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The laser dressing process is characterized by a small ablation depth and thus very limited heat-affected zone (HAZ) in each pulse.
( , , 1) ( , , ) T T i j k T i j k t t ∂ + − = ∂ ∆ (8) Substituting the above equations into Eq.3, reorganization results in Eq.9: 0 0 1 2 ( , , 1) ( , , ) ( ( 1, , ) ( 1, , ) 2 ( , , )) ( ( , 1, ) ( , 1, ) 2 ( , , )) T i j k T i j k F T i j k T i j k T i j k F T i j k T i j k T i j k + = + + + − − + + + − − (9) where ( )2 tx α∆ ⋅ ∆ and ( )2 ty α∆ ⋅ ∆ are the Grid Fourier factors which may be represented by 0 1F and 02F .
Table 2 provides the physical properties of the bronze bond and diamond abrasives.
It is observed from Fig. 2 that the laser ablation generates an extremely small and thin the heat-affected zone but a high temperature gradient.
[5] Q.F.Ma, R.S.Fang: Practical Hot Physical Property Handbook (China Mechanic Press, 1986).

But there are still some problems about dry cutting Nickel-based superalloy, one of them is the high force and temperature in cutting zone which negatively affects tool life.
Chemical composition of the material was given in Table 2 and the physical and mechanical properties of GH4169 were shown in Table 3, respectively.
Table 1 Tool geometry parameters Table Type Styles D γp γf γo αo κr κr’ λs Ф80mm 3.5o -6o 5o 6o 75o 15o -5o Table 2 Chemical components of the materials used (Wt)% Ni Cr Nb Mo Ti C Al Si Mn 51.75 17.00 5.11 2.93 1.04 0.042 0.41 0.21 0.03 Table 3 Physical and mechanical properties of the materials used Yield strength σs (MPa) Tensile strength σb (MPa) Elongation δ (%) Cross-section contraction ratio φ (%) Hardness HBS 1260 1430 24 40 390 Milling Condition.
In this study, the experiments were proposed in single-factor method, the effects of water vapor on cutting process with the change of milling speed (vc) , the depth of cut(ap), and feed per tooth (fz) were researched.
The cutting experimental study was proposed in single-factor method in milling GH4169.

Non-contact measurement will not affect the test results, but on account of the space limitations, the high test targets surface, and the high price of such sensors or other reasons, the use of non-contact mode testing is limited.
The material properties of the beam are listed in Table 1.
Table 1 Cantilever beam material properties Material Modulus of elasticity Poisson's ratio Mass density 45# 2.1e11Pa 0.3 7800Kg/m3 Fig.4 Mode shapes using FEM: (a) X axis first bending mode; (b) X axis fourth bending mode.
References [1] Kuanmin Mao, Bin Li, Jun Wu, Xinyu Shao, Stiffness Influential Factors-Based Dynamic Modeling and Its Parameter Identification Method of Fixed joint in Machine tool, International Journal of Machine tools & Manufacture, 50(2), 156-164, (2010)
Sanliturk, Elimination of transducer mass loading effects from frequency response functions, Mechanical Systems and Signal Processing 19 (2005) 87-104

Surface roughness affects the functional attributes of finished parts.
Introduction Surface roughness is one of the important properties and the major indicator of surface quality in turning process.
Thus, predicting the surface roughness is of utmost importance for economical and mechanical reasons.
In this research, the CCD Design is an experiment design in which each numeric factor varied over five levels in axial points except the face centered cube (FCC) which can run only with three levels.
Table 1: Cutting conditions in coded factors and actual values No. of Run Type of run cutting speed (m/min) Feed rate (mm/tooth) depth of cut (mm) 1 Factorial Actual Coded Actual Coded Actual Coded 2 Factorial 250 1 0.050 -1 0.100 -1 3 Factorial 250 1 0.150 1 0.100 -1 4 Factorial 250 1 0.050 -1 0.200 1 5 Factorial 250 1 0.150 1 0.200 1 6 Factorial 150 -1 0.050 -1 0.100 -1 7 Factorial 150 -1 0.150 1 0.100 -1 8 Factorial 150 -1 0.050 -1 0.200 1 9 Center 150 -1 0.150 1 0.200 1 10 Center 200 0 0.100 0 0.150 0 11 Center 200 0 0.100 0 0.150 0 12 Center 200 0 0.100 0 0.150 0 13 Center 200 0 0.100 0 0.150 0 14 Center 200 0 0.100 0 0.150 0 15 Axial 134.2 -α 0.100 0 0.150 0 16 Axial 265.8 +α 0.100 0 0.150 0 17 Axial 200 0 0.034 -α 0.150 0 18 Axial 200 0 0.166 +α 0.150 0 19 Axial 200 0 0.100 0 0.084 -α 20 Axial 200 0 0.100 0 0.216 +α Results Two options have been applied to find the best predicting model: the first order model and the second order models.

