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Online since: January 2014
Authors: Liang Dong Zhang, Yong Wang, Ying Hua Liao
It includes diameter, number and layout of holes.
Number of radial holes is less than 120.
Table 1 Grinding wheel parameters Radial holes Types of abrasive Diameter of grinding wheel Width of grinding wheel Abrasive grain Binder type Number of radial holes No White corundum 350mm 40mm 150 Ceramics — Yes White corundum 350mm 40mm 150 Ceramics 4×20 Four experiments are completed, i.e. idling experiments without and with cutting fluid, contrast experiment on inner cooling grinding of TC4 under different flow(Table 2), and contrast experiment on inner and outer cooling grinding of TC4(Table 3).
Number of radial holes is less than 120.
Table 1 Grinding wheel parameters Radial holes Types of abrasive Diameter of grinding wheel Width of grinding wheel Abrasive grain Binder type Number of radial holes No White corundum 350mm 40mm 150 Ceramics — Yes White corundum 350mm 40mm 150 Ceramics 4×20 Four experiments are completed, i.e. idling experiments without and with cutting fluid, contrast experiment on inner cooling grinding of TC4 under different flow(Table 2), and contrast experiment on inner and outer cooling grinding of TC4(Table 3).
Online since: November 2013
Authors: Tomáš Podrábský, Karel Obrtlík, Martin Juliš, Ladislav Čelko, Simona Hutařová, Martina Hrčková
The average dendritic grain size of the substrate was 0.66 mm, measured by linear intercept method on the polished cross and longitudinal sections.
Density of cracks and number of cracks in individual crack trajectories are shown in Table 2 and 3 for each specimen.
Table 2 Parameters of interrupted fatigue tests and crack classification Sample εa [%] N Crack density [cracks/mm] Delamination Number of cracks [-] [cycles] [%] total a b c d e f g LC020 0.29 20 1 - No 0 - - - - - - - LC024 0.29 200 10 0,60 No 7 7 - - - - - - LC007 0.29 1773 100 2,98 Yes 37 23 1 2 4 4 1 2 Table 3 Parameters of fatigue testing and crack classification Sample εa [%] σa [MPa] Nf [cycles] Crack density [cracks/mm] Delamination Number of cracks [-] total a b c d e f g LC007 0.29 329 1773 2,98 Yes 37 23 1 2 4 4 1 2 LC003 0.24 282 4796 1,09 Yes 22 14 3 1 3 1 - - LC014 0.16 238 8514 0,86 Yes 10 5 2 - - 3 - - LC019 0.14 190 40395 0,77 Yes 9 2 5 2 - - - - Acknowledgements The work presented in this paper has been supported by the Grant Agency of the Czech Republic by the projects Nos.
Density of cracks and number of cracks in individual crack trajectories are shown in Table 2 and 3 for each specimen.
Table 2 Parameters of interrupted fatigue tests and crack classification Sample εa [%] N Crack density [cracks/mm] Delamination Number of cracks [-] [cycles] [%] total a b c d e f g LC020 0.29 20 1 - No 0 - - - - - - - LC024 0.29 200 10 0,60 No 7 7 - - - - - - LC007 0.29 1773 100 2,98 Yes 37 23 1 2 4 4 1 2 Table 3 Parameters of fatigue testing and crack classification Sample εa [%] σa [MPa] Nf [cycles] Crack density [cracks/mm] Delamination Number of cracks [-] total a b c d e f g LC007 0.29 329 1773 2,98 Yes 37 23 1 2 4 4 1 2 LC003 0.24 282 4796 1,09 Yes 22 14 3 1 3 1 - - LC014 0.16 238 8514 0,86 Yes 10 5 2 - - 3 - - LC019 0.14 190 40395 0,77 Yes 9 2 5 2 - - - - Acknowledgements The work presented in this paper has been supported by the Grant Agency of the Czech Republic by the projects Nos.
Online since: July 2014
Authors: K. Palanikumar, K. Vigneswar, K. Umanath, S.T. Selvamani
Introduction
Friction welding (FW) appears to offer a number of advantages more than arc welding of steels.
The use of this joining process normally is correlated with the condensed development of these inter metallic phases, reduce grain enlargement in the HAZ, and boundary deformation and stress cracking in steels.
This is done to reduce the number of experiments in the research work.
The hardness test specimens are machined in all samples and to calculate the Vickers hardness number [12, 13].
The use of this joining process normally is correlated with the condensed development of these inter metallic phases, reduce grain enlargement in the HAZ, and boundary deformation and stress cracking in steels.
This is done to reduce the number of experiments in the research work.
The hardness test specimens are machined in all samples and to calculate the Vickers hardness number [12, 13].
Online since: September 2008
Authors: W.Joe Quadakkers, Lorenz Singheiser, Gerald H. Meier, D. Naumenko, J. Zurek, L. Niewolak, P. Huczkowski
For a number of chromia and alumina forming high temperature alloys and coatings,
recent studies revealed, that in some cases the specimen/component or coating thickness may
substantially affect the growth rates of the surface oxides.
