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Online since: September 2014
Authors: Nadiya Storozhuk, Andriy Gusak, Semen Kornienko, Tetyana Zaporozhets
Sources and sinks of vacancies are situated at external or pore(void) boundaries, grain boundaries, dislocations.
So, here we consider only heterogeneous nucleation and growth of voids, their number per unit area of interface is fixed.
This increase of the total number of vacancies going to the interface, gives larger effect than the decrease of vacancy fraction going to voids.
In this case we can reduce the number of variables from two to one: .
Deviation of actual vacancy concentration from the equilibrium value is determined by the number of generated vacancies: (the expression can be treated as a vacancy generation rate).
So, here we consider only heterogeneous nucleation and growth of voids, their number per unit area of interface is fixed.
This increase of the total number of vacancies going to the interface, gives larger effect than the decrease of vacancy fraction going to voids.
In this case we can reduce the number of variables from two to one: .
Deviation of actual vacancy concentration from the equilibrium value is determined by the number of generated vacancies: (the expression can be treated as a vacancy generation rate).
Online since: January 2012
Authors: Ashfa Umber, Imran Sarwar Bajwa, M. Shahid Naweed, Tayyiba Bashir
There are number of problems that help us to understand why requirement elicitation is difficult.
Problems In Requirment Elicitation Christel and kang identify a number of problems that help us to understand why requirement elicitation is difficult.
The delivered product contains a number of page layout capabilities that are quite pleasing and unexpected.
For requirement recognition it provides good cues, for example the prototypes provide users an initial version of the system which can remind them of the fine grained functions which are often otherwise overlooked.
There are a number of elicitation techniques useful for addressing one or more of the problems However; no single technique adequately addresses all of the elicitation problem areas.
Problems In Requirment Elicitation Christel and kang identify a number of problems that help us to understand why requirement elicitation is difficult.
The delivered product contains a number of page layout capabilities that are quite pleasing and unexpected.
For requirement recognition it provides good cues, for example the prototypes provide users an initial version of the system which can remind them of the fine grained functions which are often otherwise overlooked.
There are a number of elicitation techniques useful for addressing one or more of the problems However; no single technique adequately addresses all of the elicitation problem areas.
Online since: May 2015
Authors: Ji Kang Yan, Gang Yang, Wan Xia Tang, Yun Feng Wu, Zhe Shi
Also, the same phase composition titanium alloy have different film structure due to the vary grain size [10].
WHD - 30 type micro-arc oxidation power provides constant pressure and the forward voltage is 10V-120V, the vreverse voltage is 0, the pulse number is 1, the frequency is 200 Hz, the positive and negative duty ratio is 50%, oxidation time is 50 min and electrolyte temperature is room temperature.
Figure 2 (a) shows that, higher contrast of the back scattered electrons on the left side is the TC4 matrix with high average atomic number, middle low contrast is the oxide film with low average atomic number and right is the zero contrast vacuum.
Table 2 Chemical reaction and stages of titanium alloy anode oxidation Stage of anodizing physical-chemical processes chemical reactions Sequence Number the initial stage of anodizing Titanium dissolve in the electrolyte： Ti→Ti4+ + 4e– （1） Oxygen precipitate out from the anode titanium alloy: 4OH-→2H2O+O2↑+4e- （2） Formation of TiO2 film: 2Ti+8OH-→2TiO2+4H2O+8e- （3） Formation of TiO2 film: Ti+O2→TiO2 （4） Dissolve fo TiO2 film: TiO2+4H++4e-→Ti+2H2O （5） the middle stage of anodizing Titanium dissolve in the electrolyte: Ti→Ti3++3e- （6） Formation of Ti2O3 film： 2Ti+6OH-→Ti2O3+3H2O+6e- （7） Formation of Ti2O3 film： Ti+3/2O2→Ti2O3 （8） Ti2O3 film transform into TiO2film： Ti2O3+H2O→2 TiO2+2H++2e- （9） Ti2O3 film transform into TiO2film： Ti2O3+1/2O2→2 TiO2 （10） the later stage of anodizing Titanium dissolve in the electrolyte: Ti→Ti2++2e- （11） Formation of TiO film： Ti+1/2O2→2TiO （12） Formation of TiO film： 2Ti+2OH-→TiO+H2O+2e- （13） TiO film transform into Ti2O3film： 2TiO+H2O→Ti2O3+2H++2e- （14）
WHD - 30 type micro-arc oxidation power provides constant pressure and the forward voltage is 10V-120V, the vreverse voltage is 0, the pulse number is 1, the frequency is 200 Hz, the positive and negative duty ratio is 50%, oxidation time is 50 min and electrolyte temperature is room temperature.
