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In this study, reduction-oxidation cycles under different temperatures were analyzed.
The kinetic of the reduction reaction for oxygen carriers has been carried out by using TGA.
Seen from the DTG curves, there were two obvious weight loss peaks at about 450 °C and 790 °C respectively during reduction stage.
TG curves Figure 2 (a) Non-isothermal reduction curves between Fe2O3/γ-Al2O3 oxygen carriers; (b) CO at different temperatures.
The non-isothermal kinetic data were analyzed by using Coats-Redfern equation.

The complex-impedance analysis results showed that the reduction in dielectric loss of CCST-M-1 sample can be attributed to the increase of grain boundary resistance.
The real circles are the experimental data and the line is the Arrhenius fitting.
Fig.3 Temperature dependence of the dielectric constant for dielectric relaxation in CCST-M-1 ceramics, the real circles are the experimental data and the line is the linear fitting.
Fig.4 Frequency dependence of tand for the CCTO and CCST-M-100x ceramics at room temperature Fig.5 Complex impedance plots (Z² vs Z¢)for CCST-M-100x samples (a); and an enlarged view of (a) for the high frequency data close to the origin (b).
It may be suggested that the reduction in dielectric loss of CCST-M system can be attributed to the grain boundary effect.

OA-capped Cu nanoparticles as an additive in PAO10 perform good anti-wear and friction-reduction properties.
It is well known that several kinds of methods have been used to synthesize Cu nanoparticles, such as thermal reduction, chemical reduction, ion implantation, vacuum vapor deposition, two-phase method.
For each sample, three identical tests were performed so as to minimize data scattering.
The CO and CO2 enwrapping the nanoparticles forms reduction ambience.
So the addition of OA- capped Cu nanoparticles can effectively improve the friction-reduction properties of PAO10.

The copper samples were further processed by cold rolling (CR) to a strain of 0.67 (about 50% reduction).
The half sectioned (6.75 x 15 mm2) specimens were cold rolled to a strain of 0.67 (~ 50% reduction).
Mean Vickers hardness (VHN) data after ECAE and ECAE + CR Tensile strength and % Elongation at Fracture.
Figure 4b shows the microstructure of copper billet cold rolled to 50 % reduction at room temperature.
Optical micrographs of copper (a) starting material, annealed at 700 °C for 2h; (b) starting material cold rolled to 50% reduction; (c) ECAE, pass 3A and (d) pass 3A ECAE+CR.

The major disadvantage of these creep equations used in these calculations is that they require creep rupture strain data of the materials.
The creep test data is illustrated in Fig 2.
The material constants P, Q, n, et al used in creep-relaxation conversion model were derived from creep testing data.
The predicted results are compared with the data of stress relaxation tests conducted on bolting steel 1Cr10NiMoW2VNbN.
Wada: Collection and Uses for Relaxation Data in Design ( ASME, USA 1989), pp.15-19

The range of validity of the method is studied comparing results to experimental data.
The results will compare numerical to experimental data.
The total simulation time for spectral data comparisons is 0.5 seconds.
The post-processing for the experimental measurements data was performed with equivalent signal processing used for the computational simulation.
Results The comparison between the experimentally measured data and the CAA prediction is showed for a probe point by Figure 1.

An integrated mathematical model of the thermal condition of metal is realized as an application (Fig.2) adapted to real time operation based on the information from the server of the metal control system data base.
Such an analysis made it possible to form a data base of such defects (more than 1000 images), with the mill's individuality taken into consideration.
Based on the experimental data received at 2030 and 1400 Mills, an algorithm was developed to produce a criticality code (ranged between 0 and 7) depending on the steel grade, type of a defect, its location (edge or centre), and linear dimensions.
And a final result will be a stability of the rolling process, reduction in production costs, improvement in quality and competitiveness of metal products.
a) A Picture of the Strip Defect Selection of an Image from the Data Base b) Request Parameters Provision of Information on Request Rolling Date Steel Grade Strip Dimension Defect Type Geometry of Defect Information on the Defect An Image of the Defect c) Cause: Operating Roll of F7 Stand Defect Type: Roll Mark Fig. 4.

