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However, the controlled thermal management system has not been significantly employed for further reduction of specific diesel oil consumption and increase of truck mileage.
Firstly, the cooling system model was validated with experimental data, and then replaced with an advanced controlled thermal management system using a 1-D simulation model.
Thermal management System Avails The overall aim of any engine thermal management strategy is to achieve the desired stable engine operating temperature as quickly as possible, thus minimizing engine frictional losses through lubricant viscosity reduction, reducing warm up time, and delivering cabin heater performance within as short a timeframe as possible [3].
Engine main data Engine Characteristic Parameters Compression ratio 17.5 Firing order A1 B3 A3 B2 A2 B1 Cylinder arrangement V form at angle 90 ° Working cycle 4 Stroke Number of cylinders 6 Rated speed range (rpm) 1800:2100 Cylinder Geometry Bore/Stroke (mm) 132 / 145 Engine Displacement (ltr.) 11906 The controlled cooling system model is integrated to Simulink for the purpose of controlling the fan speed, pump speed and the electrically actuated thermostat in order to increase the flexibility of the cooling system to an optimum level .
The integrated model was validated using the experimental data of engine performance and thermal balance experiment which has conducted in “Power Mechanism and Engineering Laboratory, BIT”.

The simulation is based on the meteorological data of monthly typical day which was summarized from a year round data of subtropical Guangzhou.
The meteorological data of monthly typical day was used to predict the performance of solar refrigeration system reasonably.
The hourly data of typical day is the average of monthly data.
The data covers from April to October because the solar cooling system mainly works in this period.
The simulation is based on a year round meteorological data of subtropical Guangzhou.

This temperature was chosen on the basis of thermogravimetric analysis, revealed both dehydration and reduction processes ranges [4].
According to the electron diffraction data iron particles in all the samples are coated with amorphous SiO2 layers with thickness of about 3 nm.
Thus the complete reduction at MM homogenization procedure has not been achieved.
Mossbauer spectra and corresponding phase contribution for nanocomposites, obtained in course of precursors reduction in hydrogen at 400oC.
It cannot be explained by iron concentration only in accordance with Mossbauer spectroscopy data.

(2)Pollutant emissions of per unit output （2） Where,is the pollutant emissions of per unit output of the th enterprise; is the annual emissions of pollutant of the thenterprise,ton; is the annual output of the thenterprise,yuan. 2.2Resource Consumption Factor Analysis Model （3） Where, is energy consumption of per unit output; is the annual power consumption of the thenterprise,kWh; is the annual output of the thenterprise,yuan. 2.3Economic Analysis Model (1)Custom outage losses If thcustom’s interruptible load ratio is , the outage losses are: （4） Where, is the outage losses of the th enterprise when interruptible load ratio is ;are the industry outage cost coefficient, can be obtained by historical data
(2)Vule of loss load of power grid Through limiting electricity to the th enterprise, it can result in the loss of load loss of grid company, we can use the following formulas to calculate the loss in case of emergency situation when the reduction of electricity supplymentis,kWh: （5） （6） （7） Where, is the grid company’s loss in case of emergency situation when limiting electricity to the th enterprise while the reduction of electricity supplyment is ;is the reduction of the operation cost of grid company whenthe reduction of electricity supplyment is;is the reduction of the electricity sales profit when the reduction of electricity supplyment is ;is the electricity salse profit as a percentage of sales revenue, ；are constants, can be obtained by historical data; is the electricity purchasing price of grid company; is the sales price of the grid company. 2.3Customers Importance Analysis Model (1)Users payment rate

Dynamo analyses data by Hash on the basis of the number of resources, and then got cloud storage through the simple distributed system.
According to the above steps, added new nodes, and adjusting the related data to the new nodes.
MapReduce programming model mainly parallel computation large-scale data set, and the essence embodied in Map (mapping) "and" Reduce (reduction).
In the process of Map operation ,parallelling processing data, that is, using the mapping function rules to separate data; And Reduce is merged data which is seperated by the reduction function rule.
Calculation of data based on the vector clock principle Reference [1] Liu Zhengwei, Wen Zhongling, Zhang Haitao.Management technology of cloud computing and cloud data .Study and development of computer , 2012 (46):122-127

The calculating formula of reduction coefficient of bonding strength and slip ratio is proposed.
Assume is the reduction coefficient of the ultimate bond strength, which is the ratio of the trial values of the ultimate bond strength and the corresponding strength of the components that aren’t corroded.
Through the regression analysis of the experimental data, can be calculated from Eq.1
（5） Where is the constitutive relation of bond-slip of uncorroded reinforcement, is the constitutive relation of bond-slip of corroded reinforcement, is the reduction coefficient of bond strength, which can be substituted by , is the position function which is proposed by Xu Youling, in Reference [7-8], , is slip ratio, which can be substituted by .
The slippage should consider the reduction factor of the corroded reinforcement, which is the influence of slip ratio .

