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Optional secondary processing often follows to obtain special properties or enhanced precision [1- 6].
The most important factor is the porosity.
Porosity changes the properties of thermal conductivity and harden-ability of the material and affects the welding process and affects its character because of the oxides and impurities within the structure.
Other important point is the design factors.
Sarıtaş, AU Isparta: J. of Mechanical Engineering, vol. 7, (1993), p.1 [4] R.M.

Introduction Owing to its excellent mechanical properties, biocompatibillity, biodegradability, and bioresorbability magnesium is regarded as a promising biomaterial for use in porous scaffolds that are employed in tissue engineering applications [1].
Alloying is one of the most effective methods for modifying the properties of magnesium.
Zinc is an essential element for the immune system and for maintaining the co-factor for specific enzymes in bones and cartilage [5,10].
This increase in turn affects the solid solution strengthening of zinc in magnesium matrix.
Chen., Microstructure and Mechanical Properties of Rapidly Solidified/Powder Metallurgy Mg-6Zn and Mg-6Zn-5Ca at Room Temperature and Elevated Temperature.: Journal of Alloys and Compounds, 2013, 560, 161-166 [19] Y.

This terrible environment makes revealing the impact of metallurgical and environmental factors on the corrosion depth and predicting the corrosion degree more difficult.
BP neural network has been exploited to analyze the non-line relationship between various factors and material corrosion behavior for many years [2].
Some previous network models focused on the corrosion properties of conventional steels exposed to inshore atmospheric environment [4-6], but little attention was paid to the recently developed bainite steels corroded in the offshore platform circumstance.
Chemical compositions and mechanical properties of these steels are listed in Tab. 1 and Tab. 2.
The environmental factors (including average concentration of sea salt particles, corrosion cycle, average temperature and humidity) as well as the metallurgic factors (including the contents of C, Mo, Cu, Cr, P, Nb and Ni) were chosen as input parameters.

During welding various defects may occur in areas of welds, heat affected zone and weld metal, e. g. gas cavity, welding slag, incomplete fusion or cracks.
Moreover, the individual factors are frequently multiplied, which increases the total risk of rail failure.
This change in the microstructure and thus also the local properties in the foot of the rail immediately at the surface can be considered as a crucial finding of the analyses.
The transition area between the transformed and the original microstructures ten had the nature corresponding to the heat affected zone typical for the weld joints.
Any other factors having the origin in metallurgical quality, material properties and/or surface defects were not determined.

Introduction Significant progress in metallurgical technologies allows to production different grades of steels from typical ferritic steels to multiphase high-strength steels which are new materials having high mechanical properties, while retaining very good plastic properties.
TRIP steels are classified into the group of Advanced High Strength Steels which are distinguished by very high mechanical properties (above 700 MPa, reaching even 2000 MPa) and the percentage elongation being contained in a fairly wide range from 5 do 30%.
A factor determining the advantageous properties of the TRIP steel is the retained austenite contained in its structure, which undergoes transformation into martensite during plastic deformation, this phenomenon being termed the TRIP (Transformation Induced Plasticity) affect [9].
Nickoletopoulos, Influence of heat treatment of TRIP steel wire rod on structure and mechanical properties, Wire Journal (November 2007) 80–84
Sunderkötter, Properties and application of TRIP-steel in sheet metal forming, in: TRIP – Int.

Forming Mechanism of Folding Defect within Closed Die Forming Car Steering Knuckle Zhao Deying 1, a, Zhang Liandong 1, b and Sun Lina 2, c 1School of Mechanical Engineering, Yanshan University, Qinhuangdao, China 2School of Environmental and Chemical Engineering, Yanshan University, Qinhuangdao, China azhdy@ysu.edu.cn, bfrederic@ysu.edu.cn, clinasun_80@163.com Keywords: steering knuckle, folding defect, closed die forming, numerical simulation, experiment study Abstract.
The results show that the main factors that affect folding defects are the lower punch shape and size.
Severe working conditions require steering knuckles have mechanical property and surface quality strictly.
The main influencing factors of folding defect in car steering closed die extrusion are the shape and size of lower punch.

