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Constant friction factor m was considered, equal to 0.7 (calculated using an inverse approach using data from a preliminary numerical campaign).
In this study, the following process parameters were used: angular velocity to 5.235 rad/sec, reduction 50%.
Table 2: Comparison simulation data for the LFW and ARB processes Concerning the obtained data, it can be observed that in ARB process high pressure and strain rate are reached, while for LFW high temperature values are reached.
As a matter of fact, the reference time is related to the beginning of bonding, i.e. when the axial shortening, namely the reduction in height of the specimen, [4] has not occurred yet.
From the reported data, it can be concluded that pressure and temperature seems to be as the two most influencing variables for effective bonding.

It was found that the gradual replacement of cement with recycled concrete causes reduction of the dynamic Young's modulus and decreases the size of the increase in strength during the first 28 days.
Their results showed that up to 30 % coarse REC had no effect on concrete strength, but thereafter there was a gradual reduction as the REC content increased [2].
In Table 1 we can see data of the mixture of the individual sets.

The second step is to use these surface strains to identify a stiffness reduction map for real impact damages.
-H., Pierron F., Wisnom M., Syed-Muhamad K., Identification of the local stiffness reduction of a damaged composite plate using the virtual fields method, Composites Part A: Applied Science and Manufacturing, vol. 38, n° 9, pp. 2065-2075, 2007
[6] Avril S., Feissel P., Pierron F., Villon P., Comparison of two approaches for controlling the uncertainty in data differentiation: application to full-field measurements in solid mechanics, Measurement Science and Technology, vol. 21, 015703 (11 pp), 2010.

Both simulated data and experimental data obtained from a steel plate with a crack are used to demonstrate the performance of the proposed method.
Ultrasonic data collected in TOFD experiments may be noisy.
The noise may be caused by the surrounding environment, transducers, the data acquisition system and other unknown sources.
The SNR reduction needs further improvement.
Since the time of flight can be accurately obtained from collected ultrasonic data, we can use it to get accurate estimate of the crack depth using data such as the distance between the transducers and the ultrasonic speed in the specimen material.

It indicated that the layout of stiffeners is an influence factor for noise reduction for plate structures, just like that of vein layout for tree belts.
In recent years, researchers have become increasingly interested in the noise reduction.
is beam element stiffness matrix in the original coordinate system established with axle wire of the stiffener as datum line.
It indicates that the venations layout affect the noise reduction capacity for plate structures just as it does for plant leaves.
[5] Chih-Fang Fang, Der-Lin Ling, Guidance for noise reduction provided by tree belts, Landscape and Urban Planning. 71 (2005) 29-34

The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.
Forest fire disaster area prediction based on genetic algorithm and support vector machine is presented in the paper.Genetic algorithm is used to select appropriate parameters of support vector machine[3,4].The computation process of the parameters of support vector machine by using genetic algorithm is given.The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data,where the forest fire disaster area data in Jiangxi Province from 1970 to 1989 are used to select the parameters of support vector machine and train the proposed GA-SVM model,and the forest fire disaster area data in Jiangxi Province from 1990 to 1997 are used to test the proposed GA-SVM model.
Experimental Analysis As shown in Fig.1, forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.
Forest fire disaster area data in Jiangxi Province from 1970 to 1997 Fig.2.
The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data.The comparison of the forest fire disaster area forecasting results between the proposed GA-SVM model and the SVM model indicates that the proposed GA-SVM model has more excellent forest fire disaster area forecasting results than the SVM model.

Furthermore, as most of the thermal energy supplied was primarily used in diffusion for homogenisation, in agreement with the shrinkage data of Figure 2, the densification of the samples was quite limited.
From the data of the density and porosity shown in Figure 4, it seems that there is a proportionality between the sintering temperature and the physical properties of the alloys.
Density data show that the Ti-7.1S alloy has higher density than the Ti-5.1S alloy.
However, this is primarily due to the greater amount of alloying contemplated in the alloy composition, whose density is higher than that of Ti, as the porosity data reveal that the two alloys have comparable residual porosity with possibly the exception of the alloys sintered at 1300ºC.
Consistently with the data plotted in Figure 4, the hardness of the low-cost Fe-bearing PM Ti-5.1S and Ti-7.1S alloys increases with the sintering temperature as the residual porosity is reduced and the composition of the material becomes more homogeneous.

After the treatment microstructural analysis is performed and correlated to the acquired conductivity data.
Since no difference could be seen from samples treated with/without constant current no specific data is presented concerning the experiments without current.
No difference could be seen between samples treated with/without constant current and therefore only data from samples treated under constant current is presented.
Data presented for the reference sample is an average from 3 samples.
However the density of percolated Ni particles is similar for both samples when data from SEM-CC is considered.

Table 1 Materials of enclosure structure and thermal engineering parameters Standard 50% Energy-saving 65% Energy-saving standard Names of enclosure structure Materials of enclosure structure Parameters for heat transfer [W/m²•K] Materials of enclosure structure Parameters for heat transfer [W/m²•K] Exterior wall Concrete wall + Polystyrene board insulation 0.56 Ferroconcretewall + EPSInsulation board 0.50 Exterior window Standard exterior window 2.50 Inert gas + low-e membrane clothing 2.00 Inner wall ceramsite concrete inner wall 1.35 Concrete hollow block 1.20 Roofing Aerated concrete insulation roofing 0.50 Lightweight steel frame 0.45 Floorslab Ferroconcrete floorslab 3.06 Extruded polystyrene insulation board 1.11 3.2 The Setting up of Parameters for Calculation We separately set the parameters of the tow calculating modes carrying out respectively “50% energy-saving standard” and “65% energy-saving standard.Meteorological data used in calculation are all data
Results from calculation 4.1 Analysis of Energy-saving Ability Analytical data of energy-saving ability and economy from the two operating modes are shown in table 3.
From data from table 3 we know that when implementing “50% energy-saving standard”, building 3 has a annual coal consumption for heating of 28.55kg / m2; after implementing “65% energy-saving standard”, the annual coal consumption for heating is lowered to 22.75kg/ m2，which means that for every meter we can save 5.8kg coal.
Analysis of emission reduction.
[5] Bai Li etc, Analysis of Emission Reduction of Heat Pump Air Conditioning System with Sewage Source [J], Power Demand Side Management, 2008（3）:p33-36.

An increase in Tg of nanocomposites epoxy/clay was observed by Kaviratna [3], while Massam [4] observed a reduction in Tg of the material.
These considerations make XRD data only a useful approximation to the nanostructure.
These results are consistent with the literature [5,12], where the authors have shown that there is a direct correlation between the data and the XRD data with transmission electron microscopy (TEM).
The data are shown in Table 2 and Figure 4.
These results can be attributed to a high aspect ratio of clay dispersion in polymer matrix that can act as physical crosslinker whereas the epoxy resin was intercalated in the galleries of the clay forming a predominantly exfoliated structure, as indicated by XRD data shown in Figure 3.