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Online since: February 2012
Authors: Yong Chen, Wei Na Li, Xi Jun Wang, Shi Jie Shen
In this article, we made visual grading, four-point bending edge-wise and axial tensile test to grain some data according to ASTM D245 and ASTM D4716-05 on the basis of pervious studies.
Table.4 Analysis of correlation coefficient of tensile strength and combined parameters Size(mm):3900×120×32 Tension strength(σw)(r) E4s E4s+ρ E4s+Kus E4s+ρ+Kus 0.654 0.662 0.749 0.750 We can get the related coefficient between combined parameters E4s+ρ/E4s+ Kus/E4s+ρ+Kus and tension strength increased as the number of predicting parameters.
The related coefficient increased clearly when visual grading Kus combined with E4s+ρ.The more the number of combined parameter -s, the better relevance which provide stronger evidence to the prediction of larch timber strength.
So, to increase the number of predict factors is a better way to evaluate the parallel tensile strength, but further study is need.
Table.4 Analysis of correlation coefficient of tensile strength and combined parameters Size(mm):3900×120×32 Tension strength(σw)(r) E4s E4s+ρ E4s+Kus E4s+ρ+Kus 0.654 0.662 0.749 0.750 We can get the related coefficient between combined parameters E4s+ρ/E4s+ Kus/E4s+ρ+Kus and tension strength increased as the number of predicting parameters.
The related coefficient increased clearly when visual grading Kus combined with E4s+ρ.The more the number of combined parameter -s, the better relevance which provide stronger evidence to the prediction of larch timber strength.
So, to increase the number of predict factors is a better way to evaluate the parallel tensile strength, but further study is need.
Online since: April 2008
Authors: Bo Jonson, Björn Zethræus, Ruud Beerkens, Adriaan Lankhorst
The
notation in the figures sieved means that the grain size fraction of all raw materials is between 63 -
125 µm.
Figure 2 shows the number of bubbles remaining after 30 minutes melting time
Bubbles per 100 g glass 0 200 400 600 800 1000 1200 1400 1600 Na-, CaCO3 Na-, K-, CaCO3 Na silicate CaCO3 Na, CaCO3 K silicate NaCO3, Ca silicate Na-, K-, Ca silicates Compound Number of bubbles Average non sieved Average sieved Average total Figure 2.
Number of bubbles, 30 min melting at 1400 ºC, for different batch components Figures 1 and 2 clearly show that substitution of carbonates in the batch would promote batch reactivity and increase the fining efficiency.
Figure 2 shows the number of bubbles remaining after 30 minutes melting time
Bubbles per 100 g glass 0 200 400 600 800 1000 1200 1400 1600 Na-, CaCO3 Na-, K-, CaCO3 Na silicate CaCO3 Na, CaCO3 K silicate NaCO3, Ca silicate Na-, K-, Ca silicates Compound Number of bubbles Average non sieved Average sieved Average total Figure 2.
Number of bubbles, 30 min melting at 1400 ºC, for different batch components Figures 1 and 2 clearly show that substitution of carbonates in the batch would promote batch reactivity and increase the fining efficiency.
Online since: May 2022
Authors: Nikolay Ferdinandov, Ivo Draganov
The two models are based on the finite elements method (FEM) and have different complexity and number of participating parameters.
A number of authors consider metallurgical processes.
Robson and Campbell [19] offer a model for recrystallization and grain growth.
[19] Robson J., Campbell L., Model for grain evolution during friction stir welding of aluminium alloys, Science and Technology of Welding and Joining, Vol. 15.
A number of authors consider metallurgical processes.
Robson and Campbell [19] offer a model for recrystallization and grain growth.
[19] Robson J., Campbell L., Model for grain evolution during friction stir welding of aluminium alloys, Science and Technology of Welding and Joining, Vol. 15.
Online since: October 2015
Authors: Leszek Adam Dobrzański, Wojciech Pakieła, Błażej Tomiczek, Anna Ewa Tomiczek
The tribological analysis reveals that composite materials – irrespective of the measuring cycles number and load – are characterised by much smaller wear volume in comparison to the matrix material.
The MMCs obtained as a result of mechanical alloying, cold compacting and hot extrusion are characterised with the microstructure of homogeneous distribution of halloysite particles in fine-grain matrix of AlMg1SiCu alloy, facilitate the obtainment of higher values of mechanical properties, compared to the base alloy.
Acknowledgements The project was financed by the National Science Centre granted on the basis of the decision number DEC-2011/03/B/ST8/06076.
The MMCs obtained as a result of mechanical alloying, cold compacting and hot extrusion are characterised with the microstructure of homogeneous distribution of halloysite particles in fine-grain matrix of AlMg1SiCu alloy, facilitate the obtainment of higher values of mechanical properties, compared to the base alloy.
Acknowledgements The project was financed by the National Science Centre granted on the basis of the decision number DEC-2011/03/B/ST8/06076.
Online since: February 2012
Authors: Tao He
The large number of publications addressing possible methods for quantitative mineralogical analysis is a good reflection of demand for determination by the scientific and industrial communities.
