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The indentations were obtained with a Berkovich diamond indenter, applying the Oliver and Pharr model [10] for data analyses.
All data reported in the present work are average values over ten measurements for each load.
From figure 1 it is clear in fact that the introduction of hydrogen produced a visible reduction in the average roughness of the films.
AFM measurements showed a strong reduction of the columnar grains size (from 900 nm per films deposited in pure Ar to around 400 nm for those deposited in Ar/H2 atmosphere) and a similar reduction of the RMS roughness.
The observed hardness maximum can be therefore explained by the reduction of the grains size, probably due to the Hall-Petch behavior [18].

Consequently, data on weld repairs are scarce.
Furthermore, the availability of experimental data on weld repair effects on the fatigue behavior may be very useful in determining inspection intervals in critical welded structures.
On the other hand, one can also observe the axial fatigue strength reduction of the BM with the original welding (OR) application, for both low (<105) and high (>105) fatigue cycles (LFC and HFC, respectively), whose endurance limit was about 47% of the AISI 4130 yield strength.
A subsequent reduction of the axial fatigue strength is observed when 1R is applied, now with the endurance limit crossing down σn in HFC.
From Fig. 5, with exception to 3R condition and the WM regions, it is observed that all the HAZ sub-regions presented reduction of the microhardness values from FGHAZ (Fine-Grain HAZ) to BM, naturally.

This reduction was achieved in 11 passes.
This measured data was not sufficient for FEM simulation of cold rolling.
JMatPro calculates thermo-mechanical properties from chemical composition data.
The material model used for FEM simulation of cold rolling was constructed by merging measured data from Rastegaev compression test and the data calculated in JMatPro software (Fig. 7).
Overall, all computed data for the three nickel alloys were very similar.

In the year of 2007, Weibo Yang and Mingheng Shi ascribed the operation characteristics of water to water heat pump to 8 undetermined characteristic parameters, according to which they built a characteristic parameters optimized predication model of heat pump utilizing sample data to predict those undetermined parameters [3].
On this base, this paper builds computational models of the WSHP unit in WSHP system; those are energy models of evaporator and condenser, power consumption model and adiabatic compression model of compressor, throttle model of throttle mechanism as well as the data model of refrigerant (R22 is adopted in this paper).
Figure 2 a) shows that COP of the system increases with the rise of evaporating temperature or the reduction of condensing temperature, and the COP decreases with the reduction of evaporating temperature or the rise of condensing temperature; b) indicates that the heating capacity goes up when condensing temperature rises or evaporating temperature reduces, it drops when condensing temperature lessens or evaporating temperature ascends.
According to the definition of the influence rate and the data of the charts, the influence rate of evaporating temperature (3 to 10 ℃) relative to COP can be calculated, that is 2.25%; The influence rate of condensing temperature (50 to 55 ℃) relative to COP also can be calculated, that is 2.61%; By the same rule，the influence rate of evaporating temperature (3 to 10 ℃) relative to heating capacity is 1.32% and that of evaporating temperature (3 to 10 ℃) relative to heating capacity is 1.09%.
Design temperature data for surface water heating and cooling systems.

Table 1 Value-added of the Three Strata of Industry & Its Composition of the GDP in TBNA Year Primary Industry Secondary Industry Tertiary Industry [Billion yuan] [%] [Billion yuan] [%] [Billion yuan] [%] 2004 7.9 0.6 87.9 66.4 43.7 33.0 2005 7.3 0.5 109.9 67.7 51.7 31.9 2006 7.5 0.4 137.1 69.9 58.2 29.7 2007 7.2 0.3 169.4 71.7 66.2 28.0 2008 7.5 0.2 224.6 72.4 84.8 27.4 Data source.
Table 4 Primary Energy Consumption & Its Composition of Industrial Sector in TBNA, 2004-2008 Item 2004 2005 2006 2007 2008 Total Consumption [m tce] 17.8 21.9 23.7 28.6 26.3 Coal Products [m tce]/ [%] 5.1/28.4 7.9/36.1 8.7/36.8 12.8/44.8 12.3/46.7 Petroleum Products [m tce]/ [%] 12.4/69.6 13.7/62.4 14.4/60.8 15.1/52.7 13.1/49.8 Natural Gas [m tce]/ [%] 0.4/2.0 0.3/1.6 0.6/2.4 0.7/2.6 0.9/3.5 Data source.
Table 5 Comparison of the Energy Consumption by Industrial Added-Value per 10 000 yuan [tce/10 000 yuan] 2005 2006 2007 TBNA 0.950 0.797 0.807 Shanghai Pudong New District 0.900 0.830 0.600 Shenzhen Special Economic Zone 0.600 0.570 0.550 Shanghai 1.180 1.200 1.006 Beijing 1.500 1.330 1.188 Tianjin 1.450 1.330 1.220 China 2.590 2.530 2.730 Data source.
It will capture the lead edge of technological information, make evaluations on the emission reduction potential and technology maturity degree, and thus invest in low-carbon technology which meets the requirement.
With the implementation of Kyoto Protocol, the corresponding industry and the market of emission reduction technology will gradually form.

