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The grain growth becomes significant at high densities of ρt > 80% probably due to the reduction of pore dragging effect.
The present result is compared to the earlier SPS data reported by Bernard-Granger et al. [7].
Although the present result is almost on the same order as the earlier data, which is obtained at almost the same temperature of 1225°C, the -(σeff/Geff) relationship is inconsistent with that of their data.
Except for the difference in the densification rate, the present result is consistent well with that of the earlier data obtained by HP technique [8,16-18].

These formulas established on the basis of tests and large amounts of measurement data could be accurate and reliable only if the object of research is similar to the case from which the data is obtained.
The boundary element method has the characteristic of dimensional reduction and adapting to the infinite domain, thus becomes an effective numerical method of solving the structure-borne noise.
Establish the acoustical mesh and field point mesh Establish the structure model Compute the vibration response of the structure (displacement) Acoustic transient response analysis case Define the displacement boundary condition Data transfer analysis case Acoustic mesh preprocessing set Import the acoustical mesh and field point mesh in LMS Virtual.Lab Acoustics Import the structure mesh and the transient dynamic results Set mesh parts type Define fluid material and property Fig. 3 Calculation step of vibration and radiated noise Calculation example for elevated bridge vibration and radiated noise Calculation with the moving load model.
Table 1 Maximum values of bridge vibration response Position and case Displacement[mm] Velocity[m/s] Acceleration[m/s2] Left span Model 1 3.23 0.00462 0.23137 Model 2 3.23 0.00845 1.75564 Middle span Model 1 1.64 0.00452 0.25292 Model 2 1.65 0.00875 1.92357 Right span Model 1 3.22 0.00522 0.25454 Model 2 3.23 0.00916 1.75154 Table 2 Maximum values of noise pressure[dB] Position and case Point A Point B Point C Left span Model 1 87.36 86.22 82.43 Model 2 92.63 88.64 84.87 Middle span Model 1 78.96 76.11 72.06 Model 2 89.61 83.29 79.38 Right span Model 1 92.61 87.53 85.02 Model 2 94.63 87.89 86.69 These data indicates that the displacement response based on the two kinds of vehicle model is the same, as the velocity and acceleration response has an obvious difference, the response of bridge structure with mass-spring system model bigger than the one with the moving load.

During the course of continuous work or driving, significant reduction in a person’s attention, concentration, sleepiness and loss of ability to sustain a required performance are some of the major concerns brought by fatigue.
The analysis system took National Instrument’s LabVIEW software as its development platform to read and analyze the EEG data.
The EEG data were saved in .txt files and processed.
Analysis results of theta data on six experiments for good and poor sleepers.
Although the research had a limited number of subjects, data showed a sign of consistency in relation to how the subject slept the night before and their current condition.

Temperature data are recorded every 10mins by using Agilent 34970A. 1- thermostatic water tank;2-valve;3-pump;4-flowmeter;5- HPETC;6- SFPC Fig. 1 The diagram of the experimental system Experimental results and analysis The entire comparative experiment is divided into two parts: one is that the performance of these two kind collectors is observed through keeping the inlet water temperature constant and changing the mass flow rate of water; the other is just the opposite.
If the experiment is performed at normal conditions so that F'(τα)e is constant and both F' and UL are constant, a straight line will result when the efficiencies are obtained from averaged data plotted against (Tm-Ta)/I according to Eq. (4).The intersection of the line with the vertical efficiency axis equals to F'(τα)e, which means that collector efficiency is at its maximum.
In addition, with the reduction in the intensity of solar radiation, heat dissipation from the SFPC to air is higher than that from the HPETC.
Fig. 3 Outlet temperature of collectors changing with different inlet temperature The data from 8:30~10:30 are chosen for the reason that the data after 11 o'clock are unstable.

This can be provided directly, for example by means of spindle driven tools, or externally by means of a drive which is not part of the machine tool. [6] The use of actively rotation tools achieves higher machining productivity at lower temperatures. [9] The temperature reduction during the machining process is achieved by rotating the tool.
From the measured data, can be seen the difference when changing the value of the feed.
Based on these data it is possible to construct a graphical representation.
Based on the performed experiment and the measured data, we can state that the lowest values ​​of the roughness parameters were achieved at a feed rate of 1.2 mm (Fig. 10).
This is evidenced by the measured data.

The choice of the temperature range is made based on sintering temperature data under production conditions.
The data from FIZ/NIST ICSD database were used as structural models.
It can be seen, that the symmetry reduction (Fd-3, I41/amd) does not occur.
Table 2 shows the refinement data for both batches of the samples; experimental, theoretical and difference diffraction patterns are presented in Fig. 3 Figure 3.
The authors are grateful to Pavel Chizhov (Thermo Teсhno, Moscow) for help in experimental data analysis.

