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Online since: November 2011
Authors: Man Li, Jing Yu Tong, Yu Bai, Dong Bo Tian, Bin Wang, Zhi Hao Wang
When the grain size and shape distribution are affirmed, the particles of different classes can be mixed by mixing machine.
Focused Beam Reflectance Measurement (FBRM) instrument can be highly sensitive and accurate measurement of particle size and particle number changes.
With the number / length / distribution can range from the distribution of precipitation designated to improve resolution.
Vacuum chamber subsystem could simulate vacuum, high and low temperature range environment of the moon, with the deuterium lamp in it which used to provide the UV light source; The turntable subsystem with the simulated lunar dust is used to provide carrying mechanism for lunar rover wheel; simulated lunar dust manufacture subsystem could manufacture simulated lunar dust for rover wheel terramechanics test; test subsystem could test the velocity, electricity charge, size and number of the lunar dust partial.
Focused Beam Reflectance Measurement (FBRM) instrument can be highly sensitive and accurate measurement of particle size and particle number changes.
With the number / length / distribution can range from the distribution of precipitation designated to improve resolution.
Vacuum chamber subsystem could simulate vacuum, high and low temperature range environment of the moon, with the deuterium lamp in it which used to provide the UV light source; The turntable subsystem with the simulated lunar dust is used to provide carrying mechanism for lunar rover wheel; simulated lunar dust manufacture subsystem could manufacture simulated lunar dust for rover wheel terramechanics test; test subsystem could test the velocity, electricity charge, size and number of the lunar dust partial.
Online since: May 2012
Authors: Hong Yan Jin
The Xianghai nature reserve have six of the crane, accounting for 40% of the total number of crane in world, accounting for two-thirds of the total number of crane in China .
The Xianghai wetland not only has rich natural resources, also there is a huge environment regulating function and ecological benefit, it in protecting biodiversity, maintain freshwater resources, resist flood, adjusting the climate, the degradation of pollutants and provide for human life and production resources play an important role, and is also the northeast of the Songliao plain major grain producing areas important ecological barrier.
In recent years, due to the influence of the global climate, the Xianghai wetland in serious drought, the river flow, water level drops, aquatic plants degradation are the decrease in the number of species, cause wetland atrophy, which greatly reduces the Xianghai nature reserve as an international important wetland, important birds breeding, migration and the habitat of the role.
The Xianghai wetland not only has rich natural resources, also there is a huge environment regulating function and ecological benefit, it in protecting biodiversity, maintain freshwater resources, resist flood, adjusting the climate, the degradation of pollutants and provide for human life and production resources play an important role, and is also the northeast of the Songliao plain major grain producing areas important ecological barrier.
In recent years, due to the influence of the global climate, the Xianghai wetland in serious drought, the river flow, water level drops, aquatic plants degradation are the decrease in the number of species, cause wetland atrophy, which greatly reduces the Xianghai nature reserve as an international important wetland, important birds breeding, migration and the habitat of the role.
Online since: October 2011
Authors: Xue Wen Liu, Xing Chun Huang, Han Zhong Luo
Fig.3 Statement of static case
Domain length l1=2, l2=1, Young’s modulus E=1, poisson’s ratio , number of nodes N1=3, N2=2, nodal distance h=1, initial half support size a1=a2=0.7, time step .
The case parameters are: Domain length l1=10, l2=1, Young’s modulus E=1, poisson’s ratio , number of nodes N1=11, N2=2, nodal distance h=1, initial half support size a1=a2=0.7, time step .
The case parameters are: Domain length l1=10, l2=1, Young’s modulus E=1, poisson’s ratio , number of nodes N1=21, N2=3, nodal distance h=0.5, initial half support size a1=a2=0.35, time step .
Osher, A multiple level set method for modeling grain boundary evolution of polycrystalline materials.
The case parameters are: Domain length l1=10, l2=1, Young’s modulus E=1, poisson’s ratio , number of nodes N1=11, N2=2, nodal distance h=1, initial half support size a1=a2=0.7, time step .