For this, the Chinese standard Code for Design of Steel Structures (GB50017-2003) [1] is according to the formula of axial compression and introduced a coefficient η reduction on steel strength design values.
Shilun Shi and others [6] through the comprehensive experimental results with domestic and abroad relevant data, studied of one-sided bolt connecting single angle steel, put forward different calculation formula for different computing length interval.
So by using the large engineering finite element software ANSYS, carrying on the modeling from the common equilateral angle steel in 110kV, 220kV and 500kV transmission towers, and comparing with non-equilateral angle steel data to get replacement conditions.
Table 1 Comparison between experimental data and the simulation values Angle steel specification Length [mm] Yield strength [MPa] Experimental data [kN] Simulation values [kN] Errors L45×5 739 280 66 66.98 1.48% L56×5 990 280 77.6 79.8 2.84% L56×5 737 280 79.3 82.56 4.11% L110×7 3074 235 154.37 146.34 -5.2% L100×8 3543 345 129.54 137.74 6.33% The results of analysis Through to the modeling analysis of 23 kinds of equilateral angle steels and 23 kinds of non-equilateral angle steels (the long-side and short-side connection working condition should be considered), and comparing the results, due to space limitations, it gives some comparison charts [Fig. 6].
For example, when the length of L63×6 is shorter than 1215mm, the section area of L63×40×7 is smaller than L90×56×5 and the buckling force of L63×40×7 is higher, so in this range we’d better to choose L63×40×7. 4) Through more contrast, to obtain substitution table of angle steels that is shown in Table 2: Table 2 Substitution table of angle steels (parts) Original angle steels Replacement Length range[mm] Non-equilateral angle steels Connection method section area reduction [cm2] section area reduction [%] Weight reduction [kg/m] L50×5 (0,910] L70×45×4 L 0.25 5.21 0.19625 [2113,+∞) S L70×8 (0,1451] L75×50×8 L 1.2 11.25 0.942 (1451,1501] L80×50×8 L 0.8 7.5 0.628 L75×8 (0,1366] L80×50×8 L 1.63 14.17 1.27955 (1366,1541] L100×63×7 L 0.4 3.48 0.314 (1541,1661] L90×56×8 L 0.3 2.61 0.2355 L80×6 (0,1137] L70×45×7 L 1.74 18.51 1.3659 (1137,1309] L90×56×6 L 0.84 8.94 0.6594 (1309,1425] L80×50×7 L 0.68 7.23 0.5338 L80×7 (L,1472] L75×50×8 L 1.39 12.8 1.09115 L80×8 (L,1381] L100×63×7 L 1.2

The removal of the data correlation is the obvious characteristics of wavelet transform which makes it become the mainly theoretical basis of the wavelet threshold shrinkage method.
Table.1 PSNR comparison by application of different denoising threshold functions Performance indicators Hard threshold Soft threshold Improved threshold PSNR(db) 80.2977 85.5973 86.4144 The data in Table 1 shows that the peak signal-to-noise ratio is higher than the application of traditional soft and hard threshold results.
Table.2 MSE comparison by application of different denoising threshold functions Performance indicators Hard threshold Soft threshold Improved threshold MSE 2.6439×10-4 1.7921×10-4 1.4857×10-4 The data in Table 2 shows that the mean squared error is lower than the application of traditional soft and hard threshold results.
Compared to the application of the traditional soft and hard threshold function noise reduction, the application of improved threshold function could get a better peak signal-to-noise ratio, mean square error and noise reduction effect.
[7] D.L.Donoho,Nonlinear Wavelet Methods for Recovery Signals,Densities,and Spectra from Indirect and Noisy Data[J].Proc.of Symp,1993,100:173-205 [8] D.L.Donoho, I.M.Johnstone.

Abdeen Mustafa Omer (2007) thought that we should be energy conservation and emissions reduction.
After reviewing and collecting relevant data, consulting relevant experts and carrying out other methods, we implement the preliminary screening of these indicators on the basis of the actual situation.
Specific building process, the first is the indicator reduction and filtering.
Rough set theory cannot deal directly with continuous indicator, so before the application of rough set methods of indicator screening, we should first through continuous indicator data discretization processing into discrete indicator data.
After scoring data preprocessing, we can get the evaluation indicator information table (see table 2).