Figure 2 (a) shows that, higher contrast of the back scattered electrons on the left side is the TC4 matrix with high average atomic number, middle low contrast is the oxide film with low average atomic number and right is the zero contrast vacuum.
Table 2 Chemical reaction and stages of titanium alloy anode oxidation Stage of anodizing physical-chemical processes chemical reactions Sequence Number the initial stage of anodizing Titanium dissolve in the electrolyte： Ti→Ti4+ + 4e– （1） Oxygen precipitate out from the anode titanium alloy: 4OH-→2H2O+O2↑+4e- （2） Formation of TiO2 film: 2Ti+8OH-→2TiO2+4H2O+8e- （3） Formation of TiO2 film: Ti+O2→TiO2 （4） Dissolve fo TiO2 film: TiO2+4H++4e-→Ti+2H2O （5） the middle stage of anodizing Titanium dissolve in the electrolyte: Ti→Ti3++3e- （6） Formation of Ti2O3 film： 2Ti+6OH-→Ti2O3+3H2O+6e- （7） Formation of Ti2O3 film： Ti+3/2O2→Ti2O3 （8） Ti2O3 film transform into TiO2film： Ti2O3+H2O→2 TiO2+2H++2e- （9） Ti2O3 film transform into TiO2film： Ti2O3+1/2O2→2 TiO2 （10） the later stage of anodizing Titanium dissolve in the electrolyte: Ti→Ti2++2e- （11） Formation of TiO film： Ti+1/2O2→2TiO （12） Formation of TiO film： 2Ti+2OH-→TiO+H2O+2e- （13） TiO film transform into Ti2O3film： 2TiO+H2O→Ti2O3+2H++2e- （14）
Online since: October 2012
Authors: Huan Sheng Mu
The normal moveout of the common reflection point can be got from the curve of common shot reflected wave as follows:
(2)
Therefore, after the normal moveout correction during data processing, the common reflection point of hyperbolic distance curve is adjusted to a straight line, and then a number of superimposition is added.
Under the same excitation conditions, waveform characteristics including the visual cycle, the number of phases, envelope shape, amplitude ratio between the extreme values of the same reflecting interface are relatively stable due to small differences of the propagation path and dielectric properties.
Fault Identification Mark The lateral variation of the reflected wave lineups is an important symbol faults, which can be judged according to the followings: a apparent dislocation of reflected wave lineups; b sudden increase or decrease of the number of reflected wave phase axis or disappearance of wave lineups; sudden change of wave group intervals due to thicker subsiding strata and thinner rising strata or even absence of it; c mutation of reflected wave lineups shape; d forking, merging, distorting, and phase shifting of reflected standard wave lineups; e appearance of diffracted waves and fault wave etc; f Fault wave is of great significance for determination of the existence of fault.
Also the link state between mineral or lithic grains change from crystalline link or cementation link into hydrocolloid links which is more loosely, causing longer wave propagation time and lower wave velocity.
Lithology name Cone Penetration/ Standard Penetration Stress number Uniaxial saturation Compression strength [MPa] Longitudinal vave velocity [m/s] macadam Fully weathered tuff Highly weathered tuff 13* Moderately weathered tuff 3380 Slightly weathered tuff Note: Make a judgement on rock features and rock mass quality according to surrounding rock integrity and hardness.
Under the same excitation conditions, waveform characteristics including the visual cycle, the number of phases, envelope shape, amplitude ratio between the extreme values of the same reflecting interface are relatively stable due to small differences of the propagation path and dielectric properties.
Fault Identification Mark The lateral variation of the reflected wave lineups is an important symbol faults, which can be judged according to the followings: a apparent dislocation of reflected wave lineups; b sudden increase or decrease of the number of reflected wave phase axis or disappearance of wave lineups; sudden change of wave group intervals due to thicker subsiding strata and thinner rising strata or even absence of it; c mutation of reflected wave lineups shape; d forking, merging, distorting, and phase shifting of reflected standard wave lineups; e appearance of diffracted waves and fault wave etc; f Fault wave is of great significance for determination of the existence of fault.
