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By analysing a large number of soil physical parameters experimental data, the paper gives empirical value to estimate the compaction coefficient and water content base on the quality of the sample or D-value of the quality.
Increase compaction function can effectively overcome the resistance between the soil grain.
To guide field construction and improve the effect of compaction, a large number of on-site backfill soil physical parameters trials are necessary.

The localized plastic flow auto-waves observed for the stages of easy glide and linear work hardening in a number of metals are considered.
The dispersion relation of quadratic form derived for localized plastic flow auto-waves and the dependencies of phase and group rates on wave number are discussed.
It is found that the mechanical characteristics of investigated materials and the shape of plastic flow curves obtained for the test specimens would vary significantly, depending on chemical composition, grain size of polycrystalline materials and extension axis orientation of single crystals.
Then the propagation rate of auto-waves is estimated as (here is the frequency and, the wave number).
Substituting into relation (2) and (here is the dimensionless frequency and is the wave number and for ; for is a signum function of the term a from Eq. 2) yields the following canonic formula .

Two clinical relevant dental ceramics were selected as model materials for studying bottom-surface radial cracking: a dense fine-grain alumina (CoorsTek, Golden, CO), and an yttria-stabilized zirconia (Y-TZP, Norton, East Granby, CT).
The numbers of cycles n required to initiate each crack type were recorded [3].
Fig. 2 shows side views of cone crack evolution in a soda-lime glass monolith specimen as a function of number of cycles n.
The critical loads required to initiate inner cones at any given load diminish steadily with increasing number of cycles.
Number of cycles, n 100 101 102 103 104 105 106 107 108 Critical load, P (N) 101 102 103 104 Y-TZP alumina Figure 4.

Melting enthalpy is no longer a constant but a number decrease with diameter decreasing.
The Curie temperatures of iron in different particle sizes show no difference because Curie temperature is one of the intrinsic magnetic parameters related to chemical composition and crystal structure but not to the grain size.
(3) Melting enthalpy is no longer a constant but a number decrease with diameter decreasing.

Additional studies on other titanium alloys illustrate the effect of α grain size, α-β colony width and lamellae thickness, prior-β grain size the volume fraction and morphology of primary α, transformed β and aged martensite on mechanical properties [37, 95, 99, 100, 107, 109, 110].
The α/β recrystallisation temperature and time helps to adjust the primary α volume fraction and size together with determining the β grain size.
In general PM material consists of a finer grain size compared with those found in material produced by ingot metallurgy.
However, there are only a limited number of studies which illustrate the effect of microstructure on the fracture toughness of PM produced Ti-6Al-4V alloy.
KIC = 44~66 (MPa.m1/2) KIC = 88~110 (MPa.m1/2) KIC = 32 (MPa.m1/2) Fig. 6: Typical fracture toughness for different microstructures [37] Hamai and Sugiura investigated the effect of β –grain size on the mechanical properties of Ti-6Al-4V and according to their study it is clear that an increase in grain size increases fracture toughness [119].

On the other hand, the number of end-of-life Li-ion batteries grows significantly and provides an additional source for these critical materials by recycling.
Due to the limited number of recovered materials and high energy input, the overall recycling efficiency is low.
The electric discharge in the reactor medium causes a shockwave penetrating the sample’s weakest points which are the mechanical bonds between materials and grain boundaries (fig. 1).

However, a vast number of resources involving networks, computing, and storage resulted in ever increasing energy consumption.
The users in networked manufacturing submit service requests to Manufacturing IT Cloud, and then the services will be decomposed into fine-grained tasks.
Manufacturing User 1 Manufacturing User n Manufacturing User 2 Task 1 decomposition Task 2 decomposition Task n decomposition Service request Service request Service request Task Coordinator Resource demand evaluation Virtual resource scheduling VM state VM controller VM pool Physical manufacturing IT resource VM monitor Task queue Manufacturing IT Cloud Fig. 2 Dynamically-scalable resource utilization mechanism for networked manufacturing Summary Although networked manufacturing technology is efficient for integration of distributed manufacturing resources, a number of IT resources for manufacturing resulted in ever increasing energy consumption.

Also increase in grain boundaries, can arrest propagation of defects, when material is stressed, thus giving it strength.
If grain size becomes small, the interface area within material greatly increases, which enhances its strength.
Due to grain boundary scattering, electrical conductivity of nanocrystalline materials is found to be lower, than that in the coarse grain material of same chemical composition, because the larger fraction of atoms lies at grain boundaries.
In solids, N is very large, resulting in a large number of orbitals [40].
Hahn, Phase characterization and stabilization due to grain size effects of nanostructured Y2O3, Nanostruct.

This alteration is linked to an augmentation in the number of electrolytes, an elevated pH level, and a reduction in the thickness of the double layer due to cation exchange [22], [26], [27], [28].
Lime is often considered to be an acceptable, if not the most ideal, stabilizer for fine-grained soils (Silt and Clay) classified as A-4, A-5, A-6, A-7 and certain coarse-grained soils (gravel and sand) A-2-6 and A-2-7 soils according to the “American Association of State Highway and Transportation Officials (AASHTO)" classifications.
Lime is often considered to be an acceptable, if not the most ideal, stabilizer for fine-grained soils (Silt and Clay) classified as A-4, A-5, A-6, A-7 and certain coarse-grained soils (gravel and sand) A-2-6 and A-2-7 soils according to the “American Association of State Highway and Transportation Officials (AASHTO)" classifications.
Immediate bearing ratio (IPI) is also assessed in order to establish the stability of the ground, with minimum values of 20 and 50 set for fine-grained soil and gravelly soil, respectively.
This group normally comprises clay (C) and silt (M) soils, along with some coarse-grained soils that are SC and SM.

Hydraulic pressure is removed from the well, and then small grains of proppant hold these fractures open once the rock achieves equilibrium [3].
Horizontal section length is becoming longer and longer, in order to increase the yield, we should try to increase the number of crack.
For each year there are three information, they are well number, section number and open-flow capacity from left to right.
We can know that the fracturing well number and fracturing section number are becoming more and more, and at the same time open-flow capacity is increasing.
Well number Section number Open-flow capacity (104m3/d) Effective length of reservoir (m) 2010 2011 2012 Fig. 1 Horizontal well fracturing statistics from 2010 to 2012 Table 2 Correlation table on gas testing effect (V1 is well number, V2 is horizontal section length, V3 is sandstone length, V4 is sand ratio drilled, V5 is effective thickness of reservoir, V6 is effective reservoir ratio drilled, V7 is fracturing stage number, V8 is amount of sand, V9 is flowback rate, V10 is open-flow capacity) Fracturing fluid type V1 V2 （m） V3 （m） V4 （%） V5 （m） V6 （%） V7 V8 （m3） V9 (%） V10 （104m3） 0.4%low concentrations 15 964.8 793.3 81.9 574.0 59.3 5.9 42.24 77.80 29.3875 0.35% carboxymethyl 2 654.1 546.2 68.9 385.1 50.8 5.0 32.0 84.30 29.7855 0.4% carboxymethyl 2 1079.6 952.1 88.3 534.6 49.5 4.5 28.5 62.0 5.4167 0.50%-0.55%general guanidine gum 9 999.0 871.1 86.1 555.2 54.6 6.7 30.54 77.00 5.7787 Table 3 Correlation table on production data