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Existing steel wheel rim dimension was measured and Finite Element Analysis (FEA) was done to get actual dimension and mechanical properties (stresses), as baseline data.
FEA was done again on optimized steel wheel rim to compare with actual steel wheel rim data.
From the optimization processes, on the weight reduction (Table 3), it was help to improve the overall weight of vehicle as contribute to reduce the fuel consumption as final results.

For example, Jieshi Chen (2009) study Sheet metal forming limit prediction based on plastic deformation energy, the sheet metal forming limit is calculated by fitting curve from experimental data.
Calculated and plotted to FLD and Comparison of predicted forming limit strains with measured experimental data for 6061-T4 seamless extruded tubes.
The four strain paths are obtained from experimental data.
As the approximate trend lines, the strain paths at the pole of the forming tube for different strain ratios have a trend line of data as linear.
The critical strain from the experimental data and the analytical results, the FLD and forming limit curves (FLC) of STKM 11A tubes are constructed as shown in Fig. 4.

In mathematical modeling, MATLAB plays an important role, especially for large amounts of data for analysis, handling, processing, which manual calculations is difficult to complete, people often uses MATLAB to achieve.
With powerful graphics capabilities, ease of data visualization, MATLAB can not only draw a variety of different two-dimensional coordinate system curve, but also to draw three-dimensional surface, reflecting the powerful graphics capabilities.
Data were analyzed to calculate, identify factors that play a major role, after the necessary refined, simplified, made ​​a number of assumptions in line with the objective reality.
There is error analysis of the results, the stability analysis of the data model; Model checking.
With the actual phenomenon, data comparison, reasonable test model applicability; Model application.

It can extract by learning an important characteristic of a set of data or a certain inherent law, according to the discrete time way to classify[2] .
Network can take any high dimension of input mapped to low dimensional space, and makes some similar nature of the input data internal performance for geometry on the characteristics of the adjacent mapping .
After get sample data vector, due to its various indices differ, the original sample of each vector in order of magnitude difference is very big, in order to easy calculation and prevent some neurons to supersaturated state, need to sample the input of the normalized processing, the data processing for the interval of data between [-1, 1].
SOM is a typical characteristic of the network can be formed on a two-dimensional array processing unit topological distribution features of the input signal, Therefore, in the integrated network, SOM network can be regarded as feature extraction network,  data after primary network formed the clustering results of failure mode.
Fig.3: Fault diagnosis results Conclusions SOM neural network compared with other network, the degree of dependence on the mathematical model of the controlled object is low, have self learning and adaptive, associative memory, strong fault tolerance and non-linear pattern recognition ability, having the advantages of high efficiency and solving quality, can the multidimensional input vector clustering and dimensionality reduction to two-dimensional plane, through the graphical visualization easily classify the failure mode.

The process tomography system basically consists of three parts: (1) a sensoring system to acquire the measurement data, (2) an electronic system for data acquisition, and (3) a computer system for measurement control, image reconstruction and displaying the result [1,2].
Like other process tomography systems, ECT has a fatal problem, and that is the tradeoff between the accuracy of the reconstructed image and the rate of the data acquisition.
Consequently, an increase in the number of the integral measurements would increase the data acquisition time, and thus would decrease the real time capability.
The issue raised is how to acquire reconstruction results with sufficient accuracy for process quantification from the limited experimental integral data without sacrificing the time resolution for reliable real time measurements.
Prior to data recording, the system requires calibration for the two extreme cases when the sensor area is filled with the higher permitivity material (which is coal ash in this case) and the lower permitivity material (which is air in this case).

Fig. 1 show observed, calculated and difference pattern for Rietveld analysis from the XRD data using initial structure model of Ba4Ti12O27 [9].
Observed, calculated, and difference patterns for the Rietveld analysis using the powder X-ray diffraction data of Ba4Ti12O27.
In fact, the data successfully least-squares fit to the Mott-Davis VRH law with r2 = 0.9991 (r is the correlation coefficient).
The crystal structure of Ba4Ti12O27 was refined by Rietveld analysis using the powder X-ray diffraction data.
The magnetic susceptibility data showed Van Vleck Para magnetism in the range of 50 to 300K.

The lattice parameters (a and c) obtained from XRD data decreases with increase in cobalt content x.
The XRD pattern for pure Sr0.5Ba0.5Fe12O19 is in good agreement with JCPDS data (Cardno.51-1879).
Using the JCPDS data the peaks of the XRD pattern were indices for the hexagonal structure.
(a)Hysteresis loops(b)curves From Fig. 3(b), it is seen that the coercivity value decreases from 5478.8 to 2397.1 oe with increasing cobalt concentration (x=0.0 to 1.0) due to reduction in magneto crystalline anisotropy [11].

This rate of size reduction is somewhat lower than it was temporarily before 2000, where the dimensions were reduced by a factor of 0.7 every two years.
This paper will describe a pragmatic model developed for boron implanted into crystalline silicon which is able to reproduce experimental data in a wide range of annealing conditions.
Fig. 16: Sheet resistivity versus junction depth as a function of hot-shield anneal temperature (shown as numbers besides the data points) and implant dose.
Fig. 18: Comparison of the simulation of an fRTP step with a peak temperature of 1270 ◦C to experimental data.
Fig. 19: Comparison of the simulation of an fRTP step with a peak temperature of 1340 ◦C to experimental data.

Above data demonstrates that Taiwan is among the leading contributors to carbon dioxide emissions worldwide.
Therefore, based on existing consumption expenditure surveys, many consumption-based carbon footprint studies analyze household GHG footprint and also track consumer’s expenditure related GHG life cycle analysis by using the national data from "input-output life cycle analysis" (Chavez & Ramaswami, 2013; Jones & Kammen, 2011).
However, only the national carbon dioxide emissions data is used, which lacks the carbon dioxide emissions statistics of each county and city.
However, without relevant legislation, Taiwan’s Environmental Protection Administration has devised only a national GHG registration platform, which provides GHG emissions for organizations that declare such data voluntarily.
Sweden: Stockholm. (2013) [14] Jones, C.M. & Kammen, D.M..in: Quantifying carbon footprint reduction opportunities for U.S. households and communities.

The data were taken with substantially similar condition of TiO2 loading in the range of 10-12 g m 2 where the TiO2 layer contained a large TiO2 grain (250 nm) for light scattering enhancement and had porosity of about 60%.
In effect, incident-photon-to-electron conversion quantum efficiency (IPCE) data measured for the dye-sensitized TiO2-coated ITO-PEN electrode shows a maximum value around 65%, which is lower than the best value obtained for the sintered TiO2 glass electrode, 80-90%.
Fig. 4 exhibits the dependence of the main photovoltaic parameters on the loading amount of TiO2, where TiO2 loading of 20 g m-2 corresponds to a thickness of 12.5 m. also includes a comparison of data taken for high and low incident intensities, 1 sun and 1/8 sun (1 sun = 100 mW cm -2).
Third, such method leads to a large cost reduction with use of low cost materials.
This test showed a reduction of initial cell efficiency to half value after aging of 880h.