In order to weaken the dangers of vibration, vibration reduction technology has become a research hot spot[1-2].
Through the characteristics of the material to absorb or change the mechanical energy into heat energy or electricity, etc, to achieve the effect of damping vibration reduction; Active damping to reduce the vibration is an important branch of active control, with the cooperation of the sensing unit, driving unit and controlling unit, it exercise its restraints upon the vibration, then it realizes the role of vibration reduction.
The controller compare the collected data with a reference value, then calculate the new input values using the difference between the collected data and the reference value, it lets the system data to achieve or maintain the reference.
PID controller can adjust the input values based on historical data and the rates of difference, so that we can make the system more accurate and stable[7].

The temperature and force data are collected at the meantime.
The milling force data is collected at the meantime by dynamometer and dynamic data collection system, and milling force data in x, y and z direction is obtained [3].
Through A/D transfer and dynamic data collection system, the data of milling temperature and milling force were collected at the meantime.
Processing of Experiments Data Milling Force is Calibrated.
The data curve is also fitted.

Thus, energy saving and emission reduction have become an important and arduous task in the economic development for Jilin.
(2) DEA model and the related concepts of it 2.1 DEA model Data envelopment analysis (DEA), which is first proposed by Charnes, Cooper and Rhodes in 1978, is a non-parametric method for evaluating the efficiency and effectiveness of multiple Decision-making Units.
We make the comprehensive analysis of input and output data and obtain the index of the relative efficiency of every DMU.
Where, (xij and yrj are known data, generally we can get them through the historical data or forecast).
Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach[J].

Compared with a similarly rated silicon (Si) IGBT version, the SiC converter exhibits a 3% improvement in peak efficiency, 2.6 times reduction in total losses, and three times improvement in power density.
This is due to lower overdrive voltage at room temperature and reduction in the gate threshold voltage with temperature.
From this data the conduction loss for each switch in the DAB is estimated to be 25.7W under nominal conditions at a 25kW power transfer level.

Rainfall-Induced Slope Instability Rock Mixture Fluid - Structure Interaction Numerical Simulation Xiaonian She1,a , Helin Fu2,b , Zhong Zhou2,c 1Hunan Administration of Highway, Changsha, Hunan, 410007, China 2School of Civil Engineering, Central South University, Changsha, Hunan, 410075, China a sxn123@sina.com, b fuhelin100@yahoo.com.cn, c zhouz785@yahoo.com.cn Key words: Rainfall, Rock mixture, Slope instability, Fluid-structure interaction, Simulation Abstract: In this paper, did the numerical calculation of the mixture slope’s development and changes of the stress field, seepage field ,displacement field under fluid - solid coupling effects at different levels, researching and analyzing the water-rock interaction mechanisms of the mixture slope ,and based on strength reduction , calculated the slope safety factor at different water levels, revealed the failure mechanisms of a mixture of earth and rock slope when it considers the rainfall.
Introduction In this paper, numerical calculation of the different water flow when the mixture slope - solid coupling of the stress field, seepage field, displacement field of development and changes, research and analysis mixture slope of the water-rock interaction mechanisms, and based on strength reduction was calculated slope safety factor when different water levels, rainfall revealed a mixture of earth and rock slope failure mechanisms. 1 Model and calculation conditions for numerical analysis The literature [1] mixture slope field for the numerical simulation of artificial rainfall experiment object, engineering geological profile shown in Figure 4.
In laboratory and field test and field survey data, based on the slope of geotechnical parameters selected in Table 1.