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Data is collected from the literature considering the GT GE LM2500+G4 operating under similar conditions [5], OTSG for the comparable application and parameters [7] and ST with similar use and power output capacity [28, 29].
Combined Cycle Emissions Reduction: CCS.
The reduction of the number of theoretical plates in the absorber and, consequently, its height, is then assessed.
The height reduction is then limited to the maximum amine flow-rate (625 t/h), as shown in Figure 3.
Simple Cycle Emissions Reduction: CCS.

In absence of sufficient data, the biaxial yield stress was assumed as an equivalent von Mises yield criterion.
Thus, the true strain φ = 0 contains several data points which vividly illustrate the described effect.
Fig. 5: Experimental data and approximation of the strain-dependent Young’s moduli E(ε) during release Fig. 5 includes all the measured data points for the five tested ultra-high strength spring strips.
As clearly illustrated, a limited data base is available for the extrapolation of the curves.
Only material M1, which reached a true stain φ = 6%, offered a broader data base.

The impedance spectroscopy data suggest that carrier transport mechanism might change after the plasma exposition.
Table 1 shows the results from the simulated data before and after to the plasma exposition.
The results from simulated data show a decreasing on surface resistance of about 95 % after the plasma treatment, which are in agreement with the film reduction.
Table 1 - Data from the simulation of model equivalent electrical circuit.
For porous films these values should change due to bulk reduction.

During this period, the ecological capacity per capita had decreased from 1.3535 hm2/cap to 1.3028 hm2/cap, the reduction of ecological capacity per capita was 0.0507 hm2/cap, the reduction rate was 3.75%, the average annual reduction rate was 0.31%.
Prediction of ef, ec and ed Applicating grey prediction model and according to the data of ecological footprint per capita and ecological capacity per capita in Jilin province from 1998 to 2010, we establish the gray prediction model [GM (1, 1)].
GM (1, 1) model is composed of first-order differential equations of a single variable, which has fewer restrictions on data requirements and has high-precision in the short-term forecasting.
On the basis of the historical data, the prediction model functions of ecological footprint per capita and ecological capacity are as follows (4) and (5).
The reduction of ecological capacity per capita was 0.0507 hm2/cap, the reduction rate was 3.75%.

This work targets the reduction of the absolute value of Vth for SiC PMOS transistors, which were analyzed using five different methods.
Sheet resistance has been monitored across all wafers on 49 data points after both annealing steps.
To calculate Vth for each data set, literature provides numerous different methods based on Si [9].
Table 2: Threshold voltages of the experimental data evaluated by five different methods according to Ortiz-Conde et al. [9].
Further data from additional devices including variations in channel width and length are required to gather more precise statistics.

Although AIT is indispensable for safely handling and operating flammable substance, the AITs data are, however, very much diverse in different data compilations.
Data, 2010, 55, 5059–5064. (6) ASTM International.
[9] Design Institute for Physical Property Data (DIPPR), DIPPR Project 801 Pure Component Data public version.
[10] Design Institute for Physical Property Data (DIPPR), DIPPR Project 801 Pure Component Data public version.
Zalosh, J.Casey, “Autoignition Temperature Data and Scaling for Amide Solvents.”

The numerical predictions have been validated through comparison to the available experimental data.
This is thought to be due to the reduction in creep ductility and also hardening effects in the PC material [5].
In this figure the estimated trends are shown in dashed lines whereas the mean fit to the data at the upper shelf region is shown as a straight line.
Note that only the valid data points (see [7]) are shown in Figure 3.
Figure 3: Comparison of the predicted CCG trends to the experimental data for (a) PS and (b) PE conditions The numerical predictions presented in Figure 3(a) and (b) show that under both PS and PE conditions, the CCG results from the low load test on PC material (PC6) are consistent with those of obtained from the low load simulation on AR material (AR6) and the predicted data points fall close to or within the long term experimental data band for the AR material.

The noise and vibration data got from operating test of high-speed trains shows that the interior noise spectrum varies with the structure vibration, as shown in figure 2.
So the validity of the noise and vibration data used below is confirmed.
Test data and analyses 5.1 “SPL-VL” laws under force loads Applying the force excitation, the sound pressure and vibration are measured using the method as explained in section 4.1.
Notably, the noise reduction values are almost equal to the vibration reduction values below 200Hz.
In other words, the noise in the car would be reduced with the vibration reduction.

Data Collection.
In the untreated specimens, the three important peaks were recorded in the spectra and used for data analysis.
Laser effect on the reduction of Raman intensity ratio of CO32/PO43 and CH2/PO43 peaks of enamel and dentine.
Our data indicates that after laser treatment the loss occurred on organic component is at higher proportion than that of inorganic component, the organic component losses were 38.6% in enamel and 7.0% in dentine while the loss at inorganic component was 7.4% in enamel and 2.9% in dentine.
Summary The present study has demonstrated the reductions of the organic and inorganic compositions of dental hard tissues after Er:YAG laser irradiation using FT-Raman spectroscopy.

The application of TWBs has several advantages in the manufacturing of auto panels: low cost, less scrap, reduction of car weight, and flexibility for component design in mass production.
Weight savings have a marked effect on a vehicle's efficiency, with research showing that a 1% reduction in vehicle weight can result in a 0.6-1% reduction in fuel consumption[2].
HyperForm Create FEM model Set boundary conditions Generate input file for solver Solve Result files HyperStudy Extract result data Get new design variable HyperMoph Customized Optimizer Obtain responded value Optimizing policy New design variable Fig. 2 Framework of the optimization program To achieve suitable weld line offset value on the blank of TWBs, a FEM model is created for simulating and a entirely analysis is done with the model.
Then the design variables and responds are extracted by HyperStudy, which can translate the data to external customized optimizer.
Create FEM model Set boundary conditions Initialize the design variable Generate input file for solver Solve( lsdyna ) Result data Optimizing Constringency？