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Experiments have been carried out with different compression ratios of 14, 16, 18 and 20 at loads of 0, 25, 50, 75 and 100% in B23 fuel mode and the values are compared with the base line data.
It is concluded that the ignition delay at CR18 is significantly lower than the base line data.
This EGT reduction reduces the dissociation along with CO emission [6].
Variation of smoke emission with load and CR With reference to the base line data, smoke reduction for CR18 is found as follows: 0, 20.19; 25, 10; 50, 11.03; 75, 29.35; 100%, 21.3%.
Ignition delay and maximum pressure crank angle for the CR18 is most significant with the base line data. 5.

Networked manufacturing [1] has provided a promising approach to achieving effective collaboration for these virtual organizations through supplying integration techniques such as data integration, function integration, and business process integration over networks.
This means that a majority of resources would spend most of running time keeping in an idle state, although the servers, computers, data centers, and other network devices were consuming power all along.
The approach can provide effective support for efficient resource utilization and benefit reduction of energy consumption.
Related work Networked manufacturing technology can support data integration, functionality integration, lifecircle process integration, and application integration for collaborative manufacturing among distributed federation over networks.
Current network manufacturing techniques, such as SOA and Grid, always call for ever increasing processing capacity to deal with tremendous data, which give much rise to resource consumption such as power used to sustain large clusters and datacenters.

Fig. 5 shows a comparison between the experimental data and ASME design curves.
Some literatures' data [3, 4] were also included.
Most of experimental data fell on the regions above the design curves, implying sufficient fatigue safety margins.
However, a few data obtained under the conditions of low strain rate, high DO and high sulfur contents fell on the regions below the design curves, suggesting a potential strain-rate dependent reduction in the safety margins of low-alloy pressure vessel steels in high temperature water in connection with the material and environ- mental factors such as the sulfur contents in steels, DO in water and temperature.
There exists a potential reduction in fatigue safety margins for low-alloy RPV steels in high temperature water depending on the strain rate, DO in water, temperature and steel sulfur contents.

The research achievements of current water quality soft-sensing model mainly include simplified mechanism model, soft-sensing method based on the data and the soft-sensing method based on multiple model, as follows: The simplified mechanism model.
As the paper[2] adopts scale separation method for model reduction (application).In paper [3] , the linear model is simplified by linearizing switch function of components reaction rate based on nonlinear in activated sludge, paper[4] proposes the simplified model after reduction treatment based on mechanism analysis of biochemical reaction.
The soft-sensing method based on the data.
Paper[7] adopts the fuzzy c-means clustering algorithm to divide the run data space ,adopts fuzzy model as a partial sub-model, establishes the soft-sensing model of goal water quality COD.
Multi model decomposition use the method of condition identification division, use the fuzzy clustering method to identify the operating region number [11], local sub-model structure can use data driven model, also can use the simplified nonlinear or linear mechanism model of corresponding conditions[12], local sub-model parameters uses prediction error method for estimation, multi-model synthesis mechanism includes hard switching and weighted sum, synthesis the global dynamic model from the local sub-model.

Technical data of the austenitic stainless steel AISI Type 316 mesh screen shading devices were collected from the manufactures’ product catalogues [4].
This modeling method can be only combined with spectral optical data type calculation in EnergyPlus.
WINDOW 7.3 can only export Bi-directional Scattering Distribution Function (BSDF) datasets for CFS, which are subsequently read and calculated by the BSDF optical data type in EnergyPlus.
WINDOW incorporates the Klems radiosity-based method to generate BSDF data of multi-layered fenestration systems from the angularly resolved data of single layers [8,9].
Likewise, in the absence of empirical data in the framework of current study, we also selected the WINscr method with BSDF calculation to proceed for assessing the impact of all key-design parameters and discussing the energy and thermal performance of the studied office space.

The input data for network are the value of current and voltage of the VRFB stack when charging or discharging.
The network can classify the capacity loss degree into three levels: sufficient, moderate and insufficient according to these input data.
Unlike the mechanism models mentioned above, this neural network model only requires the external data of the VRFB system which can be easily measured rather than the data concerning the internal change of the cell.
The data of current, voltage and electrolyte temperature etc. are recorded every one second.
The network is trained by the previews data (X, C) using Matlab newpnn function.

Two data strictures all meet the efficiency of the search algorithm.
Point cloud data are used to make the physical part to be a digital model.
Meanwhile, no assumption can be made about the size of the data set.
So it is a dimension reduction operation[7].
So data structures where nodes have pointers to associated structures are called multi-level data structure.

Data Input of the Model 4.1 The Basic Data (1) DEM: The DEM data are obtained from the United States Geological Survey(USGS) at 1km*1km resolution
(2) Meteorological and hydrological data: The data which are from 1990 to 2010 come from the National Climatic Data Center (ftp://ftp.ncdc.noaa.gov/pub/data/gsod/).
(3) Land Use Data: The land use data in the scale of 1: 1120000 is provided by the mekong river commission
(4) The Soil Data: The soil map of the study area is obtained from the Institute of Soil Science, Chinese Academy of Science.
It can be added into the daily observation data of temperature and precipitation in 1990-2009 as the input data for the climate change research in 2010-2029. 5.

Because of the current economic disadvantage of CSP, researchers worldwide are engaged in efforts to make significant reductions in the initial cost of CSP systems and to further increase their efficiency by pushing the temperature limit beyond the current molten salt operational limit of about 565°C.
Temperatures as high as 1000°C can be achieved using this concept, thereby increasing conversion efficiency, and significant cost reductions are also expected, especially if natural particles (such as sand) are used.
The simulations provide performance and cost data, including LCOE.
The third scenario is particularly economical due to the significant reduction in cost of storage when silica sand is used as a storage medium, and due to the significant reduction in the receiver cost due to the simplicity of the falling particle receiver.

"Kyoto Protocol" was the first legal binding regulatory mechanism that requiring a reduction in greenhouse gas emissions.
There were more and more countries entering the carbon emissions reduction activities.
UN climate summit in Copenhagen did not reach consensus on carbon emissions-related issues by the end of 2009, an important reason was that the companies did not understand the carbon emissions and revenue [1].As the support side of carbon emission reduction policies, China is trying the best to do own obligations.
Due to the lack of data, this article does not make case study, but makes an innovation from the view of analysis, and takes into account all factors that affect the carbon emissions trading cost to improve the accuracy of predictions.
Carbon emission fluctuation in China's economic development and carbon reduction path [d].