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It is helpful to energy saving, environmental protection, reduction of construction cost, and would become an important platform for planning and construction of green village buildings.
BIM technology is a data model based on 3D digital technology, that integrates kinds of information related to the buildings.
BIM can provide reliable reference simulated data by using its analysis software with analysis of meteorological parameters and solar radiation analysis to help determine the solar panels area, installation location, etc.

In this paper, we put the emphasis on the synthesis and properties characterization of this new type material, and try to provide a new method to fabricate a viscoelastic damping material(VDM）with tunable Tg and excellent dynamic mechanical properties usable for applications in the field of vibration reduction industry.
Data were recorded in the temperature range −100 to +100 °C at a heating rate of 10 °C per minute.
The Tg of the SSBR can be tuned according to the particular application requirements from about -60°C to 10°C according to the data of DMA.

In the high frequency of 4.8Hz, the reduction ranges of the friction coefficient is not obvious with the contact pressure increased, but the effect of contact pressure on the wear of the spherical plain bearing is great.
By using a friction torque sensor with 0.1 Nm measuring precision, the parts of friction torque can be directly measured and recorded by the data acquisition software.
After the test, these specific data were analyzed, based on the curves of the friction coefficient and linear wear changes with load and frequency increased, the rule of macroscopical variation was found. (2)By using SEM and EDS analyzer, the friction surface micro-analysis was gained.

Collection S include s data sample, assuming Class label attribute has a different value m, making a kind of different definition.Set the number sample of , to classify a given sample, the information of the required expectation for: Whereis the probability of any sample belong to, with estimates of.
Then some scholars put forward some improved algorithm, such as C4.5 algorithm, CART algorithm, SLIQ algorithm, SPRINT algorithm, etc. 2 Multivariate Decision Tree Algorithm Based on Rough Sets 2.1 Multivariate Decision Tree Construction Algorithm Based on Rough Sets In the selection of conditional attributes set, firstly, to deal with the data previously, delete the data with noise, to the default value for neat, and a discrete a series of data value, its construct algorithm as follows.
Table 1 Decision table U A B C D E F G d U A B C D E F G d 1 1 2 2 1 1 2 1 1 9 1 2 2 2 1 2 1 1 2 1 2 3 2 2 2 1 1 10 1 1 3 2 1 2 1 1 3 1 2 2 3 1 2 1 1 11 2 1 2 2 1 2 1 2 4 2 2 2 1 1 2 1 1 12 1 1 2 3 1 2 1 1 5 2 3 2 2 1 1 1 2 13 1 2 3 2 1 2 2 1 6 1 3 2 1 1 2 1 1 14 2 3 2 2 1 2 2 2 7 1 2 3 1 1 2 1 2 15 1 2 3 2 3 2 2 2 8 2 3 1 2 1 2 1 1 16 2 3 2 2 1 3 2 1 We can get condition attribute set R = {A, C, D, E, F} after attribute reduction, and K (D, D) = 2/16, K (C, D) = K (E, D) = K (F, D) = 1/16 through calculation, so SIG = {{D}, {C,E,F}}, therefore =D，={C,E,F}.

When determining the grid number the analysis data type should be considered.
When calculating the positions with large gradient data changing or stress concentration we need utilize intensive grid.
While calculating the positions with small gradient data changing we should divide relatively sparse grids.
By comparison, the experimental data and calculated values are close, the average relative error 11.1% is within the allowable range, indicating the case finite element model and its results are correct.
Table 2 Effect of Rib Size on the Stress Model type Rib thickness (mm) Rib height (mm) The maximum von mises stress (MPa) The reduction of the maximum displacement Original model 6 30 587 - Option II A 6 32 325 81.2% Option II B 6 34 308 83.6% Option II C 8 30 291 84.7% Option II D 8 32 278 86.7% Option II E 8 34 262 91.7% Option II F 10 30 275 86.9% Changes in Size of Reinforcement Plates.

Therefore, research on highway hydrology Zoning can provides scientific basis for disaster prevention and reduction of highway.
In order to improve the accuracy of the division and provide basic data and theoretical basis for national highway hydrology Zoning, this paper established the index system of highway hydrology Zoning and proposed a framework of provincial highway research framework of hydrological Zoning based on the relationship of hydrological elements and highway engineering research.
Provincial Highway Hydrological Zoning Research Framework Provincial Highway hydrological Zoning research in general is divided into basic data collection, index analysis and zoning map compilation in three steps.
First, the data of geographical elements related to hydrological environment in the research area should be collected.
Then, the index system of highway hydrological Zoning should be established and the Zoning index should be analyzed based on basic data.

