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Thereby, the model can describe the experimentally observed dissolution of dislocation cells and the reduction of dislocation densities occurring shortly after load path changes.
In particular, the model [1] describes the transient dissolution of dislocation cells and the reduction of dislocation densities occurring shortly after load path changes.
The corresponding material parameters should be identified using experimental data regarding both macro- and micro-structural behaviour.

Eight passes applied (with the accumulated strain of 9.2) with the rotation about the Z axis brought about the reduction in the grain size down to 600 nm with the 80% fraction of high angle grain boundaries and a very homogenous equiaxial microstructure.
The data collected during the mapping were subsequently used to determine the grain equivalent diameter (d2), defined as a diameter of a circle with the same area as the measured grain, and the distributions of grain boundary misorientation angles.
Ø Eight passes with the rotation about the Z axis resulted in the grain size reduction to below 600 nm and a very high fraction of high angle grain boundaries of about 80%, while the rotation about the X axis resulted in the grain size below 700 nm with a relatively low fraction of high angle grain boundaries (58%).

The value of information sharing has been well revealed by many researchers, such as Cachon and Fisher [1] and Lee et al. [4] argued that the benefits of sharing real-time information on demand and/or inventory levels of materials between suppliers and customers could provide significant inventory reduction and cost savings to the manufacturer.
Supposing there are n alternatives and m evaluation indicators for each alternative, the original data are shown by the following matrix: (1) The following steps are the procedures of TOPSIS: Step 1: Uniformization of the data matrix There may be positive ones such as benefit indices and negative ones such as cost indices among the evaluation indicators.
And then the converted data are normalized to eliminate the dimensions of different indicators as follows: , for and (2) Step 2: Determination of the positive ideal solution and negative ideal solution Positive ideal solutions are described by vector Z+ and negative ideal solutions are described by vector Z-: , (3) in which , , for.
Results and discussions The data obtained from simulation listed in Table 1 were normalized firstly, and then the positive ideal solution and the negative ideal solution were computed, finally the ranking of polices was achieved by computing the similarities to ideal solution.

For continuous yielding materials, FE analysts can directly use the true stress true strain curve converted from engineering stress strain data.
Propagation of Luders band [2] Modeling stress strain curves using engineering stress strain data Figure 3 shows true stress true strain curve of a low carbon low alloy steel (0.18% carbon), which includes a significant portion (plastic strain of 0.013) of yielding point elongation caused by Luders band propagation, as indicated by L in Figure 3.
Strength coefficient K and strain hardening exponent n are calculated according to ASTM standard E 646-00 [3], which recommends using five data pairs from stress strain curve to calculate both parameters, with the maximum strain is at or slightly prior to the strain at which the maximum load occurs and the lower bound of these strains is the yielding strains (for continuous yielding materials) or the end of yielding point extension (for discontinuous yielding materials).
In many cases, materials handbooks only lists yield strength, tensile strength, area reduction and/or elongation.
Otherwise, guess the uniform elongation at ultimate tensile strength based on stress strain curves available for a similar material (in ASM handbook, or tested data); 3) Convert yield strength and ultimate tensile strength to true stress Sy and Sf using equation 2; 4) Multiply Sf by 1.5 and use it as a initial guess for strength coefficient (K); 5) Use Hooke's Law to calculate strain for stress below Sy and the Ramburg-Osgood equation (1) to calculate the total strain after yielding. 6) Change K and Repeat step 5) until the elongation matches what was obtained in step 2) (Figure 6) 7) Use equation 4 to remove the flat region near yielding point (Figure 7).

.); E7 – establishing of the research equipments (transducers, data acquisition cards, signals conditioning systems, computers, frequency analyzers etc.; E8 – establishing of the programming language for the data control, analysis and displaying; E9 – choosing (designing) of the virtual instruments for the data control, analysis and displaying; E10 – establishing of the variable parameters of the virtual instruments (sampling ratio, window size, temporal window, measuring units); E11 – establishing of the variable parameters of the clamping devices (number of pieces to be clamped, magnitude of the clamping forces, number of clamping forces, etc.); E12 – working out of the experiment strategy (method of the complete factorial experiment, Taguchi methods, etc.); E13 – accomplishing of the experiments; E14 – interpretation of the results.
The measuring equipment consists of: force transducer type S9, made by Höttinger Baldwin Messtechnik, PCB Piezotronics B52 accelerometer used to measure the vibrations; multi channel electronic PC measurement unit, made by Höttinger Baldwin Messtechnik; computer with Catman Easy/ AP data acquisition software, made by Höttinger Baldwin Messtechnik.
Leontiev Reduction of flexible workpiece vibrations with dynamic support realized as tuned mass damper. 14th CIRP Conference on Modeling of Machining Operations(CIRP CMMO), Procedia CIRP. 8 ( 2013 ) 230 – 234

Enter a different frequency control word can get the phase increment accordingly, and then control the output signal frequency; change the amplitude data waveform storage table of contents, can produce a variety of waveforms.
(1) The phase accumulator The basic structure of the phase accumulator is as shown in Fig.4, which consists of binary adder and parallel data register.
Fig.5 The structure diagram of complex function generator system Realization of ROM programming After the initialization data files sinusoidal waveform, using Quartus software customization basic macro function, create ROM waveform data storage corresponding to import the.Mif file.
Function generator is not only support the drawing board for graphics, waveform scan obtained can also identify and reduction output.

