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In the field of welding, the welding thermal cycle generates inhomogeneous heating and cooling, resulting in inhomogeneous microstructure and mechanical properties in the weld joints.
HAZ is so narrow (about 2-3mm) that it is hard to determine mechanical properties on microscale by use of traditional methods.
The variation in microstructure is compared with the changes in micro mechanical properties.
Fig.5 Micro mechanical properties of weld joints Fig.5 SEM image of nanoindentation (a) CGHAZ (b)FGHAZ The relationship of micro mechanical properties and microstructure Nanoindentation hardness variation has a strong relationship with microstructure.
Cementite precipitates and high dislocation density in CGHAZ and FGHAZ are two key factors to strengthen the microstructure with the principle of precipitation hardening and dislocations strengthening, which increased the value of nanohardness.

Therefore, the withdrawal rate is the main factor affecting the as-cast microstructure of the alloy.
Its growth morphology directly affects the distribution of casting defects and has an important effect on the mechanical properties of single crystal superalloys.
There are many factors to affect the rupture property of Ni-based single crystal superalloys, such as dendrite morphology, residual eutectic, pore, TCP phase and γ¢ phase morphology, etc.
The internal pores of the alloy is also one of the important factors affecting the rupture properties.
The fracture microstructure analysis shows that the factors affecting the rupture life are mainly related to the precipitation of TCP phase, pore content and γ' size.

Microstructure, microhardness and tensile properties were investigated in this studied.
Besides that, there is a significant loss in mechanical properties as compared to the base material.
These factors make the joining of aluminum alloys by conventional welding processes unattractive.
The influences of the tool parameter (rotation speed, travel speed, shoulder size) on microstructure and mechanical properties of the FSWed plates were experimentally investigated.
This is because HAZ is a heat-affected-only region.

The factors affecting surface quality of SEAM include electrical characteristics, tool electrode properties, workpiece machining properties, dielectric liquid properties.
Tool electrode properties mean tool electrode material properties, tool movement mode and tool loss properties.
Workpiece processing characteristic includes workpiece material properties, workpiece cutting depth, cutting feed rate and other factors.
Dielectric properties are the injection pressure and proportioning of water-air mixture.
The authors make use of current experiment in order to find out the main factors which influence the workpiece surface quality.

Investigating the Influence of Trace Tantalum on the Microstructure and Mechanical Properties of Niobium Microalloyed Steels Felipe M.
To address this knowledge gap, our study directly compares the microstructure and mechanical properties of two alloys.
All measured mechanical properties were then correlated with the microstructure obtained after rolling and heat treatment.
Mechanical Properties Tensile test Figure 6 shows the tensile test results of the samples NM450 and LG960QT.
Conclusion The presence of tantalum in metal alloys has been shown to affect both microstructure and mechanical properties.

In addition to the gun tube profile, geometric factors such as aspect ratio L/D of the penetrator rod and clearance between sabot and inner diameter of gun tube may affect on the stress of rod.
In addition to factors that affect the stress of rod mentioned above, the clearance between forward sabot diameter and inner diameter of gun tube can affect projectile performance.
As studies combined those factors are very few, this study performed to identify combined effects of those factors on the stress of rod.
ANALYSIS MODEL Material properties used in the analysis are found in Table 1.
Therefore the maximum von Mises stress in Fig.7 is not proportional to L/D, but it is affected by the correlated factors of �� � � � .

This paper base on the actual form and structure of the original bridge piers actual data, according to the exposure collision theory and nonlinear finite element analysis theory, using LS-DYNA software, research the realationship of drift ice strength, modulus of elasticity, thickness factors with affecting convection ice impact force, while the drift ice impact force impact of the bridge was tested and simulated contrast.
In this paper, touch - collisions and nonlinear finite element analysis theory, convection ice impact force on the pier sensitivity factors were analyzed, and the impact of various factors on the impact force of the law and gives reduce the force of impact of drift ice ice body reasonable shape.
In order to understand the main factors convection ice impact force on the pier Effect, according to the results of the previous section drift ice impact force on the piers of the simulation model, this section of stream glacial ice floe size, ice body shape, material strength and elasticity modulus, impact strength and other factors of convection ice.
Affect the flow of ice ice strength is an important factor in the force of impact, and the size of the main ice strength and ice temperature, strain rate are closely related.
Experimental study on mechanical properties of river ice.

On Yarn Unevenness Test and its Influence Factor Analysis Jing Jin 1, a, Jiangping Wang2, b, * 1College of Mechanical & Electronic Engineering, Xian Polytechnic University, Xian, China 2School of Mechanical Engineering, Xian Shiyou University, Xian, China ajinjing5959@sina.com, bjpwang@xsyu.edu.cn, *corresponding author Keywords: Polyester POY, yarn evenness, test, influence factors Abstract.
So the factors which affect filament evenness are complex.
According to the principle of the evenness tester, variation coefficient of yarn unevenness is based on the electrical properties of the capacitor plates and the geometrical factors of measuring space, and is independent of speed in which the sample passes through the gap between the plates.
The paper analyzes the test influence factors when the capacitive evenness tester is used to measure polyester filament yarn unevenness.
Woolen Textile Technology. 9 (2007) 54-57 [2] Zhang Xiaolong, Study on influence factors of evenness test, J.

Application of Artificial Neural Network Based on GA-BP Algorithm To Predicting Mechanical Properties of TC4 Zhezhe Hou1,2,a, , Yanliang Du2,b 1.
Introduction The mechanical properties of steels are remarkably affected by many factors, such as its chemical composition and experienced progress procedures.
The heat treatment is the most effective in all factors so that many efforts have been made to investigate the modeling of the relationships of the mechanical properties and heat treatment of steels at ambient temperature.
On the one hand, the experimental data on composition and mechanical properties of steels are generally polluted by some random factors, and there is little that can be done to avoid such pollution.
After adequate training according to sufficient pilot experimental data, it is applied to predict the mechanical properties of TC4 alloys.

The aim of the paper is to improve the mechanical properties of liquid hydrocarbon storage tank materials.
For environmentally hazardous facilities, it has been important to constantly monitoring [11] their technical condition, monitoring the condition of the surrounding area [12], which they could affect, assess of natural and technogenic factors affecting these facilities, operational loads assess, prediction the changes in technical condition and prediction the impact of factors of various origin.
It is also important to implement the proper materials with necessity mechanical properties for safe condition of tanks.
For instance, in publications [20-22] devoted to effective mechanical properties of nanocomposites, the influence of interfacial surfaces [23] is studied, that significantly affect both elastic fields and effective modules of composite materials.
A study of significant factors affecting the quality of water in the Oskil River (Ukraine).