The case parameters are: Domain length l1=10, l2=1, Young’s modulus E=1, poisson’s ratio , number of nodes N1=21, N2=3, nodal distance h=0.5, initial half support size a1=a2=0.35, time step .
Osher, A multiple level set method for modeling grain boundary evolution of polycrystalline materials.
Online since: September 2014
Authors: Yan Hong Zhao, Hu Zhu Zhang
The number of each parallel mixture specimens was 13.
With the exception of lime and fly-ash stabilized coal gangue base, other pavement layer adopts the same material and thickness, and the surface layer adopts 5cm medium grained asphalt concrete.
Tab.8 Transverse crack observations of test road code number of crack average crack length/m average crack width /mm code number of crack average crack length/m average crack width /mm A1 6 5.89 4.95 A3 5 5.01 5.26 A2 5 4.76 4.15 A4 7 6.23 6.10 As can be seen from table 8, the results in transverse crack observations of test road are consistent with laboratory test results.
With the exception of lime and fly-ash stabilized coal gangue base, other pavement layer adopts the same material and thickness, and the surface layer adopts 5cm medium grained asphalt concrete.
Tab.8 Transverse crack observations of test road code number of crack average crack length/m average crack width /mm code number of crack average crack length/m average crack width /mm A1 6 5.89 4.95 A3 5 5.01 5.26 A2 5 4.76 4.15 A4 7 6.23 6.10 As can be seen from table 8, the results in transverse crack observations of test road are consistent with laboratory test results.
Online since: September 2013
Authors: Ting Huang, Wei Huang, Kun Song, Ming Jie Gao
Therefore, building the visualization display and analysis system, controlling the wind farm real-time running state and mining operation rules from a large number of historical data to specify the wind turbines operation strategy is of great significance.
The system stores fine-grained data of certain period, provides a part of query function and cleanses non-standard data, which gets ready for data warehouse/mart.
(iv) Unified configuration of the system security strategy Business integration platform can provide unified security strategy for the system, including allocation strategy of the online number of users, user waiting time, instance number in the component instance pool, user password and other security options, and can make configuration changes flexibly.
The system stores fine-grained data of certain period, provides a part of query function and cleanses non-standard data, which gets ready for data warehouse/mart.
(iv) Unified configuration of the system security strategy Business integration platform can provide unified security strategy for the system, including allocation strategy of the online number of users, user waiting time, instance number in the component instance pool, user password and other security options, and can make configuration changes flexibly.
Online since: December 2012
Authors: G. Agarwal, Manoj Modi
Koshy et al. [4, 5] in EDDG process, the workpiece is thus simultaneously subjected to heating due to electrical sparks occurring between the periphery of metal bonded grinding wheel and the workpiece, and abrasion by diamond grains having protrusion height more than the inter-electrode gap.
,m; k=1, 2, . . ., n, respectively, where m is the total number of experiment to be considered, and n is the total number of observation data [7].
Table 4: Response and ANOVA table for grey reasoning grade Response table for mean grey relational grade Symbol ANOVA table for grey relational grade Level 1 Level 2 Level 3 Max-Min DF SS MS C (%) 0.5939 0.5266 0.6312 0.1046 I 2 0.0169 0.0084 16.28 0.4839 0.5822 0.6856 0.2017 TON 2 0.06104 0.03052 58.80 0.5929 0.6203 0.5385 0.0819 S 2 0.0104 0.0052 10.0 0.5611 0.6421 0.5485 0.0937 DF 2 0.0155 0.0078 14.93 Total 8 0.1038 100 3 2 1 0.70 0.65 0.60 0.55 0.50 3 2 1 3 2 1 0.70 0.65 0.60 0.55 0.50 3 2 1 I Ton S DF Fig. 1: Response Graph of Average grey relational grade Confirmation test: The estimated grey relational grade , Where is the total mean grey relational grade, is the mean grey relational grade at the optimum level and ‘q’ is the number of significant design parameter that affect the multi performance characteristics.
