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Equation 5 reveals that NH3 begins the reduction reaction with NOx.
SCR system to reduce emissions of the experiment Diesel engine bench system Diesel engine bench system is composed of diesel, dynamometer, fuel consumption meter, temperature control system, control cabinet, data acquisition system, online computer etc.
The analysis of latter two results has reached the Europe IV standard for NOx emissions requirements.But the self-control of urea injection on the reduction of NOx emissions result is better than the DCU control of urea injection in reducing NOx emissions result and the conversion efficiency is also higher.

The reduction of the plasma flow capacity and the input area of the reactor impeller leads to a reduction of the plasma module coefficient of efficiency down to 45.7%.
Table 1 Indicators of extractants burning Name Flash point, [°С] Ignition point, [°С] Self-ignition point, [°С] Tributylphosphate 144 175 345 Hexachlorobutadiene – – 580 The comparison of the findings (Fig. 3) and the data in Table 1 proves that using the given modes, the HFT plasmatron can provide for the inflammation of dispersed burning wastes and the reactor ignition which result in the optimal operational mode.

With the reduction of the angle, the reacted particles increase, leading to the increase of combustion reaction time.
With the further reduction of the angle, the combustion zone reduces and the microwave energy is enough to make the particle temperature rise rapidly, the time greatly reduces.Fig.2 (b) indicates that regeneration efficiency is higher with the increasing central angle of the filter unit in fixed microwave power, but after the center angle is greater than 40℃,the regeneration efficiency will be significantly reduced, because the larger central angle and greater collection area will due to the lower flow rate.
Table I Comparison of theoretical calculation and experimental data Fig.5 Test equipment Conclusions (1) The larger or smaller central angle of the new DPF is not conducive to improve the regeneration efficiency and reduce the regeneration time.

Some advantages of the semi-solid state processing over the conventional cast include a reduction in the consumption of energy and the cycle time for processing, an extrusion of the die life, elimination of inclusions, improved yield of fine-grained and uniform structures, a reduction in micro- and macro-segregation, shrinkage, micro-porosity and cracking, and enhanced mechanical properties of ingot products [2].
The size of primary solid particle was found to be decreased with increasing cooling rate agreed well with the data of author's previous work.

All iron and steel industry show great attention to energy conservation and wasted heat utilization, because government vigorously advocate energy-saving and emission-reduction.
Thermodynamic system flow is shown in Fig.3.[4] Design data is shown in Table1.
So it can advance interests of energy-saving and emission-reduction, environmental protection, save electricity for company.

The comparison result suggests a very good correlation between experimental and predicted data.
It can learn the variety between the input and output viable, and then get the target data by memorization, association and extrapolation for its good nonlinear mapping ability.
ANN requires that the range of both input data and output data should be 0-1.
The method used in this study is: (5) where X is the original data, Xmin and Xmax is the minimum and maximum value of X, Xi is the normalized data.
Fig. 5 gives the comparison between predicted curves (include the data for training) and measured curves.

S-N data in mid-fatigue life range and fatigue limit data of smooth small specimens are applied for material fatigue behavior.
The data of real axles reveal the difference between material and a special structure.
Totally, 4 pairs of "failure" vs "survival" data for real axle specimens, 7 pairs of the data for material specimens, 6 pairs of the data for similar specimens, 31 pairs of S-N data for material specimens are obtained for the present study.
The "failure" vs "survival" data are given in Table 3.
S-N data in mid-fatigue life range and fatigue limit data of smooth small specimens are applied for material fatigue behavior.

The simulation sensor array template receives field odor data or simulates the data via recorders in database, and transmits to the platform.
The data from the subsystem and the preprocessed data are sent to the web server center and stored in the databases.
In fig. 1, the platform has 5 logic layers that include device layer (data acquiring layer), I/O bus layer (data transmitting layer), data processing layer, algorithm layer and user interface layer.
User interface layer can process user data and user requests, and manage users, data, database, algorithms, and application systems.
So the database system of supporting platform of machine olfaction provides much data for researchers which mine machine olfaction data, create algorithms, and release new data to the server database system.

The adsorption data fitted well with the Thomas and Yoon–Nelson models.
Thus, the contact time for TNT molecule to AmL is shorter at higher flow rate, causing a reduction in qeq* and removal efficiency.
From Table 2, the adsorption data can be best described by Yoon–Nelson models (R2 > 0.92).
The data in Table 2 also indicated that τ values from the calculation were basically consistent with experimental results τEXP.
For TNT adsorption, the column experimental data can be described and fit using the Yoon–Nelson model.

There are reasons for coupling investigations on the residual mechanical properties to fire resistance data, aiming at a more complete knowledge of the behavior of a masonry member during and after fire exposure.
The approach, successfully tested against experimental data already available, features a preliminary transient heat flow analysis which gives a numerical prediction of fire resistance after violation of I (Insulation) criterion; then, a staggered heat flow - stress analysis repeats the heating of the wall up to insulation failure and calculates the thermal strain accounting for cracking; finally, a ‘cold’ structural analysis in compression is performed on the thermally-deformed model after cooling.
It is worth noticing by now that the four values of thickness allow to appreciate the effect of the same exposure duration (240 min) on walls of different thickness (38 and 51 cm); moreover, with a comparison to already available numerical and experimental data, also the effect of different exposures on the same wall (25 cm thick) will finally be appreciated.
All the numerically detected features of residual behaviour, i.e. significant reduction in compressive strength after exposure to a severe fire condition, small (but increasing at increasing exposure duration) reduction in elastic modulus, significant reduction in strain capacity in the pre-peak field, are substantially in agreement with available information from literature and testing and analysis experience [21, 23, 24].
This will allow to appreciate (unlike the graph in Figure 5-2) the effects of different exposure durations on walls of the same thickness and, moreover, to compare data from different sources.