Search results

Biofine and Texaco research [3] demonstrated that introduction of EL into fuel compositions causes reduction of particulate matter (PM), hydrocarbons and carbon dioxide emissions.
The increase of EL-FAME content resulted in further reduction of WS1.4.
Addition of 1% (V/V) of a EL-FAME caused the reduction of the friction coefficient to 0.193 and the increase of the lubricating film thickness to 65%.
Further increase of biocomponent concentration to 7% (V/V) caused the reduction of the friction coefficient to 0.134 and increase of the lubricating film thickness to 72%.
Data in the second column is based on the reference [6].

Using the obtained data (weight changes), absorption (Q) is calculated according to the following formula, (1) where Q is the absorption, is the change in specimen mass in grams, at the time t, a stands for exposed area of the specimen, in mm², and d is the density of the water in g/mm³.
Reductions in the maximum rate of heat evolution for those mixtures of SAE and SBR were also reported in the mentioned references.
An interesting observation is a reduction in initial absorption rate dramatically after the addition of polymeric material.
The highest further reduction in the initial sorptivity was obtained on the mixture of C75-P10 with a 55% rate, which corresponds to a reduction of 84% with respect to the control mixture (the one without polymer or nano-silica).
Guerrero, Reduction of the calcium leaching rate of cement paste by the addition of silica nanoparticles.

Although end-use data is still limited, current indicators suggest that the greatest energy efficiency potential lies in industry (34% of the total), the residential sector (33%) and energy conversion at coal-fired power plants (22%) [7].
Economic aspects: • sale of electricity and heat; • carbon credits for emission reductions; • reduction in the cost of purchasing traditional fuels; • job creation.
Environmental benefits: • reduction of greenhouse gas emissions; • improvement of air quality; • reduction of the risk of explosions in mines; • reduction of groundwater pollution.
The synergistic effect, when the interaction of several of the above factors leads to a result that exceeds the sum of the results of each factor separately, provides the following advantages: · The installed capacity utilization factor increases to 0.85-0.90 · Reduction of electricity production costs by 25-35% · Increase in the region's energy independence to 60-70% 3.
Environmental benefits include a 25-35% reduction in greenhouse gas emissions and a 30-40% reduction in disturbed land areas; 4.

The analysis results of roller bearing experimental data confirm the feasibility and validity of this method.
Sparse decomposition has good noise reduction effect, and reconstructed signals can secondary denoise effectively by delayed correlation, so it could extract the resonance zone of weak fault signal from strong noise by choosing appropriate iterative termination conditions.
The analysis results of roller bearing experimental data confirm the feasibility and validity of this method.
Bearing experiment signal analysis The experiment data was obtained through experiment system, which is made of bearing test bench, data acquisition instrument named HG3528A and computer.
Fig.1 Experiment system Selecting the inner ring of the single point early pitting fault test data to analysis，the original signal waveform and spectrum diagram is shown in Fig.2.

However, due to the enormous cost of the large number of flight conditions and configurations to be analysed, a significant part of aircraft and engine certification still relies on linear models supplemented and tuned by test data.
The computations match the hump mode flutter onset experimental data well for both configurations.
The nonlinear steady flow field data for the F-16 simulation were supplied by Navier–Stokes CFD.
This analysis predicts aero elastic instability at speeds, frequencies and negative damping levels that are consistent with the F-16 flight test data.
Modelling Structural Nonlinearity in Airframes A recent study has been directed at developing the computational aero–thermo–elastic methods necessary to model all these effects and validating that model with wind tunnel data.

The continuous decreasing trend of saturation magnetization (Ms) with increasing of milling time can be explained by the reduction of copper oxide by (CoNi) oxide formation, confirmed by powder XRD patterns.
In this study, the Rietveld analysis program of TOPAS (Bruker AXS, version 4.0) was used for the XRD data refinement.
The microstructure features of powder samples which were calculated from XRD data and refined with Rietveld analysis, one mechanism could be concluded for these alloys as, the broadening of the reflections of Cu is primarily due to milling caused distortion in the lattice.
In accordance with the experimental data obtained for 3 samples (cold pressed and sintered) in each series, the optimized data has been presented in the Table 1.
The mean strain values (msv) measured by XRD data ranged from 0.14 for 30h to 0.215 for 60h milling, explains grain fragmentation, increase of residual microstress by the continuous grain fragmentation and the lattice deformation due to the formation of metastable CuCoNi solid solution.

As seen from the figure, the data points of tangential stress range and compressive stress range for 12 Cr at 300 oC corresponding to particular fretting fatigue strength (107 cycles), regardless of contact pressure shows a linear relationship.
Fig. 3 Relationship between tangential force coefficient and stress amplitude for 12-Cr steel at room temperature and 300 oC However as seen from the Fig. 4 the data points corresponds to room temperature and at 300 oC did not lie on the same line.
The mismatch in data points was due to their difference in tensile strength, as TSR-CSR diagram is a material property and its depends on tensile strength of the material.
The data points of tangential stress range and compressive stress range in Fig 4 were normalized using tensile strength and plotted in the generalized TSR-CSR diagram which is shown in the Fig. 5.
As seen from the figure, after normalizing the data points of tangential stress range and compressive stress range for 12-Cr steel at room temperature and at 300 oC were lie on the same line.

In order to quantify the energy-saving and emission reduction potential of large sail-assisted ship, the energy-saving and emission reduction were estimated and analyzed in paper [1].
The thrust simulation data of this range, as shown in table 2: Table 2 .Wing thrust simulation data (N/m2) Wind speed Wind direction 5(m/s) 10(m/s) 15(m/s) 20 (m/s) 60° 49 143 315 582 70° 60 178 371 672 80° 68 200 424 742 90° 78 225 467 808 100° 81 239 474 808 110° 84 238 483 814 120° 81 231 466 779 Average thrust 72 208 429 744 Experts believe that when we choose 4 wing sails, which surface is 400 m2.
Wind speed was 10 m/s and 15 m/s, there were ship speed data of installed wing diesel ship and no-sail ship, as Fig. 3 shown.
The parameters data of “Wenzhuhai” Item Symbol Unit Value Length overall L m 225.0 Length B.P.
Real ship wind speed data of the test method of correction.

This value is smaller than the previously reported data; ΔL/L =2.2% (2.5×1022cm-2, En>0.1MeV, 650-700K).
This means that another rate limiting process is necessary to understand the PIE data.
The dissolution rates were calculated to be 1.714×10-8g cm-2 h-1 by these impurity data.
Figure 4 shows the comparison of the PIE data of H/Hf ratio with that calculated by the dissolution rate (□).
The calculation results are in good agreement with PIE data.

Hagen et al. [3] and Hagen and Larsen [4] conducted a numerical study to generate data for developing a design model for the shear force capacity of steel beams with web holes, both with and without transverse steel stiffeners and opening strengthening.
The program was calibrated and verified using experimental data from the literature.
Fig. 9(b) shows a bar chart with data on how ultimate load percentage and effective stiffness losses are impacted due to the size of the opening.
These data demonstrate that all unstrengthened steel I-columns suffered local buckling of column sections, although at various places along the column length depending on the size of the web holes.
Fig. 11 shows the sizes of the web holes against the final axial compressive strength ratio by using data from Table 2.