,m; k=1, 2, . . ., n, respectively, where m is the total number of experiment to be considered, and n is the total number of observation data [7].
Table 4: Response and ANOVA table for grey reasoning grade Response table for mean grey relational grade Symbol ANOVA table for grey relational grade Level 1 Level 2 Level 3 Max-Min DF SS MS C (%) 0.5939 0.5266 0.6312 0.1046 I 2 0.0169 0.0084 16.28 0.4839 0.5822 0.6856 0.2017 TON 2 0.06104 0.03052 58.80 0.5929 0.6203 0.5385 0.0819 S 2 0.0104 0.0052 10.0 0.5611 0.6421 0.5485 0.0937 DF 2 0.0155 0.0078 14.93 Total 8 0.1038 100 3 2 1 0.70 0.65 0.60 0.55 0.50 3 2 1 3 2 1 0.70 0.65 0.60 0.55 0.50 3 2 1 I Ton S DF Fig. 1: Response Graph of Average grey relational grade Confirmation test: The estimated grey relational grade , Where is the total mean grey relational grade, is the mean grey relational grade at the optimum level and ‘q’ is the number of significant design parameter that affect the multi performance characteristics.
Online since: October 2014
Authors: Murat Dilmeç, Hüseyin Arıkan
When the material is heated to above the maximum solution temperature, the problem of grain boundary melting may originate and so the material failures.
=3mA1-m2+mA2-m2+mA3-m2 (3) Table 3 L9 orthogonal array Test number A B C D 1 485 2 15 250 2 485 10 30 750 3 485 30 45 2500 4 493 2 30 2500 5 493 10 45 250 6 493 30 15 750 7 505 2 45 750 8 505 10 15 2500 9 505 30 30 250 Where m is the overall mean of the η.
Degree of freedom is equal to one minus the level number.
The error mean square is calculated by adding the minimum values of the sum of squares up to the number parameters.
=3mA1-m2+mA2-m2+mA3-m2 (3) Table 3 L9 orthogonal array Test number A B C D 1 485 2 15 250 2 485 10 30 750 3 485 30 45 2500 4 493 2 30 2500 5 493 10 45 250 6 493 30 15 750 7 505 2 45 750 8 505 10 15 2500 9 505 30 30 250 Where m is the overall mean of the η.
Degree of freedom is equal to one minus the level number.
The error mean square is calculated by adding the minimum values of the sum of squares up to the number parameters.
Online since: January 2014
Authors: Lei Tang, Yong Zhang, Xiao Hui Ying
This message contains detailed information about the number of DPT, GPS message, sensor message and so on.
As the server knows the number of sensors hosted on each node, the DPT only needs to send the raw data obtained by the sensors, in the correct order.
Because of the increasing of the node number due to the addition of a satellite communication and rescue system.
[2] Kezhong Liu, Ji Xiong, A Fine-grained Localization Scheme Using A Mobile Beacon Node for Wireless Sensor Networks(expand)[J].Journal of Information Processing Systems, Vol.6, No.6, Sep 2010, pp:147-162
As the server knows the number of sensors hosted on each node, the DPT only needs to send the raw data obtained by the sensors, in the correct order.
Because of the increasing of the node number due to the addition of a satellite communication and rescue system.
[2] Kezhong Liu, Ji Xiong, A Fine-grained Localization Scheme Using A Mobile Beacon Node for Wireless Sensor Networks(expand)[J].Journal of Information Processing Systems, Vol.6, No.6, Sep 2010, pp:147-162
Online since: June 2012
Authors: Jie Huang, Shu Ya Zhi, Hong Jun Liu
(a) second section curve (b) fourth section curve (c) 15th section curve (d) 20th section curve (e) 23th section curve (f) 25th section curve
Fig. 3 Model by through the point Fig. 4 Model by combination modeling method
We know UG provides a variety of curved surface tectonic methods, including straight grain surface, through the curve group, through the curve grid, scanning, etc.