Also the link state between mineral or lithic grains change from crystalline link or cementation link into hydrocolloid links which is more loosely, causing longer wave propagation time and lower wave velocity.
Lithology name Cone Penetration/ Standard Penetration Stress number Uniaxial saturation Compression strength [MPa] Longitudinal vave velocity [m/s] macadam Fully weathered tuff Highly weathered tuff 13* Moderately weathered tuff 3380 Slightly weathered tuff Note: Make a judgement on rock features and rock mass quality according to surrounding rock integrity and hardness.
Online since: July 2022
Authors: Andrea Ghiotti, Stefania Bruschi, Rachele Bertolini
Conventional machining operations with either a tool of defined geometry or abrasive grains of undefined geometry are the most widespread to finish AM parts, even if they may not be suitable for finishing hidden zones, enclosed features, very small corners, or lattice structures.
Even if a reduced number of layers was shown to lead to a better quality of the claddings, their machinability was negatively affected since the higher the number of the layers the higher the cutting forces and the worse the surface integrity (see Figure 2).
Tool wear was evaluated at increasing number of drilled holes and related to the hole quality.
Rech, On the influence of laser cladding parameters and number of deposited layers on as-built and machined H13 tool steel multilayered claddings.
Even if a reduced number of layers was shown to lead to a better quality of the claddings, their machinability was negatively affected since the higher the number of the layers the higher the cutting forces and the worse the surface integrity (see Figure 2).
Tool wear was evaluated at increasing number of drilled holes and related to the hole quality.
Rech, On the influence of laser cladding parameters and number of deposited layers on as-built and machined H13 tool steel multilayered claddings.
Online since: June 2014
Authors: Claudia Trillo
In the last decades a considerable numbers of economists and social policy theorists challenged the dominant intellectual paradigm in economic sciences, i.e. the capitalism.
In so doing, he discussed the five common misunderstanding still sometime plaguing the case study research approach, challenging each of them as follows: (1) it may seem that “general, theoretical (context-independent) knowledge is more valuable than concrete, practical (context-dependent) knowledge”, while on the contrary experts are those who collected a huge number of experiences, and not those who studied issues in theory; (2) it may seem unmanageable “to generalize on the basis of an individual case”, while on the contrary any scientific discovery is potentially subjected to be falsified according to Karl Popper; (3) it may seem that “the case study is most useful for generating hypothesis, … while other methods are more suitable for hypothesis testing and theory-building”, while on the contrary generalisability does have the potential to be achieved through an appropriate selection of the cases, based on clear criteria; (4) it may seem that “the case study contains a bias…, a tendency
At this purpose, the city of Boston appeared as an ideal field of analysis, considering the long tradition in terms of advocacy planning that dates back to the 60s (as excellently narrated by Gans [10]) and produced a vibrant urban community still active in terms of a considerable number of community-led initiatives [11].
CDCs allow to put into reality a fine grain of local enterprises, capable to stir the potential of the community in terms of entrepreneurship.
Nowadays, while crossing Washington Street, it is possible to appreciate the great number of new businesses in the area, lot of them locally rooted or run by entrepreneurs from minority groups, as well as it is possible to admire very well kept community gardens right in the heart of the neighborhood that testify the high level of engagement of the community in maintaining the urban environment.
In so doing, he discussed the five common misunderstanding still sometime plaguing the case study research approach, challenging each of them as follows: (1) it may seem that “general, theoretical (context-independent) knowledge is more valuable than concrete, practical (context-dependent) knowledge”, while on the contrary experts are those who collected a huge number of experiences, and not those who studied issues in theory; (2) it may seem unmanageable “to generalize on the basis of an individual case”, while on the contrary any scientific discovery is potentially subjected to be falsified according to Karl Popper; (3) it may seem that “the case study is most useful for generating hypothesis, … while other methods are more suitable for hypothesis testing and theory-building”, while on the contrary generalisability does have the potential to be achieved through an appropriate selection of the cases, based on clear criteria; (4) it may seem that “the case study contains a bias…, a tendency
At this purpose, the city of Boston appeared as an ideal field of analysis, considering the long tradition in terms of advocacy planning that dates back to the 60s (as excellently narrated by Gans [10]) and produced a vibrant urban community still active in terms of a considerable number of community-led initiatives [11].
CDCs allow to put into reality a fine grain of local enterprises, capable to stir the potential of the community in terms of entrepreneurship.
