 the added value of information transmission, computer service and the software industry 0.643 0.069 C9 the number of health institutions 0.671 0.072 C10 proportion of the first industry in GDP 0.734 0.079 C11 proportion of the second industry in GDP 0.641 0.069 C12 proportion of the third industry in GDP 0.565 0.061 C13 Social total retail sales of consumer goods
0.674 0.073 C14 commodity house sales area 0.556 0.060 C15 Grain consumption 0.657 0.071 Fifth, through the formula (5) the score of urban competitiveness development level is calculated and sorted. [[] Zhang Xianchun, Zeng Peng, Yang Shasha.
Online since: May 2012
Authors: Yuan Cai Liu, Bing Hua Xia, Ji Wang, Da Lei
This is because fly ash is spherical beads grain, it has outstanding liquidity when mixing.
The models include Linear, Quadratic, Compound, Growth, Logarithmic, Cubic, S, Exponential, Logistic and so on, results following: Table3:Variable Processing Summary Variables Dependent Independent Decreasing Water Rate Polymer Cement Ratio Number of Positive Values 12 12 Number of Zeros 1a 1b,c Number of Negative Values 0 0 Number of Missing Values User-Missing 0 0 System-Missing 0 0 a.
This may be due to the package function of polymer emulsion grain and the water molecules’ isolation effect.
The models include Linear, Quadratic, Compound, Growth, Logarithmic, Cubic, S, Exponential, Logistic and so on, results following: Table3:Variable Processing Summary Variables Dependent Independent Decreasing Water Rate Polymer Cement Ratio Number of Positive Values 12 12 Number of Zeros 1a 1b,c Number of Negative Values 0 0 Number of Missing Values User-Missing 0 0 System-Missing 0 0 a.
This may be due to the package function of polymer emulsion grain and the water molecules’ isolation effect.
Online since: January 2026
Authors: Gen Sasaki, Kenjiro Sugio, Yuuki Shinohara, Yoshikazu Hayashi
(2)
where q0 is the total change in relative density, n is a coefficient relating to the sintering mechanism; viscous flow (n=1), lattice diffusion (n=1/2) or grain boundary diffusion (n=1/3). q0, A/G and Ea were used as the feature values for machine learning. n was fixed to 0.43 considering that lattice diffusion and grain boundary diffusion are dominant.
Kind of samples Volume fraction of reinforcement Number of samples Pure-Al - 33 Al-SiC 0.1, 0.2 11 Al-C 0.05 1 Al-TiB2 0.05, 0.15 2 Al-Al2O3 0.01, 0.1, 0.2, 0.3 28 Total 75 Table 2 shows the list of features.
This may be due to the small number of data.
On the other hand, XGBoost has good prediction accuracy at low relative densities despite the small number of data.
Acknowledgements This work was supported by JSPS KAKENHI Grant Number JP22K04727 and Light Metal Educational Foundation in Japan.
Kind of samples Volume fraction of reinforcement Number of samples Pure-Al - 33 Al-SiC 0.1, 0.2 11 Al-C 0.05 1 Al-TiB2 0.05, 0.15 2 Al-Al2O3 0.01, 0.1, 0.2, 0.3 28 Total 75 Table 2 shows the list of features.
This may be due to the small number of data.
On the other hand, XGBoost has good prediction accuracy at low relative densities despite the small number of data.
Acknowledgements This work was supported by JSPS KAKENHI Grant Number JP22K04727 and Light Metal Educational Foundation in Japan.
Online since: September 2013
Authors: He Ping Jia
At the same time, according to the general characteristics of fingerprints, fingerprint image can be easily divided into bow line, vessel form grain, spiral grain and so on.
What’s more, b is the width of each segment and k is the number of pieces of each segment.
In addition, , B is the section number of center area which is used as feature extraction.
Every characteristic can be measured as a number within 256 which needs 1 bytes of storage space, so there is 640 bytes of storage space for feature vector.
We compare the fingerprint characteristics in field collection with the Biological characteristics in template database to contact with a unique personal identification number.
What’s more, b is the width of each segment and k is the number of pieces of each segment.
In addition, , B is the section number of center area which is used as feature extraction.
Every characteristic can be measured as a number within 256 which needs 1 bytes of storage space, so there is 640 bytes of storage space for feature vector.
We compare the fingerprint characteristics in field collection with the Biological characteristics in template database to contact with a unique personal identification number.
