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Major Events that have Shaped the Field of Quantitative Nondestructive Evaluation Title of Publication (to be inserted by the publisher) Building and Maturing the Science Base The 1970's and 1980's were a period of creating and maturing the scientific knowledge needed to allow the more quantitative interpretation of NDE data.
• Air Force o Provide data, from which information can be extracted regarding the status of systems � area health monitor � real-time sensing of performance o Increase use of models for interpretation o Form multidisciplinary teams to attack complex problems • Navy o Systems operate in a very aggressive environment o Costs of inspection are escalating (8 maintenance hours for each flight hour on one particular aircraft) o Need automated, wide area, and in-place sensors • NASA o Assess structural integrity in difficult to access regions of the orbiter o Reduce incidence of crew loss in Reusable Launch Vehicles � integrated vehicle health monitoring (requires new algorithms to relate output to integrity) o Develop Robust Aerospace Vehicles � sense damage and take corrective action to heal It is clear that embedded sensors and structural health monitoring will be the topic of an increased research and development effort in the future, a primary motivation
being the reduction of time and cost associated with maintaining aging systems.
Work in health monitoring must address a number of important questions such as the development of new sensors, the assurance of their reliability, the development of algorithms to interpret data and make accept-reject decisions, and the determination of the optimum balance between local and global measurements.

In conclusion, reduction peaks in 1724, 1170 cm-1 after O2-plasma treated related to active group which is intense in O2-plasma treat carbon nanotube coating basalt fiber surface, the peak for carbon nanotube damaged or removed. 1180 and 908 cm-1 peak for -Si-O-C- stretching demonstrate that carbon nanotube or other group graft on surface of basalt fiber by the O2-plasma treated.
It shows that nano-phase will enhance the strain rate sensitivity for the neat Basalt, and helium and oxygen plasma treated make the data of the strain rate sensitivity is negative.
The activation volumes of the neat Basalt and the plasma treated Basalt calculated using the yield strength data.
Nanophase will enhance the strain rate sensitivity for the neat Basalt, and O2 plasma treated make the data of the strain rate sensitivity is negative.

Coenzyme Q10 is a lipid soluble antioxidant constituted a tyrosine-derived quinone loop linked to a polyisoprenoid side chain, composed of a unique species of compounds that undergoes reversible oxidation and reduction function of the electron-transport path way [2, 3].
In the present paper, all data were presented with mean values ± standard deviation (SD) for three to six samples.
The data analysis was subjected to the statistical software Origin 8.0.
The size data of CoQ10-NLC was detected by PCS.

Theoretical Background A transitional kinetic model for dehydrogenation of С9–С14 paraffins, which is based on a formalized mechanism of transformations of compounds with allowance for the reactivity of feedstock components and catalyst activity, was developed by combining computational analysis and experimental data.
Table 1 Values of the main kinetic parameters of C9 –C14 alkanes dehydrogenation Reaction Kinetic parameter of the reaction Ea, [kJ/mole] k0, [s-1] k,[s-1] N-alkane Alkene-1+Н2 110 7.45·107  0.5698  N-alkane Alkene-2(n)+Н2 118 8.03·107  0.5235  Alkene-1 N-diene +Н2 190 2.65·1011  2.1079  Alkene-2(n) N-diene +Н2 190 2.65·1011  2.1079  Isoalkene Izo-diene +Н2 150 8.30·108  1.7688  The basic parameters of the model were determined by solving the inverse kinetic problem [13,14,15,16] using data obtained on an industrial plant.
Taken as initial data in this case was the composition of the feedstock hydrocarbon mixture supplied to the dehydrogenation reactor. (2) Depending on the coke concentration, the number of moles of water needed to maintain the equilibrium of the oxidation reaction according to Eq. (1) was calculated.
Results and Discussion During the search for new method of enhancing the LAB production efficiency, it has been found that maintaining the optimum humidity in the dehydrogenation reactor to meet the reduction in paraffin conversion and the increase in the coke concentration on the catalyst surface improves the selectivity of the process and extends the catalyst life.

On the other hand, the objective weighting approaches determine the criteria weights based on the characteristics of the data with mathematical methods, such as the information entropy approach.
After the data standardization with Eq.1, all the criteria scores are converted into positive.
The suppliers’ data of the supply capacity, unacceptable product and delivery delay rate are shown in the 3rd to the 5th column in Table 3.
Talluri, A supply-risk reduction model using integrated multi-criteria decision making.

.% Mo) alloy synthesized by co-precipitation of Ni- and Mo-salts with subsequent reduction in H2 atmosphere at 800 °C was taken as a precursor for the self-organizing catalyst (SOC) [12].
XPS data.
XPS data.
According to XPS data, oxidation of CNF in concentrated HNO3 leads to enhancement of content of surface O-groups (from 2.2 to 6.8 wt.%).

