Search results

The system can complete the measurement data receiving, data processing, curve output, shape and position error calculation, alarm display, such as a series of functions.
Principles and methods of measurement System to the PC as the core, completes the measurement data reception, data analysis and the results of the display.
On the part of the received data, the use of on MCGS own function, can receive data from the next crew sent data, without the need for data conversion, binary data can be directly converted into decimal data; in the data analysis section ,the system will use the previously established good the mathematical model to write programs, which each corresponds to a form of bit error ; in the display section, with MATLAB software mapping function, the received data is used to plot a three-dimensional graphics, and thus the data Analysis results were compared, and the accuracy of the test results was detected, while MCGS configuration software will analyze the results in order to display data in the form of the curve.
For MATLAB software, it can be directly type "load" command in the command window, which calls in the database, thus, the measurement data for data analysis, draw mathematical model.
OPC communication with real-time, rapidly data transfer rate, and simple method, considering the data communications requirements, system selection integrated OPC Toolbox MATLAB and MCGS configuration software to achieve real-time data exchange between the completion data exchange, enabling MCGS configuration software and MATLAB software combination.

The elastic and plastic strain data of tubular specimens undergoing rupture under internal pressure tests are presented and analyzed.
The reduction factor in the hoop direction (fR)h is given by equation (5).
The data point falling in the right extreme of the plot is related to specimen CDTS 3 and it clearly predicts that fracture will occur along the longitudinal direction, i.e., it is determined by the longitudinal stress.
Figure1: Normalized plot of fracture data points for the pair of DNV-Kastner equations.
An investigation is underway to acquire own and selected published data to look for any extraneous behavior of specimens that present very thin remaining ligaments (less than 2.5mm in large diameter pipes) and that belong to corrosion regions with lengths greater than 50mm.

All cyclic voltammograms datas were acquired using a computer-based potentiostate/galvanostate (model 283) (EG&GP Princeton Applied Research, Princeton, NJ, USA).
All results indicate that three hybrids are typical sandwich organic-inorganic perovskite hybrids, which are coincided with that of XRD data.
It is well known that the oxidation and reduction of Fe(CN)63 is the most active in all bare electrodes.
From Fig. 4, we can see the oxidation and reduction potential is 413.0 and -164.9 mV and △Ep is 577.9 mV.
These results demonstrate that the oxidation and reduction of the sensing device 1, 2, 3 are neither from Fe(CN)63- nor from AP.

Data aggregation algorithm removes the redundancy of data each node collects, reduces data transmission quantity and transmits the aggregation results to base station to save energy [4], but it is at the cost of increasing data transmission delay.
Therefore, the cluster head node needs to data aggregation to reduce the amount of network data transmission.
Benefits of establishing data aggregation tree is relatively stable data transmission path, but it requires full integration of data from all child nodes in each parent node.
Data loss exists in the actual network data transmission, retransmission caused by packet loss data, And the more fully aggregated data retransmission, the larger the extra energy.
Though data packet loss rate among nodes is being large with the increase of cluster radius, increases the extra retransmission time, the reduction of Af makes up for its defect, then the total transmission delay is reduced, and ADAUC algorithm saves more than 18% transmission delay than UCFA algorithm, it is better for real-time monitoring.

Historically, four methods have been employed to produce these propagation and loading data. 1) Closed form mathematical analysis of shock wave propagation/interaction. 2) Experimental test data. 3) Numerical analysis of the relevant differential equations governing shock propagation and target interaction. 4) Empirical or quasi-empirical prediction methods.
Thus, data from a large number of disparate experimental trials can be combined into simple load prediction relations.
Figure 6 shows an example of the very good correlation between the cleared pressure prediction derived this way and the experimental data from Figure 4.
Data from Figure 4 with Hudson clearing prediction added Figure 7.
Cumulative specific impulse vs time data from Figure 6 Figure 8.

Analysis of variance abuout the sadiment size in Jiuyuangou and Tuwei River Watershed’s silt dam Li li1,2, a,Weiying Sun2, b,QI He2, c,Xinxin Hou2,d (1 Xi,an University of technology, Xian, 710048, China；2Yellow River Institute of Hydraulic Research , Zhengzhou, 450003, China) aemail:hnlily168@163.com, bemail: 16691232@qq.com, cemail: 287364315@qq.com, demail: xinxin_hou@qq.com Keywords: Silt dam; Jiuyuan gou Watershed; Tuwei River Watershed; Coarse sediment; granularmetric analysis Abstract: Analysising twenty-one silt dams in Jiuyuangou watershed and thirty-six silt dams in Tuwei River Watershed drilling hole sampling’s data, Jiuyuan gou Watershed’s silt dams in coarse sand size mainly concentrated in the 0.05mm,Tuwei River Watershed’s silt dams in coarse sand size mainly concentrated in the 0.05mm～0.10mm,The dam upstream sand size is generally larger than the dam downstream, sorting depends on sediment dam on the dam upstream tosand size, dam upstream sediment grain size is
coarse separation effect is better, warping dam and reduction effect is more obvious.
Analysising 15 silt dams in Jiuyuangou watershed and 31 silt dams in Tuwei River Watershed drilling hole sampling’s data.
Two data sets showing,the Watershed’s loess is a main coarse sediment source in Wuding River Watershed,the Watershed’s sandwind is a main coarse sediment source in Tuwei River Watershed.The coarse sadiment size of Jiuyuangou Watershed concentrats mainly in 0.05mm,the coarse sadiment size of Tuwei River Watershed concentrats mainly in 0.05mm～0.10mm.

