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Then, the data were measured at a temperature of (290 ± 7) K for 6 hours.
At this temperature, the data were measured for 6 hours.
Like the SRD data [6,7], there was no change in the appearance of the ND data when the experiment was repeated.
Comparison of the fits in Figure 3 where neutron and synchrotron data are both plotted with the same x-axis (d-spacing) shows that the peak intensities are quite different in the two data sets.
Trial refinements initially using only the synchrotron data sometimes found a false minimum with somewhat worse goodnessof-fit indices, however, when both data sets were used the same minimum was always recovered.

Nevertheless, welding defects generated during the process result in reduction in strength of both the weld; and heat affected zone which could limit its applications.
SS Ib [mA] v [mm/s] If [mA] Hardness [BHN] Yield strength [MPa] PD [mm] BW [mm] 1 2 3 4 5 6 7 8 9 0 3 6 6 0 3 3 6 0 15 18 21 15 18 21 15 18 21 4 4 4 7 7 7 10 10 10 909 906 903 906 903 909 903 909 906 73.5 70.02 64.96 72.77 75.68 74.25 79.68 78.77 76.67 157 144 126 148 181 202 140 240 198 4.32 5 5 3.58 5 5 3.52 5 5 4.05 5.27 5.41 3.72 4.19 3.92 3.79 3.65 3.95 Figure.1 Hardness profile across the FZ, HAZ and BM Data preprocessing After performing the experiments and measuring yield strength, hardness, PD and BW the grey relation analysis was used to obtain the optimal welding parameters leads to maximum yield strength, hardness, and PD and minimum BW.
According to the data in Table 4, the absolute difference of array ∆0,i(m) and grey relational coefficient γi are obtained, respectively, from the analysis model of grey relational analysis.

The experimental Roll Diffusion Bonding (RDB) pilot plant permits a reduction of process costs of about 40% with respect to the HIP process.
The process parameters needed for the design of the pilot-equipment (rolling speed; strain-rate; temperature; pressure etc.) have been defined by means of literature data and experimental hot-compression tests including some pack-rolling tests.
These data are in good agreement with the results of mechanical tests which evidence better mechanical properties of RDB composite.

The external forces are computed from the image data.
(2) This variation formulation follows a standard principle to make the result smooth when there are no datas.
The obvious reduction in number of iterations and less time consumption are seen from contrasting two figures.
The reverse subdivision scheme produces very dynamic data structures.

And the relevant model are compared and verified with the experimental datas. .
It is known that experimental values are in agreement with those predicted by Maxwell-Eucken equation at low filler content[10], while the discrepancy is present between the experimental data and the numerical simulation results at much higher filler content (≥15%).
From Fig.3, a reduction in CTE was observed with increasing filler loading.
It can be seen that the CTE obtained from experimental data is lower than that of the theoretical model.

Field Instrument Data Acquisition.
The health of equipment state detection includes three parts: data acquisition, data transmission network, fault diagnosis and early warning system.
Energy Saving and Emission Reduction.
Process information layer is used to manage the process control equipment and its data.
Enterprise network includes high performance servers, which are used to complete the industrial networking data processing, including data storage, collection, scheduling and forwarding.

Calculation program calls the data in data storage area to conduct calculation and save the calculation results in data storage area for calling by machining program.
Data management.
Calculation program needs to call out data from data storage area and save the calculation results in data storage area for machining program.
Meanwhile, input and output data is also saved in data storage area.
Thus data storage area contains interactive data and intermediate data.

Regression models best adjusted to the experimental data.
Fig. 2 shows the 12 validation workpieces, with 4 Ra experimental data for each one, and the corresponding 48 validation data (20% of the data experimental).
Both models were similar with good prediction of most of the data, with a good fit with the roughness data, with only a few atypical values in certain data of workpieces 5, 21, 25, and 33.
The regression model was the most stable, and fitted the experimental data in more areas than the neuronal network model, but it also exhibited the largest deviations in some of the data of workpieces 5, 17, 21, 25 and 33.
The neuronal network model did not fit the individual data well, but the overall fit was better.

Data was analysed using classical content analysis method.
The interview was conducted before the analysis of data from observation in order to minimise the influence of observational data on the study[43].
Data Analysis Observational data collected using field notes of the researcher and photographs were analysed using constant comparison analysis[44].
Steele, Collecting Evaluation Data: Direct observation method.
Leech, “An Array of qualitative data analysis tools: A call for Data analysis Triangulation,” School Psychology Quarterly, vol. 22, no. 4, pp. 577–584, 2007

Most previous work using NDT data has been done with dynamic rather than static data.
Reduction in the amount of static test data as opposed to dynamic test data, and the abatement of disturbance from the environment which leads to more stable data, derive parameter estimation that is more precise and practical.
There has been limited methodological work done using static test data.
“Structural element stiffness identification from static test data.”
"Damage assessment of structures using static test data."