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With respect to precedent work [5], the experimental protocol and the data analysis of X-ray micro-diffraction have been improved and validated to get reliable results.
Following a data collection strategy, a 20 x 30 µm area of the electrolyte surface has been scanned in white beam mode with a 1 µm step.
Thanks to an in-line data analysis, monochromatic measurements have been performed at the center of the grains studied with a scan step of 1 eV.
To ensure stable and reliable data processing, a specific process with different check points has been developed.
The measurement protocol and the data analysis have been validated using two test samples: a stress-free single crystal of germanium that allows calibrating white beam measurements and a stress-free 8YSZ poly-crystal.

A schedule was designed in order to maintain an approximate reduction of 20% between each rolling pass, allowing achieving a final thickness of 0,2 mm for a total reduction of 98% after 12 passes, without any interpass annealing.
Fig. 2(b) further depicts the average values of the effective shear strain (the data scatter bars represent the standard deviation) as a function of the imposed asymmetry ratio.
Despite the wide range of R values (from 1 to 2) initially considered, the data demonstrate that, for the present alloy and for the selected reduction per pass of 20%, R values exceeding 1,6 were inappropriate since the increased shear strain could not be totally transferred to the processed material.
From these experimental data it can be observed that alternate asymmetric rolling is more effective in increasing the crystallite misalignment with respect to unidirectional ASR.
Comparison between unidirectional and alternate ASR for the 5083 (a) and 6082 (b) alloys rolled by asymmetry ratio of 1,2 From the data gathered in figures 6 and 7, it can be stated that hardness significantly increases for both alloys after the first rolling passes (the data point at equivalent strain of 0,77 corresponds to the third pass) whereas, when approaching the highest strain levels, hardness saturates at about 90 and 160 HVn for the 6082 and 5083 alloy, respectively.

Citation & Copyright (to be inserted by the publisher ) Al/Ti Ohmic Contacts to P-type Ion Implanted 6H-SiC: Mono- and TwoDimensional Analysis of the TLM Data F.
Extracted contact resistivity values fall in the low range of data from the literature.
In the case of our experimental data we noted that this reduction (Rc(1D) – Rc(2D)) is always between 20 and 30 Ohm.
In particular, at 290°C the value extracted using the 1D model is 2.3×10-5 Ωcm2 (to be compared with 5×10-4 Ωcm2 at room temperature), which is in good agreement with data from the literature [1]-[5].
We choose to plot 1D results since most of the literature data come from such an analysis.

The data shown in this Table indicates that the plastometric modeling was conducted in two stages.
In the first series of the tests, deformation with a total reduction – 1.15 set in 10 passes was modeled, while in the second series, a total reduction of – 1.12 was set in 11 passes.
Distributions of σp values in successive passes in the process of forging a 190×190 [mm × mm] square cross-section E635М alloy forging from a 445 mm-diameter ingot; a) in passes 1–10, b) in passes 11–21; according to the industrial technology From the data shown in Figure 1 it can be found that the distribution of yield stress values during successive passes, and thus forging pressure forces, is non-uniform.
The data shown in the Figure above indicates that, due to the reduction of the number of passes in this particular forging scheme, the yield stress value practically did not change in the entire loading cycle.
It can be noticed that in this particular reduction scheme (Fig. 2), it could be possible to reduce the magnitude of single reductions εi in the first three passes, as well as in passes 16 and 17, by reducing simultaneously the single reductions in passes 4–6 and 9–12.