Nowadays, while crossing Washington Street, it is possible to appreciate the great number of new businesses in the area, lot of them locally rooted or run by entrepreneurs from minority groups, as well as it is possible to admire very well kept community gardens right in the heart of the neighborhood that testify the high level of engagement of the community in maintaining the urban environment.
Online since: June 2020
Authors: Anish Sachdeva, Sehijpal Singh, Mukesh Kumar, Rajiv Kumar Garg
By using ANOVA, the effect of factors can be estimated, and by orthogonal arrays, the minimum number of experiments are required.
(1) Where y is the observed data and n is the number of observations; decibel scale (dB) is used expressed the S/N ratio.
SE is the sum of squares due to error, ŋi is the ŋ value of each experiment (i = 1,… .,9), J is the number of experiments in the orthogonal array (in this work, J = 9), ŋAi is the sum of the ith level of parameter A (i = 1, 2, 3,), N is the repeating number of each level of parameter A, fA is the degree of freedom of parameter A and VA is the variance of parameter A.
X-ray diffraction analysis (XRD) is the technique to find out the Crystal structure, crystalline grain size.
(1) Where y is the observed data and n is the number of observations; decibel scale (dB) is used expressed the S/N ratio.
SE is the sum of squares due to error, ŋi is the ŋ value of each experiment (i = 1,… .,9), J is the number of experiments in the orthogonal array (in this work, J = 9), ŋAi is the sum of the ith level of parameter A (i = 1, 2, 3,), N is the repeating number of each level of parameter A, fA is the degree of freedom of parameter A and VA is the variance of parameter A.
X-ray diffraction analysis (XRD) is the technique to find out the Crystal structure, crystalline grain size.
Online since: June 2014
Authors: Bin Hu, Xiao Ning Zhang
Based on the principle of stereology, when the number of sections reaches, voidage average of sections will be, namely the true voidage of the asphalt mixture specimen.
The research takes the stereological method to speculate space distribution characteristics of aggregates with grain sizes at all levels and make fractal analysis for different gradations of asphalt mixtures to achieve a quantitative description of asphalt mixture gradation type.
The industrial CT scanning images for which the Otsu method cannot accurately divide different components can be divided into a number of overlapping annular sub-samples from internal to external and the Otsu method is used repetitively for the annular sub-samples to calculate grayscale thresholds of target and background.
After repeated comparisons of a number of materials, Yue-hua Duan et al [15] finally determined the technical solution of the epoxy resin and zirconium glass beads.
Industrial CT Technology-based Asphalt Mixture Virtual Mechanical Test Method Some scholars have carried out over a number of researches on the finite element virtual mechanical test of homogeneous asphalt mixtures, to find these virtual mechanical test methods subject to significant defects.
The research takes the stereological method to speculate space distribution characteristics of aggregates with grain sizes at all levels and make fractal analysis for different gradations of asphalt mixtures to achieve a quantitative description of asphalt mixture gradation type.
The industrial CT scanning images for which the Otsu method cannot accurately divide different components can be divided into a number of overlapping annular sub-samples from internal to external and the Otsu method is used repetitively for the annular sub-samples to calculate grayscale thresholds of target and background.
After repeated comparisons of a number of materials, Yue-hua Duan et al [15] finally determined the technical solution of the epoxy resin and zirconium glass beads.
Industrial CT Technology-based Asphalt Mixture Virtual Mechanical Test Method Some scholars have carried out over a number of researches on the finite element virtual mechanical test of homogeneous asphalt mixtures, to find these virtual mechanical test methods subject to significant defects.