In the present paper recent findings concerning the effect of specimen thickness on oxidation kinetics will be illustrated for a number of alumina forming FeCrAlY-base alloys and NiCoCrAlY coatings as well as for chromia forming high-Cr ferritic steels and Ni-base alloys.
Alloy and oxide microstructure and composition were analysed using a number of common analysis methods such as optical metallography, scanning and transmission electron microscopy (SEM/TEM), laser Raman spectroscopy (LRS), X-ray diffraction (XRD) and sputtered neutrals mass spectrometry (SNMS).
This can be explained by a higher density of rapid diffusion paths for oxygen such as oxide grain boundaries and/or, for instance during thermal cycling, micro cracks [3].
As a result, further scale growth proceeds in a similar way as observed for alloy Y, i.e., a Zr-free oxide layer (Fig. 1b) with the same columnar grain structure is formed in the inner part of the scale [3].
In the present paper recent findings concerning the effect of specimen thickness on oxidation kinetics will be illustrated for a number of alumina forming FeCrAlY-base alloys and NiCoCrAlY coatings as well as for chromia forming high-Cr ferritic steels and Ni-base alloys.
Alloy and oxide microstructure and composition were analysed using a number of common analysis methods such as optical metallography, scanning and transmission electron microscopy (SEM/TEM), laser Raman spectroscopy (LRS), X-ray diffraction (XRD) and sputtered neutrals mass spectrometry (SNMS).
This can be explained by a higher density of rapid diffusion paths for oxygen such as oxide grain boundaries and/or, for instance during thermal cycling, micro cracks [3].
As a result, further scale growth proceeds in a similar way as observed for alloy Y, i.e., a Zr-free oxide layer (Fig. 1b) with the same columnar grain structure is formed in the inner part of the scale [3].
Online since: August 2013
Authors: Yi Zhang, Gang Wang, Ping Rong Lin
.
== (1)
In order to express the satisfaction of integration test coverage after number test case is executed, the satisfaction of integration test coverage is designated as Eq. (2):
(2)
And,is the expected value number of test coverage for moduleafter number test case is executed.
At present, the usual method to measure the test efficiency is to detect the number of flaws.
We can combine the average rate of growth with the increased number of flaws to measure the test efficiency, and it can be expressed by a pair value, just as Eq.(3): (3) Here, is the average growth rate of a number of m test coverage, that is: (4) refers to the time used to execute a continuous test cases from executing number test case; and is the test coverage variation of number used to execute a continuous test case from executing number test case.is the increased number of detected flaws during executing a continuous test cases: (5) Step 2: Decide the ideal modifying act -- for test utility.
In the state and the number of test coverage decision after state as the ratio of the number of.
Researches will be conducted to deal with the testing coverage metrics, to increase the comprehensive test more fine-grained coverage decision attribute, to further improve the decision support rationality, safety, and to provide scientific guidance for the testing process.
At present, the usual method to measure the test efficiency is to detect the number of flaws.
We can combine the average rate of growth with the increased number of flaws to measure the test efficiency, and it can be expressed by a pair value, just as Eq.(3): (3) Here, is the average growth rate of a number of m test coverage, that is: (4) refers to the time used to execute a continuous test cases from executing number test case; and is the test coverage variation of number used to execute a continuous test case from executing number test case.is the increased number of detected flaws during executing a continuous test cases: (5) Step 2: Decide the ideal modifying act -- for test utility.
In the state and the number of test coverage decision after state as the ratio of the number of.
Researches will be conducted to deal with the testing coverage metrics, to increase the comprehensive test more fine-grained coverage decision attribute, to further improve the decision support rationality, safety, and to provide scientific guidance for the testing process.
Online since: August 2013
Authors: Ming Fu, Jun Xu, Jun Huang
Based on analyzing and experimenting a large number of the existing fingerprint image preprocessing algorithm, this paper presents a novel high-quality fingerprint image preprocessing algorithm.
Based on analyzing and experimenting a large number of the existing fingerprint image preprocessing algorithm, this paper presents a novel high-quality fingerprint image preprocessing algorithm.
Based on making full use of the thought that fingerprint ridge along and vertical flow of grey level variance size are obviously different, this method uses the variance calculation of typical block size across 1 ~ 2 grain line distance.
Based on analyzing and experimenting a large number of the existing fingerprint image preprocessing algorithm, this paper presents a novel high-quality fingerprint image preprocessing algorithm.
Based on making full use of the thought that fingerprint ridge along and vertical flow of grey level variance size are obviously different, this method uses the variance calculation of typical block size across 1 ~ 2 grain line distance.
Online since: August 2014
Authors: Martina Drdlová, Radek Holešinský, Radek Řídký, Jan Křesťan
The fine-grained concrete matrix has been reinforced by various types of dispersed fibers (metallic, mineral and polymer) of different sizes and by their combination, while the same volume content of fibres has been kept.