But the anti-interference ability of this method is low and the monitoring data were hard to get.
Firstly, the data of transformer winding is monitored.
Then it has (4) By the above formula，The reduction of the sound intensity gainis (5) (6) where is the speed of the ultrasonic wave, is the time of the propagation.
The data is processed by a computer and the test report of transformer winding is given.
Table 1 Measurement data of winding deformation test point actual distance (mm) measured value (mm) absolute error (mm) relative error (%) 1 300 299.3 -0.7 0.23 2 300 299.6 -0.4 0.13 3 290 289.2 -0.8 0.26 4 285 285.5 0.5 0.17 5 300 300.8 0.8 0.26 …… …… …… …… …… By the above table, using the Improved Ultrasonic Ranging method to assess the winding deformation of transformer has the very high resolution and accuracy, can detect the winding deformation accurately.

The objective of these experiments is the optimization on maximum performance and minimum cost taking the following specifications: - No emitter saturation density increase (< 50fA/cm2) - No effective minority carrier lifetime reduction ( > 1ms) due to remaining saw damage, contamination or uneffective passivation - Short process time (<5min SDR, <10min texturing); - Low KOH concentration for SDR (<20%); - Low process temperature for both processes (<80˚C); - Low silicon removal with both processes (<10µm) and reflection at 700nm < 10.5% after texturing).
Results and discussion Figure 3 - SDR experiment (a) Bulk lifetime data for the different etched samples (b) Joe values for the same groups.
Figure 4 – VPD-DC-TXRF data for the different SDR conditions Additionally, surface metal contamination values were measured before pre-diffusion cleaning using VPD-DC VPD-DC : Vapor Phase Decomposition and Droplet Collection -TXRF TXRF : Total Reflection X-ray Fluorescence [7] for all five groups (figure 4).
Figure 5 – SDR - Texturing experiment (a) Bulk lifetime data for the different etched samples.
The silicon removal is still relatively high, between 8µm and 16µm but the lifetime and Joe data shows that an optimum could be found for low SDR and low texturing depth.

Several studies have produced estimates on the influence of rolling parameters [1], but there is still insufficient data for complete understanding.
This data was used to determine the relationship between precipitation state progress - degree of recrystallization of the material, based on the work of Jonas et al [3] where the transformation textures in steel are discussed in detail.
From this data one can see that routes 1 and 3 resulted in the highest relative intensity of the {100} á011ñ component at the final production stage while routes 2 and 4 display maxima in {113}á110ñ, {112}á110ñ transformation components.
Iso-intensity lines: 0.8x -1x -1.3x -1.6x -2x -2.5x -3.2x -5x -6.4x random Route 1 Q1 at 1180 ºC After Roughing Q2 at 980 ºC After finishing Final After ACC + coiling Nb Precipitated (%) 15 33 39 ODF section at φ2 = 45° Route 2 Q1 at 1180 ºC After Roughing Q3 at 800 ºC After finishing Final After ACC + coiling Nb Precipitated (%) 15 40 52 ODF section at φ2 = 45° Route 3 Q1 at 1180 ºC After Roughing Q2 at 980 ºC After finishing Final After Air Cooling Nb Precipitated (%) 15 33 76 ODF section at φ2 = 45° Route 4 Q1 at 1180 ºC After Roughing Q3 at 800 ºC After finishing Final After Air cooling Nb Precipitated (%) 15 40 90 ODF section at φ2 = 45° It should be mentioned that no significant reduction in the intensity of {113}á110ñ and {112}á110ñ texture components was found after Q3 in comparison to the finally processed material in routes 2 and 4.
These results are consistent with data in Fig. 1 which shows that low SFRT promotes grain refinement in the plates subjected to both ACC and air cooling drafts.

During each test, strains, displacements and loads were recorded by a computer-controlled data-logging system at intervals of 0.1 second.
By plotting load and deflection data, derived from the column buckling tests, in this form, "best-fit" straight lines may be derived.
The compression force and strain data used were those corresponding to the compression strain range 500 - 2500 micro-strain.
It was also found that Southwell plots of the test data in the form w/F versus w (Eq. 3) and ε/F versus ε (Eq. 4) enabled the buckling loads to be determined.
In Table 2 a comparison is presented of buckling loads obtained from the FE analyses, the load versus end-shortening curves and the Southwell plots of the test data.