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Axial Load (MN) Ratio of Compressive Strength Longitudinal Reinforcement Horizontal Reinforcement Configuration Reinforcement Ratio Diameter (mm) Spacing (mm) Volumetric Ratio S1 0.28 0.1 40 8 0.014 6 40 0.035 S2 0.56 0.2 40 8 0.014 6 40 0.035 2.2 Loading Devices and Loading Schemes The Loading system is composed of vertical loading device, horizontal loading device, data acquisition system and control system.
British IMP data acquisition equipment was used in the data acquisition system acquisition.
The speed of data acquisition is 1 / 2S.
Initial displacement change in the unloading stage lagged far behind the reduction of load after the maximum horizontal load was reached, which shows obvious pinching phenomenon.

An elliptical crack in the middle of the plate Elliptical crack progress features and part materials Assuming the crack progress rate data is increasing regularly according to ∆k, the software works and it is activated by a high physical sensitivity.
Although crack progress data is increasing regularly, stress curve against crack life is decreasing regularly.
dadN=C∆Kn(1-RKc-∆K) (1) Where: c: (length stressdadN×(Kc-1) when time R=0 and ∆K=0 n: (dimensionless) in Paris equation when time ∆K=0 The only exception in standard state when R (stress ratio) is negative is the use of Forman equation which has great flexibility in controlling the indicated information of crack progress ratio. [3] The model is assumed as Aluminum sheets with different heat treatment by following mechanical properties in Table1 and see crack growth rate data for Aluminum Alloy in Figure 2.
Crack Growth of Crack data of Aluminum Alloy Calculation of intensity Stress Factor This problem, which is a classic one in the elastic theory, surely is not a simple problem.
Harter, AFGROW USERS GUIDE AND TECHNICAL MANUAL, Air Force Research Laboratory [4] Socie, D., 1980, Fatigue life for bluntly notched members, Journal of Engineering Materials and Technology, Transactions of ASME, Vol. 102 [5] Leis, B.N. and Topper, T.H., 1977, Long-life notch strength reduction due to local biaxial state of stress, Journal of Engineering Materials and Technology, Transactions of ASME, Vol. 99 [6] Crews, J.H,.

However, inverse techniques are computationally intensive and operate on huge amounts of data.
Knowing that attenuation of A0 mode in such composite material is very strong (about 85% reduction of amplitude is observed over a distance of 0.4 m for the excitation frequency 120 kHz) let us use 20 piezoelectric transducers.
Normalisation helps to generalise amplitude levels for different types of data.
This procedure gives averaging data samples or rather moving averaging data because of using windowed signal.

Figure 1 Microwave-based heating device and measuring equipment Figure 2 Taguchi method flow After the optimal heating conditions were determined, the experiment was performed, and input power and output (temperature) data were recorded.
The orthogonal arrays planning and the experimental data of L9(33) experiment are as listed in Table 2.
The influence of the factors on the system can be calculated using the data in Table 2 to create the response table.
Pretreatment of biomass material in steam explosion: (1) The data are recorded after experimentation.
Conclusions Due to the energy crisis and the policy of energy savings and carbon reduction, microwave-based heating is the future trend.

The present study was aimed at preparing biphasic CF/FHAp solid solution through a continuous precipitation method especially for dental applications, which could be used not only as an osteoconductive material due to the nature of FHAp but also, as a labile F- reservoir for developing potentially more effective F- regimens and as an agent for use in the reduction of dentin permeability and dental caries prevention.
Crystallographic identification of the phases of synthesized powder was accomplished by comparing the experimental XRD patterns to standards compiled by the International Center for Diffraction Data (ICDD), which was card #09-0432 for HA, #15-0876 for FA and # 77-2096 for CaF2.
The average size of the individual crystallites was calculated from XRD data using the Scherrer approximation (Eq. 1): (1) where t is the crystallite size, λ is the wavelength of Cu-Kα radiation (1.540560 Å) and β1/2 is full width at half maximum intensity.
Since, Ca and F exist either in FHAp and CF, mathematical equations were drawn based on the data shown in table 2, to evaluate the percentage of each compound in the final precipitate.
Dowker, Apatite Structure, JCPDS-International Centre for Diffraction Data, Advances in X-ray Analysis.45 (2002) 172-181

