Search results

Reduction of giga-cycle corrosion fatigue strength was 12.5%.
On the contrast reduction of giga-cycle corrosion fatigue strength of austenitic stainless steel was small[5,6].
These data for SUS329J3L can be seen above the best fit lines for austenitic stainless steels.
The reduction rate of giga-cycle corrosion fatigue strength was 12.5%.
It can be concluded that the corrosion fatigue strength reduction was due to corrosion pit formation at corrosion fatigue crack initiation site.

As an approximation it was assumed that the diffusion coefficient of dissolved sodium in molten NaCl is the same as that of sodium cations in molten NaCl for which the data of Bockris and Hooper [28] can be used.
Pre-Reduction of TiCl4.
Unfortunately no data could be accessed for the solubility of TiCl4 in molten CaCl2.
Janz, Thermodynamic and Transport Properties of Molten Salts: Correlation Equations for Critically Evaluated Density, Surface Tension, Electrical Conductance, and Viscosity Data, A Chem.
Reference Data, Volume 17, 1988, Supplement No.2

Therefore reduction inspection field, tracking inspection process and the cause of the accident are especially important.
Application of mobile data acquisition technology can make the whole  lightning inspection data of highway be traced back. 
Data transmission.After field data acquisition,  it should be return through the wireless network or USB storage device. 
The mobile data acquisition terminal is used to collect data. 
Then fill the data real-time after inspection.

Flood reduction requires water flow detention or deceleration of during the storm water season.
This study investigated the reduction of water flow in Yom basin (a sub-basin of Chao Phraya basin) using the synthetic unit hydrograph to synthesize deluge parameters.
The relationship between volume (S) and height (H) of the detention pond system was found to be S=18866224.8H1.15 based on the analysis of elevation data using Geographic Information System (GIS).
Normal elevation of the water surfaec is 40 m (MSL). 4Correlation between water elevation-land-storage volumes The areal data was analyzed by means of the SWAT model [8] and MapWindow [9] based on DEM [10] and a map of scale 1:50000.
The parameters and areal data enabled us to find a correlation between volume and height of the swamp studied, i.e., S=18866224.8H1.15m3.

The server take out the corresponding data from the data queue of receiving and to extract In accordance with the key rules, then to reduce of information in corresponding positions.
The data structure of DS is a two byte DS= (A, R), where A is a finite set of data nodes, R is a finite set A relationship.
Linear table is a data structure, it can be expressed as DS= (A, R), A is a collection of n nodes with a0，a1，……，an-1, R has only one relation , (N={(ai-1ai) |1Definition 4: Data structure of compressed storage.There are two main types methods of compressing data matrix in traditional: random sparse matrix compression and special shape matrix (symmetric matrix and diagonal matrix) compression.
Corresponding to this,the server take out the corresponding data from the received data queue,in accordance with the rules and to extract key,then the reduction of information in corresponding positions,finally realizes the identity information authenticity, integrity verification of communication subject.Can effectively prevent man in the middle attack and reduce the amount of data transmission, greatly reduce the transmission time for the information.

The two dimensional IDDM algorithm is checked herein through numerical simulations, using the FE model of a plate and modeling local reductions of stiffness through a reduction of the elastic modulus of the material of one or more elements of the model.
Furthermore, as shown in reference [3][5], useful information on damage is lost when data, in a frequency range away from resonance, are discarded (as occurs in the modal analysis process).
If a reduction of stiffness occurs at a certain location, the operational shapes change in the region close to that location.
Bi-cubic interpolation is a cubic interpolation in two dimensions and calculates the value of a given function at a point P(xl, yp) by considering 16 data points in the neighborhood of P.
The interpolation damage index The drawback of bi-cubic interpolation for the application of the IDDM is that it can be applied only to data point lying on a two dimensional regular grid.

An analysis of X-ray diffraction, XRD data using refinement method shown both x = 0 and x = 0.02 samples were in single phased and crystallized in rhombohedral structural with Pnma space group.
The experimental resistivity data for metallic and insulating regions are further analysed by fitting with the scattering and hopping models, respectively, and the data are presented to elucidate the possible mechanism involved on the observed resistivity behaviour.
The phase purity and crystal structure of samples were confirmed by Rietveld refinement of XRD data using the GSAS-EXPGUI software.
The solid line plotted on the graph, which represents the SPH model, fits the resistivity data, thus indicating that the electrical behaviour of La0.7Ba0.3Mn1-xFexO3 (x = 0 & 0.02) is governed by the SPH mechanism.
The solid line indicates the best fit SPH model to the resistivity data The Ea values obtained from the slope of the ln (ρ/T) vs. 1000/T are found to increase from 66.61 meV (x = 0.0) to 80.68 meV (x = 0.02) under applied current of 10 mA due to Fe substitution.

Automatic parameter classification for dimension reduction as basis for robust parameter identification D.
Numerical approximation methods of high dimensional data suffer from the curse of dimensionality [1].
Dimension Reduction.
The dimension reduction is performed user-controlled.
These parameter classification results are used for a parameter space reduction.

The TPR curves showed peaks of reduction of the NiO species, and reduction of nickel present in the NiAl2O4.
Then, the data were collected at fixed intervals of time (15min).
Fig. 1 – X-ray diffractograms of NiAl2O4 catalysts Through a refining analysis of the XRD data it was possible to obtain the mass percentage of the formed phases.
Fig. 4 – TPR profiles of NiAl2O4 catalysts It was observed that the sample UES presented a low temperature reduction peak at around 350°C that can be assigned to the reduction of NiO species interacting weakly with the support.
These samples with excess urea (10UE and 20UE) also presented a reduction peak at around 500°C referring to the reduction of NiO dispersed on the surface, and a very intense peak centered at 950º C, which can be attributed to the reduction of nickel in NiAl2O4 spinel [20, 21].

Most of the data, available in the literature, is related to flat GBs obtained for bicrystals [4].
Since the GB structure and properties is influenced by its curvature (grain size) [5] this data is not applicable in the case of nanomaterials.
The data from this investigation may be further used for understanding processes, which occur at different length and time scale, such as grain growth or plastic deformation.
The slope of the data from this region represents the velocity of the grain shrinkage, dV/dt (grain boundary migration).
The quantitative data of these parameters for GB in α-iron have been presented in the present paper.