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It was found that intercritical annealing temperature and holding time affected the microstructure and mechanical properties of dual phase low carbon steel.
Thus, dual phase steels have characteristic mechanical properties which include low yield strength and high ultimate tensile strength as compared with conventional low-carbon steel [3].
For mechanical properties, the samples were cut in to two parts.
Decrease in strain can occur due to two factors, such as the residual stress during the transformation of austenite to martensite during cooling and dislocations increases with increasing volume of martensite [4].
Miler, Mechanical properties of ferit–martensit steels, New Orleans, LA, USA, 1979

Taguchi method is used to design and accordingly L27 orthogonal array with five factors viz particle size, weight percentage, cutting speed, feed and depth of cut each at three levels is employed.
While machining AlMg alloy feed rate was the major significant factor for surface roughness and other factors viz cutting speed and depth of cut slightly affect the surface roughness [9].
Uniform distribution of reinforcement material should be ensured because homogeneous reinforcement distribution gives better properties.
Analysis of Variance is performed to investigate the significance of process parameter affecting the response.
From the ANOVA table, it is incurred that all factors significantly affect the response of surface roughness.

In principle, they determine part of the affected relevant utility properties for example by welding technology used during the manufacture process.
The weldability itself varies from material to material and depends on several factors, such as welding conditions, chemical composition or demands on joint properties.
There are two types of documents that guarantee the required quality and properties of weld joints.
This serves as a guarantee of achieving the desired weld properties and protection against the formation of undesirable defects in the weld area such as cracks in the Heat Affected Zone (HAZ) or in the weld, lack of fusion between materials or weld undercut [5].
These defects can be classified as external macroscopic factors.

In other side, mechanical properties are an important factor in determining the quality of artificial leather [3].
Therefore the finer filler particle size gives higher value of the mechanical properties [10].
Mechanical Properties.
Therefore, any change in the formulation, such as filler materials, would directly affect the product properties.
Veeranant, A Study of the Factors Affecting the Separation Force of Artificial Leather Laminating Process, Key Engineering Materials. 728 (2017) 307–312. https://doi.org/10.4028/www.scientific.net/KEM.728.307

This paper is dedicated to the study of the structure, microstructure and mechanical properties of the Cu-Co-based alloys.
It is worth to say that Oliveira and Filgueira [7] stated that the mechanical properties are the main properties for the selection of a metal matrix for bonding diamonds in impregnated diamond cutting tools.
And the same effect on mechanical properties of bulk sintered is also concluded.
From the mechanical properties results, shown in Fig.5 and Fig.6, respectively, one can observe basically three affects: (1) the solid solution hardening in Cu-Sn and Al-Fe solid solution is one key factor caused the mechanical properties enhanced as the sintering temperature increase; (2) pores are the origin of crack, melted and plastic deformation of Cu occurs during hot pressing, so pores will be filled and refined and lower porosity with higher temperature, in addition, lower porosity causes the increasing of mechanical properties of Cu-Co-based alloys bulk; (3) for 750°C and 790°C, hardness values for Cu-Co-based alloys matrix are the same, but tensile strength and compressive strength values become higher from 750°C to 790°C, due to the second phase dispersion hardening enhanced with the dark particles more dispersed.
As the sintering temperature increased, the mechanical properties of Cu-Co- based alloy matrix enhanced.

The Volume Strain Energy Density Factor Criterion for Sharp V-notches under Mixed-mode I and II Xiaomei Liu 12*, Yongming Bian 1, Yongcheng Liang 3 1 School of Mechanical Engineering, Tongji University, Shanghai, 200092-China 2 College of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai, 200062-China 3 College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, 201306-China *corresponding author, email: liuxm76@163.com Keywords: V-notches, brittle fracture, volume strain energy density factor, experimental verification Abstract This paper presents a new energy approach based on the concept of a volume stain-energy-density factor useful to deal with the general problem of brittle fracture for sharp V-notches under mixed-mode I and II.
V-notch specimens and coordinate systems In this paper and , notch intensity factors for mode I and mode II , are defined as ： （3a,3b） When notch angle and , the expression (1) will be degenerated into the mixed mode crack problems.
The required material properties for PMMA were taken from [21] as elastic modulus GP poisson’s ratio strength stress MPa fracture toughness Furthermore specimens of two different notch angles for the mixed-mode of v-notch I and II were also made.
The notch intensity factors for mode I and mode II when the far field stress MPa were also taken from [21] and listed in Tab.1.
Journal of Mechanical Strength, 2008,30(2):288~292 [22] L.

All machining processes result in changes of surface layer properties.
All these characteristics may affect fatigue cracks in machined parts.
In general, compressive residual stresses are to be preferred since they improve the fatigue life of parts and increase stress-corrosion cracking resistance, where as tensile residual stresses are usually detrimental to these properties.
The tool edge geometry also affects the generated residual stress profiles [5].
The finishing process in metal machining is affected by a number of factors mainly from differences in tooling and process kinematics [8,9,10].

Introduction Due to high surface area and low density, nanoporous metals (NPMs) show some novel properties, such as high chemical activity and robust mechanical strength, which have attracted more and more attention as a kind of brand new functional materials.
In fact, such assumptions were firmly demonstrated by the investigation on the mechanical properties of thin films, which was proposed by W.D.
In addition, it was concluded that annealing temperature was the most dominant factor affecting the microstructures of NPC using the range analysis method, on which was our emphasis placed.
Wong, Size-dependent melting properties of tin nanoparticles, Chem.
Nix, Mechanical properties of thin films, Mater.

This paper presents an approach that uses pseudo-3D fracture propagation model to study the influence of petrophysical properties, differential stress, treatment conditions, etc. on fracture geometry.
The stimulation effect is largely affected by the geometry of artificial fractures produced by hydraulic fracturing whose influencing factors include in-situ stress conditions, physical and mechanical properties of coal rocks, treatment conditions, etc.
Factor Analysis Several researchers have studied the influence factors on fracture height[2,3,4,5], while few of them focus on the influence factors on fracture length and width.
Poisson`s ratio affects fracture geometry as well.
Petrophysical properties (elastic modulus and Poisson`s ratio), formation conditions (differential stress), construction conditions (pump rate), etc. have different influences on fracture geometry.

It is difficult to achieve automatic and intelligent monitoring for mechanical properties, and real-time and effective control of mechanical equipment.
The Monitoring System Structure of Mechanical Equipment based on Multi-Agent The monitoring system structure of mechanical equipment based on multi-Agent is shown in figure1.
Do statistical analysis, obtained estimated mechanical equipment condition, forecasts of operating mission objectives and the impact of environmental factors that might work on the device.
The raw materials of concrete are so many; including cement, fly ash, water, carpolite, grit, additive, etc., the ratio of these materials will affect the compressive strength, flexural strength of concrete.
As there are many factors affect the concrete index, and quantitative adjustments more complex, so adopt BP neural network algorithm [10] in the knowledge base of decision Agent.