The observed diffraction pattern was in good agreement with the PDF-2Plus data of β-AgI (No. 01-078-1614), hence the crystal phase was identified as β-AgI.
The trajectory of the plotted data follows a semicircle.
The DC resistivity was estimated from the intersection of the data in the low-frequency region and the real axis, and DC electrical conductivity s was estimated by taking the reciprocal of the resistivity.
Fig. 4(a) XRD profile of the as-prepared AgI thin film, (b) PDF-2Plus data of β-AgI (No. 01-078-1614).
That is, it is concluded that this contraction is reflected in the reduction of ionic conductivity and the increase of activation energy.

Fig. 5 Curve of vault settlement with time Fig. 6 Curve of peripheral convergence with time Figs. 5~6 show that the curves of vault settlement and peripheral convergence are basically the same; the vault settlement is always greater than peripheral convergence, both of which increase rapidly in about 300 hours (t=350h) after excavation and then turn into a gradual growth stage with basically stable deformation in line with the u-t curve law of in-situ monitoring data.
Thereinto, the vehicle load is considered as highway class I load with horizontal load reduction coefficient.
The corresponding data of vertical displacement obtained by numerical calculation of ANSYS show that the tunnel vault would produce certain additional settlement of about 3.27cm under the action of inverted arch backfilling+ vehicle load+ collapsible loess soaking; the reinforcement treatment of foundation by high-pressure rotary spraying can improve the property of soil mass to make the additional settlement decrease in a certain degree with value of about 2.27cm.
The comparison between numerical results and measured data shows that the u-t curves of vault settlement and peripheral convergence are basically the same with close data, which can validate the validity of presented models and explain the tunnel displacement characteristics reasonably providing reference for the design, construction and monitoring of loess tunnel projects in the future.

Force components were measured with KISTLER 9257B three-component, piezoelectric force measuring machine and data recording system.
Diagram f-Fc, f-Ff, f-Fp Literature data and later experiences shows, that surface roughness after burnishing depend on hard turning surface roughness.
fb Fb rv Workpiece PCD-insert Fig. 5.Schematic and photo of burnishing tool with PCD-insert Experimental results During the experiments, we measured force components by dynamometer KISTLER 9257B and by data recording system.
In tables values with index o presents the average of roughness data after hard turning.
The reduction slightly depends on feed and greatly depends on burnishing force.

- command and control system for furnace based on a digital temperature regulator that allows the implementation of different regulating laws, an programmable microcontroller and data acquisition interface; Fig. 1.
Mechanical and technological characteristics of the material are [2,6]: - characteristics of material (at t = 20 0C): density r0 = 7753.6 [Kg/m3], specific heat C0 = 475.42 [Wh/Kg 0C], thermal conductivity l0 = 44.51[W/m 0C] - mechanical characteristics: hardness = 22 [HRC]; internal stress = 920 [Mpa]; elongation =14 [%]; reduction of section = 60 [%]; charpy value = 60 [J] - critical temperatures: Ac1 = 713.20 [0 C]; Ac3= 787.24 [0 C]; Ms = 331.72 [0 C] The parameters of the heat treatments which is applied to piece determined by the program to predict the structure and mechanical properties of heat treatments piece: - normalizing: temperature 841 [0 C], heating time 5.040 [sec], maintaining time 1.048 [sec], cooling on air; - quenching: temperature 831 [0 C], heating time 5.326 [sec], time 1.065 [sec], cooling on oil; - tempering: temperature 570 [0 C], heating time 12.546 [sec], time 1.048 [sec], cooling on air.
The experimental results, taken from data acquisition board installed in the electric furnace control system for quenching and high tempering treatment temperature diagrams - diagram calculated with classical algorithms heating and actual temperature of the furnace resulting from predictive PID control algorithm shown by thermocouples placed in the furnace vault and the finite element analysis (FEM) of the evolution in the time of the temperature and heat flux quenching and tempering the piece subjected to heat treatment conducted in the furnace with thermoregulatory controlled with PID predictive.
Graph of change in hardness HB of according to the measuring points According to the data presented in specialized standards-hardness steel C45 RO1.0503 they are made of low-power turbine blades for the treatment of normalization is 235 HB, comparing the results obtained shows that when treatment is classic the average hardness of 231.5 HB less than the requirements of the standard, and if the heat treatment temperature sensitive 244.8 HB average values are predictive for thermostatic a step higher values of standard requirements.
The experimental results are taken from data acquisition board installed in the control system of electric furnace for heat-sensitive treatments.