Search results

Firstly, based on the design data of the plant, energy balance was constructed to obtain the thermodynamic properties of each stream.
It is also shown that the AFSCs of both condenser and feedwater pump reduce along the load reduction and that of regenerative system changes only slightly.
The AFSC of the last stage increases much larger with the load reduction, while that of the governing stage increases with the decrease of load during the constant pressure operation and remains stable during sliding pressure operation.
With the decrease of the load factor, the AFSC of regeneration system reduces slightly due to the reduction of AFSC of No.8 feedwater preheater.
However, considering the efficiency decrease of ST and feedwater pump with the reduction of load, the AFSC of feedwater pump will increase slightly and then decrease when the load changes from 50% to 30%.As is shown in Figure 9, the total AFSC of the shaft sealings of main and secondary turbine is 0.6-1.2g/kWh.

Recording of measured data was performed by the acquisition system DH3816.
(3) In particular, beam L4 having a larger reinforcement ratio showed a reduction of the experimental crack width compared to beam L2 and L3 with a higher number of cracks developed in the bending region (Fig. 3d).
While shear failure occurred in the flexure-shear region due to the reduction of effective shear area caused by propagation of the inclined cracks.
At onset of cracking, flexural cracks developed rapidly for specimens with low CFRP reinforcement ratio (L2 and L3), and the beams exhibited reduction in flexural rigidity.
Flexure failure occurred for moderately-reinforced stone beams, and flexure-shear failure occurred for over-reinforced stone beams, in which a reduction in ductility was obtained

We chose high-field injection of electrons from the silicon substrate in order to provide the accumulation mode in the surface area of semiconductor and to eliminate an influence of space-charge region on experimental data [1, 11].
At the same time at the injection-thermal treatment a slight reduction of injection resources of the MIS structures and devices based on them can take place.
The resource reduction is caused by the charge degradation of both the gate dielectric and the semiconductor/dielectric interface observing at the charge injection [1, 8, 9].
The reduction of the injection resource raises with an increasing of the charge density of charge injected at the injection-thermal treatment.
Andreev, Modification and reduction of defects in thin gate dielectric of MIS devices by injection-thermal and irradiation treatments, Phys.

In this contribution, the influence of fibre-based sensor elements with selected dielectric jackets on the mechanical properties is investigated using an analysis of variances approach based on experimental data.
At this point, it is not clear, if these reductions are statistically significant and actually caused by the embedded sensory elements or if the reduction of the results is part of the material intrinsic scatter.
In detail, the PES fibre jackets (V1+V2) lead to a significant reduction in tensile strength, although the starch sizing reduced the impact slightly.
One explanation could be the local reduction in fibre volume content compared to the reference structure.

Hence, the C1, C2 and N3 atoms provide only for the reduction sites to form H2, whereas the N2 atoms provide sites for both the oxidation and reduction.
Scheffler, Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data, Phys.
R., and Du A., Single Atom (Pd/Pt) Supported on Graphitic Carbon Nitride as an Efficient Photocatalyst for Visible-Light Reduction of Carbon Dioxide, J.
Wang, Enhanced CO2 photocatalytic reduction on alkali-decorated graphitic carbon nitride, Appl.

A number of works [1-3, 12] proposed an approach based on the integrated use of mineral raw materials when exposed to concentrated energy flows in order to extract alloying elements and oxides, which corresponds to the proposed theory of entropy reduction in the production of the final material, bypassing the stages of primary enrichment and processing.
The reduction of the production period of materials is due to the use of modern technologies that exclude the use of environmentally hazardous pyro- and hydrometallurgical processes.
It was possible to observe other compounds, for example, tungsten carbides W2C, formed by reduction of tungsten from WO3 .
Experimental data help to determine the nature and mechanism of the transition of the alloying element into the liquid metal.
Reduction of tungsten during the electroslag remelting of flux containing the scheelite concentrate for production of tungsten-containing steels.

Line loss rate forecast can help supply companies develop reasonable loss reduction and energy efficiency goals.
This article based on less information needs in gray system model, and with high accuracy, as well as how much of the raw data is not the demanding requirements of characteristics [6].
Gray relational analysis by the geometric relationship of the system data sequence to analyze the degree of correlation between the various factors in the system [7], The use of gray relational grade to determine the line loss rate greater impact variable and as the neural network input variables .
Grey Forecasting Model For Line Loss A.The basic model Gray prediction model GM (1,1) is frequently used ,and the model building process as follows: (1)Accumulated generating operation for the original data sequence: (1) (2) (2)The establishment of differential equations (3) (4) And in the formula (5) (3) a, b, back to the original differential equations: (6) Regressive to get the original data: (7) B.Correction Model In order to improve prediction accuracy, combining the initial data with the predicted results optimized.
The application of double BP neural network combined forecasting model in real-time data predicting)[J].

The numerals indicate the number of complete reduction cycles along three orthogonal directions (a, b, c) and single reduction along the axis a.
Inside the bands of the structure, according the TEM data (Fig. 6b), there is a finer structure of microbands with geometrically necessary boundaries; inside the fine microbands (≤1.5 mm), incidental dislocation boundaries are formed.
Hence, the parameters in Eq.1 should be specified not from reasonable consideration but from experimental data.
Despite the great body of experimental research in the influence of severe plastic deformation on microstructure of metals and alloys, the parameters ec, n, and m are mostly impossible to estimate because the data necessary for this are incomplete (in particular, the average grain size in initial specimens is often unknown).
By and large the foregoing data demonstrate that the critical strain for the onset of dynamic recrystallization in TiNi-based alloys under warm deformation is relatively small.

Method and Data From the previous studies, we can find, on the analysis of impact factors of carbon dioxide emissions were mainly used in static panel data model.Static panel data models have the advantages that the individual effect of effective control samples which is uneasy to observe and doesn’t change with time
(2) Where refers to the lagged value of the CO2 emissions per capita,the explanations to other variables is the same to the static panel data model.
And the coefficient of the per capita GDP’ s square is negative, which further proved a inverted U-shaped relationship is found between per capita GDP and CO2 emissions per capita in the dynamic panel data model too.But what is worth pointing out is in the dynamic panel data model, because of joining the lagged dependent variable,which lead to some coefficients of variables diminished to some extent, even the changes of some variables are not significant.It may attribute to the effect of these factors which has already reflected in the lagged dependent variable.
Conclusions We can draw the same conclusions from the Static and Dynamic panel data model: Firstly, a inverted U-shaped relationship is found between per capita GDP and CO2 emissions per capita, and Environmental Kuznets Curve Hypothesis has been verified.
The trade openness inhibits CO2 emissions in the static panel data model, and the inhibitory effect is very obvious in the dynamic panel data model.

An alternative reliable source for obtaining data regarding surface finish is the use of sensors (dynamometers, acoustic emission sensors, accelerometers, etc.) that provide real-time data of the machining process (cutting forces, acoustic emissions, vibrations, etc.).
The processing and characterization of these signals provides reliable real-time in-process data for the calculation of several parameters of the machining process and the product.
Predictive models were obtained using regression techniques with 75% of the experimental data, and the remaining 25% for model validation.
The system relies on data feedback obtained from the real-time monitoring of surface finish (Rapred).
The second order multiple regression model showed a good fit with the experimental data (R2-adjusted ~ 96%) and a low mean relative error (~ 9%)