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The influence factors, such as reactant concentration, reaction temperature and ultrasonic frequency were discussed.
However, with the rapid development of modern military technology and weapons systems upgrading, the existing hot-pressing magnesium fluoride material has not been able to meet the requirements of high-speed missile on the mechanical properties of the material.
The ultrasonic can significantly affect the product size and morphology.
(2) Reactant concentration, temperature, ultrasonic frequency affects experiments
[5] Cao Minhua, Controllable Preparation and properties of low-dimensional nanomaterials [D] .Northeast Normal University, 2006.05.10

Fig. 2 Adhesive failure between hot melt adhesives and epoxy primer The bonding failure between hot melt adhesive and epoxy primer was mainly due to following factors: (1) The impact of preheat temperature.
Thus there was not effective physical diffusion or chemical reaction between adhesive and epxoy primer coating, affecting the interfacial adhesion performance
Some of hot melt adhesives were better melted, but others were melted imcompletely, affecting the bonding effect of the adhesive and primer.
It might contain a variety of impurities, which affects the interfacial adhesion property
Therefore, on the condition that there was not effect on the polyethylene anticorrosive, appropriate changing components should be considered to improve the adhesive properties of hot melt adhesive and polyethylene, thereby improving the adhesive properties of the hot melt adhesive and PE layer of main pipe , enhancing the interfacial adhesion strength.

Variable Momentum Factor: We introduce a variable momentum factor in the BP algorithm, and on the one hand, it can accelerate convergence, and can prevent oscillation at the same time[4].
We introduce a factor in incentive function.
Fig. 1 Learning error curve of standard BP algorithm Fig. 2 Learning error curve of variable momentum factor method Fig. 3 Learning error curve of method combining variable step and introducing factor Fig. 4 Learning error curve of fusion algorithm with variable momentum factor and variable step Through compareing and analysing various simulation results of BP neural network algorithm, we can find under the situation in which convergence rate is the slowest is basic BP algorithm showed as Fig. 1 in the same precision, after 5562 times learning ceases, From variable momentum method showed as Fig. 2, we can find the introduced momentum is almost equal to damping term, and it suppresses the oscillation movement of training process, thus affects the network convergence properties, so learning terminate after 3522 times training, and network study times come down, and learning rate increase, but error convergence rate increased a lot, the method combining variable step and
[6] Jian-yuan Zhu, Marine diesel engine vibration monitoring based on BP neural network, Mechanical and Electrical Equipment(2008),p33-36
[7] Xiu-ying WANG, Fault Pattern Recognition Based on Improved BP Network Algorithm, Mechanical & Electrical Engineering Technology(2008),p103-105

Magnetic properties of Y3Fe5O12 magnetic feeders illustrates that Y3Fe5O12 has high Initial permeability (58.054), high Q-factor (59.842) and low loss factor (0.0003) at sintering temperature of 1150°C.
Magnetic properties such as initial permeability, relative loss factor, saturation magnetization and remanence etc depend on the crystal structure and morphology of the garnet materials [7].
Zhang, Structure and magnetic properties of SnFe2O4 nanoparticles, Phys.
Bhattacharya, Size-dependent magnetic properties of nanocrystalline yttrium iron garnet powders, J.
Pascard, The electromagnetic properties of Cu-substituted garnets with low sintering temperature, J.

Method of compound machining is used to process single crystal silicon and SrTiO3 ceramic substrates, and the factors on effects of compound machining are studied such as magnetic field intensity, processing time, rotating speed of lapping plate and lapping pressure.
The type and properties of workpiece material, and machining parameters both have a significant impact on the roughness and material removal rate of compound machining process of polyurethane polishing pad and cluster abrasive brush based on MR effect.
Influence of The Processing Parameters We analyze the factors of affecting compound machining, mainly including: magnetic field strength, processing time, rotating speed of lapping plate and lapping pressure.
Fig. 4 Influence of the magnetic field strength Fig.4 shows the surface roughness and material removal rate are directly related to material properties.
(2) The surface roughness and the material removal rate of compound machining have a direct relationship with the type of material and property.

Mechanical properties of core areas of joints are complex affected by many factors.
Many scholars study mechanical properties of beam-column joints through the testing method.
Joints Design and Material Properties This test researches one specimen under reversed cyclic loading, in which yielding firstly occurs at beam ends and shearing failure secondly occurs at joints [1].
The plastic deformation of the concrete is determined based on tension damage factor dt and compressive damage factor dc.
Based on the energy equivalence principle, concrete constitutive model is determined by Equation (4) ~ (5) considered damage factor

Generated model of the temperature pattern in the lamellate system takes into account system structure, thermo-physical parameters of the each layer material, and process factors: acting heat source duration and intensity, heat dissipation to process liquid, allowing calculating cutting modes, maximum allowed per heating temperature for each layer of the system.
This also affects the process thermo-physics.
Denoting , , for determining coefficients , we generate following system of equations: (15) Because of the quadratic polynomial properties we have formulas: (16) Introducing designations: (17) and , and solving the system Eq. (18) we receive following for the polynomial coefficients:
Xue Mechanical and biological properties of titanium syntactic foams, Proceedings of TMS 2010 Annual Meeting & Exhibition.
Xue Manufacture and Mechanical Properties of Metal Matrix Syntactic Foams, Тр.

The 2XXX and 7XXX alloys series, for example, are defined non-weldable because they form brittle chemical compounds in the heat affected zone and are characterized by high porosity in the weld metal; these characteristics give the joint mechanical properties significantly lower than those of the base material [1, 2].
The mechanical properties of this material are given in Table 1.
If necessary, an aging heat treatment could be envisaged, in order to restore the mechanical properties of the heat affected zones.
[9] Missori S., Sili A., Mechanical and microstructural properties of AA8090 Al-Li alloy welded joints, Metallurgical Science and Technology, pp. 22-26, (2002)
[17] Mashiri FR., Zhao XL., Grundy P., Stress concentration factors and fatigue behavior of welded thin-walled CHS-SHS T-joints in-plane bending.

Experimental results show that the residual stress distribution and the number of cycles to failure of a drive plate are greatly affected by peening process.
Introduction Automobile is operated by interactive movements among respective parts and the fatigue fracture which is generated at this time affects the reliability of automobile.
Mechanical properties of this material are shown in the Table 1.
Table 1 Mechanical properties of high carbon steel.
This is judged to be because grain shape is changed and the effect of factors from microstructure of grain and the effect of stress from uneven deformation affected with compounded effect.

To ensure the using safety and extend applying area of the new green civil material, the key material properties of HPS should be studied, such as fatigue crack growth rate.
As a result, the study in fatigue property of HPS base metal deserves sufficient attention.
Several factors affect whether or not the fatigue cracks propagate and how these cracks propagates, such as elastic modulus, threshold value, and fracture toughness.
Table 1 The Mechanical Behavior of HPS 485W.
Table 2 Crack Propagation Properties of Q&T HPS 485W Steel.