The model projects consistent and quantitative socio-economic variables, energy demand, GHG emission and diffusion of mitigation options in order to achieve an emission target or assess the potential of emission reduction by various counter measures.
In 2011, China government issued the "12th Five-Year" program about greenhouse gas emissions reduction, the target of carbon intensity of Guangdong Province decreased by 19.5% compared with 2010 year during the 12th Five-Year.
(a) (b) Fig.1 Primary energy consumption For the final energy consumption data of 2005-2010 , we can see that: Terminal energy consumption from 2005 to 2010 increased year by year; Oil consumption ratio increased from 26% to 29%; Gas including LPG and NG, its proportion increased from 4% to 7%; Power consumption between 35% and 33%; Other energy including other petroleum products , refinery dry gas and coke products, proportion are in 11% between 13%; The proportion of oil consumption has been greater than the proportion of coal consumption.
Fig. 6 CO2 emissions by sector Conclusion 1 ) Application energy model of Guangzhou energy situation and development situation of carbon emissions are simulated and analyzed, the model of situational analysis and reduction measures of impact analysis can be use for decision maker. 2) The energy structure adjustment and technology efficiency improvement are the two key method to reduce carbon emissions. 3) Through the scenario analysis, we can see that Guangzhou has realized this urgent situation .For constructing low carbon economy, not only to further strengthen the energy structure, industrial structure adjustment, climate change and improve energy efficiency technology application, but also should further control population and economic growth.
[8] Detlef P.vanVuuren,MoniqueHoogwijk.Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials.

A Way to Determine the Economic Operation Mode of Substation Transformer Deli Zhao1, Huilin Zhang1, Fengzhen Liu1 and Xin Zhao2,a 1 State Grid Liaoning Chaoyang Power Supply Company, Chaoyang, Liaoning,122000, China 2 State Grid Beijing Tongzhou Power Supply Company,Beijing,101100,China atsustar@126.com Keywords: Transformer, Loss reduction, Economic operation Abstract.
Comparison between the two , the use of two main transformers in parallel operation mode rather than just put in the 2nd main transformer is significant to reduce the variable loss (1.33 ~ 11.04) kW, the annual reduction in electricity consumption variable loss of about (1.165 ~ 9.67) × 104kWh.
Summary The overal calculation is based on the actual data and its effectiveness has been proved in the system, so it is very meaningful to readjust the method to make preparation for the economic operation.The further research will be done on the physical solution to the real system and the balanced arrangement of different substation devices ans apparatuses.

Meanwhile, the PIV system was employed to measure and analyze the experimental data.
Fig. 5 Relative circulation of different wingspans of data set 1# Fig. 5 depicts that the circulation increases between wingspan 1 and wingspan 17, despite of the reduction of the maximum velocity in Fig. 4.
The relative circulation process result of data set 11# shows in Fig. 7.
Fig. 8 Relative circulation variation of the six data sets When divide the statistical average of the last six data by the statistical average of the six maximum data, the percentage of the circulation reduction of the flow field will be derived.
Table 4 Circulation reduction of every data set Data set 7# 8# 9# 10# 11# 12# Circulation reduction 62% 60% 54% 64% 52% 57% Table 4 shows that the reduction of the circulation varies from 52% to 64% which powerfully proved the effectiveness of Rayleigh-Ludwieg instability in weakening the wake vortex compared to the circulation change of the main wing vortex in Fig. 5.

China’s tourism will face increasingly severe pressure from low carbon and emission reduction.
Data and Method Data Source.
The data includes: 1) Scale and occupancy rate of China’s star-rated hotel rooms in 2009, based on The Yearbook of China Tourism Statistics 2010 (Supplement). 2) Energy requirements of star-rated hotel rooms per bed night, based on the data provided by Jinhe[5]. 3) Railway, roads and waterway passenger-kilometer of 31 Chinese provinces in 2009, based on China Statistic Yearbook 2009. 4) Limited to the difficulty in collecting data, aviation passenger kilometers of 31 Chinese provinces in 2008 is used to replace the data in 2009, based on the China Compendium of Statistics 1949-2008. 5) Tourism Industry revenue of China’s 31 provinces in 2009, based on The Yearbook of China Tourism Statistics 2010 (Supplement). 6) Carbon emission factors for railway, roads, waterway and aviation, based on the data provided by Yanxu and et al.
Considering the collection of statistics data of tourism transportation, passenger-kilometer can be quoted directly because tourism transportation is part of the passenger transportation.
Considering completeness and reliability of data collection, the paper takes star-rated hotels for object.