Crystal Data [Mn2 (C8H7O3)4(H2O)2] Dx = 1.489 Mg m3 Mr = 375.23 Mo Kα radiation triclinic, P -1 Cell parameters from 8291 reflections a = 8.038(5) Å θ= 2.99 -27.43° b = 9.695(5) Å μ= 0.822 mm-1 c = 11.149(5) Å T = 293(2) K α= 86.158(5)° chunk, yellow β= 81.239(5)° 0.20 * 0.18 * 0.16 mm γ= 77.298(5)° V = 837.2(8) Å3 Z = 2 Data collection Rigaku R-AXIS RAPID 3795 independent reflections diffractometer 2816 reflections with I > 2σ(I) ω scans Rint = 0.0207 Absorption correction: multi-scan θmax = 27.43° (ABSCOR; Higashi, 1995) [11] h = -9→10 Tmin = 0.832, Tmax = 0.877 k = -12→12 6519measured reflections l = -14→14 Refinement Refinement on F2 H-atom parameters constrained R[
Hydrogen-bond geometry (Å , °) D—H…A D—H H…A D…A D—H…A O4—H4A…O13ii 0.73(4) 2.01(4) 2.733(5) 170(3) O4—H4B…O2iii 0.93(5) 1.69(5) 2.621(4) 177(6) [Symmetry codes: (ii) 2-x, 1-y, 1-z; (iii) 1-x, 1-y, 1-z] Data collection: PROCESS-AUTO [8]; cell refinement: PROCESS-AUTO; data reduction: CrystalStructure [9]; program(s) used to solve structure: SIR92 [1]; program(s) used to refine structure: SHELXL97 [2]; molecular graphics: ORTEP-3 for Windows [5]; software used to prepare material for publication: WinGX [6].

The study of possible mechanisms active during sintering was attempted by continuously recording the shrinkage vs. time and elaborating the data on the basis of Kingery' s model for liquid phase sintering.
Finally, magnetic ac susceptibility measurements were performed on the sintered samples (Quantum Design, Lakeshore), collecting data with a driving field amplitude varying from Hac≈10 A/m to Hac≈1200 A/m, oscillating at a frequency of 1000 Hz, on warming from 15 K after zero-field cooling of the samples.
The value of 1/6 is very near to the theoretical one (1/5) for a mechanism of diffusion of prismatic particles into the intergranular liquid phase as the rate-governing step; on the other hand 1/n=1/8 can be justified on the basis of a progressive reduction of the viscosity of the intergranular fluid with the increase of temperature.
To best characterize the samples as a function of treatment temperature (i.e. the actual density), we evaluated the critical current density (Jc) using the susceptibility data in the framework of the Bean model [5, 6]; the data seem to claim the existence of two different types of samples (Fig.4) and those with d > 90 % seem to produce the better results in term of critical current.

At last the simulation results were compared with experimental data.
The control equations for turbulence model as follows: (1) Where is kinematic viscosity of turbulent,is adding item of turbulent viscosity,is reduction item of turbulent viscosity.is source term of user defined.is the kinetic viscosity of a fluid , is 0.622.
The distribution of velocity field and pressure of the center point obtained.The Table 1 and Table 2 is experimental data.
Table 1 Experimental data of 5D spacing measurement point parameters 3D 4D 5D 6D 7D 8D pressure（pa） 17.0 18.5 18.0 19 20.0 20.5 velocity（m/s） 5.4 5.63 5.60 5.7 5.8 5.85 Table2 Experimental data of 8D spacing measurement point parameters 3D 4D 5D 6D 7D 8D pressure（pa） 8.5 11 13.5 13.8 14.5 15.0 velocity（m/s） 3.85 4.6 4.85 4.87 4.9 4.95 Comparison of Measurement Results and Experimental Results Fig. 3.

Analysis data a)Actual partsb) Modeling in the CAD software Fig.1.
The table-1 shows the flow stress data of AISI-1020, along with different strain rates and strains at the temperature of 1,000℃,Fig.2 shows the cure of theflow stress of AISI-1020 at 1,000℃.
The data for this material for 20℃to 2,500℃ are presented[1].
Flow stress data of AISI-1020, along with different strain rates and strains at 1,000℃ Flow stress Strain rate strain 2 20 200 2000 20000 0 152.11311 186.11111 286.212 394.68989 857.82644 0.001 160.419 200 303.287 415.006 869.272 0.1 235.172 325 456.962 597.851 972.282 0.5 307.259 525 608.57 771.626 1051.45 1 344.759 613.625 688.506 861.255 1087.5 5 450.438 682.192 916.944 1111.59 1176.04 Eq. 1 is the flow stress calculation formula.
Reduction in postforging errors for aerofoil forging using finite element simulation and optimization.Modell Simul Mater SciEng 2006), p.79–93