Monecke and S.Hillier: Preferred Orientation of Mineral Grains in Sample Mounts for Quantitative XRD Measurements: How Random are Powder Samples?
Monecke and S.Hillier: Preferred Orientation of Mineral Grains in Sample Mounts for Quantitative XRD Measurements: How Random are Powder Samples?
Online since: November 2013
Authors: Han Zhang, Cong Geng, Rui Feng Guo
Aiming at avoiding problems of uncertainty, coarse-grained, diversity and dynamic in the process of services resource combination, a hierarchical model based on the hierarchical manufacturing implementation processes was firstly proposed.
Using xjk to express the serial number ‘h’ of cloud service RSSjkh in RSSjk, the solution of hierarchical cloud service combination(S) can be represented as Equ.4:
Using xjk to express the serial number ‘h’ of cloud service RSSjkh in RSSjk, the solution of hierarchical cloud service combination(S) can be represented as Equ.4:
Online since: July 2013
Authors: Zheng Hua Wang, Yao Yuan Zeng, Wen Tao Zhao
For a k-way partition, the coarsening phase ends when the number of vertices becomes less than .
Priority rule number two: deciding the merging sequence of the vertices with equal weighted inner product based on the ascending order of their neighbor number.
The convergence rate of vertices number comparisons of nine algorithms.
The convergence rate of vertices number comparisons between PWIPM and hMETIS.
Fine-grained supply gating through hypergraph partitioning and Shannon decomposition for active power reduction. in Proceedings of the conference on Design, automation and test in Europe. 2008: ACM
Priority rule number two: deciding the merging sequence of the vertices with equal weighted inner product based on the ascending order of their neighbor number.
The convergence rate of vertices number comparisons of nine algorithms.
The convergence rate of vertices number comparisons between PWIPM and hMETIS.
Fine-grained supply gating through hypergraph partitioning and Shannon decomposition for active power reduction. in Proceedings of the conference on Design, automation and test in Europe. 2008: ACM
Online since: October 2011
Authors: Yan Li Jiang, Sen Kai Lu, Liang Yu, Jian Huan Su, Shu De Liao, Jia Qiang Su, Bo Wang, Shou Hong Wen
A
C
Fig.1 Geometry of the axle housing
Fig. 2 Finite element model of the rear axle housing
Housing Material.Shells are manufactured by the stamp-welding process from 12 mm thick sheets made from a micro alloyed fine grained, hot formable, normalized structural steel S460N (Material number 1.8901, equivalent to E460 according to ISO standard [3]).
It can predict fatigue life at the product design stage, reduce the number of experimental prototypes, and shorten the development cycle.
FEM analyses also enable to provide an estimation of the number of cycles before fatigue failure initiation.
It can predict fatigue life at the product design stage, reduce the number of experimental prototypes, and shorten the development cycle.
FEM analyses also enable to provide an estimation of the number of cycles before fatigue failure initiation.
Online since: December 2013
Authors: Xiao Ning Zhang, Li Wen Zeng, Shun Xian Zhang
The particle area ratio is defined as the accumulated scanning section area of the coarse aggregate particles to the fan-shaped area, the first step calculates particle area size in each scan area respectively, and the second step is to evaluate the uniformity of asphalt mixture aggregate distribution through the statistical analysis of the grain area ratio.
The each cross section scanning results of core samples from specimens are shown in table 1, in this table, located in the central position of No 20 and located in number at the bottom of the 40th section scanning images and sector scan image are shown in figure 5 and figure 6.
Section scan results Section number particle size ratio quantity maximum minimum average standard deviation variable coefficient Section 1 24 0.682 0.445 0.572 0.085 0.164 Section 2 24 0.724 0.443 0.571 0.083 0.158 Section 3 24 0.733 0.439 0.573 0.080 0.152 … … … … … … … Section 39 24 0.485 0.268 0. 545 0.068 0.135 Section 40 24 0.535 0.351 0.529 0.070 0.140 (a) No.20 cross section image (b) Sector scan images Fig .5, No 20 cross section images and sector scan images (a)No 40 cross section image (b) sector scan images Figure. 6, No 40 cross section images and sector scan images Coarse aggregate uniformity evaluation index.
Ideally, when the number of scanning the section and each section thickness , the more scanning areas are got at this time, the more details of asphalt mixture inside is reflected, the better uniformity of mixture is evaluated and more close to the true value.
The each cross section scanning results of core samples from specimens are shown in table 1, in this table, located in the central position of No 20 and located in number at the bottom of the 40th section scanning images and sector scan image are shown in figure 5 and figure 6.
Section scan results Section number particle size ratio quantity maximum minimum average standard deviation variable coefficient Section 1 24 0.682 0.445 0.572 0.085 0.164 Section 2 24 0.724 0.443 0.571 0.083 0.158 Section 3 24 0.733 0.439 0.573 0.080 0.152 … … … … … … … Section 39 24 0.485 0.268 0. 545 0.068 0.135 Section 40 24 0.535 0.351 0.529 0.070 0.140 (a) No.20 cross section image (b) Sector scan images Fig .5, No 20 cross section images and sector scan images (a)No 40 cross section image (b) sector scan images Figure. 6, No 40 cross section images and sector scan images Coarse aggregate uniformity evaluation index.
