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The key features of reinforcing steel are illustrated in this paper through conceptual diagrams and experimental data.
The degree of the reduction of elastic ranges and the growth of the curvature [5] varies as a function of the accumulated plastic strain.
In other words, the larger deterioration inside the material influences the reduction of the elastic range (yield surface) and also the growth of curvature depending on the accumulated plastic strain, which results in strain hardening upon loading as shown in the Fig. 5a and strain softening during the reversed loading.

It consists in a diameter reduction from 40mm to 12mm.
The Vickers hardness reduction at the points 13 and 14 illustrates a low cooling speed after the forming (the cooling is made into the dies) or a chemical gradient of the slug.
Influence of different thixoforging parameters on C38 steel mechanical characteristic Speed [mm/s] T°die/T°sl ug [°C] Rp0,2* [N/mm 2] Rm* [N/mm 2] Rp/Rm A% 50 30/1420 537 818 0,66 18,9 50 400/1429 457 756 0,60 21,0 200 30/1420 504 800 0,63 20,7 200 400/1429 458 765 0,60 16,0 Steel data from C38 ≥ 430 650 to 800 ≥ 16 2.

A study of Ti-based implants demonstrated a reduction of ion dissolution by aging of the surface oxide or by thermal oxidation [18].
Statistical Analysis For any given experiment, each data point is represented as the mean ± standard deviation of the mean of all replicate samples.
However, significant reductions in thrombogenicity were observed for ZO and NTO surfaces compared to TO and NT.

Results indicate that significant reductions in the transient swings are obtained with UPFC.
The system data are given in the Appendix.
Appendix Input data for SMIB system.

Introduction Detecting outliers in multivariate data often proves to be more difficult than in univariate data because of the additional ‘space’ within which a potential outlier may hide.
It was decided to use Frequency Response Function (FRF) data in order to monitor the specimen.
The normal model condition is created by the data extracted for the undamaged situation.
· A fair feature is a region of spectral lines on which the normal data and damage data appear to be different or the damage data is separated compared to the spread of the normal condition
· A weak feature is a region of spectral lines on which the normal data and damage data are just separated.

And the relevant model are compared and verified with the experimental datas. .
It is known that experimental values are in agreement with those predicted by Maxwell-Eucken equation at low filler content[10], while the discrepancy is present between the experimental data and the numerical simulation results at much higher filler content (≥15%).
From Fig.3, a reduction in CTE was observed with increasing filler loading.
It can be seen that the CTE obtained from experimental data is lower than that of the theoretical model.

