Search results

As shown in the survey data issued at the C40 Large Cities Climate Summit on May 19, 2009, 80% of global greenhouse gas emissions come from urban areas occupying only 2% of the earth's surface[1].
Data Source and Methodology As it is impossible directly obtain the original data of the survey report on the environmental awareness of all the cities in China, the relevant papers included in CNKI between 2007 and 2009 have been taken as the data source, and the urban residents have been selected as the research objects to carry out analysis based on the percentage data publicized in the survey report.
For example, the average scores in 2 relevant survey reports have been selected for data of Yunnan, Lanzhou and Dalian, and that of data in 3 relevant survey report have been selected as data for Shanghai, while that of data in 3 urban survey data in Hohhot, Baotou and Ordos has been adopted as the data source for Inner Mongolia Autonomous Region.
Such data can represent the current situations of the level of environmental awareness of urban residents in the eastern, central and western areas of China in recent 3 years to a certain extent [3-6].
All the data came from "China City Statistics Yearbook 2008", and data processing was finished by SPSS, while the principal component analysis was adopted for analysis [9].

Building energy saving is one of the most important areas in energy saving and emission reduction, but it needs more funds and technology to achieve the target of building energy saving.
In addition, although the total amount of building energy-savings and emission reductions is large, reductions of individual project is small.
Certified Emission Reductions (CERs) is also small.
On the other hand, the emission reductions should be quantifiable, but some difficulties associated with monitoring and verification exists in building energy saving CDM projects.
Determine the data gathering and monitoring methods of building energy consumption. 4) Intensify propaganda to push the building energy efficiency transactions carrying out smoothly.

Based on the experimental data, the micro-upsetting process is simulated using the proposed friction model.
The effect of reduction amount.
The amount of reduction is one of the influence factors on the friction behavior in forming process.
The larger amount of reduction means the higher normal pressure on the contact surface.
Fig.1 Relationship between Friction coefficient μ and reduction ΔH/H with specimen sizes Fig.2 Relationship between friction coefficient μ and specimen diameter D with reductions 5.

Fig. 3 Data acquired with the laser stripe sensor (left), result of the crack inspection (right) In both digitalization steps the acquired surface data has to be transformed into a common workpiece coordinate frame.
Fig. 6 Steps to compute the robot path based on digitalization data Crack Identification.
After removing false positives, the remaining data can be used for path computation as detailed in the following section.
All robot paths and all digitalized data are relative to that work piece coordinate system.
Since all data is described in the same (work piece-dependent) coordinate system, the programed repair path points can be compared directly to the digitalized data, without the need to transform the data first.

The aim of the current study was to assess effectiveness of automatic braking system quantitatively using real pedestrian accident data selected from IVAC database.
The current study is an attempt to predict the benefits of automatic braking system based on real-world accident data.
Data Set In 2006, a special team from Hunan University carried out a vehicle traffic accident investigation in Changsha located in middle of China.
Drivers of 78 cases did not brake before the collision, accounted for 94% of the data set.
A Method for Estimating the Benefit of Autonomous Braking Systems Using Traffic Accident Data.

In which, building Time period, Response Reduction factor and Importance factor alters design base shear majorly.
Pushover analyses are carried out to find its effects on over strength factor and response reduction factor.
This equations comprosies of Zone Factor (Z), Importance factor (I), Response Reduction factor (R), Spectral acceleration based on building fundamental time period (Sa/g) and total gravity weight of the structure (1) Many studies have reported the appropriate values for Zone factor, Response Reduction factor and Spectral Acceleration based on building fundamental time period.
In other words, it is a force reduction factor used to reduce the linear elastic response spectra to the inelastic response spectra.
Push over curves are idealised to bilinear curves and corresponding data are caluclated as per procedure explained above.

The flight test data and helicopter characteristics are taken from Ref. [[] R.
The power required of current analysis fits well with the flight test data, implying that this model is sufficient to predict the power required.
The flight data of SA349/2 helicopter is used here to correlate with the load analysis.
The details of blade structural properties, static airfoil data and rotor geometry characteristics can be found in Ref. [[] R.
The first ten harmonics of moment in Fig. 3 shows a close agreement between the present analysis and the flight test data.

Reduce the degree of direct reduction.
It provides enough high-quality reducing gas and enhances the indirect reduction degree of iron ore.
The technology has been applied for a long time in the Russian RPA Toulachermet 2# BF (furnace capacity is 1033m3), the Production data showed that compared with the conventional operations, the coke rate of this approach decreased by 28.5%, while 27.3% yield, carbon utilization increased from 37% to 67%, while the CO2 output is significantly reduced.
If coupled with the fixed CO2, emission reductions can reach 86%.
According to the agreement, China is a developing country, only undertake CO2 emission reduction requirements after 2012.

To enhance the forming quality of pneumatic bulging for abnormity thin-wall pot and reduce such forming defects as severe wall thickness reduction and fold breaks.
Changing the friction factor μ respectively, the semi-finished materials have pasted the mould completely, and the simulation result data is obtained.
The chart shows that when pot wall thickness increases, the maximum reduction rate, the maximum stress value and the axial contraction all reduce.
Changing bulging pressure p respectively, the simulation result data is obtained as shown in Figure 5.
Fig.7 Fig.8 Fig.9 Fig.7 Experimental Test Specimen before and after Forming Fig.8 The Chart of the Cut Experimental Test Specimen Fig.9 Thickness Distribution Map of Simulation Test Specimen Taking 3 cut test specimen, and comparing the measured values of the pot wall thickness and the simulation data, the biggest error is smaller than 10%, the numerical simulation result coincides the test result well, which proves the feasibility of numerical simulation.

Therefore, all the test data were modelled as function of strain, temperature and strain rate for precious reflection of material behavior in rigid-plastic finite element model.
It can be found that the simulated force is in a good agreement with the measured data, which demonstrates the reasonable of finite element model.
Figure 2 Cogging Process Model Figure 3 Acquisition data from industry Figure 4 Press force validation Sensitivity Analysis of Forging Process Parameters In this section, the effect of feed, reduction and press speed on workpiece deformation and internal quality was investigated using numerical model combined with Design of Experiment (DoE) method.
Figure 6 Illustration of data acquisition lines The average effective strain data in each data acquisition line is noted as follows, i=0, 1, 2, 3, 4 (1) where i represents the number of data acquisition line, j represents the number of effective strain data in the selected data acquisition line, represents the effect strain data point in the selected data acquisition line.
The normalized standard deviation of average effective strain data in these five lines is defined to reflect the strain variation in the radial direction due to the change of different process parameters.