Ideally, when the number of scanning the section and each section thickness , the more scanning areas are got at this time, the more details of asphalt mixture inside is reflected, the better uniformity of mixture is evaluated and more close to the true value.
Online since: November 2014
Authors: Yuan Song, Guang Hui Cheng
In addition, industry standards are published, for example, the standard for coal ash power is that GB/T1596—2005 is used for coal ash power in cement and concrete [5], and the standard for ground granulated blast furnace slag is used for graining blast furnace slag in cement and concrete [6].
Table 2 Grinding test scheme of ground granulated blast furnace slag Sample number Grinding technique, time(min ) Grinding body form Weight of grinding materials (kg ) Note Pre-grinding time Final-grinding time 0 Final grinding, time 45 min Ball section 5.0 Control sample 1 15(pre-grinding ) Ball section 7.5 2 2( pre-grinding ) Ball section 7.5 3 2( pre-grinding ) Ball section 7.5 4 30 (secondary grinding ) Ball section 5.0 Final grinding of 1# 5 25 (secondary grinding ) Ball section 5.0 Final grinding of 2# 6 20 (secondary grinding ) Ball section 5.0 Final grinding of 3# 7 8.
Table 3 Experimental results of different grinding ways (from good to bad) Smaple number Peak um Mean um D10 um D50 um D90 um Specific area cm2/ml Specific area m2/kg 14 16.02 8.326 0.727 6.200 18.47 25183 458 4 20.02 8.885 0.807 6.758 20.77 23780 440 0 17.98 9.013 0.826 7.043 20.56 22664 407 6 42.39 17.56 0.919 11.92 44.39 18385 384 11 43.19 18.03 0.926 12.26 44.18 18069 378 5 42.39 17.62 1.019 12.06 43.95 17363 375 13 44.59 18.69 1.135 14.70 46.40 16548 366 12 45.09 18.99 1.200 14.89 47.08 16196 360 The experimental results in Table 3 indicates that grinding technology, grinding time, grinding body and ball ratio has different effect on indicators on micro powder.
And the fluidity is higher than that of 0#, which indicates that the quality of ground granulated blast furnace slag applying the technique is the best, Table 4 Activity test results of ground granulated blast furnace slag with different grinding ways Sample number 0(407) 4(440) 14(458) 5(375) 11(378) 7d activity index 70 77 85 60 58 28d activity index 93 96 106 82 86 Fludity ratio 100 103 109 110 110 Conclusions The experiment researches the effect of using different grinding bodies and grinding time on ground granulated blast furnace slag in the process of producing cement, and the research results indicate that :(1) Grinding effect of different grinding bodies has great difference, (2) The grinding effect of applying pre-grinding technology is not better than that of applying final grinding technology. (3) Longer pre-grinding time is not good.
Table 2 Grinding test scheme of ground granulated blast furnace slag Sample number Grinding technique, time(min ) Grinding body form Weight of grinding materials (kg ) Note Pre-grinding time Final-grinding time 0 Final grinding, time 45 min Ball section 5.0 Control sample 1 15(pre-grinding ) Ball section 7.5 2 2( pre-grinding ) Ball section 7.5 3 2( pre-grinding ) Ball section 7.5 4 30 (secondary grinding ) Ball section 5.0 Final grinding of 1# 5 25 (secondary grinding ) Ball section 5.0 Final grinding of 2# 6 20 (secondary grinding ) Ball section 5.0 Final grinding of 3# 7 8.
Table 3 Experimental results of different grinding ways (from good to bad) Smaple number Peak um Mean um D10 um D50 um D90 um Specific area cm2/ml Specific area m2/kg 14 16.02 8.326 0.727 6.200 18.47 25183 458 4 20.02 8.885 0.807 6.758 20.77 23780 440 0 17.98 9.013 0.826 7.043 20.56 22664 407 6 42.39 17.56 0.919 11.92 44.39 18385 384 11 43.19 18.03 0.926 12.26 44.18 18069 378 5 42.39 17.62 1.019 12.06 43.95 17363 375 13 44.59 18.69 1.135 14.70 46.40 16548 366 12 45.09 18.99 1.200 14.89 47.08 16196 360 The experimental results in Table 3 indicates that grinding technology, grinding time, grinding body and ball ratio has different effect on indicators on micro powder.
And the fluidity is higher than that of 0#, which indicates that the quality of ground granulated blast furnace slag applying the technique is the best, Table 4 Activity test results of ground granulated blast furnace slag with different grinding ways Sample number 0(407) 4(440) 14(458) 5(375) 11(378) 7d activity index 70 77 85 60 58 28d activity index 93 96 106 82 86 Fludity ratio 100 103 109 110 110 Conclusions The experiment researches the effect of using different grinding bodies and grinding time on ground granulated blast furnace slag in the process of producing cement, and the research results indicate that :(1) Grinding effect of different grinding bodies has great difference, (2) The grinding effect of applying pre-grinding technology is not better than that of applying final grinding technology. (3) Longer pre-grinding time is not good.