Search results

Fretting causes a considerable reduction in fatigue strength.
In recent years, many studies have used multiaxial fatigue criterion to establish correlations with fretting fatigue experimental data. 
This leads to a reduction in fatigue strength.

Conventional wisdom suggests that the reduction of ductility is due to the effect of particles as nucleating sites for damage.
We present experimental data which supports this conclusion.
Conventional wisdom suggests that the reduction of ductility is due to the effect of particles as nucleating sites for damage.
Particle field of CC0.08 alloy observed under optical microscopy The forming limits of both CC and DC materials were constructed using data from three different tests: uniaxial tensile test, wide-plate plane strain tensile test and hydraulic bulge test.

Theoretical models are usually derived from a shear zone model of chip formation, assuming a steady-state cutting data.
The various forms of regression analysis concentrate on using existing data to predict future results.
Methodology Table 1 shows the experimental data obtained using carbide inserts.
Table 1 Experimental data for each cutting inputs.
From the value of R2 (89.88%), the fits of data can be measured from the estimated model.

Experimental softening (black symbols) and recrystallization (grey symbols) data.
The mobility data can be well fitted to an expression: [m4/Js].
The model predictions are compared with the softening and recrystallization data in Fig. 3.
Comparison of softening (black) and recrystallization (grey) data with the model predictions.
Fig. 4. a) Precipitate size predictions and experimental data and b) Precipitate number density and volume fraction (normalized by the equilibrium fraction) predicted by the model.

In the analysis the characteristic dimension has been set at mmb 05.20 for ballistic data.
For machined data two curves have been plotted.
Firstly mmb 3.20 satisfies the machined hole data of diameter 8mm and secondly mm bo 48.2 satisfies the machined hole data of 12.7mm diameter.
These results imply a difference in perforation diameter between the ballistic and machined hole data suggesting that the 7.62mm and 12.7mm ballistic perforations contain delaminations.
This testing data has allowed the formulation of a failure method to be proposed for such composites.

A future trend seems to be a reduction of the product dimensions while keeping their product capabilities.
To get the maximal information of the measured data, 3D graphs in Matlab software were created.
The data is displayed scatter plots see Fig. 11 and 12.
According to the obtained data (groove depth, mean arithmetical deviation and maximal profile height) an optimum configuration of power and feed setting resulting in achieving of the desired values for surfaces machined with laser feed at 500 DPI and 1000 DPI.
An overview of statistical methods for data processing, Portal, Praha 2008, ISBN 80-7178-820-1

The data of queue length and the speed on the outlet is input into the optimal controller through sensor module.The optimal controller can realize optimal calculation based on the data detected and turn the preset scheme on.
(1) In the formula:L1: the distance from the saturation point to the stop line, S1：the saturation flow of the road,1：reduction factor of the upstream traffic going straight ahead affected by the steering vehicles,Lc：vehicle length,m1：number of the lanes,ge：effective green time of the intersection.
The demonstration project is evaluated by the methods of video recording and manual counting statistics.The evaluation parameters are the traffic flow, the traffic time, the average speed of vehicles, the queue length and the stop delay of the intersection.The assessment results are shown in the following: Through the investigation and data assessment,this paper compares the traffic flow before and after optimization.As is shown in Table 2, Table 3 and Table 4.
[3]GAO Linlin.Traffic State Estimation Using GPS/SCATS Data[D].Shanghai jiaotong University,2008
Project Report MIOH UTC TS4 2008-Final,Michigan Ohio University Transportation Center, December,2008 [5]JIANG Guiyan,LI Yi,DONG Shuo.Travel Time Estimation Method Using SCATS Traffic Data Based on k—NN Algorithm[J].Journal of Southwest University,2013,48(2):343-349.DOI:10.3969/ j.issn.0258-2724.2013.02.024.

The experimental data of flow noise are few so does the simulation on flow noise.
The accuracy of this method was verified by comparison with experimental data.
The model has a complete hydrodynamic experimental data which obtained from the experiment that conducted at the China Ship Scientific Research Center.
It is seen from the Table 3 that the computation results agreed well with the experimental data.
[7] LiuHall-Lieh, Thamas T Huanh, Summary of DARPA SUBOFF experimental program data[R].

This increases the possibilities in terms of large reductions and change in shape with less complex tooling and also reduces the required load capacity and cost of the forming machine.
For friction reduction and surface quality improvement the lubricant oil of type AVIA GLEITBAHNÖL RSU 220 has been applied.
Control factors and levels Parameter Sign Level 1 Level 2 Level 3 Spindle speed (min-1) n 300 600 900 Feed rate (mm/rev) f 1 1,5 2 Workpiece geometry (-) pm (1) radius R10 (2) conical area (3) cylindrical area Rolling direction of the sheet (deg) rd 0 45 90 Analysis of data Using Minitab 16 software, ANOVA (Analysis of Variance) was performed to determine which controlled process parameters and two-way interactions significantly affect the performance characteristics.
The LB (lower-the-better) type of S/N ratio (Signal-to-Noise ratio) was used for transforming the raw data in the case of residual stresses analysis (Eq. 1) and the HB (higher-the-better) type of S/N ratio was used in the case of surface microhardness analysis (Eq. 2): (1) (2) where n is number of measurements in a trial and yi is the ith measured value.
Fig. 3 Effects of process parameters on residual stresses (S/N data) b Fig. 4 Effects of process parameters on surface microhardness (S/N data) Table 3.

In this way, it can be ensured the maximum vibration intensity at point E would not greater than the allowable value. 6) Overrun control settings: This program has the main parameters like vibration intensity overrun control functions, if the measured vibration intensity value beyond allowable value, the vibration mill would be stopped working; During the whole process, all vibration intensity and amplitude values ​​will be credited to the PLC memorizer, and the software process the corresponding data into charts automatically; It makes inspection and analysis of vibration effects more convenient.
Test and Analysis Debugging includes 4 stages: presetting values of program, data collection, data processing, and data analysis.
After data collection, it can be drawn into the vibration frequency, vibration intensity and amplitude versus time curve.
According to the analysis of measured data tables and curve diagram, the largest vibration intensity is 24, there is no overrun; Amplitude maximum is 21.5mm, and no overrun too.
It can be known from Fig.3 that the overrun of the maximum reduction functions in advanced control of measured and expected vibration intensity have been achieved, and does not appear vibration intensity overrun phenomenon, and it is proved that system with transient super-high vibration intensity has been controlled.