(2.4) According to Fig 2.3,make figure of lg[-ln(1-XC)] plotted against lgt (Figure2.4), Obtained from the slope n, obtained from the intercept Zt,then it is available to know non-isothermal crystallization kinetic parameters according to formula 2.4,and obtain half crystallization time t1/2[6], t1/2=(ln2/Zt)1/n, characterize the rate of crystallization during the process of crystallization,as Fig 2.4 shows, all data are presented in Table 2.
a)pure PET b)3.5ppm c)5ppm Fig. 2.4 DSC curves of samples at different cooling rate by lg[-ln(1-Xc)] to lgt Tab. 2-1 DSC datas of samples at different cooling rate sample R(˚C/min) 5 10 20 30 40 Pure PET Zt -31.786 -22.2724 -14.624 -11.275 -8.343 Zc 0.474 0.881 0.939 0.958 0.982 n 25.966 23.720 21.592 21.375 19.570 t1/2(min) 16.526 8.240 4.522 3.210 2.540 3.5ppm Zt -32.465 -17.182 -11.558 -8.286 -6.596 Zc - 1.37E-09 1.87E-13 8.42E-16 2.61E-18 n 26.213 17.905 16.261 14.481 13.737 t1/2(min) 17.035 8.675 4.910 3.545 2.830 5ppm Zt -32.465 -17.182 -11.558 -8.286 -6.596 Zc - 0.467 0.814 0.897 0.946 n 26.213 17.90534 16.261 14.481 13.737 t1/2(min) 17.125 9.383 5.238 3.745 3.007 Both pure PET and endothermic agent nano composites, the relationship of lg[-ln(1-XC)]and lgt is not entirely linear, the occurrence of a linear deviation comes out during the crystal growth process.
Based on the data of Table 2-1 ,conclusion comes out, subjecting to pure PET and nano composite materials with endothermic agent, kinetic rate constant Zc grows up with the increase of cooling rate, while contrastly, the half crystallization time t1/2 reduces, it shows that the higher undercooling rate lead to the faster growth of the crystallization; Under the same cooling rate, Nanocomposite materials with endothermic agent has less Zc than that of pure PET and larger t1/2, the addition of the third component destructed the regularity of the chains, the reduced crystallization ability of molecular chains, making the polymer crystallization rate decreased, crystallization time prolonged.
Fig.2.5 lgR and lgt to samples Tab.2-2 F(T) and a to samples by the crystallinity of 0.9,0.7,0.5,0.3,0.1 Sample Xc 0.9 0.7 0.5 0.3 0.1 pure-PET F(T) 123.856 115.813 109.627 105.866 98.7165 a 1.132 1.1247 1.113 1.119 1.110 3.5ppm F(T) 182.355 160.786 145.737 128.434 112.675 a 1.2196 1.201 1.191 1.176 1.1481 5ppm F(T) 182.355 160.786 145.737 128.434 112.675 a 1.219 1.201 1.191 1.176 1.148 To achieve the same relative degree of crystallinity, F(T) is larger, the cooling rate is larger, the crystallization rate of system is lower, Because F (T) is the unit time to achieve a relative crystallinity value of the cooling rate .The result is consistent with Jeziorny, with the reduction of crystallinity of samples F (T) values are in turn reduced from table 2-2.

The ten measurement error datum are shown in the Table 1.
Table 1 measurement error datum (mm) Measured NO. 1 2 3 4 5 6 7 8 9 10 Fisrt method Max 0.31 0.322 0.314 0.312 0.315 0.321 0.309 0.311 0.320 0.314 Mean 0.062 0.061 0.061 0.062 0.061 0.062 0.060 0.059 0.059 0.058 St.d 0.049 0.049 0.048 0.049 0.048 0.049 0.047 0.048 0.048 0.047 Second method Max 0.178 0.180 0.179 0.191 0.187 0.181 0.179 0.178 0.179 0.186 Mean 0.040 0.041 0.040 0.049 0.040 0.049 0.048 0.049 0.040 0.049 St.d 0.021 0.024 0.022 0.021 0.024 0.021 0.020 0.023 0.023 0.023 Table 1.
The ten measurement error datum using the two methods.
Sensors, Sensor Systems, and Sensor Data Processing(1997)June 16-20; Munich, Germany
Zhang, Phase unwrapping error reduction framework for a multiple-wavelength phase-shifting algorithm.

Various technologies have been used to remove trace lead, namely chemical precipitation, adsorption, ion exchange, reverse osmosis, and oxidation-reduction [6-8].
The data obtained indicates that the polymeric material modified with iron (C100-Fe) exhibits the highest lead removal capacity and can be applied for the efficient removal of lead from drinking water below drinking standard (0.05 mg/L) around 15,000 BVs.
The data obtained indicate that C-100 Fe exhibits the highest lead removal efficiency and lasts for 15000 BVs when compared with the others.
Available from: http://kmcenter.rid.go.th/kmc10/data/water_annual52.pdf

Results of the present computations are compared with the available experimental data.
The data used in this study are from the experimental research carried out and given in the reports [17,18].
These values of drag coefficient (CD) were compared with the data given in the report [33].
The validity of these empirical relations beyond this range must be investigated with more data.
The computed results showed reasonable agreement with experimental data.