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Introduction The Strength reduction method for slope stability factor calculation is used more and more widely.
Example analyses Basic data
The strength reduction finite element method of three dimensional slopes is adopted to analyze the stress, strain, deformation and stability.
The exact method is simulated by temperature driving strength reduction.
The calculation non-convergence results corresponding reduction factors are shown as Table 3.

Technolygy Center of Yunnan Metallurgy Group Co. , Kunming 650031, China ayxhyxh1978@yahoo.com.cn, b281303319@qq.com, chhouyanqing@163.com, dgangxie@sina.com Key Words: Thermodynamic, Polysilicon, modified Siemens process, silicon yield Abstract: The complex chemical reactions in the Si-Cl-H system with relation to modified Siemens process have been studied in this paper based on the thermodynamic data of related substance.
The thermodynamic data and Characteristic of System There may be the following reactions in the high temperature hydrogenation process [1], the main reaction is SiHCl3(g)+H2(g)=Si(s)+3HCl(g), and the other are the side reactions, which is listed in Table 1.
The gas kinetic constant for the hydrogen reduction of SiHCl3 has been investigated [7].
SiHCl3→SiCl2+HCl (2) The kinetic constant is able to determine by fitting the decomposition rate on the growth rate data is given as Eq. (3) .
Miller; "The Thermodynamic Data for Silanes and Chlorosilanes," Sandia National Laboratories Report SAND, 87-8215B, 1-87 (1990) [7] Su, M.

The chosen of heating scheme is affected by the index of energy-saving and emission-reduction.
The data of Scheme 1 is shown in Table 1.
The thermal system of Scheme 2 is shown in Fig.2 and the data of Scheme 2 is shown in Table 2.
The data of Scheme 3 is shown in Table 3.
Conclusions In this thesis the energy-saving and emission-reduction of the heating schemes for the urban area are compared.

Once the calibration is done, the prediction data can be corrected by
However, the process of the prediction data is according to the structure of the regression data.
(2) Data Preprocessing.
Data preprocessing includes both data cleaning and data standardization.
The model is built through the history process data.

It is used for delivery of data to support assessment of losses, and in evaluation as well as formulation of rehabilitation plans.
The sources of the data will include scholarly journals, government documents, and case studies.
Data Collection The data collection for this part will be done through surveys and documents, reports, journal papers and publications about infrastructure development and disaster risk management.
Data Analysis The collected qualitative data shall be analyzed via the thematic analysis approach in order to reveal the key themes and insights concerning infrastructure resilience and DRM.
• Utilization of Geographic Information Systems (GIS) and data analytics is much needed.

Through study on the regulation of tensile strength and reduction of area after artificial aging and natural aging for SWRH82B wire rod, indicate that the tensile strength of wire rod unchanged through artificial aging or natural aging treatment while the reduction of area changes significantly the reduction of area is effected by aging temperature and aging time.
The initial reduction of area of SWRH82B wire rod is usually lower after hot rolling, but the reduction of area has aging phenomenon[4]. 
The Table 1 data shows: with the increase of holding temperature of artificial aging, the Z value of change rate was significantly increased, that means the reduction of area of wire rod has a significant aging phenomenon.
The variation trend of the tensile strength (Rm) and the reduction of area (Z) of the SWRH82B wire rod with natural aging shows in Table 2. 
The reduction of area of increasing rate (Δ) listed in Table 2.

In this report, the Zr-MCM-41 catalyst prepared by the grafting method was investigated on the MPV reduction of acetophenone.
The surface areas were evaluated with the BET methods by the N2 adsorption-desorption data at 77 K using BELSORP mini (BEL Japan, Inc.).
Results and discussion The catalytic activity of Zr supported MCM-41 have been evaluated in the liquid phase MPV reduction of acetophenone.
Figure 2 indicates the effect of reaction temperature on MPV reduction over Zr supported MCM-41 catalysts prepared by the grafting and impregnation method.
Fig. 2 Effect of reaction temperature on MPV reduction over Zr supported MCM-41 catallyst: (■) 4.6 wt% Zr-MCM-41-graft and (●) 5 wt% Zr/MCM-41-imp. 20 K Fig. 1 Effect of Zr loading on MPV reduction over Zr supported MCM-41 catallyst: (■) Zr-MCM-41-graft and (●) Zr/MCM-41-imp.

NO reduction is up to 50%.
It mainly consists of five parts, that is, the coal pulverizing system, the combustion system, the data acquisition and control system, the compressed air cooling system and the online flue gas sampling analysis system.
The data collection and controlling system is composed of the corresponding software and hardware.
It is used for collecting, recording and processing data.
In the experiment, each experimental cases is conducted six times at the same condition, the data in figure 2 and the following figure is the average data of the six times.

The mechanism of soot emission reduction was discussed.
The predicted pressure and the heat release rate are compared in Fig.1 with experimental data.
The predicted emissions data agree reasonably well with the measured values.
In general, the NOx predictions agree with the measured data to within 10%, while the soot is predicted to within 20% of the measured soot in most cases.
The mechanisms of soot emission reduction were discussed.

The study underscores a reliable approach to noise reduction and insight into concentration-dependent heat transfer dynamics.
This application finds utility in diverse fields like signal processing, data analysis, and mathematical modeling, enhancing the accuracy of information extracted from noisy functions.
Methodology Noise reduction.
Results and Discussion Noise reduction.
In summary, the proposed methodology offers an approach for noise reduction in mathematical functions, with potential applications in areas such as signal processing, data analysis, and mathematical modeling.