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Metodology The first stage of this research is carried out by collecting the required fundamental data and literature used as the design basis references.
Therefore, a reduction in the temperature of overhead gas from the stabilizer column causes a reduction in the temperature of the feed stream to the LP/MP compressors package.
Thus, the reduction of the feed stream’s temperature to the LP/MP compressors package causes a reduction in the total electrical load requirement (reduction from 823 kW to 730 kW).
Therefore, a reduction in the temperature of overhead gas from the stabilizer column causes a reduction in the temperature of the feed stream to the LP/MP compressors package.
Thus, the reduction of the feed stream’s temperature to the LP/MP compressors package causes a reduction in the total electrical load requirement (reduction from 1035 kW to 760 kW).

Based on the comparison of computing results and experimental data, we analyzes the differences between ventilated cavitating flow fields with and without considered the compressibility of gases.
The results show that the simulation data of cavity form and resistance, which takes the compressibility of gases into account, accord well with the experimental ones.
Introduction The drag reduction technique with supercavity, which can reduce the resistance of the body in the water by 90%, has a wide application prospect[1-2].
At present, most studies on ventilation supercavitating flow mainly focus on the drag-reduction mechanism of ventilated supercavity at normal temperature, prediction of cavity form, the effect of parameters, such as cavitation number, ventilation flow rate, cavitator parameters, Froud number and so on, on the cavitating flow[3-6].
Due to the density in cavity around ventilation hole decreases and the time-averaged velocity is relative higher, leading to the drag reduction to some extent, the drag coefficient decreases as the ventilation temperature increasing.

This paper mainly settles key problems such as boundary definition, data collection, calculation model, data acceptance/rejection and data calculation method concerned with concrete carbon emission calculation, establishes the national uniform concrete carbon emission calculation method and emission factor within the same cultural boundary, and provides theoretical and data calculation basis for determining the reference value and grade of concrete carbon emission.
As for other products, the carbon emission of unit product may also be calculated by reference to this paper; therefore, inherent carbon emission data of buildings are accumulated, providing quantized data support for taking measures to reduce the carbon emission intensity.
data of buildings may be accumulated, providing theoretical basis for establishing carbon emission limit for green building assessment standard and quantized data support for taking measures to reduce the carbon emission intensity.
Electricpower production life cycle list data are the fundamental data for developing LCA analysis of material industry or even all industrial products.
of enterprise, in case of data missing, the value in this table may be adopted.

The data in the paper is complete, true and credible.
First, discretizing the data, and using Equal Frequency here.
Original data set Thresholding discretization Data pre -processing Format conversion Rough sets processing module Attribute reduction Training sample set Supporting vector machine regression module Choose kernel function Parameters optimization Test samples SVM regression model Output Fig 1 Model flow chart of Rough Set and Supporting Vector Machine Conclusions According to Table 2 the error in the support vector machine regression is less, we can conclude that using RSSVM to evaluate the sustainable development of regional power generation enterprise can get a better result.
From the feedback data of the questionnaire, we can clearly see that……the effect of sustainable development is notable.
The evaluation method is of certain reference for the comprehensive evaluation with less data sample and higher precision requirements.

The results show that reductions in errors of predicted maximum impact reaction force (compared to experimental data) were achieved from 29% using Static ADM to 14% using SRD ADM and from 35% using Static ADM to 15% using SRD ADM respectively for impactor speeds of 2 ms-1 and 5 ms-1.
In the present study, extrapolated test data obtained at low strain-rate tests are input to a three-point impact simulation using ABAQUS/VUSDFLD and compared with published three-point impact test data.
Material properties data obtained from tensile tests [1] and extrapolated up to 5 s-1, were represented as Eq. 1, with the data shown as in Table 1.
Four components of energy release rate, associated with longitudinal failure in tension and compression (Gftc and Gfcc, respectively) and transverse failure in tension and compression (Gmtc and Gmcc, respectively) were extracted from published experimental data [6].
The prediction of maximum reaction force for cross-ply using SRD ADM at impactor speed 2 ms-1 is better than using static ADM with an error of 14% and 29% respectively when compared with impact tests data and the prediction of maximum reaction force for cross-ply using SRD ADM at impactor speed of 5 ms-1 is better than static ADM, with an error of 15% and 35% respectively when compared with impact test data.

The sintering temperature and composition are chosen according to phase equilibria data.
The present work gives guidelines based on a materials selection tool and on physico-chemical data for the design of two-layer parts made of tough steel and hard cemented carbides layers.
During sintering, the reduction of the superficial oxides by C with release of CO and CO2 depletes the C content and promotes the M6C formation.
This is consistent with phase equilibria data [5] even after only 2 minutes at the sintering temperature.
Conclusion Multimaterials with specific properties can be selected from materials properties data bases.

In order to verify the simulation, experiment data are compared with simulation result.
Angular velocity will multiply by coaxial reduction gearbox (25:1), and make coaxial magnetic member rotate at same angular velocity ω.
The tendency of experiment data agrees with the simulation result.
The selection of reduction gearbox depends on what kind of electric devices are going to be driven.
Fig. 9 Coaxial reduction gearbox can multiply input angular velocity.

However, there isn’t much data about the flight kinematics of silent owl.
MX infrared camera can capture motion data and provide real-time optical data with the other components.
The Fig.1 shows the experimental field, C1~C8 are infrared cameras, which capture the coordinate data of marks.
Fig. 1 Experimental field Before the data acquisition, the spherical markers with reflective properties were placed on key parts of wings.
Data processing and analysis software is Vicon Workstation (Vicon Motion System, United Kingdom).

The Capacity Diagram Method procedure, which is based on R-�-T (Reduction-ductility-Period) relationships, is investigated to compare with the modified CDM procedure.
The CDM procedure, which is based on R-µ-T(Reduction - ductility - Period) relationships, is investigated.
(5) where ω is the weight of the building, Ry is a reduction factor due to ductility (Ry = Ae/Ay), and Ay is the pseudo acceleration, which is related to corresponding ductility, the natural period, and the damping ratio of the elastic system.
The detail data was derived from the results of separate interior and exterior beam-column sub-assemblage tests by Reinhorn [5].
These tests provided the data on yield strength and hysteretic behavior.

Both denitrification and DNRA could contribute to nitrate reduction and proportions of them were about 60% and 40% respectively at the tested condition of COD/NO3-Nof 50.
However, nitrate reduction pathway might favor dissimilatory nitrate to ammonia (DNRA) process under the conditions of high C/N ratio and fermentable substrate.
Analysis of varance (ANOVA) at 0.05 level was used to analyze the data.
The denitrification efficiency was about 60%, which implied that both denitrification and DNRA processes were contributable to the nitrate reduction.
Moreover, our results show that in the former system both denitrification and DNRA contributed to the nitrate reduction pathway.