Nearly half of the presented number were bomb attacks, targeted mostly on strategic buildings and places with high people concentration, such as railway and bus stations, subway stations, airports, shopping centres, etc.
Fine-grain high performance concrete (consisted of fine SiO2 sand, cement 52.5R, microsilica, superplasticizer) was selected as a standard.
Nearly half of the presented number were bomb attacks, targeted mostly on strategic buildings and places with high people concentration, such as railway and bus stations, subway stations, airports, shopping centres, etc.
Fine-grain high performance concrete (consisted of fine SiO2 sand, cement 52.5R, microsilica, superplasticizer) was selected as a standard.
Online since: February 2024
Authors: E. Sugurbekov, Gulnar Sugurbekova, Rabiga Kudaibergenova, A Gabdullina, Gulzat Demeuova
And magnesium ferrites (Fig. 2a) and copper (Fig. 2d) had a finer grain size and lower porosity.
The SEM image of zinc ferrite (Fig. 2e) showed the same grain size and good porosity compared to other ferrites.
Cobalt ferrite and zinc ferrite had more crystalline grains and high porosity (Fig. 2b, d), showing a higher sensitivity coefficient.
In structures containing iron cations surrounded by anions - weak field ligands, such as O2 - iron cations are usually in a high-spin state and include the maximum possible number of unpaired d-electrons.
For the Fe2+ (3d6) ion in the high-spin state, their number will be four (S = 2).
The SEM image of zinc ferrite (Fig. 2e) showed the same grain size and good porosity compared to other ferrites.
Cobalt ferrite and zinc ferrite had more crystalline grains and high porosity (Fig. 2b, d), showing a higher sensitivity coefficient.
In structures containing iron cations surrounded by anions - weak field ligands, such as O2 - iron cations are usually in a high-spin state and include the maximum possible number of unpaired d-electrons.
For the Fe2+ (3d6) ion in the high-spin state, their number will be four (S = 2).
Online since: May 2012
Authors: Abdul Razak Daud, M.Y. Ahmad, M. Daud, M.C. Isa, S.R. Shamsudin, M.S. Din Yati, M.M. Muhammad, N. Hassanuddin
This observation can be attributed to the presence of Sn in the alloy particularly at the grain boundaries due to the fact that the solid solubility of Sn in Al matrix is below 0.09 wt.% at room temperature [16].
Therefore, more Sn will be distributed at the grain boundaries, forming a heterogeneous oxide layer with different electrical properties and at the same time, playing a role to enhance the adsorption process of chloride ions at more electronegative potential leading to the dissolution of the alloy [17].
Moreover, as the immersion time increases, the OCP values for Al-Zn-Sn recorded a stable value which can be ascribed from more local breakdown of passive film generated at grain boundaries, making the alloy more susceptible to attacks by or interactions with aggressive chloride ions.
There are a number of possible causes to the presence of an inductive loop for this type of sample.
ZCPE = 1/[Y0(jω)n] (1) Where j is the imaginary number, j = (-1)1/2, ω (=2πf) is the angular frequency [37, 38].
Therefore, more Sn will be distributed at the grain boundaries, forming a heterogeneous oxide layer with different electrical properties and at the same time, playing a role to enhance the adsorption process of chloride ions at more electronegative potential leading to the dissolution of the alloy [17].
Moreover, as the immersion time increases, the OCP values for Al-Zn-Sn recorded a stable value which can be ascribed from more local breakdown of passive film generated at grain boundaries, making the alloy more susceptible to attacks by or interactions with aggressive chloride ions.
There are a number of possible causes to the presence of an inductive loop for this type of sample.
ZCPE = 1/[Y0(jω)n] (1) Where j is the imaginary number, j = (-1)1/2, ω (=2πf) is the angular frequency [37, 38].
Online since: September 2003
Authors: Hans Kurt Tönshoff, T. Friemuth, Berend Denkena, Th. Glatzel
In many cases too low loads on the grits result in flattened grains
which have no ability to penetrate into the workpiece surface and to generate chips.
The engagement frequency causes a forced vibration depending on the peripheral speed and the number of teeth.
To be able to determine the load of different grinding operations on the single diamond grain a model of the chip formation process was generated.
Usually low feed rates induce a small chip thickness at the grit generating a huge number of flat diamonds.
Especially the huge number of flat diamonds for a feed rate of 2 and 20 m/min is responsible for high forces during the process.
The engagement frequency causes a forced vibration depending on the peripheral speed and the number of teeth.
To be able to determine the load of different grinding operations on the single diamond grain a model of the chip formation process was generated.
Usually low feed rates induce a small chip thickness at the grit generating a huge number of flat diamonds.
Especially the huge number of flat diamonds for a feed rate of 2 and 20 m/min is responsible for high forces during the process.