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Based on the experimental data, the curve as the internal force of pipeline is first drawn out and discussed, in turn the characteristic of stress distribution and destruction rule of pipeline are analyzed and summarized, which may be referred for designer to take appropriate measures.
According to the data of the test, the author draws a picture in curves that shows the changes of the internal force and settlement along with the change of the pore size, then gets the regular destruction pattern of pipeline and the influence on the upper pipeline by the foundation settlement, offering references to protect the pipeline in practical projects in its regular use.
In 3 o 'clock direction and 9 o 'clock direction, the transverse stick strain gauge (018 cases) gets tension from the direction along the test pipe, and the vertical stick strain gauge (017 cases) gets tension perpendicular to the test pipe. 1.3Test Principle Strain gauge and displacement meter, which are installed in default position in the pipe, through conductor, are linked with the static resistance strain acquisition instrument that through the power line connected to the computer, then sets parameters, adjusts balance, read and maintain the data of the settlement displacement and strain through a automatic data acquisition system.
In addition, if the pipe is in 3 o 'clock and 9 o 'clock direction, the data is lesser in lateral strain gauge testing.
If soil deformation is obvious and pipe displacement is relatively limited by soil, underground pipe will suffer severe damage [8] [9]. 3 Conclusions The curve of the relationship between the settlement and the internal force and the hole forming drew based on the data in the test, the conclusions are as below: (1)As the influence from the settlement of foundation soil, the maximum value of stress in buried pipe appears the top and the bottom of the pipe in the middle of the hole, the pipe in 3 o 'clock and 9 o 'clock direction also appeared some strong stress as well, so these are the most vulnerable area to be damaged, and uneven subsidence area is vulnerable section for the pipe.

Load-deflection data from the test for static flexural strength was used to calculate the toughness index.
The deflection data was also provided as the closed-loop control signals (0.05-0.1 mm/min) during the test.
Fatigue equation Upon the data given in Table 8, the fatigue equation can be setup.
From the correlation coefficient R 2, it can be seen that the regression fatigue equations agree with the test data well.
The double-logarithmic fatigue equations regressed agrees well with the test data for various mixes.

There is limited data on the environmental impacts of CEBs.
Figure 1 shows data the environmental impact of the various additives discussed above.
As such the data presented should be considered indicative and approximate rather than absolute.
Data from various sources was used for the analysis.
There remain concerns over the variability of this data and the allocation of embodied energy and GWP.

The generated diffraction data are compared to standard data on minerals from the ICDD mineral powder diffraction file, which contains data on over 3000 minerals.
The coated samples have similar standard minerals and diffraction data.
The data indicates that Zn-6MnO2 exhibited the most substantial mass gain, measuring at 0.30 g.
It's conceivable that process parameters played a role in the reduction of mass gain as MnO2 content increased [22–24].
Table 5 and Fig. 1 present the polarization data and polarization curve of the Zn-MnO2 coated sample in 3% wt NaCl environment.

The data were then converted to yield per hm2.
Data analysis The data were analyzed with SPSS13.0 by one-way Anova with Bonferroni’s correction.
Treatment with 100 mmol/L NaCl for 2 weeks caused 43.9 and 62.5 % reduction in fresh weight of leaf blade for Jitianza 2 and Lvneng 1.
Data are the means of 7 replicates and vertical bars represented SD.
Table 1 Comparison of two sweet sorghum varieties in field Parameters Jitianza 2 Lvneng 1 Emergence rate (%) 75.34±5.26a 36.67±3.35b Plant height (cm) 3.98±0.13a 2.68±0.12b Stem width (cm) 2.25±0.17a 1.75±0.14b Number of leaf blade (slice) 17.3±0.67a 13.2±0.34b Total leaf area (m2) 0.66±0.02a 0.31±0.01b Stem stalk Yield (kg/hm2) 73815±57a 30450±40b Ear Yield (kg/hm2) 5760±28a 3390±13b Juice yield (%) 55.12±2.78a 38.78±3.23b Stalk Brix (%) 19.6±0.42a 16.3±0.34b Sugar content (%) 16.66±0.33a 13.86±0.27b Note: Different letter on the right of data indicated significant difference between Jitianza 2 and Lvneng 1 at P < 0.05 level, and data are the means of 20 replicates.

Statistical analysis (Kolmogorov-Smirnov and Kruskal-Wallis Statistic) was also carried out on the experimental data.
These tests were chosen to check if the data was normally distributed, a prerequisite for subsequent statistical analysis.
Pairwise comparisons of grouped data Cost Analysis The equipment set up and raw materials used where all locally sourced.
Multiple experiments per categorization was not carried out, leaving little opportunity to calculate error estimates in data.
b) The research data is statically proven as the Kruskal-Wallis test shows significant difference between untreated 50:50 mixture and the pretreated 75:25 mixture.

The numerical results of the compound wing for fixed ground validated with the experimental data.
Total wing span (b) [mm] 250 Root chord length (c) [mm] 200 Middle wing span (bm) 125 Taper ratio (c/ ct) 1.25 Anhedral angle (a) [°] 13 For the validation propose, the CFD simulation was compared with experimental data using the low speed wind tunnel at the Universiti Teknologi Malaysia.
The reduction of drag coefficient related to moving ground as compared with fixed one was greater at lower ground clearance of 0.1.

Experiments using real-life routing tables demonstrate that careful design of the data structure can reduce the power consumption dramatically.
In this paper we will show that, being aware of the underlying architecture, there remain some opportunities to exploit the data structure optimization for power reduction.
Experiments using real-life routing tables demonstrate that careful design of the data structure can reduce the power consumption dramatically.
[10] RIS Raw Data.
Available: http://data.ris.ripe.net

Based on the result obtained, prediction equations for responses studied are adequate to describe the experimental data on tensile strength, elongation at break, and toughness.
Then, a white calibration was done to get accurate and precise data.
The data that had been taken are the values of the L*, a*, and b* which represent lightness, redness, and yellowness, respectively [8].
A high R2 value, close to 1, is desirable and ensures a satisfactory fit of the quadratic model to the experimental data.
Prediction equations for responses studied are adequate to describe the experimental data on the tensile strength, elongation at break and toughness.

The existence of a correlation between the entered parameters is shown, the regression equation is obtained based on the analysis of experimental data of the wear of a tool made of steel CrWMn and U10 treated with a laser with coatings in the reflow mode.
Based on the processing of experimental data, it is shown that there is a significant correlation between this parameter and the wear resistance of the modified surface layer.
The reduced wear Y is a dimensionless value that characterizes the reduction of wear (increase of wear resistance) of the modified surface layer.
The advantage of the introduced parameter is the simplicity of its calculation according to the experimental data: the value of the reduced integral microhardness is proportional to the area of the curvilinear trapezoid limited above by the graph of the change in the microhardness of the modified layer depth.
The correlation between the entered parameters is shown on the basis of the analysis of the experimental data.