The energy efficient friction welding process perform with excellent mechanical properties even in long welds due to the absence of porosity, distortion spatter, shrinkage.
The nominal chemical and mechanical properties of the base metal are given in Table. 1 and Table. 2 respectively.
Contour plots show a distinctive circular mound shape indicative of possible independence of factors with the response.
Heat affected zone (d).
[6] C.Maldonado-Zepeda, The effect of interlayers on dissimilar friction weld properties, PhD thesis, University of Toronto, Canada, 2001

Results & Discussion Add and discuss measurement of ionic conductivity and mechanical properties of solid state electrolyte and give at least three examples.
Mechanical Property Test.
But we also need to focus other factor which will affect supercapacitors’ application.
So, the mechanical property is another important factor we need consider about.
The inorganic/organic DN gel shows impressive mechanical property, but, as a electrolyte in SCs, conductivity is another importance factor we need to concern.

The arc form is affected by several factors, diameter size, the amount of current flowing through the electrode [5].
Porosity is an inherent risk factor that is imposed, which is a problem when the intent is to have a weld without cavities.
The heat affected zones ‘s change in length was also analysed.
The factor of power of the machine is 0.73 and has a power efficiency of 80%.
) [22] Senthil K.: Effect of Microstructure and Mechanical properties, in: ResearchGate{online} https://www.researchgate.net/publication / (accessed2021/11/07, 14:21 p.m.).

Optimization needs a lot of on-line parameter calculation of linear motor structure,needs to find out the given parameter input case properties data output corresponding,equivalent to "create" a large number of linear motor,"measurement" performance parameters corresponding to the optimized for comparison.Here to build a new type of cylinder linear motor electromagnetic model is actually a mapping relation:variable is the main structure of the machine parameters,output for the motor that generates the thrust and starting current,the relationship between the two can be expressed as a function: (1) Among them:n is the number of turns of the coil,r0 is the coil inner diameter,g is the air gap,s is the secondary thickness,h is the secondary level,T is the motor thrust,I is the motor current.
The structure of filling functionAnalysis of the influence factors of filling effect.Function filling technology trying to "spackling" local extreme area to avoid local convergence of the algorithm,but structural ideal filling function very difficult.By introducing filling control factor,trying to construct a new filling function,due to the rapid convergence to the global optimal "escape" the search area.With the improved filling function applied to the center of gravity neighborhood estimation algorithm,using classical function verification based on the filling function of center of gravity neighborhood estimation algorithm optimization results.Through the literature data,we can construct the following filled function: (5) Among them, is the current local minimum points of ,if satisfy:1) ,2) has differentiable functions and with ,we can prove that is filling function of at the point .
Cylinder linear motor is researched in this paper,under the assumption that the motor coil symmetric section area in a certain situation,many parameters that affect the performance of the motor,there are 5 main structural parameters:the number of turns of single coil ,which determines the line diameter and current carrying capacity;coil diameter ,which determines the actual volume of motor;the air gap between the primary and secondary ,it directly affects the performance of the motor;the thickness of the secondary ,its change has certain influence on the thrust and starting current in a certain range,but too high will increase the motor's load;secondary height ,directly affect the motor thrust,the current is not affected, but also to bring their own motor load.The original data is obtained by orthogonal optimization,cylindrical linear motor parameters obtained after a range of support vector machine model as shown in table 2: Table 2.
In the parameter range of the linear motor,by the orthogonal method to construct an orthogonal test of 5 factors and 3 levels for the table as shown in table 3: Table 3 Linear motor structural parameters of factor level table Examine factors Level 1 Level 2 Level 3 turns per coil 1500 1700 2000 Coil inner diameter 15 10 20 air gap 2.5 2 3 secondary level 85 95 105 Secondary thickness 20 15 25 The focus on the structural parameters of linear motor is optimized calculation formula,and compared with the traditional orthogonal test optimization results ,the optimization results in table 4: Table 4 The optimization results compared optimization method n r0 g s h T I R Center neighborhood estimates 2120 16.84 1.61 7.68 104.6 42.104 2.891 14.564 Orthogonal optimization 2000 20 1.5 10 105 41.154 2.827 14.557 R is the ratio.Data comparison table showed:center neighborhood estimation optimization and orthogonal optimization of agreed that in the center neighborhood estimation algorithm
References [1] Ye Yunyue,Principle and application of linear motor[M],Beijing,Mechanical industry press.2000 [2] Han Pu, Dong Ze, The development and application of the optimization algorithms,computer simulation,2003,No.z1