Online since: June 2014
Authors: Yan Bing Cai, Xue Ni Liu
There are five items involving fifteen questions: ①structure of supply chain, involving three questions: whether retailers and suppliers are one of the departments of the same parent company or not; the total number of suppliers who corporate with retailers. ②out of stock effect, a total of three questions: grain inventory problem; meat and dairy stock inventory problems. ③the market structure, a total of three questions: retailer order of competitive consciousness and price consciousness in the four main competitors; the distance from the main competitors. ④retailer awareness, three questions: retailer whether to share information with suppliers or not; the trust level of retailers to suppliers and the publicity degree of food safety information. ⑤basic characteristics of food supermarkets, two questions: sales area and operation time of food supermarkets.
Table 2 The list of explanatory variables in the model of information sharing Variables Value Definition X1 A part of distribution company 0~1 A part of distribute=1;others=0 X2 Independent department 0~1 Independent department=1;others=0 X3 The total number of suppliers 1~6 10~100=1;100~200=2;200~300=3; 300~400=4;400~500=5;above 500 =6 X4 Average stock effect 0~1 Have problem=1;no problem=0 X5 Grain inventory problem 0~1 Have problem =1;no problem =0 X6 Meat inventory problem 0~1 Have problem =1;no problem =0 X7 Dairy product inventory problem 0~1 Have problem =1;no problem =0 X8 Order of competition awareness 1~4 Fourth=1;third=2;second=3;first=4 X9 Order of price consciousness 1~4 Fourth=1;third=2;second=3;first=4 X10 Distance from main competitor 1~5 Farthest=1;farther=2;average=3;nearer=4;nearest=5 X11 Information sharing awareness 1~4 Unwillingness=1;less willing=2 more willing=3;very willing =4 X12 The level of trust 1~5 Lowest=1;lower=2;average=3; higher=4;highest=5 X13
Same with the EDI technology, the total number of suppliers influences on the use of POS technology positively and significantly.
The results of model regression show that the significant influence coefficient of retailers willing on use of POS is positive, and the number of sales promotion also influences on the use of POS technology significantly and positively.
Table 2 The list of explanatory variables in the model of information sharing Variables Value Definition X1 A part of distribution company 0~1 A part of distribute=1;others=0 X2 Independent department 0~1 Independent department=1;others=0 X3 The total number of suppliers 1~6 10~100=1;100~200=2;200~300=3; 300~400=4;400~500=5;above 500 =6 X4 Average stock effect 0~1 Have problem=1;no problem=0 X5 Grain inventory problem 0~1 Have problem =1;no problem =0 X6 Meat inventory problem 0~1 Have problem =1;no problem =0 X7 Dairy product inventory problem 0~1 Have problem =1;no problem =0 X8 Order of competition awareness 1~4 Fourth=1;third=2;second=3;first=4 X9 Order of price consciousness 1~4 Fourth=1;third=2;second=3;first=4 X10 Distance from main competitor 1~5 Farthest=1;farther=2;average=3;nearer=4;nearest=5 X11 Information sharing awareness 1~4 Unwillingness=1;less willing=2 more willing=3;very willing =4 X12 The level of trust 1~5 Lowest=1;lower=2;average=3; higher=4;highest=5 X13
Same with the EDI technology, the total number of suppliers influences on the use of POS technology positively and significantly.
The results of model regression show that the significant influence coefficient of retailers willing on use of POS is positive, and the number of sales promotion also influences on the use of POS technology significantly and positively.
Online since: May 2005
Authors: Frank Vollertsen, Claus Thomy
It was sufficiently demonstrated by the help of an alternating magnetic field coaxial with the
arc axis, that, among other effects, the degree of dilution can be increased and a refined grain
structure is achieved.
It was established that fields with flux densities < 70 mT and frequencies < 20 Hz generated by coaxial coils have several beneficial effects, among which there are a significant grain refinement, an improved weld metal dilution and the suppression of pore formation.
The Hartmann number Ha as a dimensionless number is defined as the relationship between electromagnetic forces and frictional forces in the melt flow.
[11] Pearce, B.P.; Kerr, H.W.: Grain refinement in magnetically stirred GTA welds of aluminium alloys.
[12] Mousavi, M.G.; Hermans, M.J.M.; Richardson, I.M. u.a.: Grain refinement due to grain detachment in electromagnetically stirred AA7020 welds.
It was established that fields with flux densities < 70 mT and frequencies < 20 Hz generated by coaxial coils have several beneficial effects, among which there are a significant grain refinement, an improved weld metal dilution and the suppression of pore formation.
The Hartmann number Ha as a dimensionless number is defined as the relationship between electromagnetic forces and frictional forces in the melt flow.