The project number is YK07-01-11.
The international Journal of Advanced Manufacturing Technology, 2005, Volume 27, Numbers 11-12, Pages 1119-1123 [10] Xavier Pessoles, Yann Landon and Walter Rubio, Kinematic modelling of a 3-axis NC machine tool in linear and circular interpolation.
The International Journal of Advanced Manufacturing Technology, 2010, Volume 47, Numbers 5-8, Pages 639-655
The project number is YK07-01-11.
The international Journal of Advanced Manufacturing Technology, 2005, Volume 27, Numbers 11-12, Pages 1119-1123 [10] Xavier Pessoles, Yann Landon and Walter Rubio, Kinematic modelling of a 3-axis NC machine tool in linear and circular interpolation.
The International Journal of Advanced Manufacturing Technology, 2010, Volume 47, Numbers 5-8, Pages 639-655
Online since: September 2009
Authors: Bing Suo Pan, Zhan Yang, Kai Hua Yang
Table 2 Experimental scheme of matrix formula of iron-based matrix with high phosphorus
Number
x1 x2 x3 x4 x5
Fe-P(B) WC 663Cu Ni-Co Mn-Ti etc.
1 0.53 0.14 0.18 0.09 0.06
2 0.48 0.19 0.18 0.10 0.05
3 0.40 0.16 0.25 0.12 0.07
4 0.36 0.20 0.23 0.11 0.10
5 0.32 0.26 0.20 0.10 0.12
6 0.31 0.16 0.30 0.12 0.11
7 0.30 0.29 0.27 0.09 0.06
8 0.29 0.18 0.20 0.22 0.11
9 0.28 0.20 0.27 0.21 0.05
10 0.25 0.24 0.23 0.19 0.08
11 0.24 0.27 0.31 0.09 0.10
12 0.23 0.16 0.22 0.21 0.17
13 0.23 0.30 0.20 0.17 0.10
14 0.22 0.18 0.29 0.21 0.09
15 0.21 0.33 0.26 0.15 0.05
16 0.19 0.42 0.20 0.13 0.06
Table 1 Content range of composition
Element Content range notes
Fe-P (B) (x1) 0.18≤x1≤0.54 Fe-P, Fe-B alloy added with iron powder
WC (x2) 0.14≤x2≤0.42
663-Cu (x3) 0.18≤x3≤0.32
Ni-Co (x4) 0.09≤x4≤0.22 The ratio of Ni to Co is 2 :1
Mn-Ti-Si etc.
Table 3 Testing results of matrix performances Testing number Hardness [HRB] Wear resistance [g] Testing number Hardness [HRB] Wear resistance [g] 1 110.96 0.10 9 97.38 0.15 2 112.82 0.09 10 95.08 0.20 3 107.08 0.12 11 99.63 0.21 4 105.47 0.13 12 96.80 0.15 5 104.97 0.11 13 98.71 0.14 6 100.16 0.14 14 98.32 0.16 7 102.72 0.16 15 97.10 0.17 8 96.47 0.19 16 93.10 0.24 Regression Analysis.
The rock formation which has strong abrasiveness is adamellite with biotite of medium-fine grain size, whose drillability is nine-grade.
Table 3 Testing results of matrix performances Testing number Hardness [HRB] Wear resistance [g] Testing number Hardness [HRB] Wear resistance [g] 1 110.96 0.10 9 97.38 0.15 2 112.82 0.09 10 95.08 0.20 3 107.08 0.12 11 99.63 0.21 4 105.47 0.13 12 96.80 0.15 5 104.97 0.11 13 98.71 0.14 6 100.16 0.14 14 98.32 0.16 7 102.72 0.16 15 97.10 0.17 8 96.47 0.19 16 93.10 0.24 Regression Analysis.
The rock formation which has strong abrasiveness is adamellite with biotite of medium-fine grain size, whose drillability is nine-grade.