Online since: July 2012
Authors: Hai Yan Zhong, Yong Zhu, Bo Zhou, Qi Zhi Long, Pei Zhu, Han Zhou Sun
Development of quantitative analysis of fatty acid for monitoring changes of fatty acid profile of camellia oil
ZHU Yong1, 2, 3, a, ZHONG Haiyan*, 1, 2, 3, b, SUN Hanzhou4, c,
ZHOU Bo1, 2, 3, LONG Qizhi1, 2, 3, ZHU Pei1, 2, 3
1Faculty of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China;
2National Engineering Laboratory for Further Processing of Grains, Changsha, 410004, Hunan, China;
3Hunan key Laboratory of Deeply Processing and Quality Control of Cereals and oils, Changsha, 410004, Hunan, China;
4Research Institute of Applied Chemistry, Central South University of Forestry and Technology, Changsha 410004, Hunan, China
a zhuyonghappycool@163.com, bzhonghaiyan631210@126.com, ceast0000000@126.com
Table 1 Linear regression equations of external standard and r2 of FAMEs standards (1.0-10.0 mg / L) NO. a linear regression equations r2 linear ranges ( mg / L ) 1 Y=0.0001X-0.1214 0.9968 1.193-9.544 2 Y=0.0001X+0.0265 0.9967 1.269-10.15 3 Y=0.0001X-0.3304 0.9966 1.116-8.928 4 Y=1.0×10-4 X -0.13 0.9941 1.160-9.280 5 Y=9.0×10-5 X -0.3136 0.9974 1.340-10.72 6 Y=1.0×10-4 X -0.1523 0.9965 1.099-8.792 7 Y=1.0×10-4 X -0.1297 0.9939 0.9030-7.224 8 Y=0.0001X-0.5352 0.9940 1.102-8.816 9 Y=0.0001X-0.2467 0.9945 0.8890-7.112 10 Y=9.0×10-5X-1.0417 0.9956 1.132-9.056 11 Y=1.0×10-4X+0.1306 0.9968 1.098-8.784 12 Y=1.0×10-4 X -0.3086 0.9962 1.246-9.968 13 Y=0.0001X-0.4814 0.9969 1.062-8.496 14 Y=0.0001X-0.2322 0.9953 1.022-8.176 15 Y=0.0001X+0.2094 0.9934 1.451-11.60 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table 2 Linear regression equations of external standard and r2 of FAMEs standards (10.0-100.0 mg/L) NO. a linear regression equations
r2 linear ranges ( mg/L) 1 Y=0.0001X+0.8510 0.9982 11.93-95.44 2 Y=9.0×10-5X+2.4925 0.9983 12.69-101.5 3 Y=9.0×10-5X+1.147 0.9963 11.16-89.28 4 Y=8.0×10-5X+3.0603 0.9975 11.60-92.80 5 Y=8.0×10-5X+3.5448 0.9944 13.40-107.2 6 Y=9.0×10-5X+0.2913 0.9990 10.99-87.92 7 Y=9.0×10-5X+1.1934 0.9983 9.030-72.24 8 Y=9.0×10-5X+1.1428 0.9978 11.02-88.16 9 Y=9.0×10-5X+2.1479 0.9982 8.890-71.12 10 Y=9.0×10-5X+0.9725 0.9935 11.32-90.56 11 Y=9.0×10-5X+1.1106 0.9990 10.98-87.84 12 Y=9.0×10-5X+1.0694 0.9989 12.46-99.68 13 Y=1.0×10-4X+1.2391 0.9981 10.62-84.96 14 Y=9.0×10-5X+2.0822 0.9980 10.22-81.76 15 Y=0.0001X+4.6399 0.9981 14.51-116.0 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table 3 Linear regression equations of internal standard and RRF NO. a linear regression equations r2 RRF b 2 Y=1.0443X+0.0052 0.9998 1.0443 3 Y=1.1009X+0.0069 0.9997 1.1009 5 Y=1.1173X-0.1203 0.9995 1.1173 6 Y=1.0719X+0.0117 0.9995 1.0719 7 Y=1.0783X-0.0035 0.9992 1.0783 8 Y=1.0638X
-0.0049 0.9966 1.0638 9 Y=1.0278X+0.0125 0.9979 1.0278 10 Y=1.0913X-0.0813 0.9924 1.0913 11 Y=1.0403X-0.0015 0.9982 1.0403 12 Y=0.9885X+0.1085 0.9961 0.9885 13 Y=0.9319X+0.0424 0.9973 0.9319 14 Y=1.0627X-0.0154 0.9981 1.0627 15 Y=1.0011X+0.0013 0.9974 1.0011 a The numbers reprensented the fatty acids which were corresponding to Fig.1 b The RRF was consistent with the K of the linear regression equations Table 4 Recovery of FAMEs standards when added to raw camellia oil ( internal standard ) The amount of added (mg) NO.a 1.000 2.000 The amount presented in GC The amount of added Recovery (%) The amount presented in GC The amount of added Recovery (%) 2 1.277 1.269 100.6 2.620 2.538 103.2 3 1.114 1.116 99.82 2.225 2.232 99.69 5 1.385 1.340 103.4 2.701 2.680 100.8 6 1.028 1.099 93.54 2.121 2.198 96.50 7 0.9348 0.9030 103.5 1.811 1.806 100.3 8 1.014 1.102 92.01 2.181 2.204 98.96 9 0.9481 0.8890 106.7 1.867 1.778 105.0 10 1.100 1.132 97.17 2.140 2.264 94.52 11 1.012 1.098 92.17 2.194
