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On the basis of taking initial bending and other factors into consideration, through theoretical analysis and finite element calculation, this paper studies the T-stub steel axial compression buckling behavior and carrying capacity mainly using three different cross-section and different lengths ZC cross-sectional specimens.
Introduction T-stub section axial compression bar is flexural-torsional buckling [1], the initial defect plays a dominant role in affecting the stability of the T-stub section axial compression bar, and it is also the core issues in structural design.
Many researchers did some research on the mechanics and deformation properties of T-stub steel, but domestic research on the T-stub steel is late.
Nonlinear buckling analysis In actual project, due to the presence of initial defects and mechanical defects, we often use nonlinear buckling analysis to solve stability problem.
Tab. 3 Simulation values of three section components with fixed-length and fixed bending Components (setting in three kinds of components constant length =1000mm) simulation eigenvalue（kN） L/1000 simulation value affected by Initial bending（kN） ZA 952 936 ZB 950 936 ZC 800 787 The Length of the column is defined in accordance with the standard length of the column in [4].

Even there are many studies about microstructure and mechanical properties of raw Inconel 718 material, effects of welding process to these properties have rarely been examined.
One of the major problems in post-welding properties of nickel based alloys is embrittlement.
Precipitation of γ′′ and coarsening of NbC phases in interdendritic regions of welded specimens are main factors of this decrease.
Average impact resistances of specimens Thereby, both γ′′→δ transformation and interdendritic precipitation and coarsening of this phase were included to fracture mechanism, decrease in the properties of welded specimens was higher. δ phase is in the form of needle-like or lamellar particles and accelerates the decrease in mechanical properties by creating a secondary notch effect [3-5].
Dislocations due to instant application of impact load and deformation hardening due to plastic strain are main factors of the fluctuation in hardness values of non-welded specimens [9-10].

The microstructural changes which occurred during annealing have a significant effect on the mechanical properties.
Grain refinement leads to an improvement in some mechanical properties according to the HallPetch equation [6] and might improve fatigue properties [7] and wear resistance [8].
Measurements of the microhardness using a load of 200 g was used to asses the mechanical properties of the samples.
The shape factors are lower, demonstrating that grains became more equiaxed.
The influence of the type of nanostructure on the mechanical properties of 316LVM steel is the subject of ongoing research.

Beach Profile and Shoreline Sediment Properties at Eroded Area in Batu Pahat M.
The objective of this research is to identify the change in beach profile in the shoreline areas using an Unmanned Aerial Vehicle (UAV) to investigate the physical properties that contribute to the changes in sediment properties.
Failure to determine all the factors stated above will lead to inappropriate data acquisition obtained by UAV, thus, resulting in failure to determine beach volume changes by the aerial image obtained.
The location of Zone B could be one of the factors that contribute to the particle size distribution.
Hakimd, “Sediment Properties of Pantai Punggur,” no.

The cutters especially the disc cutters are the main rock breaking components, which efficiency of breaking rock directly affected the TBM performance [2].
The influence of these factors needed to further investigation.
According to the report of the geological survey and mechanical measuring of rock mass, the intact sandstone is assumed to be the Mohr-Coulomb material [9] and its properties are listed in Table 1.
Table 1 Properties of sandstone Property Value Bulk density [kg/m 3] 2200 Bulk modulus [Gpa] 4.11 Shear modulus [Gpa] 2.95 Cohesion [Mpa] 27 Friction angle [°] 35 Tensile strength [Gpa] 12.7 Dilation angel [°] 10 Simulation Result and Analysis The simulated results are summarized in Table 2.
As the limitation of the software, many factors like the confining pressure, rock joints and fracture are not taking into account.

Zhang 1 1 School of Mechanical and Electrical Engineering, Harbin Institute of Technology, Harbin 150001, P.R.
Cutting speed is a dominant factor affecting the flank wear.
Introduction Particle reinforced metal matrix composites (MMCs) have been widely used in aerospace and automotive industries due to their excellent mechanical and physical properties such as high specific strength, high specific stiffness and high wear resistance.
The intermittent cutting process leads to the mechanical impact.
Although it will affect the surface quality, the construction of BUE can remove the workpiece material instead of the cutting edge during the cutting process.

Buildup of model l The establishment of the fuzzy evaluation model.Fuzzy evaluation involves three main factors：(1)Evaluation factors set U=｛u1,u2,…,un｝, a collection of N kinds of factors of evaluation objects.(2)Comment set V=｛v1,v2,…,vm｝, the various factors of the M kinds of evaluation results of collections.(3)The single factor evaluation r ,To get the corresponding evaluation set V( ri1,ri2,…,rim) ,each of the factors is judged Respectively.
l The establishment of the evaluation factor set.There are many factors affecting the pipeline tube, The influence of various factors on the tube is not independent of each other, on the contrary,it is interrelated.
It Is often a result of the combined actions of multiple factors.Therefore, it is very important to select reasonable evaluation factors.Combined with actual situation, ultimately,we choose six factors ,concluding pipe material (M), pipe diameter(C),laying depth(D), pipe age(L), soil conditions(S), hydraulic pressure(P),as the contestant factor setting up the assembly of evaluation factors.
Factor score are between 1-5, and the higher the score is, the more easily to broke tube ,and the lower the score is, the more securer the pipe is.(1)Score of different pipes.According to the analysis of different pipe material properties, under the same condition, the probability of tubing pipe explosion from high to low is: grey cast-iron pipe> nodular cast iron pip> galvanized pipe> steel tube and pipe> plastic pipe.
For qualitative factors, such as soil conditions, pipe material, expert scoring method is used to determine its membership degree.for quantitative factors, such as pipe diameter, water pressure, pipe material, membership function is used to determine the membership degree.

They can also affect the stability of the visual axis of camera.
The motion of pitch frame is affected by coupling moment and.
The motion of roll frame is affected by coupling moment and.
The paper proposes a novel method for the characteristic, which is introducing a judgment factor abs()<10-7.
Fig.2 The control block diagram of azimuth frame In Fig.2, if the judgment factor abs()<10-7.

AMCs when compared to the base of aluminum alloy, they showed good combinations of mechanical and tribological properties, additionally these properties can be adapted to an explicit requirement [2].
The factors that affect wear have been grouped under the following headings.
There is a growing interest worldwide in manufacturing hybrid metal matrix composites [HMMCs] which possesses combined properties of its reinforcements and exhibit improved physical, mechanical and tribological properties [4].
Therefore, some of mechanical properties and wear rate have been studied in this paper.
“studies on mechanical properties and tribological behaviour of lm25/sic/al2o3 composites” Journal of Engineering Science and Technology Vol. 10, No. 2 (2015) 134 – 144

Where Fl = service factor for driven load Fa = service factor for atmospheric condition Fp = service factor for period of operation [24] The values are given in the table on safety factors for power chain.
A review of physical and mechanical properties of cassava related to harvesting machines. 
Study on the socioeconomic factors affecting adoption of agricultural machinery. 
Research risk factors in monitoring well drilling—A case study using machine learning methods.
Factors Affecting Ballability of Mixture Iron Ore Concentrates and Iron Oxide Bearing Wastes in Metallurgical Processing.