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Possibilities of a volumetric flow rate modification [1] and the medium temperature change, allow to determine sensors curves and basic dynamic properties.
The tasks of mechanical subassemblies can be described in several points: fixation of temperature sensors and the heater, heat losses minimization (with the aid of seals), providing direct (without disturbances) interaction stream of the medium at a sensor probe, minimization of an influence of environmental factors on the sensor indications.
Results correctness depends on factors such as: a sampling characteristic, an exactitude of used dividend, an instrument error.
Analysis of the graph shows temperature values recorded by sensors, regarding to the established input function, constitute a base used to determined characteristic sensor properties.
To assigned properties belongs: a repeatability, a hysteresis, dynamic characteristics etc.

The electrical resistances and compressive strains of these cured nanocomposites under cyclic uploading/unloading were real-time collected, to explore their stress/strain-sensitive properties.
Luo et al. [4, 5], Li et al.[6, 7], and Yu et al.[8] have successively reported its good stress-sensitive function, besides its enhanced mechanical and vibration-damping properties.
Its main physical properties are listed in Table 1.
The auto data acquisition system setup for the piezoresistivity property of the cured nanocomposite was a similar schematic to our previous work [5].
As known, the main factors affecting the conductivity of composites are the contact resistance and the number of conductive netlike pathways [7].

Based on applying efficiency function in finding the property of each flatness actuator, a new method is developed to describe a mill's comprehensive ability of flatness control.
And we found the factors which contribute to whether a mill can weaken a certain flatness error.
It indicates that |σ| is affected by another two factors: severity of the initial error (|σini|), and similarity between σini and Eff.
Based on using efficiency function in finding the property of each actuator, a mill's comprehensive ability depends on the set of the difference between one actuator and others.
Furthermore, whether a flatness error can be eliminated is determined by three factors: the severity of the error, the strength of the mill's ability, and the similarity between them.

Considered the weight differences in attribute sets, plus the weighting factor, we get the weighted Euclidean distance: ∑ ∑ = = − = n i i n i i b b i a a i ba n ixix xxd 1 2 1 22 ))](())(([ ),( λ λ µ µ (2) )(xµ is the membership function indicated the state of object properties.
So the attributes reflected cost should choose factors which are interrelated with manufacturing process and strongly affect cost as possible.
The above parameters can be used as association factor of estimation.
In such condition the level ratio factor must be taken into consideration to ensure the reliability of estimation results.
It provides a reliable foundation for estimating the affect that estimation samples exert on estimation results.

Prediction of Temperature Distribution in High-Speed End Mill assisted by Heat Pipe Cooling JU Huaweia, TANG Weixiaob, SONG Qinghuac and ZHOU Hongliangd Key Laboratory of High Efficiency and Clean Mechanical Manufacture, School of Mechanical Engineering, Shandong University, Ji’nan 250061 P.R.
The cutting temperature is a key factor which directly affects thermal distortion, the machined part’s dimensional accuracy, as well as the tool wear in machining process.
For simplicity, the heat generated in the tool blade is modeled as a cylindrical band heat source surrounding the cylinder, and the inner heat source is neglected, this approach has been proved by former research [4]. heat convection on the pipe and mill surfaces exposed to the environment is considered as boundary condition Fig. 1 Idealized heat conduction model of an end mill with a heat pipe All the thermal properties of the heat pipe and the milling tool are treated as constant.
The thermal property of the heat pipe is obtained from experiments by Chiou et al. [3].
Component dimensions and material properties are shown in Table1, and all parameters are independent of temperature and time.

Blending of PHBV with PLLA can modify both mechanical properties and degradation rates of the polymer blends [3].
It was demonstrated that compared with PHB, the polymer blends exhibited improvements in mechanical properties.
The pore structure and morphology, crystallinity, and compressive mechanical properties of scaffolds were subsequently investigated in terms of in vitro degradation study.
Compressive mechanical properties of scaffolds were determined using an Instron mechanical tester at a crosshead speed of 0.5 mm/min.
Nicolais, Poly(3-hydroxybutyrate)-co-(3-hydroxyvalerate)/poly-L-Lactide blends: thermal and mechanical properties, J.

Their excellent specific mechanical properties make them ideal as reinforcement in many different kinds of material.
Magnesium-based MMCs have shown high specific mechanical properties [14], low density, improved thermal and dimensional stability and better damping properties.
Goh et al. have studied the mechanical, physical and thermal properties of Magnesium-CNT nanocomposites.
The fact that MWCNT clusters are strong and difficult to break, using mechanical means, may also affect homogeneity of the powder mixture and the reproducibility of material properties.
Tan, in Aluminium Alloys; Their physical and Mechanical Properties edited by J.

Based on the analysis of the main factors of work roll’s thermal behavior, the mathematical models are studied for predicting the work roll’s temperature distribution.
Meanwhile, the work roll’s temperature is affected by the deformation work and friction heat.
The resistance of deformation affects the friction heat and deformation work.
The value c1 depends on various factors including the roll velocity, interface conductance and temperature.
The heat flux generated due to the friction between the roll and the strip depends upon the normal pressure, the roughness of the surfaces in contact, and the properties of material.

Previous studies determined the ranges of two angles mainly depending on the effect of broken rock rather than its mechanical strength to examine the issue.
Based on the strength factors, the paper uses finite element program ANSYS to optimize the fore-angle and the lateral-rotation angle of PDC cutters.
The theoretical research, especially the optimization of two geometry parameters on strength affect literature, is rarely reported.
Optimization analysis After defining element type, material properties, meshing element, applying load, and performing the finite element calculation, ANSYS assigned the result to the corresponding parameters.
Mechanical structure optimization design [M].

An actual problem is the synthesis of ceramic composite materials based on refractory compounds to produce nanostructured materials with high mechanical strength, namely, flexural strength, fracture toughness, hardness, heat resistance and thermal strength.
Particles of the powder (P1) substantially monodisperse associated in loose aggregates with a low bond strength between the particles and the particles have topology a with not spheroidized character (Fig. 1a), which may indicate the anisotropy properties of the resulting material.
Also, a significant decrease in density of these samples may affect a small particle size starting powder - 19nm, compared with the granular powder particle size P2 at which the starting powder size is 90nm.
These factors lead to low efficiency of pressing ultrafine powders.
Conclusions  - A set of experimental observations suggest that the behavior of the polycrystalline body is determined by sintering not only the properties of individual particles as aggregates properties and strength of bonds between particles of the powder has a significant effect on the sintering process and the final properties of the ceramic;  - Implemented by electroconsolidation getting bulk samples submicron ceramic compositions ZrO2 - n wt.% Al2O3 (n = 10, 20, 30) with a density of up to 99% of the theoretical and the scale of the microstructure of the order of 270nm.