2.196 99.91 12 1.266 1.246 101.6 2.577 2.492 103.4 13 1.113 1.062 104.8 2.178 2.124 102.5 14 1.000 1.022 97.85 1.885 2.044 92.22 15 1.492 1.451 102.8 2.923 2.902 100.7 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table5 Detection and quantitation limit of 15 FAMEs standards analyzed by GC Fatty acid methyl esters DL (ppm)a QL(ppm)b C11:0 0.09278 0.3093 C12:0 0.09198 0.3066 C14:0 0.08582 0.2861 C15:0 0.1035 0.3451 C16:0 0.1080 0.3601 C16:1-9t 0.1117 0.3722 C16:1-9c 0.1200 0.4000 C18:0 0.1365 0.4551 C18:1-9t 0.1338 0.4461 C18:1-9c 0.1338 0.4461 C18:2-9t12t 0.1305 0.4351 C18:2-9c12c 0.1167 0.3890 C20:0 0.1129 0.3763 C18:3-9c12c15c 0.1130 0.3766 C22:0 0.1348 0.4492 a DL: limit of detection based on S/N3.
Table 1 Linear regression equations of external standard and r2 of FAMEs standards (1.0-10.0 mg / L) NO. a linear regression equations r2 linear ranges ( mg / L ) 1 Y=0.0001X-0.1214 0.9968 1.193-9.544 2 Y=0.0001X+0.0265 0.9967 1.269-10.15 3 Y=0.0001X-0.3304 0.9966 1.116-8.928 4 Y=1.0×10-4 X -0.13 0.9941 1.160-9.280 5 Y=9.0×10-5 X -0.3136 0.9974 1.340-10.72 6 Y=1.0×10-4 X -0.1523 0.9965 1.099-8.792 7 Y=1.0×10-4 X -0.1297 0.9939 0.9030-7.224 8 Y=0.0001X-0.5352 0.9940 1.102-8.816 9 Y=0.0001X-0.2467 0.9945 0.8890-7.112 10 Y=9.0×10-5X-1.0417 0.9956 1.132-9.056 11 Y=1.0×10-4X+0.1306 0.9968 1.098-8.784 12 Y=1.0×10-4 X -0.3086 0.9962 1.246-9.968 13 Y=0.0001X-0.4814 0.9969 1.062-8.496 14 Y=0.0001X-0.2322 0.9953 1.022-8.176 15 Y=0.0001X+0.2094 0.9934 1.451-11.60 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table 2 Linear regression equations of external standard and r2 of FAMEs standards (10.0-100.0 mg/L) NO. a linear regression equations
r2 linear ranges ( mg/L) 1 Y=0.0001X+0.8510 0.9982 11.93-95.44 2 Y=9.0×10-5X+2.4925 0.9983 12.69-101.5 3 Y=9.0×10-5X+1.147 0.9963 11.16-89.28 4 Y=8.0×10-5X+3.0603 0.9975 11.60-92.80 5 Y=8.0×10-5X+3.5448 0.9944 13.40-107.2 6 Y=9.0×10-5X+0.2913 0.9990 10.99-87.92 7 Y=9.0×10-5X+1.1934 0.9983 9.030-72.24 8 Y=9.0×10-5X+1.1428 0.9978 11.02-88.16 9 Y=9.0×10-5X+2.1479 0.9982 8.890-71.12 10 Y=9.0×10-5X+0.9725 0.9935 11.32-90.56 11 Y=9.0×10-5X+1.1106 0.9990 10.98-87.84 12 Y=9.0×10-5X+1.0694 0.9989 12.46-99.68 13 Y=1.0×10-4X+1.2391 0.9981 10.62-84.96 14 Y=9.0×10-5X+2.0822 0.9980 10.22-81.76 15 Y=0.0001X+4.6399 0.9981 14.51-116.0 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table 3 Linear regression equations of internal standard and RRF NO. a linear regression equations r2 RRF b 2 Y=1.0443X+0.0052 0.9998 1.0443 3 Y=1.1009X+0.0069 0.9997 1.1009 5 Y=1.1173X-0.1203 0.9995 1.1173 6 Y=1.0719X+0.0117 0.9995 1.0719 7 Y=1.0783X-0.0035 0.9992 1.0783 8 Y=1.0638X
