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Data input form in simulation program The method of developing simulation model is systematic.
Figure 2 shows data input form in simulation program.
Numerical example data value Parameters of thermal model value Parameters of simulation model 2.5 61 10 35 70 3 -10 10 0.5 200 30 49 1 1 Parameters in simulation model and in thermal model are equivalent.
In simulation model, was the threshold level which in case of inventory reduction to the level of, has to be refilled, and is the threshold level of temperature which in case of temperature reduction to the level of , it is necessary that the mechanism of increasing temperature to be activate.
For example, variable in simulation model is economic level of recovery of returned product ‘A’ into product ‘A’ which in critical conditions (under reduction) produces unstable behavior.

The reconstruction bases on volume heat source models and makes use of experimental data.
The parameter identification leads to an inverse heat conduction problem which cannot be solved exactly but in terms of an optimal alignment of the simulation and experimental data.
One major problem of heat source models is the adaption of model parameters with respect to reference data.
Models for Temperature Field Analysis and Experimental Reference Data Mathematical Fundamentals.
This yields to an optimal alignment of both data sets.

The thermodynamic assessments utilize the knowledge of phase equilibria and thermochemical data to accurately delineate the phase constitutions.
The reliability of a thermodynamically assessed system depends on the accuracy of the thermochemical data used to optimize the Gibbs energy functions.
The thermodynamic driving force for diffusion, characterized by the thermodynamic factor (Φ), is indirectly estimated from the activity data of individual elements in a phase.
The microstructure of alloy ‘1’ is presented in Fig. 24a and the corresponding XRD data corroborating the phase quantification is displayed in Fig. 24e.
To check on the accuracy of the optimized Gibbs energy functions, the derived thermochemical data were compared with those of Maciag and Rzyman [106, 107], Oforka and Argent [108] and Kek et al. [109].

In conclusion, the two sets of data indicate good agreement and show the utility of CFD as a rating and design tool for coal pulveriser manufacturers.
A 1% improvement in plant efficiency can result in a 2.5% reduction in CO2 emissions for example [1].
The rig will be used to provide experimental data in order to understand the process of coal classification and engineer improvements to the classifier and hence the classification process.

Stress-life fatigue data were generated for both shocked and as-machined conditions.
The reason is that the compressive residual stress superimposes with the applied stress to provide a net reduction in the total stress intensity.
Fatigue data represented by the S-N curve were determined, following the standard procedure, by fitting the lg (N) vs. lg (σ) results.

Collected data are correlated with meteorological conditions.
The device handles all operations needed for a measurement, namely energizing the hot-ball sensor, measuring its temperature response, storing the scanned data and wireless data communication for managing the device using a laptop.
A sequence of monitored data related to the effect of freezing – thawing is shown in Fig. 4.
Data are taken from the sensor that is located at 450 mm.
We have data on Sander sandstone only where magnitude of the thermal conductivity change for saturated and dry sander sandstone is 29% [11].

The data were collected with a 0.01o step size and a count time of 60 s/step.
Diffraction data sets were refined by the Rietveld method using the FullProf software [19].
Rietveld refinement of the XRD data confirms the symmetry and the space group and gives other structural parameters.
Fig. 1 shows the Rietveld refinement of the XRD data and Table 1 shows the refined structural parameters.
Rietveld refinement of X-ray powder diffraction data.

It is generally believed that microcredit is a success of poverty reduction, for socially weak force and it is a means of credit that will develop sustainably, which concerns about the low-income class.
The microcredit companies in all these cities don’t have even one nonperforming loan by May 2010. 2.1 Data Selection Considering from the representativeness and availability of the data, in this paper, authors finally select nine microcredit companies as a sample for analysis, which include Xinchang, Dayang Huixin and Huitong microcredit companies from Xian; Hujun and Dingyuan from Yan'an; Huimin, Jinxin, Jinxing and Xingmao from Yulin.
All the data are obtained from the Information Special Reports of People's Bank of China Xi' an Branch, as are shown in Table 1 and Table.
Data of other microcredit companies ends by May in 2010.
I hope that this article could be of little use for the government to further promote sustainable development of microcredit companies, strengthen the construction of new rural finance and provide scientific, effective data and relatively sound proof for governmental decision-making.

This constructed model is then correlated to the experimental data to make sure the accuracy of this model.
A lot of input data are required during the engine model construction.
It is important to produce an accurate engine model to get better simulated output data.
These results are used to correlate the model with experimental data.
The model has been correlated well with measured data.

For vibration reduction in truss structures, piezoelectric shunt damping has been investigated in [7, 8, 9].
In this paper, the rotational and lateral spring element stiffness used in the piezo-elastic supports is first verified by experimental data and the updated model is then validated by comparing numerical and experimental capability to attenuate vibration.
For the experimental setup, the vibration reduction in y-direction is 16 dB and in z-direction is 26 dB.
Therefore, the updated numerical simulation still overestimates the possible vibration reduction compared to experimental results, Fig. 9.
However, the updated numerical simulation still overestimates the possible vibration reduction compared to experimental results.