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Effect of Moisture Content on the Tensile Properties of Viscose Filaments Lifeng Xu1,a, Jin Li1,b, Jisong Wu2, Pengcheng Zeng3 1 School of Textiles, Tianjin Polytechnic University Tianjin China 2 School of Textiles, Wuhan Textile University, Wuhan China 3 Xinhua Share Co., Ltd., Fujian China axlfcxlx@126.com blijin@tjpu.edu.cn Keywords: Viscose, Filament, Moisture Content, Strength Abstract.
The results showed that the strength property of viscose filament was decreased after moisture absorption.
The absorption or release humidity not only causes the change in the quality of material itself but also lead to a series of changes in the fiber appearance, mechanical property etc.
Strength of viscose samples This is because the fiber structure directly affects its physical properties.
It's also a factor that reduces its strength greatly.

That is, to satisfy the geometrical similarity as accurately as possible, materials similarity, loads similarity, similar physical properties and similar boundary conditions.
Among them, the geometric similarity ratio of the main controlling factors of the model was determined as 1/40, the mass density similar ratio as 1/1, elastic modulus similar ratio as 1/20, As Table 1shown.to the lining structure, capacity of resistance to bending and bending strain make a control role to security , the bending stiffness should is major in the similar model.
Tab.1 Shaking table model test similarity relation table name indicator ratio name indicator ratio length Cl 1/40 internal friction angle — 40179 Mass desity Cρ 40179 Strain Cε= ClCρCE-1 40180 elastic modulus CE 40198 Displacement Cu=ClCε 1/80 time Ct=Cl1/2 1/6.325 Velocity Cv=ClCt-1 1/6.324 Passion ratios — 40179 acceleration Ca=ClCt-2 40179 stress Cσ=CECε 1/40 force CF=CρCl3 1/64000 cohesion Cc=CECε 1/40 frequence Cω= Ct-1 1/0.158 Viscosity coefficient Cγ=CECt 1/126.5 Damping coefficient Cξ=CρCl2Ct 1/10120 The formulation of similar material in mode The principle to select similar materials[6] Similar original materials of surrounding rock are generally compared of three types of materials ,such as core material , glue materials and auxiliary materials, The choice of similar materials should generally be complied by the following requirements: 1) Uniform, isotropic; 2) The mechanical properties is stable, not easily affected by environmental factors (such as temperature, humidity
, etc.); 3) The ratio of the material can vary the mechanical properties of materials in a larger context; 4) sources of original materials is widely, low cost, solidification time is short, easy to make models.
[5] LI Yong; ZHU Wei-shen; WANG Han-peng; etc.．Study on Mechanical Experiment of A New Type of Geotechnical Analogue Material[J].

A smart, controlled delivery system needs synergistic consideration of several factors; these have been summarized in Fig. 7 [27].
Fig. 7 Requirements of several factors for simultaneous consideration to design a polymeric nanoparticle for the smart drug delivery system.
The two primary parameters controlling the release rates in these systems are the magnetic field characteristics and the mechanical properties of the polymer matrix.
The mechanical properties of the polymeric matrix also affect the extent of magnetic enhancement [40].
Photo-responsive gels reversibly change their physical or chemical properties upon photo-radiation, thus affecting the release rate of drugs incorporated in the polymer.

All factors decide that sheet deep drawing way is the best production method.
Finite Element Model The high-speed railway's track template is formed by 3mm thick 08Al , which sketch is shown in Fig. 1 and which material properties are listed in Table 1.
Then input the parameters of material properties.
Table 1 Material properties of 08Al sheet sσ [MPa] bσ [MPa] E [GPa] n K [MPa] ν 00R 45R 90R 217 388 210 0.21 517 0.28 1.86 1.58 2.01 Fig. 1 Sketch of high-speed railway's track template The Simulation of One Time Deep Drawing The blank shape and its rectangular fitting are calculated by BSE (Blank Size Estimate) function of Dynaform.
He: Mechanical Technologist No. 8 (2001), pp. 37-40 (In Chinese) [8] B.

