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The consistency of the model is verified with experimental data obtained from a 2014 Al alloy.
This equation takes into account the progressive reduction of Cu supersaturation in the matrix as θ’ precipitates grow
In this stage, the driving force for precipitates dimensional changes is the reduction in surface energy of the system: smaller precipitates tends to dissolve, while bigger precipitates coarsen.
During aging, λav decreases, inducing a strengthening effect in the material despite the reduction of Cu in solid solution described by Eq.4 and the consequent decrease in σss.

The presented method is able to estimate the effect of the helix angle on the sliding loss correctly whereas the estimation without using the data of tooth contact pattern cannot.
(1) Where n is the position ratio related to the meshing position, Φ is the pressure angle, μ is the friction coefficient and m is the speed reduction ratio.
This may cause the reduction in overall sliding loss ratio due to the reduction of contact area.

Based on these data, the effects of AgNPs stability and the conformational changes of collagen upon interaction with the AgNPs are discussed.
The FT-IR data proves the presence of the complex formed by AgNPs, carboxylate (COO−) and amine (NH2+) groups from collagen.
The reduction in the α-helix in favour of the β-sheet, random coil, β-antiparallel and intermolecular β-strand indicates a partial unfolding of protein in the presence of AgNPs.
The reduction in the α-helix in favour of the β-sheet, random coil, β-antiparallel and intermolecular β-strand structure indicates a partial unfolding of protein in the presence of the AgNPs.
Krueger, Protein secondary structure from Fourier Transform Infrared Spectroscopy: A data base analysis, Anal Biochem 194 (1991) 89−100

A fourth method can be used if pressure data is not available and temperature data is available, then the air density ρ can be calculated as in equation 5: 5 Where P is atmospheric pressure at a standard sea level = 101,325 Pascal, and g is the gravity constant 9.8 m/s².Equation 1 stated that wind speed was blowing at V speed all times, which is not possible in real life since wind speed varies all the times.
As air density ρ and wind speed V keep changing, the most accurate result would be by following a calculation to every data interval for a whole year, which takes us to a very lengthy calculation process.
Central and North Queensland meteorological data analysis and discussion In this research, data was collected from 6 Australian meteorological data stations and from Ret screen, namely; Gladstone, Emerald, Rockhampton, Yeppoon, Townsville, and Cairns.
This data is used in this research to assess the potential of solar and wind energy in Central and North Queensland.
The meteorological data obtained are based on daily average measured data in the last 15 years [30-31].

After data reduction, Do, D1 and n were obtained by fitting the creep data with the power-law expression shown in Eq. 1 without consideration of εp(σo, t) as its value was relatively small under low stresses.
Creep data of 45 oC composite coupons and the power-law curve fitting scheme Predictions for Other Orientations.
-6 MPa -n min -n , n = 0.238 (a) Creep data and predictive curve (φ = 15o, 5 h creep) (b) Creep data and predictive curve (φ = 34o, 5 h creep) Fig. 3.
Comparison of experimental creep data with simulation models for stress-strain responses under different orientation angles Prediction of Long Term Creep Data.
For example, consider the data for a 24 hour creep time shown in Fig. 4 (b), the optimal power law parameters, determined so as to fit the first 5 h creep data alone, yielded overestimated creep strains for the subsequent longer creep duration up to 24 h.

The grouping variable is AAL2 which has two values: 0 (absence of hail), 1(hail fallout). 43 cases with hail and hail were considered, all these data were involved in discriminant analysis.
From data of the table 2 "results of classification" it is visible that the studied group "without hail" (0) consists of 29 cases.
Summary Multidimensional physical and statistical schemes, which have been trained both on the basis of the concept of "ideal" PP-prediction (actual data) and the concept of output data of the global atmosphere model (MOS concept) has been developed.
Kanamitsu, Description of the NMC global data assimilation and forecast system, J.
Kagermazov, Forecast of hail on the output data of the global atmosphere model (T254 NCEP).

However, there is still a lack of quantitative data on how manufacturing route, porosity and moisture uptake jointly affect the static properties of flax laminates and their hybrid variants compared with conventional glass and carbon fibre composites [1; 2; 5].
Experimental data obtained during the mechanical testing are summarised in Table 1.
In the case of using a coating, the reduction is only about 17% for both laminate thicknesses.
For samples without a coating, higher absorption also indicates a greater reduction in tensile strength.
In the case of using a coating, the reduction was only about 17% for both laminate thicknesses.

Due to the reduction in modern vehicle development program timescales, it is necessary to reduce prototype testing.
In the first method, measured heat flux data on exhaust pipes surface are used as the boundary condition to CFD simulations.
Complete vehicle analyses have been made in a single vehicle model using Fluent CFD code by Skea et al but correlations of surface temperature with test data were not published [4,5].
Computation Model The model surface data was supplied by CAD data.
Quantitative Data --Figure 6 lists the top temperature of at three operations.

The main purpose of calculating the principal component is to project high dimensional data to low dimensional space.
PCA is mainly used for data dimensionality reduction.
Characteristic value will be sequenced according to the size; (3) The third step is to project data into the new space.
If r is small, then the dimension of the data is low, so it is easy to analyze, and it also can reduce the noise.
The contribution rate stands for the number of gravity which the major principal component possesses in the whole data analysis.

The data was collected for 3 engine operating points with three injection strategies: 1.
The comparison data are considered for the accumulator and the associated injector #4, as given in Fig.4.
Fig.4 Experimental data and simulation results comparison of the pressure within the injector and the accumulator The overall control parameter is the injected fuel amount.
Fig.5 Experimental data and simulation results for injector inlet.
In Fig. 5 can be observed that the simulated shape of the pressure wave, amplitude and trends are similar to the experimental data.