[11] Pearce, B.P.; Kerr, H.W.: Grain refinement in magnetically stirred GTA welds of aluminium alloys.
[12] Mousavi, M.G.; Hermans, M.J.M.; Richardson, I.M. u.a.: Grain refinement due to grain detachment in electromagnetically stirred AA7020 welds.
Online since: June 2021
Authors: Sheng Zhong Kou, Rui Xian Ding, Ye Jiang, Jian Jun Fan
However, there are many choroid striations on the smooth and flat fracture surface, and the choroid grain as a whole is large and well developed (Fig. 3f).
Due to ΔSm and the internal state of the micro components of alloy system are proportional to the number.
There is no obvious grain lining, grain orientation, obvious second phase or related crystal defects in the internal structure of the sample (Fig. 6b).
There are a small number of choroid veins without obvious shear bands.
And there are many choroid striations on the smooth and flat fracture surface, and the choroid grain as a whole is large and well developed (Fig. 3f).
Due to ΔSm and the internal state of the micro components of alloy system are proportional to the number.
There is no obvious grain lining, grain orientation, obvious second phase or related crystal defects in the internal structure of the sample (Fig. 6b).
There are a small number of choroid veins without obvious shear bands.
And there are many choroid striations on the smooth and flat fracture surface, and the choroid grain as a whole is large and well developed (Fig. 3f).
Online since: January 2014
Authors: Fang Yu, Lie Ping Ye, Zhi Jun Dong
The relation curvature of fatigue strength and fatigue life (S-N) is represented by power function with log-log lineal relation:
(2)
Given that the S-N curvature describes the long life fatigue and is not suitable for situations below N<103, so generally assume that life N=103 and we have
(3)
As for metal materials, generally the cycle number corresponding to the fatigue limit is N=107.
The S-N curve for different steels of different strength drawn with fatigue limit Se (stress amplitude S6 during 1*106 cycles) and limit tensile strength (Su) is shown in figure 1: Figure 1 General S-N curve for forged steel Since the fatigue limit is the index of micro plastic deformation resistance of grains on metal surface whose physical property is different from tensile strength.
Analysis of fatigue life of cables In polycrystalline metal, due to the difference of grain orientation and micro structure, even the stress or strain is lower than macro elastic limit, it will still cause plastic deformation in a few grains.
When the stress or strain exerted on the specimen is lower or equal to this critical value, all the grains in the metal will have no plastic deformation.
When the stress range on the specimen is or the strain range is, all the grains in the metal will have no local cyclic plastic deformation and no fatigue damage will be produced in the metal and the fatigue life of the specimen tends to infinity.
The S-N curve for different steels of different strength drawn with fatigue limit Se (stress amplitude S6 during 1*106 cycles) and limit tensile strength (Su) is shown in figure 1: Figure 1 General S-N curve for forged steel Since the fatigue limit is the index of micro plastic deformation resistance of grains on metal surface whose physical property is different from tensile strength.
Analysis of fatigue life of cables In polycrystalline metal, due to the difference of grain orientation and micro structure, even the stress or strain is lower than macro elastic limit, it will still cause plastic deformation in a few grains.
When the stress or strain exerted on the specimen is lower or equal to this critical value, all the grains in the metal will have no plastic deformation.
When the stress range on the specimen is or the strain range is, all the grains in the metal will have no local cyclic plastic deformation and no fatigue damage will be produced in the metal and the fatigue life of the specimen tends to infinity.
Online since: August 2015
Authors: S. Venkatesan, G.P. Rajamani, V. Balasubramanian, G. Padmanaban
The S-N curve in the high cycle fatigue region is represented by the Basquin equation [6]
Sn N = A (1)
Where ‘S’ is the stress amplitude, ‘N’ is the number of cycles to failure and ‘n’ and ‘A’ are empirical constants.
From the micrographs, it is evident that stir zone grains are finer than the base metal due to FSW process.
But the shape and size of the dimples are different in all the joints and it is controlled by grain size and precipitates distribution.
Though the stir zone of friction stir welded joint consists of very fine grains, tensile properties are deteriorated.
Though FSW produces very fine grains in stir zone, the tensile properties are reduced due to dissolution of precipitates.
From the micrographs, it is evident that stir zone grains are finer than the base metal due to FSW process.
But the shape and size of the dimples are different in all the joints and it is controlled by grain size and precipitates distribution.
Though the stir zone of friction stir welded joint consists of very fine grains, tensile properties are deteriorated.
Though FSW produces very fine grains in stir zone, the tensile properties are reduced due to dissolution of precipitates.