Establishment and reduction of unified differential equation Assuming the distribution coefficient of vehicle mass is 1 and the vehicle has the same road roughness function on four tires, thus the system can be simplified as a 1/4 vehicle model with 3DOF, as shown in Fig.1.
By the contrast it can be determined that the curves simulated in Matlab and Adams have the same shape and data points, which proves that both the simulation results are correct.
PSD of Vertical Acceleration in MAD Comparing the data in Table 2 and 3, we can find the error of the RMS of vertical acceleration in Matlab and Adams is considerably small.
Through the data form Table 2 and Table 3 ,it can be found that compared with the vehicles using wheel hub motor, the Motor Integrated Modular plays a certain role in reducing the vertical vibration and increasing ride comfort, but the effect is not obvious.

In aerated sodium chloride solution, the reduction of dissolved oxygen is considered (Eq.1) Fe = Fe2+ + 2e- (1) O2 + 2H2O+4e- =4OH- (2) The hydroxyl ions (OH-) react with Fe2+ ions to form iron hydroxides according to the reactions: Fe2+ + 2OH- = Fe(OH)2 (3) Fe(OH)2 + OH- = Fe(OH)3+e- (4) Dehydration of Fe(OH)3 leads to the formation of Fe2O3 according to the reaction: 2Fe(OH)3= Fe2O3 + 3H2O (5) According to these equations, Iron oxide (Fe2O3) is the main component of corrosion products [7].
According to the previous results, the corrosion rate increases in the following order: Ni-Resist < ADI < IADI < DI < GI * Electrochemical impedance spectroscopy (EIS): The analysis of Nyquist plots from experimental data is done by using circuit [8] in Figure (6) in which (Rs) represents the electrolyte resistance; (Rct) represents the charge transfer resistance and the constant phase element (CPE).
The impedance data are presented as Nyquist plot for different grades of cast iron samples in figures (7a and 7b).
The main parameters deduced from the analysis of Nyquist diagram which reported in Table (4) From the impedance data given in Table (4), we conclude that: • The value of Rct increases in the order sample GI < DI < IADI < ADI < Ni-Resist • The value of double layer capacitance Cdl decreases in the order: GI > DI > IADI > ADI > Ni-Resist This attributed to increase in thickness of electric double layer, suggested that Ni-Resist sample and ADI sample give a better protection against the corrosion [8].

Its statistical parameters can be calculated by measured load data in the past service period, and it also can be calculated by design load when the measured data is not enough.
But the resistance reduction is considered according to various paths with time.
Its parameters can be comprehensively analyzed and determined by structure actual circumstance, measured statistical data and engineering experience.

Table 2 Data of RSM Number A B C P/% 1 -1 -1 0 92.40 2 1 -1 0 93.57 3 -1 1 0 93.89 4 1 1 0 94.68 5 -1 0 -1 80.98 6 1 0 -1 81.67 7 -1 0 1 96.03 8 1 0 1 96.51 9 0 -1 -1 79.46 10 0 1 -1 84.26 11 0 -1 1 95.65 12 0 1 1 96.28 13 0 0 0 94.82 14 0 0 0 94.79 15 0 0 0 94.58 16 0 0 0 94.85 17 0 0 0 95.68 Analysis of variance Analysis of variance was carried out by Design expert and the results showed that the p values of adsorption time (B), adsorbent quantity (C), the interaction of B and C,quadratic term of adsorbent quantity (C2)were all less than 0.01, which showed that the modified brewer's grains had most important influence on Cr(VI) adsorption; the p value of pH value (A) and quadratic term of pH value (A2)were less than 0.05 and more than 0.01, which had significant influence on Cr(VI) adsorption.
Table 3 Analyze of mean square Sourc of Squares Sum of Square Degree of freedom Mean Square F Value Prob > F Model 567.92 9 63.10 205.06 < 0.0001 A 1.22 1 1.22 3.98 0.0863 B 8.06 1 8.06 26.19 0.0014 C 421.95 1 421.95 1371.21 < 0.0001 A2 2.13 1 2.13 6.94 0.0337 B2 1.50 1 1.50 4.88 0.0630 C2 124.35 1 124.35 404.11 < 0.0001 AB 0.036 1 0.036 0.12 0.7420 AC 0.011 1 0.011 0.036 0.8552 BC 4.35 1 4.35 14.13 0.0071 Residual 2.15 7 0.31 Lack of Fit 1.43 3 0.48 2.64 0.1855 Pure Error 0.72 4 0.18 Cor Total 570.07 16 A fitting model To fit the response surface test data, to obtain the coding variable regression equation of two order polynomial( The eq. 2).
The p vale of the model was less than 0.0001 (very significant), the lack of fit value was of 0.1855 (not significant), which showed that the model fit the RSM data significantly, the equation was of the good mathematic model fit the Cr(VI) adsorption by brewer's grains and adsorption parameters.
[2] G.Qin,M.J.Mcguire,N.K.Blute,et al.Hexavalent chromium removal by reduction with ferrous sulfate,coagulation,and filtration:A pilotscale study.Environ.Sci.Technol.,2005,39(16): 6321-6327