The standardization and reference data for physical property evaluation are necessary as well as the development of high purity materials by physical or chemical refining.
In this study, physical (thermal, electrical and mechanical) properties of Nb and Ta rare metals with various purities were investigated to obtain the fundamental data on the physical purity evaluation. 2.
This is due to the reduction of impurity effects on the electrical resistivity according to the Matthiessen rule [5].
Conclusions Physical properties of Nb and Ta metals with various chemical purities were investigated to obtain the fundamental data on the physical purity evaluation.
Data, Vol. 13, No. 4 (1984), p.1069

Hence, it is of great significance to do well in energy-saving and emission-reduction.
The measures of energy-saving and emission reduction taken by the enterprises are as shown in Table 1.
These measures bring an obvious effect in energy-saving and emission reduction, as shown in Table 2.
Typical enterprise has gained more apparent effect in energy-saving and emission reduction.
Xiao-yuan Wang and Xiao-juan Zhang for their assistances in data gathering.

N2 adsorption/desorption data show that the highest surface area of aerogel fibers reached 241.6 m2/g with the average pore diameter about 10 nm.
With the reduction of the TiO2 content, the fiber continuity of the sample decreases, and the fracture becomes more severe.
With the reduction of the TiO2 content, the porosity of fibers increased gradually.
When MPVP: MTiO2 is more than 2.13, the porosity of aerogel fiber gradually decreases with the reduction of the TiO2 content.
The BET surface area, pore volume, and average pore diameter calculated from the N2 adsorption data are listed in Table 1.

For the variable specific surface area, using the data of Table 4 and the factorial experimental design, the Table 5 was obtained.
Table 5.24 experimental factorial designs –Estimated effects and coefficients for the data of Table 4.
Figure 3 shows the x-ray diffraction data of sample 5.
The x-ray diffraction data shows that samples 1 and 2 have 100% and 96.3% of a-alumina.
Statistics for experimenters: an introduction to design, data analysis, and model building.

When attribute in information system (is the set of condition attributes, is the set of decision-making attributes, an information system may be indicated conveniently with the data tabular form, therefore, information system is also called decision table.
RS is used to Discreting Sample Data.
Using the dynamic reduction method, with the help of SOM neural network, the paper carries on the reduction to the decision system (Table 2), and obtains reduction of , where .According to the actual situation in engineering fields, this article chooses the reduction of the smallest reduction .
Then, the data of sample 8 is used to be monitoring sample.
The evaluation model based on AHP-RS and RBF neural network realizes the advantages of the three parties and makes up for their deficiencies, and more, SOM neural network is used to discrete the continuous data, all which make the evaluation model more scientific and reasonable for grasping the hydropower project financing risk.

With the inclusion of CCGS as Clean Development Mechanism (CDM) project activity, companies will invest more on CCGS projects due to the possibility of generating Certificated Emission Reduction (CER).
Through data on emission and capture of CO2 [1,2,3], published in technical and scientific reports and articles, such as emissions inventories, it was possible to calculate the total emissions and those that can be captured from four industrial enterprises in the state of Rio de Janeiro that emit large quantities of carbon gas: the CSN and CSA steel mills, the REDUC refinery and the COMPERJ petrochemicals complex.
Source: Authors - Data: ANP [1], CDP [2] & Ecofys [3] Total Emissions (tCO2/year) Emissions Captured (tCO2/year) REDUC 2,510,698.86 2,259,628.98 CSA 5,700,000.00 2,850,000.00 CSN 11,958,667.00 5,979,333.50 COMPERJ 1.863.695.64 1.677.326.07 TOTAL 22,033,061.50 12,766,288.55 By preparing a map (Figure 1) through the SIG interface, it was possible to calculate the distances between the emission sources and the production fields, permitting calculation of the expenses.
Source: Authors - Data: ANP [1] For injection of CO2 (Figure 2), 18 injection wells were chosen (6 in Barracuda and 12 in Marlim), associated with four platforms of Petrobras, two semi-submersible platforms P-19 and P-26 and two Floating Production and Storage Offtake platforms (FPSOs) P-37 and P-43.
Source: Authors - Data: ANP [1] The extra production of crude oil because of the CO2 injection in the reservoir was calculated at 22.5 million barrels a year, which 13.8 million were from Marlim (4.5 ton of CO2 per ton of oil) and 8.5 million from Barracuda (3.7 ton of CO2 per ton of oil) [6].