-0.0049 0.9966 1.0638 9 Y=1.0278X+0.0125 0.9979 1.0278 10 Y=1.0913X-0.0813 0.9924 1.0913 11 Y=1.0403X-0.0015 0.9982 1.0403 12 Y=0.9885X+0.1085 0.9961 0.9885 13 Y=0.9319X+0.0424 0.9973 0.9319 14 Y=1.0627X-0.0154 0.9981 1.0627 15 Y=1.0011X+0.0013 0.9974 1.0011 a The numbers reprensented the fatty acids which were corresponding to Fig.1 b The RRF was consistent with the K of the linear regression equations Table 4 Recovery of FAMEs standards when added to raw camellia oil ( internal standard ) The amount of added (mg) NO.a 1.000 2.000 The amount presented in GC The amount of added Recovery (%) The amount presented in GC The amount of added Recovery (%) 2 1.277 1.269 100.6 2.620 2.538 103.2 3 1.114 1.116 99.82 2.225 2.232 99.69 5 1.385 1.340 103.4 2.701 2.680 100.8 6 1.028 1.099 93.54 2.121 2.198 96.50 7 0.9348 0.9030 103.5 1.811 1.806 100.3 8 1.014 1.102 92.01 2.181 2.204 98.96 9 0.9481 0.8890 106.7 1.867 1.778 105.0 10 1.100 1.132 97.17 2.140 2.264 94.52 11 1.012 1.098 92.17 2.194
2.196 99.91 12 1.266 1.246 101.6 2.577 2.492 103.4 13 1.113 1.062 104.8 2.178 2.124 102.5 14 1.000 1.022 97.85 1.885 2.044 92.22 15 1.492 1.451 102.8 2.923 2.902 100.7 a The numbers reprensented the fatty acids which were corresponding to Fig.1 Table5 Detection and quantitation limit of 15 FAMEs standards analyzed by GC Fatty acid methyl esters DL (ppm)a QL(ppm)b C11:0 0.09278 0.3093 C12:0 0.09198 0.3066 C14:0 0.08582 0.2861 C15:0 0.1035 0.3451 C16:0 0.1080 0.3601 C16:1-9t 0.1117 0.3722 C16:1-9c 0.1200 0.4000 C18:0 0.1365 0.4551 C18:1-9t 0.1338 0.4461 C18:1-9c 0.1338 0.4461 C18:2-9t12t 0.1305 0.4351 C18:2-9c12c 0.1167 0.3890 C20:0 0.1129 0.3763 C18:3-9c12c15c 0.1130 0.3766 C22:0 0.1348 0.4492 a DL: limit of detection based on S/N3.
Online since: April 2024
Authors: Mahesh Gopal, Endalkachew Mosisa Gutema, Dame Alemayehu Efa, Hirpa G. Lemu
The results reveal that defect-free joints may be obtained by employing taper and screw-threaded cylindrical pins and that greater rotational speed and lower traverse speed result in larger grain sizes and, as a result, inferior mechanical characteristics [5].
At each simulation time step, complete re-meshing involves, splitting the workpiece into a finite number of meshes.
ALE allows independent mesh movement from material and high-quality meshing in the analysis, so nodes and the number of elements do not vary.
Table 1 Meshed Result Description Value Mesh vertices 8439 Prisms 828 Hexahedra 5010 Triangles 828 Quads 5862 Edge elements 892 Vertex elements 40 Number of elements 5838 Minimum element quality 0.5799 Average element quality 0.9184 Element volume ratio 0.0031966 Mesh volume 6.25x106 mm3 IV.
Acknowledgment This research was supported by INDMET project; grant number 62862 funded by the NORHED II program.
At each simulation time step, complete re-meshing involves, splitting the workpiece into a finite number of meshes.
ALE allows independent mesh movement from material and high-quality meshing in the analysis, so nodes and the number of elements do not vary.
Table 1 Meshed Result Description Value Mesh vertices 8439 Prisms 828 Hexahedra 5010 Triangles 828 Quads 5862 Edge elements 892 Vertex elements 40 Number of elements 5838 Minimum element quality 0.5799 Average element quality 0.9184 Element volume ratio 0.0031966 Mesh volume 6.25x106 mm3 IV.
Acknowledgment This research was supported by INDMET project; grant number 62862 funded by the NORHED II program.