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This heat input is responsible for a number of defects in the workpiece like metallurgical alterations, microcracks and residual stresses [6], creating the so-called heat affected zones.
The heat produced by the interaction of the abrasive grains of the grinding wheel and the workpiece is represented by a heat source, computed by Jaeger model [6].
For a specific flow rate, the velocity of nanofluid can be computed and given its properties, i.e. kinematic viscosity and density, the calculation of heat transfer coefficient h is performed after dimensionless numbers Reynolds (Re), Prandtl (Pr) and Nusselt (Nu) are determined for each case.
Nusselt number in the case of nanofluids based on Al2O3 can be computed using the formula proposed by Minea [14]: (4) where φ is the volume fraction of particles.

The resistance coefficient is a function of the particle Reynolds number Rep and is expressed as follows in the Stokes region.
CD=24Rep#2 In addition, the particle Reynolds number Rep is defined as the ratio ma⁄τA of the inertial force ma of the fluid around the particle and the viscous force τA of the fluid around the particle.
Therefore, the particle Reynolds number Rep is expressed by the following equation.
The ingot was quenched 12 (a) and 27 (b) sec. after stirring To fabricate composites with a clear gradient distribution, sedimentation experiments were carried out using fine-grained Al2O3 particles and by extending the sedimentation distance.

The research was conducted as a designed experiment [6, 7] to maximize an information amount about performance parameters at the fixed number of experiment.
Approved design of the experiment Treatment Number Diameter of cavity, A, mm Level of blackening, B, % 1 78 18 2 134 18 3 78 42 4 134 42 5 70 27 6 150 27 7 102 15 8 102 50 9…13 102 27 The statistical analysis followed a typical approach: the analysis of effects, the analysis of variance (ANOVA), the analysis of standardized effects, the possible correction of a model terms set, a test of normality for residues and, finally, prognostic plots: the contour and 3D.
Coefficient of friction– measured and predicted Treatment Number Measured ln(m) Predicted ln(m) Residuals 1 -2.23493 -2.29084 0.055917 2 -2.64508 -2.69001 0.044933 3 -2.27303 -2.28695 0.013926 4 -2.53831 -2.54487 0.006565 5 -3.21888 -3.18426 -0.034611 6 -2.30259 -2.28075 -0.021839 7 -2.14558 -2.08878 -0.056802 8 -2.24432 -2.24180 -0.002516 9 -2.27303 -2.37139 0.098369 10 -2.51331 -2.37139 -0.141911 11 -2.36446 -2.37139 0.006934 12 -2.29263 -2.37139 0.078760 13 -2.41912 -2.37139 -0.047724 The residues were tested for normality by Shapiro-Wilk test and p-Value = 0.9668 was obtained.
Sozanska, A Comparison of Grain Quantitative Evaluation Performed with Standard Method of Imaging with Light Microscopy and EBSD Analysis, Prakt Metallogr-Pr M 46 (2009) (9) 454-468.

(1) Geometry clean and build the FE model (element size is 10mm, component numbers is 47, element numbers is 91853, nodes numbers is 93951), refine the grid quality until the main parameters refer upside reach the initial values; (2) Connect every component.
A Thermomechnical Process for Grain Reinforcement in Precipitation Hardening AA6xxx Aluminium Alloys[J], Materials Letters, Vol.65, NO.6, pp.1028-1030, 2011 [10] Sarikaya O., Anik S., Aslanlar S., et al.

One of the major advantages of using polymers for biosensing is due to their large surface area, allowing a greater number of biomolecules to be immobilized and this consequently increases the number of reaction sites available for interaction with a target species.
The crystallite sizes or grain sizes of the thin film samples were calculated using Debye- Scherrer’s equation, D= 0.94 λβcosθ (1) where, D is the crystallite size, λ is x-ray wavelength (1.5406 Å), β is full width at half maximum (FWHM) of the observed peak and θ is the diffraction angle.
The decreased in roughness can be excused due to the number of voids decreases excessive due to the combination of the voids with each other after irradiation process.

Flux used in this experiment is fused type silicon product with grain size 0.2 to 1.6 mm with basicity index 1.6.
Higher – the- better : (1) Here i =1, 2 ...m and k =1, 2 ...n Assuming, the number of experimental runs in Taguchi’s OA design is m, and the number of quality characteristics is n.
Smaller-the-better: S/N ratio = (3) Here ‘n’ is the number of measurements, and yi the measured ith characteristic value.