Due to the fact that the bridge structures experience a service period lasting for several decades or even hundreds of years, under the circumstances of load change, material variation, natural disasters, human factors, etc, it’s inevitable that the damage accumulation or even accidents would happen to the bridges, causing enormous economic loss[1][2].
The development of advanced testing technology requires such properties for the sensors like the small and thin size, which would not affect the structure appearance; the nice connection with the original structure material, on which has slighter effects; the wide coverage of sensing and the wide range of frequency response; the compatibility of the sensors and the other electrical equipments in engineering; the strong anti-interference from the outside; the proper functioning in the temperature range of structure performing[15][16].
Usually the selection of sensors mainly takes the following factors into consideration: the type, precision, resolution, frequency response and dynamic range; the distribution positions, the influence degree of the surrounding dynamic environment and measurement noise.
At now there’re many forms of the data acquisition and communication network, the selection of which should be based on the comprehensive consideration of the factors like the spot condition of bridge, the type, number and sampling rate of sensor.
Because of the wide range and multiple factors involved in condition evaluation of bridge, the understanding of its connotation always gets unbalanced.

Introduction Bismaleimide (BMI) resins, as a kind of high-performance materials, have received more and more interest because of their good thermal stability, low water absorption, and good retention of m -echanical properties at high temperatures.
Although there are many reports about how to improve its performance such as, but fewer attempts have been made to research its rheological properties and curing reaction behavior.
(3) Where η∞ and k∞ are the Arrhenius pre-exponential factors, respectively, Eη and Ek are respectively the activation energies for the flow and the curing reaction, R is an ideal gas constant.
Sci. 45(2010) 1859-1865 [2] Sunxin Zhu, Aijuan Gu, Guozheng Liang, Yuan Li, Dielectric properties and their dependence of polyetherimide/bis -maleimide blends for high performance copper clad laminates, J.
[7] Tang H, Li W, Fan X, etal, Synthesis, preparation and properties of novel high-performance allyl–maleimide resins, Polym, 50 (2009) 1414-1422

Therefore, it is believed that the fatigue threshold of the UFG metals is profoundly affected by the microstructural stability.
Because the stress intensity factors are calculated based on linear elastic fracture mechanics (LEFM), to satisfy the small scale yielding condition, the specimens should be thicker than 2.5(Kmax/σys)2, where Kmax is the maximum stress intensity factor during cyclic loading and σys is the yield strength [11].
Therefore, it is believed that intergranular FCG is characteristic of UFG structures, and obviously, the grain coarsening profoundly affects the FCG behavior.
Benson, Mechanical properties of nanocrystalline materials, Prog.
Cavaliere, Fatigue properties and crack behavior of ultra-fine and nanocrystalline pure metals, Int.

The electrical connection properties cannot send to 3D environment through an interface to simulate the wiring.
The electrical equipment properties can only rely on the bench test, and the test vehicle .etc to verification, that will have an impact on the progress of the project
Wire-harness design is more affected by entire systems of the vehicle.
The electrical properties in wiring diagram can be imported in PRO/E software to do data exchange.
The electrical properties of the schematic design are imported into in the layout diagram.

Consider the influence of multi-factor to the transmission inaccuracy of the output.
In Adams, Define the material properties of each unit.
The inaccuracy of manufacturing and assemble was affected by many factors and has complex combination which should conduct analyze separately.
Paper only considers the key factors which have influence of transmit error in the second level of RV reducer: (1) Deformation in the transmission parts (2) Backlash between crank shaft and bearing (3) Backlash between cycloid gear and pin gears Deformation in the transmission parts.
But the backlash was influenced by gap, deformation and many other factors.

Control and Mechanism Analysis of Serrated Chip Formation in High Speed Machining of Aluminum Alloy 7050-T7451 Qihang Shi1,a, Zongcheng Hao1,b, Shuai Wang1,c, Xiuli Fu1,d* and Hui Wang1,e 1Department of Mechanical Engineering, University of Jinan, Jinan, 250022, China aqh_shi1@163.com, bzc_hao22@163.com, c1256382660@qq.com, d*me_fuxl@ujn.edu.cn, ew_hui21@163.com Keywords: Aluminum alloy 7050-T7451; High speed cutting; Chip formation; Plastic-brittle conversion Abstract.
Under the condition of high speed cutting, the high speed impact of the cutter on the workpiece and the shear behavior lead to the high strain rate of the material in the deformation zone, which makes the dynamic mechanical properties of the workpiece change dramatically, and then directly affects the chip formation mechanism [4,5] and chip shape evolution [6,7].
Since the thermal softening effect occupies the main deformation influencing factors, the material softens, and the serration section is easier due to the pressing action.
The serration frequency is the determining factor for the chip serration unit.
Figure 4 Morphological evolution of aluminum alloy 7050-T7451 high speed cutting chip (a. v = 314 m/min; b. v = 943 m/min; c. v = 1257 m/min; d. v = 1571 m/min; e. v = 2513 m/min; f. v = 3738 m/min) The dynamic mechanical properties of materials are changed by high strain rate in high speed cutting.