Prediction of the Flow Stress of 00Cr17Ni14Mo2 Steel During Hot Deformation using a BP Artificial Neural Network Nanhai Hao1, a, Jiushi Li2, b 1 School of Mechanical Engineering, Beijing Information Science & Technology University, Beijing 100192, China 2 Xinxing Hebei Engineering & Research Incorporation Limited, Hebei 056017, China an.hao@bistu.edu.cn, blijiushi08@163.com Keywords: Flow stress; stainless steel; artificial neural network Abstract.
Introduction As a low carbon austenitic stainless steel, 00Cr17Ni14Mo2 (ANSI 316L) possesses properties like high ductility, good weldability and resistance to corrosion and staining.
Due to intensified competition and quality awareness worldwide, now the forming processes have to fulfill more stringent requirements of as complex shape, close tolerances, no defects, improved material properties, control of microstructure, minimized scrap material, long tool live and right first time.
However, most of the factors affecting the flow stress are non-linear, which makes the accuracy of the flow stress predicted with analytical model low and the applicable range limited.
Continuous compression tests were conducted with strain rates, i.e., 0.01, 0.05, 0.1, 0.5 and 1 s-1, to a maximum true strain of 0.7 at temperatures of 800, 900, 1000 and 1100℃ on a Gleeble 1500 thermo-mechanical simulator.

Dynamic model of WIM system The mathematic model of the system as following: (1) m represents its own weight, k is the Stiffness coefficient of the spring and c represents the mechanical damping of the system.
By the analysis in the last section, we know that the poor dynamic quality of the system affects the rate and the grade of accuracy of the weighting .So when the system increases series links, carrying out pole placement adaptive compensation makes the damping ratioζincrease to 0.707, and the natural frequency ωn increase to 100, which constitutes the ideal sensor weighting system[7].
From the figures we can see that the dynamic response property of the system is improved significantly.
Response with compensation 6 Conclusion The paper analyzes an important factor of limiting the speed by which the vehicles to go through from it by building the mathematical model of WIM system.
Factors of dynamic electronic truck scale measurement accuracy and countermeasures [J]. weighing apparatus, 2001, (5) : 33-36 [10] ChenJiZong, Digital signal processing spectrum calculation and filter design, Electronic Industry Press, 2002.09

This combination of properties renders such alloys quite unique when compared to conventional crystalline materials [2, 6].
In order to evaluate the mechanical properties under compression, cylindrical specimens with a 2:1 aspect ratio were prepared and tested under quasistatic loading at an initial strain rate of 810-4 s-1 at room temperature.
By combining the results on the mechanical properties and the microstructural investigations, it is feasible to assume that the microstructural differences in the Cu47.5Zr47.5Al5 and Cu47Ti34Zr11Ni8Si1 BMGs can give rise to the different work hardening abilities.
Consequently, the presence of the fcc nano-particles seems to be essential for ductilizing the material by effectively affecting the shear banding processes (i.e. formation and propagation of shear bands).
Moreover, the differences in elastic properties may introduce stress concentrations favoring shear band initiation in the vicinity of the nano-crystals [41].

However, as a thermal process through melt expulsion and vaporization of unwanted material, laser irradiation causes material properties in the surrounding area to change through heat effect and melt resolidification.
This appears to be different from the grooving of Si under similar condition [11], since the different material properties have important effect on the performance of laser dry machining [13].
The recoil pressure and thermo-capillary force [14] formed in the process, which depend on both the material properties and laser condition [15], supply the driving force for liquid ejection, thus the material is removed both in vapor and liquid forms.
Besides the difference in thermal properties, Ge is roughly twice as dense as Si in both solid and liquid states, thus it is harder to eject molten Ge than molten Si under the same conditions.
The factors affecting the heat source, impinging force and energy loss can affect the results in the hybrid laser-waterjet cutting process.

PVP is a synthetic polymer that has good complexity and adhesion properties, excellent compatibility, good solubility in water, and almost all organic solvents, and low chemical toxicity.
It is widely known that the properties of nanofibers, such as diameter, pore size, porosity, and thickness, are affected by the electrospinning parameters [1].
To design more targeted nanofibers for certain actual use, some factors should be explored, including various factors altering the morphology of nanofibers and the effects of these factors on the properties of electrospun nanofibers.
Carbon nanotube (CNT), which was first discovered by Ijima in 1991, has gained the researcher’s interest because of its superiority in physical, chemical, and electronic properties.
Besides, the dispersion of CNT in the precursor solution is also affecting the fiber formation.

Thermoelastic properties have changed for each heat treatment.
For industrial applications, the characteristics of the thermoelastic properties should be known in advance and must remain constant.
The main factors influencing the shape memory properties are: chemical composition, crystal structures, grains size, thermomechanical treatments, training types among others factors [7,8,9].
Results and discussion The samples were analyzed by DSC to determine the thermal properties and to verify the changes promoted by heat treatments applied.
These curves show the strong influence of heat treatments on the thermoelastic properties in the shape memory phenomena.