Search results

A sand column prepared for experimental data and a set of engineering equations for 1-D numerical modeling data of the sand cementation process were adopted.
Clearly, the feature of the modeling data was in resemblance with the one of the experimental data.
The constant of linear reduction of urea hydrolysis rate varied from 0.0009 mM/h2, 0.0015 mM/h2 to 0.002 mM/h2, which represented an inspiring approach to modify the numerical data.
Obviously, the feature of the modeling data (Fig. 5a) was in resemblance with the one of the experimental data (Fig. 4b).
The experimental data were presented in Fig. 5b.

The peak profile analysis data and the self-consistent predictions of texture evolution showed a good agreement with the experimental deformation texture evolution.
Other advantages are the “easier” sample preparation routine, relative short time required by the “state of the art” equipments to render results and the fact that the data obtained is statistically averaged over the area/volume irradiated.
The rw1 data files generated by the Philips software were converted into raw archives, recognizable by PopLA [6), using PC-Texture 3.0.
The profile data acquisition was done using a solid-state position-sensitive ultra-fast detector (X’Celerator, Panalytical).
The initial texture, corresponding to the As-received material, consisted of a file with a set of grains orientations extracted from the SOD file (sample orientation distribution) obtained from the X-ray data for pole figure measurement using the routine PoPla (Preferred orientation package Los Alamos).

It allows the deformation of the material to be studied in detail with minimum or even without the need of performing expensive and/or time-consuming experiments once necessary material data are available.
From simulations, the result data had converged to a single solution as the number of elements increased; however, time consumed in the simulation also increased.
This decreasing in the load was due to the reduction in the frictional contact length between the workpiece and die.
The increasing in the reduction of cross sectional area had increased the press load [8].
The increased of reduction in cross sectional area caused higher equivalent stress in the deformation area.

The hatched areas highlight the drag-increase cases and the zero-R lines (dashed) are found by linear data interpolation.
of velocity components and Reynolds stresses, where u, v, w are indicated in the legend. 0 161 0 1610 287 574 861 1148 0 161 −0.50 −0.13 0.25 0.63 1.00 1.38 1.75 2.13 2.50 x+ z+ Fig. 8: Contour plot of ⟨udvd⟩ + in the y−z plane at x+=0, x+=143.5, and x+=287 respectively.Outlook on the future Empirical correlations from Pope [14] were used to estimate data for low-speed laboratory conditions and for three flows of technological interest for disc-flow parameters leading to R=20%.
Turbulent drag reduction through rotating discs.
Compliant coatings for drag reduction.
Aircraft viscous drag reduction using riblets.

GC data was used to calculate conversion, selectivities and Anderson-Schultz-Flory (ASF) parameter for [4, 20].
Obviously there is a difficulty in showing the promoter effect on the conversion which will be explained when discussing the selectivity data.
FTS reactor runs data Catalyst CO conv.% α S% CO2 S% C1-5 Fe/rGO 95.4 0.30 37.9 62.1 Fe-K/rGO 96.2 0.27 34.8 38.0 Fe-Mn/rGO 82.6 0.29 37.3 44.6 The selectivity of the C1-5 range showed promising trends.
From Fig. 3(a) which shows C1-5 detailed selectivity data, it is clear that promoters severely decreased the CH4 selectivity which started at a high of about 37% Fe catalyst and fell to a low of about 20 % with Fe-K and Fe-Mn.
For complete reduction to α-Fe0, higher temperatures or more reduction time is required.

In order to improve the overall efficiency of energy utilization in silicon smelting furnace, a technology solution to recover the furnace radiant heat and exhaust energy was described in this paper; and based on the operation data of a 3200 KV·A industrial silicon smelting furnace, a 400 kW steam turbine generator unit was designed, and the economic benefit from the technology solution was also analyzed.
The results show that this technology solution brings a remarkable performances of energy saving and emission reduction: about 14% of the supplying energy could be recovered; the investment payback period is between two and three years, the economic benefit from the technology solution would reach 4.72 million yuan in ten years.
Industrial statistic data show that in most Chinese silicon manufacture companies, the average power consumption of silicon production per ton is over 13000 KWh, much higher than 11000 KWh in the advanced foreign companies.
During smelting process, it would generate high-power electric arc which cause the reduction reaction between the carbon and silicon dioxide, and the flue gas produced from the reduction reaction should be emitted freely so as to release the furnace’s pressure and decrease the electrode’s temperature.
With the application of waste energy recovery system, energy saving and emission reduction would be achieved greatly: about 14% of the supplying energy would be recovered; the investment payback period is between two and three years, the economic benefit from the technology solution would reach 4.72 million yuan in ten years.

To data, most of the applications for Mg-Alloy are based on casting processes(1,2).
Initial properties of extrusion stock Based on the material data of the fundamental investigations, the explicit finite element code Marc-Autoforge was used to simulate the extrusion processes of the profile.
Fig.3a and 3b shows the influence of the length of reduction zone on material flow for flat die.
In Fig. 3b the length of reduction zone is different, where both of them are identical.
Then extrusion was carried out on the bars at 573,623 and 673K with a reduction ratio of 5:1.

To add damping in reduction gear box is an effective measurement to suppress box resonance.
This paper made an analysis at design stage of reduction gear product by finite element method.
Finite Element Model of Reduction Gear Box Model clean-up and finite element mesh.
Own to the connecting role of various bolts in reduction gear, this is also ignored in the modeling.
All load data of box in this paper is provided by an institution.

Electrical data is analyzed and deviations in the ΔV signal are compared with defectivity observed by the optical surface detection system with UV-PL capability.
Reliable statistical data of the relationship between decreasing voltage and defect classification show good detection of triangles and several other defects in the epitaxial layers.
The data is collected on 25 wafers of 200 [mm] 4H-SiC with n-type SiC epitaxial layers.
Logarithmic distribution of defectivity with overlapping voltage leakage sites, see Tab. 1 for corresponding data.
The data from QUAD and UV-PL do not correspond one to one and UV-PL gives more detections.

This method adopts PSO to eliminate the superfluous parameters in SVDD and carries out dimension reduction to data; then, establish the super sphere model to detect the network intrusion data and output the results of intrusion detection.
Provide the data set , of which the normal data set is and abnormal data set is .
Experimental Verification Sources of Data The experimental data set adopts standard data set KDD CUP’99 assessing intrusion detection.
Fig.1 Process of PSO-SVDD Intrusion Detection Method Experimental Plan Design Since KDD CUP’99 original data set is very large, the experiment chooses kddcup.data_10.percent of representative data in KDD data as the training data.
Considering that there are only 52 records of U2R in kddcup.data_10.percent data set, in order to expand the sample set, 396 sets of data are extracted in the kddcup.data.corrected data set as the training data.