The information object can be selected from the CSBD with a catalog or search mode to meet the specific needs of the user through the data module code (Data Module Code, DMC), information control code (Information Control Number, ICN), the type of information and other metadata information.
Each object is assigned an Information Control Number (ICN).
Information control code is structured identifiers composed of numbers, letters and other characters.
The native XML database also has some defects, such as lack of fine-grained data processing ability, not suitable for processing the XML document that data is centralized.

The number of pulses of the plasma arc discharge was 3000 at frequency of 3 Hz.
The kinetic dependences of the friction coefficient of µ on the number of friction cycles N for multilayer coatings of Me1/a-С/Me2 Me1/a-С/Me2 type for the initial fresh coatings obtained were analyzed as well as after annealing at the annealing temperature of 200 and 400 °C.
At temperature annealing of Ti/a-С/Ti coatings, solid phases of TiN, TiC and TiCN, and TiхОу oxides are formed with the formation of crystalline grains.
This increases their ordering and stimulates the formation of carbide carbon-titanium bonds (for Ti/a-С/Ti coatings) or the increase in the number of Сsp2 clusters in the case of Cu/a-С/Cu.

The AWJM consists of different input parameters such as standoff distance, water jet pressure, abrasive flow rate, grain size, traverse speed etc. based on this output responses such as taper, kerf width and surface roughness of the composite are to be studied to have optimized process on cutting.
Using grey relation analysis optimal machining combination is identified [7-9].To know the formation of delamination SEM technologies have been utilized, so that it is easy to study the mechanism of formation of delamination [10].Generally kerf width at top is more in number than bottom kerf [11].
As the feed rate is increased, least number of abrasives takes part in cutting action.
Mass Flow Rate: From the main effect plot shown in figure. 3b, as the large number of abrasive particles indulges in cutting, tends to have proportional increase in depth of cut.

Its crushing value for 7.8%, continuous graded aggregate well grained, specified （JTG F30-2003）. 2 Method of test 2.1 mix of cement concrete The mix of the cement concrete is specified the heavy trafficked road design, e.g the flexural strength is 5.0MPa.
Table 3 The mixes of the concretes and the strength tested（kg/m3） Number cement Fly-ash sand Crushed-rock water admixture nano 28dflexural （MPa） PC 360 0 650 1270 151 3.6 0 5.93 PCF 306 75.6 513 1270 151 3.6 0 5.88 NSC1 304.5 75.6 513 1270 151 3.6 1.5 6.08 NSC2 302.9 75.6 513 1270 151 3.7 3.1 6.49 NSC3 301.4 75.6 513 1270 151 3.8 4.6 6.32 NSC4 299.9 75.6 513 1270 151 3.9 6.1 5.84 The test results showed above, the flexural strength will be increased in concrete added with nano-SiO2, known from the table 1, there is a peak in the series of flexural strength, when the content of nano-SiO2 is big enough, the flexural strength be decreased.
All samples be dried, then signed and weighed and, then be put on the same shelf of bars in according to the signed number.
Table 4 Rate of the Concrete Strength Lost After a Freezing and Thawing for One Cyclical Time Signed number 50times strength contrasted （MPa） Strength tested after 50times （MPa） rate of the concrete strength lost（%） 100times strength contrasted（MPa） Strength tested after 50times100（MPa） rate of the concrete strength lost（%） PC 60.2 56.5 6.2 62.8 54.2 13.7 PCF 58.4 55.6 4.8 63.5 56.7 10.7 NSC1 64.3 63.3 1.6 68.7 65.5 4.6 NSC2 67.6 66.7 1.4 70.0 67.3 3.8 NSC3 66.2 65.5 1.0 69.3 67.2 3.1 NSC4 57.5 56.8 1.2 67.5 65.3 3.3 Table1 Influence of Resistance to Frost of Cement Concrete With SiO2 From Table 4 and Figure 1, frost-resistance of the cement concrete substituted with fly-ash and nano-SiO2 as admixture will be increased higher accordingly than the resistance to freezing of the cement concrete substituted with fly-ash.