Table 2 Factors and levels in the test Factor Level A B C Heating temperature T (℃) Pushing speed v (mm/s) Friction coefficient f 1 650 3 0.14 2 700 3.5 0.16 3 750 4 0.18 4 800 4.5 0.20 Simulation design scheme and data analysis Simulation design scheme and data are shown in table 3.
Table 3 Simulation design scheme and data Number Simulation scheme Simulation result Results analysis Means Variance 1 A1B1C1 6.1592 0.0873 Wall thickness means analysis (R=Kmax-Kmin) 2 A1B2C2 6.3388 0.0390 K1 K2 K3 K4 R 3 A1B3C3 6.3664 0.0099 A 6.321 6.276 6.244 6.522 0.278 4 A1B4C4 6.4196 0.0245 5 A2B1C2 6.1742 0.0769 B 6.240 6.299 6.378 6.444 0.204 6 A2B2C1 6.0780 0.0904 7 A2B3C4 6.3678 0.0409 C 6.257 6.343 6.380 6.382 0.125 8 A2B4C3 6.4846 0.0756 9 A3B1C3 6.1468 0.2064 Wall thickness variance analysis（R=Kmax－Kmin） 10 A3B2C4 6.2590 0.1485 K1 K2 K3 K4 R 11 A3B3C1 6.2432 0.0656 A 0.0402 0.0709 0.1194 0.0564 0.0792 12 A3B4C2 6.3257 0.0572 13 A4B1C4 6.4810 0.0623 B 0.1082 0.0855 0.0364 0.0569 0.0718 14 A4B2C3 6.5238 0.0639 15 A4B3C2 6.5364 0.0290 C 0.0784 0.0505 0.0889 0.0691 0.0384 16 A4B4C1 6.5468 0.0705 The wall thickness mean value of No. 6 scheme in table 3 (A2B2C1) is 6.078 mm which is the nearest to the initial wall thickness 6 mm.
In this paper, the simulation results and measured data both refer to the second elbow pipe, as shown in figure 5.
As can be seen from figure 6, the wall thickness of the elbow pipe on the convex side is decreasing slightly, but distributed evenly and the thickness value is around 5.8 mm (the wall thickness reduction ratio is about 3.3%).

With technical progress and cost reduction, the lightweight wall greening technology represents the new development trend of wall greening.
This technology is convenient to change parameters or variables and even the model structure, input the command at any time through the keyboard or voice and output data, charts, renderings (Figure.3.) or even animations in the simulation process.
Under the limit of known conditions, we can scientifically compound matching data through variable selection, highlight the characteristics of local configuration, and predict the visual effect of the construction.
In addition, BIM also need to build the actual database to timely import and integrate the cost data in cost accounting, so that visibly collect or split the cost.
While BIM platform can establish the five dimensional relationship of time, space, process to the cost data.

Specifications for Design According to the filtering requirement of project, the specifications are defined as follows: a lowpass filter whose cutoff frequency is 1MHz, and whose scale is 33taps(coefficients).The input signal comes from a 10-bits A/D convertor at the sampling rate of 100MHz, and 16-bits complement data are expected at the output.
The sign bit of product can be obtained by XOR (eXclusive OR) between the most significant bit of two input data, while the value part of product is the product of two positive number.
As a result of reduction on logic occupation, complement is conducive to high-speed FIR filter design.
Let’s assume the input signal is multi-frequency sampling data whose frequency components mainly include 500 KHz and 3 MHz The filtering appearance, as shown in Fig. 5, is enough to meet the design requirements.
By importing the output data of two FIR filters into MATLAB, the analysis indicates the average precision of the optimized filter design have already increased by 2.5%, compared to the traditional fixed point implementation.

Table 1 presents the statistic data of the tire, whereas in Table 2 the other suspension system parts statistic data are presented.
Statistic data of discrete tire model Part No. of elements (HEX8) No. of nodes Material model Tread 3840 6360 Rubber Inner fabric 3600 7680 Rubber Carcass 1680 3600 Rubber Sidewall 4800 8160 Rubber Bead core 2400 3840 Rubber Part No. of beam elements Nodes Material Model Circumferential cords 4560 4561 Steel Radial cords 8639 8881 Steel Table. 2.
Statistic data of discrete suspension system model Part No. of elements (HEX8) No. of nodes Material model Tire 16320 25520 Rubber/Steel Rim 7192 12164 Steel Drum brake 4680 7440 Cast iron Axle 4278 5236 Steel Hub 2268 3132 Steel Axle bush 4585 6207 Steel Spring 4368 7077 Steel Longitudinal 7302 9052 Steel Fig. 3.
Moreover, the most positive aspect of the method is significant reduction of computational time.

Analysis of the scientific and technical literature [7-19] showed the lack of data on the rheological characteristics of the PdNi-5 alloy in it.
To determine them, special experimental studies performed [8, 9], as a result of which data obtained on the tensile strength and elongation, the values of which imported into the DEFORM-3D software package.
A graph of the variation of the drawing ratio λsing by passes for the current and proposed drawing modes Simulation of the drawing process made it possible, for given deformation parameters (single εsing and total ε∑ reduction), to calculate the ultimate tensile strength Rm in the deformation zone, as well as to obtain data on the drawing force Pdraw and the fracture criterion for CC-L passes (Table 2).
Calculation data for the process of drawing the wire from alloy PdNi-5 Number of pass Diameter, mm λsing εsing, % ε∑, % Rm, MPa Pdraw, N CC-L 3.82 1 3.46 1.22 18.0 18.0 242 845.0 0.17 2 3.13 1.22 18.2 32.9 295 726.6 0.23 3 2.82 1.23 18.8 45.5 336 823.2 0.32 4 2.53 1.24 19.5 56.1 647 625.1 0.33 5 2.26 1.25 20.2 65.0 578 505.0 0.41 6 2.02 1.25 20.1 72.0 538 628.7 0.23 7 1.81 1.25 19.7 77.6 597 545.1 0.29 8 1.62 1.25 19.9 82.0 626 530.5 0.35 9 1.45 1.25 19.9 85.6 649 477.0 0.42 10 1.31 1.23 18.4 88.2 648 312.3 0.48 11 1.184 1.22 18.3 90.4 652 247.3 0.53 The distribution of drawing stresses in the deformation zone for the proposed modes is shown in Fig. 3.