Lab Correlation module not only supports the correlation analysis between the simulation model and the test data, modify the simulation model, but also provides guidance and help for the test structure, can be very convenient for comparative analysis of simulation results and experimental results.
Lab uses DOF reduction to produce the Test Analysis Modal (TAM), which reduces the freedom degrees of the finite element model to the test model.
Fig. 4 The finite element modal results reduction Fig.5 Mac matrix graph Table 1 Boring bar modal correlation MAC matrix Order Test mode Finite element mode MAC Difference 1 138.0 140.8 0.912 2.75 2 1117.5 1169.5 0.827 52.00 3 2375.3 2330.7 0.714 44.60 The other four kinds of rubbers is respectively analyzed according to the above steps.
Table 2 Rubber parameters used in the simulation Material Modulus of elasticity[MPa] Poisson's ratio Damping coefficient[Ns/m] Stiffness [N/mm] ordinary rubber 2.65 0.48 1.2 1.25e5 EPDM rubber 7.84 0.48 1.1 1.35e5 Nitrile butadiene rubber 5.15 0.48 1.4 1.31e5 Fluorine rubber 8.5 0.48 1.1 1.38e5 Silica gel 2.14 0.48 1.3 1.2e5 Conclusions Vibration is an undesirable phenomenon in machining processes because it results in the reduction of material removal rate, poor surface finish and increase of tool wear.
Modal test data adjustment for interface compliance [C].

In addition, data on the removal of these compounds from water under alkaline conditions using the ozonation process in the plasma field were obtained in the form of the final concentration with varying exposure times, including 0, 15, 30, 45, 60, 75, 90, 105, and 120 min.
This triggers a reduction in pH as the process commences.
Furthermore, from the research conducted, data was obtained as in Figure 2 where the exposure time proved to be very influential in the p-chlorophenol concentration decrease.
This was due to the reduction in phenol decomposition products during the oxidation process.
Meanwhile, the COD reduction for the respective samples was 42.19%, 38.51%, and 48.34%.

Through the analysis of existing data, the shock absorber parameters optimization direction is determined.
Test load: light weight is 465 kg; Full weight to 705 Kg; Number of shock absorber: 29 / group; Test of vibration load (0.4 + / - 0.1) g; Incentives: on line test data as input test floor output response of the shock absorber and vibration reduction efficiency; With white noise excitation test floor shock absorber output response and damping efficiency. 2 The experiment results analysis Experiment is divided into light and loaded with two cases, this paper experiment was conducted under the condition of full load, and the experimental analysis results are as follows.
Line spectrum incentive The line spectrum of shock absorber incentive, you will be the original stiffness damper in accordance with the real vehicle installation structure and floor, seat, and test equipment, when they are assembled and under the condition of full load to test each measuring point vibration output response and vibration reduction efficiency.
With the stiffness increases, dynamic response to high frequency movement, with the increase of the damping peak, dynamic response of peak reduction, and the corresponding bandwidth increases.

Therefore, the development of steels and alloys, new brands of should undertake a systematic study to accumulate reliable data to establish the optimal concentration of technological additives.
Calculating the size of nonmetallic inclusions showed that for samples without modifying the data sizes of inclusions are in the range from 18 microns to 145 microns, and the sample after introducing a type modifier "MS" inclusion size in the range from 5 microns to 15 microns, i.e. observed a significant reduction in the size of non-metallic inclusions, which leads to a reduction in the range of sizes of inclusions and improves the density of the steel structure.
Mechanical properties of steel cores Sample Ultimate strength, kg/mm2 Yield strength, kg/mm2 Relative elongation, % Relative reduction, % Impact strength, kg-m/cm2 GOST 7370-98 80–90 36 25–30 22–27 20–25 Unmodified core 86.7 48 30.7 24.4 25 Modified core 89.5 48 38.0 29.6 25.2 Conclusion As a result, the modification does not change the basic chemical composition of the steel, but reduces the number and size of nonmetallic inclusions in the grain boundaries and also a decrease in grain size.