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We illustrate the methodology with published data from micromechanical tests on small-scale flexure specimens from the literature.
A comprehensive set of data on built-in single crystal silicon beam specimens is available for analysis [7].
The fitted lines through the data afford evaluations of the Weibull parameters m and σ* for each data set.
Data reproduced from Namazu et al [7].
The data for the two groups of specimens show distinctly different spreads, suggesting fundamentally different flaw populations.

The wide application of this system will be helpful for machining tool programmers, the improvement of machined part quality and the reduction of machine cost.
The source of cutting data includes literature data (Cutting handbooks, cutting tool catalogues and journals with printed or electronic form), data from shop floor and experimental data.
Experimental trials provided information that was not already available and verified some uncertain data.
Cutting data have been evaluated by experts before they are input into database.
Instead of just retrieving cutting data from the database, this system can calculate and modify the machining parameters according to the user's input on the basis of metal cutting principle.

Mechanical and physical tests were used to measure the retained properties and to observe the causes of damage and strength reduction.
The experimental data showed that resin properties may strongly influence the durability of FRP reinforcement, environmental combined cycles did not take to significant damage of conditioned specimens; steel fibers are sensitive to alkaline attack when resin does not provide adequate protection to fibers.
Then management of thickness, sizing and sorting with a starch removal and moisture reduction are performed.

Connecting these data with microstructures examined in optical and electron microscopes and resultant mechanical properties have improved the understanding on complex phenomena occurring in the processing of these steels and the role of numerous process variables in the optimization of enhanced mechanical properties.
Based on the data generated on a Gleeble simulator, new equations have been proposed for the predictions of SRX kinetics and the SRX grain size in TWIP steels [17].
An example of the ultra-fine grain structure obtained in 301LN steel, cold rolled to 60% reduction and annealed at 800°C for 1 s is shown in Fig. 5.
Simulation experiments based on the industrial processing conditions, both with or without controlled deformation below Tnr, followed by cooling at different rates, enabled generation of reliable phase transformation data for plotting of the CCT diagrams.
Summary Physical simulation has been effectively employed to generate relevant material data for improved modeling of microstructural phenomena and thermomechanically controlled processes during the development of advanced high strength steel types.

The cascade correlation algorithm that is cascade-correlation(CC) algorithms, CC network structure and CC network weights learning algorithm are introduced, based on the real data in hydropower station, considering the cavitation characteristics, the network model is established based on CC algorithm, and the applications of CC and BP algorithm of turbine are compared.
In first place, the growth of the turbine output power is based on the reduction of dimensions to decrease the cost of its components.
To date, we have explored the all-sigmoid and all-Gaussian cases, but we do not yet have extensive simulation data on networks with mixed unit-types.
Model and Application of Vibration Characteristics based on CC Algorithm In this paper, the operating data were analyzed, part of the measured data were shown in Table 1, the model of cavitation characteristics f = (H, �) was established based on the CC, where H is unit rotation ( 1 11Q l s−⋅ ), � is the unit discharge( 1 11 minn r − ⋅ ), and f is the turbine runner cavitation index of output.
Conclusion In this paper, the definition of CC algorithm and structure of the network are described, and based on the operating data, the model of CC vitation characteristics was established based on the CC, the application of BP neural network and CC algorithms were compared.

It is based on forging hollow axles which allows a significant reduction in steel consumption.
The final objective is to obtain the cyclic loading paths, in order to provide the data needed for the analysis of fatigue.
This simulation is validated by using experimental forces data (Fig. 8).
In terms of results, the different simulations present a good correlation with the experimental data.
A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures, volume 21. 1983 [15] T.T.

By means of factor analysis and logistic regression approaches, this paper predicted financial failures of Chinese listed companis in 2009 from the published data in 2006 of those companies.
But most of these financial risk analysis are based on accounting data and financial ratios.
Sample and Data Selection.
Then the financial failure analysis was based on those data of 2006 fiscal year, in order to achieve the purpose of prediction, i.e., risk analysis and control beforehands.
In rotating the factor loading matrix after extracting factor, and its economic significance to clear explanations, which not only can find out the influence of a company's financial condition main factors, but also for warning model dimension reduction processing, to simplify the regression model.

For the current situation and deficiency of the enterprise material management system: huge material data, species diversity, single management means, management behavior is not standard, people involved in most materials management activities, materials management standards is not unique, materiel maintenance and resource sharing is difficult, and so on.
Da Hong Shan Pipeline company has already built a website platform, integrated management and control systems, data acquisition and monitoring of SCADA systems, slurry characteristics data management system and production information such as video monitoring platform.
It is in the "unified planning, step by step implementation, the key breakthroughs" management philosophy, advocate and support the digital management of enterprise production, real-time monitoring of production site and dynamic analysis and decision of production data.
Materials department of use according to "material management regulation", fill in the scrap material disposal application, after approved by head of department, review by the competent department of company, put forward disposal opinions, after approved by the company in charge of the leadership, report to energy conservation and emissions reduction center. 2.6 Material of repair.

Abstract Experimental data indicate that carbon vacancies incorporated in active regions of SiC devices are important electrical defects, responsible for device limiting effects such as carrier lifetime reduction.
Experimental data indicate carbon vacancies (VC) are incorporated as a consequence of the growth conditions, and act as important electrical defects, having device limiting effects upon the carrier lifetime.
Combining all diffusion process, the data reported here therefore support the notion that VC can move more freely within a basal-plane via h-sites or k-site than in the c-axis direction in the immediate interfacial layers, but is hindered relative to diffusion in bulk.

At the same time the melting capacity of the furnaces ranges at the lower end according to the manufacturer's data.
Figure 3: Fluctuations of aluminum mass in the shaft The mentioned effects were confirmed by comparing measurement and manufacturer's data (Table 1): The analysis displays a 25 % higher specific energy consumption compared to manufacturer's data and a melting capacity of 3.68 t/h.
Table 1: Comparison of performance Specific energy consumption [kWh/t] Melting capacity [t/h] Manufacturer data + 25 % 3,5 - 4,5 Measured data 3,68 Improved charging management.
Nevertheless the validation on the basis of measured data is essential.
Overall, a good accordance between the simulation model and the measured data has been achieved.