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The point is that fatigue crack growth data on the 15-5PH-type steel are not widespread in literature, especially in relation with ageing.
The secant method was used to analyse the fatigue crack growth rate (FCGR) data.
Repeated tests were conducted for each given testing condition and only small scattering of the experimental data was observed.
However, a reduction of this domain is observed with ageing time and temperature.
This data will be used to describe the crack tip behaviour which is going to be implemented in a model that could account for the observed phenomena [9, 10].

The fit, ( ) ( )[ ] 18 *10 1371.2 ln / 255 / 1.2924 DN RGB t = − − to the data in Fig. 3a may be used for calibration, where RGB and t are the transmission intensity with a scanner 0.57γ= and the thickness of the wafer, respectively.
While -1 0 2.546 cm α = compares quite well with data from Wellman et al., ,0 18 -3 7.122*10 cm DN − = is approximately 20X smaller [9].
The samples were provided by two vendors, A and B with the corresponding data presented in Fig. 3 b) and c), respectively.
Presented as open boxes in Fig. 3b are data recorded for a moderately doped 4H-SiC substrate following the growth of a ~100 µm n- epitaxial film.
The open boxes represent data from a sample with a 100 µm epitaxial film.

As a result, variation in the calculated roughness value was more or less different from the measured data produced by them.
By comparison between empirical data and computed values, the validity of the proposed formulation was proved.
The material in the filament is melted in a specially designed head, which extrudes a layer according to generated section data from a prepared 3D CAD model.
Gaps between empirical data and computed values are within 3 micrometers.
This is also due to reduction of layer thickness by the equation (7).

(2)regulating cost of AGC and, :unite it's regulating cost in period j; :unit is quoted price of AGC market capacity in period j;:frequency regulation of AGC causes the increase of cost; Therefore, the objective function of AGC dispatching model is: Except the above data, other data explain as follows: I,m,n: correspond to the numbers of the conventional generation, the micro-gas turbine and gas generator;,0-2 variation, it depends on whether unit i, m, n participate AGC service;respectively correspond to AGC upward regulating capacity of unit m,n;respectively correspond to AGC upward regulating capacity of unit I,m,n. 1.2.2 Constraints The concrete expression is as follows:
Except the above data other data explain as follows:the total demand of AGC in period j;AGC response time; respectively correspond to AGC regulating speed of unit I,m,n;the base load capacity of unit i in period j; respectively correspond to the upper limit of AGC regulating capacity of unit i,m,n; lower limit of AGC regulating capacity of unit i. 1.3 Accounting Examples 1.3.1 the relevant data This chapter takes the micro-grid system which consists of DG and thermal generation units as the Studying system.
Figure 1.2, whether that system is a stand-alone or networked mode, the system frequency deviation, non-plan exchange of power in under the control of DG units to participate in a faster reduction in amplitude and in a networked way, DG to participate in AGC system to a larger reduction in oscillation frequency offset rate.

Analysis of test data shows that, addition of organo-clay improved mechanical properties of O-Mica/PP nanocomposites.
As it can be seen, the melting point (Tm) of the nanocomposites showed a reduction as compared to neat PP because increased interactions of clay particles-pp matrix affect chain mobility [14].
This reduction is attributed to poor adhesion between clay particle and matrix as a result of incompatibility when rigid filler is added.
Conversely, the degree of crystallinity decreases with clay content as shown in DSC data.

The authors in [8] deploy least squares error correction based on overall median of individual single lead data to reduce baseline drift.
The ECG data comes from the database of MIT-BIH.
Fig. 4 and Fig. 5 describe No. 109 and No. 203 ECG data in the MIT-BIH arrhythmia database including a lot of baseline drift.
We choose eight group data from the database, and the data of No. 100 and No. 102 keep the same accuracy rate for the two methods.
Our method can improve the accuracy rate from 0.1% to 5% in the other six group data, especially for No. 203 and No. 222 data including a deal of baseline drift noise.

The survey and reserch takes the data during the morning rush-hour crush.
Phase diagram Analysis of vehicle flow and flow direction during the morning rush-hour crush Our survey and reseach took the data of the morning rush-hour crush.
As the setting of left-turn waiting area, we got following data based on actual observation.
Observation data showed that each left-turn waiting lane could have a capacity of 5 vehicles.
This paper simulate intersection various imported traffic capacity using following steps: Extend lanes (prevent vehicle queue length more than vehicle produce position)if VISSIM error, and termination; The vehicles generator produce vehicles by 3600 peu/h, provideing saturated flow; Set the simulation 5 h, get a statistical data every 30 min; Extract the biggest set of data from 10 sets of data, through calculation get all imports traffic conpacity ; Simulation get each import traffic capacity contrast histogram of no stay line areas, setting left-turn waiting area ,settings left-turn and straight-on waiting areas ,as shown in left picture of Fig.6.From Fig.6, we can see that all import traffic capacity is higher than calculated value because the simulation is under the most ideal situation .The simulation show that setting left-turn waiting area , the intersection capacity increase 7% than no stay line areas set ; Setting left-turn waiting and traight-on waiting area

Data Collection.
Most of the state parameters are gained by data collection work based on sensors.
Cluster analysis belongs to no supervised recognition mode which is suitable for multidimensional data set and powerful for the research of data evenness.
The technologies of data collection, feature extraction and state recognition which are the fundamentals of PHM technology are also presented.
Research of Data Fusion for Diagnosing Types of Tribological Failures by Dampster Shafer.

The reduction in the [VC] after the intermediate and slow cooling suggests that equilibrium is established rather rapidly as the temperature drops.
Data are included for both the group A and B samples.
The reduction in [VC] is accompanied by the appearance of the so-called ON1 and ON2 deep levels at ~0.9 eV and ~1.1 eV below EC.
Finally, DLTS measurements performed at temperatures above 350 K show that the reduction in [VC] is accompanied by the appearance of the so-called ON1 and ON2 deep levels, as illustrated in Fig. 6 for the group A sample annealed at 1500 °C.
However, further studies need to be pursued in order to make a more unambiguous conclusion on the dominant kinetics process and especially, accurate experimental data on the migration of VC and Ci are highly desirable.

Even though there are no experimental data specifically referred to turbo roundabouts, the effect of pedestrian flow on the lane capacity can be assessed by means of German method [4, 11, 12, 13].
The model includes the determination of a capacity reduction factor M.
For a single lane entry the reduction factor M is as follows: (7) where: qk= conflicting flow rate (pcu/h); Qped= pedestrian flow (ped/h).
If we elaborate the case under study, it follows: (8) (9) (10) (11) where: ME,R ped = right-turn lane pedestrian capacity reduction factor; ME,TLT ped = through and left-turn lane pedestrian capacity reduction factor; CE,R ped = right-turn lane vehicle capacity considering impact of pedestrians [veh/h]; CE,TLT ped = through and left-turn lane vehicle capacity considering impact of pedestrians [veh/h]; CE,R = right-turn lane vehicle capacity (no pedestrian crossings, only vehicles) [veh/h]; CE,TLT = through and left-turn lane vehicle capacity (no pedestrian crossings, only vehicles) [veh/h]; CE ped = entry capacity considering impact of pedestrians [veh/h].
The global average delay at entries is expressed by the following equation [3, 4, 5]: (16) In order to define the level of service at each entry, in absence of experimental data (for evaluation of the traffic flows in existing intersections, the image processing technique can be used [21, 22, 23, 24]), valid indications for roundabouts can be given by HCM 2010 (see table 1).