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Then the entire assembly is rolled under a small reduction when heated to bonding temperature.
In rolling-diffusion bonding process, reduction is a key parameter influencing interface bonding strength.
Theoretical calculations were performed with above mathematical models, and the computation results were compared with experimental data. 1.
The microstructure obtained at the bonding region under reduction 13.1% for 30min is shown in Fig.2.
Vol. 40(1995), p.181 [14] H Mehrer: Numerical Data and Functional Relationships in Science and Technology ( Druckhaus Langenscheidt KG, Belin 1990)

For the 30% glass replacement was applied there was a reduction in the compressive strength at both ages 7-day and 28 day ages, as for 7-day age the reduction was 6.39% whereas at 28-day age the reduction in compressive strength was 8.8%.
The reduction is compressive strength can be explained as a result of two causes; the first cause is that the glass wastes has smooth surface compared to the normal aggregates and that leads to the decreased bond between the particles and the cement matrix and with increasing the percentage of glass the reduction in the compressive strength increases.
But overall, the reduction in compressive strength can be considered as insignificant one as the highest reduction percentage was less than 10% ( at 30% replacement ratio).
Compressive strength at 7-day age Type of specimen Weight (kg) Compression Test (KN) Compressive stress (MPa) Average (MPa) Control 8.200 567 25.25 23.77 8.032 532 23.64 8.11 505 22.44 10% Replacement 8.396 582 25.86 25.77 8.264 568 25.24 8.242 587 26.08 20% Replacement 8.170 567 25.2 25.35 8.249 592 26.31 8.240 549 24.4 30% Replacement 8.196 522 23.2 22.25 7.988 448 19.91 8.146 532 23.64 Although there was a reduction in the compressive strength for all mixes with glass wastes, but the reduction was minor as the maximum reduction occurred did not exceed 10%.
Sadiq (2018), “Experimental data on flexural strength of reinforced concrete elements with waste glass particles as partial replacement for fine aggregate”, Data in Brief Journal, Vol. 18, pp. 846-859

In these methods, the vibration data are first pre-processed to obtain a reduced feature vector that contains the key characteristics of the original data.
Both techniques show that the spectral data for the repaired bridges are significantly different from the data for the undamaged structures, which is expected given the nature of the repair.
incoherent frequency shift The same ANN as used on the experimental data was also used to classify the simulated data, although it was retrained using a subset of the simulated data for the undamaged and fully damaged cases.
As in the experimental data there was no confusion when the ANN was used to classify test data from these two extremes.
The problem of identifying data sets that differ significantly from an original undamaged data set, the novelty detection problem, requires a different approach to training the ANN (unsupervised learning) and these methods are currently being applied to the data sets to achieve this.

Two main outputs are ECCC data sheets and ECCC Recommendation Volumes.
Moreover, the test data are often sparse at low temperatures.
The resulting 2017 data set had collected test results 48 heats at temperatures range 550-700°C, with test-data extending to 150kh (failed) and ≈200kh (un-failed).
During the last 20 years, many materials have been considered, in terms of experimental data production, data collation and assessment, and microstructural characterization.
Further data collation aimed to full assessment ongoing [3].

Also, a reduction of the specific power consumption and extrudate-swell have been found.
Generally a reduction in viscosity and/or an increase in temperature are proposed as major causes for this behavior.
At low flow rates pressure reduction due to ultrasonic vibration is important and seems to be associated with an increase in melt temperature.
As the flow rate increases the pressure reduction becomes less significant and so does the temperature increase.
At high flow rates, the vibration does not affect the quality of the extrudate. 60 70 80 90 100 110 120 130 140 150 0 50 100 150 200 250 Data Reading ����P [10 4 MPa] Shear rate (1/s) 6.94 13.89 20.83 27.83 Fig. 2 - Influence of vibration on pressure drop.

At the same time, the drying rate and moisture content data were performed using linear and non-linear regression analysis to estimate a suitable model.
Therefore, the sludge incineration is the most effective way for harmlessness and reduction disposal.
Reduction of energy usage in drying of sludge is a major concern among environmentalists in terms of reducing greenhouse gas (GHG) emissions.
Drying patterns for EHD, hot air and ambient air drying of sludge The EHD experimental data of moisture content obtained at different time were predicted by were predicted by linear and non-linear regression analysis using SPSS computer program, the following exponential equation was found to express the drying rate: (1) where y is the moisture content of sludge in %, t is the drying time in h.
The drying curves of sludge treated by EHD with different voltage values The experimental data of drying rate obtained at different drying voltage were performed for all five drying models, and, the drying constants and the values of R, R2 and S were given in Table 2.

Calculated polarization curves are shown to compare favourably with published experimental data for ultra-thin catalyst layers.
Thereafter, modeling results are analyzed and compared with the available experimental data.
The experimental data of Parthasarathy et al. [7] were used to correlate the reference exchange current density for oxygen reduction in the acidic electrolyte with temperature.
We compare our model calculations of polarization as a function of operating current density to the experimental data of Debe [2].
Since many researchers report that the hydrogen electrode in the PEFC performed with negligible overpotential, the experimental fuel cell voltage data are comparable to our calculated potentials by including the membrane proton resistance.

Crystal structure parameters from XRD powder data of initial ternary compounds CeCoC2, CeNiC2, and their boundary solid solutions.
Inset: Specific heat data of CeCoC2 depicted as C/T versus T2.
(a) Temperature dependent dc magnetic susceptibility, c(T) º M(T)/H, of solid solutions CeCo1–xNixC2 measured at a field of 1 T and (b) the corresponding inverse susceptibility data, 1/c, where the solid line indicates a Curie Weiss fit (see text); data of CeNiC2 are taken from Ref. [6].
Because of some ambiguity of the absolute values of the measured resistivity data due to the presence of small cracks in the investigated samples, these data are presented in Fig. 6 as normalized resistivity data, r(T)/r(300 K).
Acknowledgement We thank Amitava Bhattacharyya for providing susceptibility data of CeNiC2 presented in Ref. [6].

In addition, ratings indicators are much more indicators, which in turn will increase the difficulty in the work of data collection and arrangement.
Sample selection: Choose 38 Hotels in Beijing, Guangzhou, Nanjing, Ningbo and so on as the object of research, 8 hotels of which as verification set data, 30 as test set data (W1, W2, ...
W30) Data Collection: 150 survey questionnaires were distributed, and 139 available questionnaires were retrieved which resulted in 97.3% sample return and 92.6% the ratio of callback of valid questionnaire.
After careful interviewing, ultimately determine W20 as the Autocracy type of TMT, and W10 and W29 as democratic type of TMT. 3.2 Data processing and analysis 3.2.1 Test of Reliability and validity of Indexes’ system BY use of Cronbach α-reliability coefficient assessing the credibility, after the original data are standardized, then put it in the formula testing reliability and validity, calculated result as shown in Table 2.
Weight coefficient matrix of indicators multiply the corresponding value of the research data standardized, the value obtained is based on the one based on Rough Set.

Energy requirement (Data source [6][8]) Figure 2.
Table 1 Weight Reduction with natural fiber composites（Data source[12]） Component Auto side panel[9] Auto insulation panel[7] Transport pallet[6] materials ABS Hemp/epoxy Glass fiber Hemp-pp Glass fiber China reed-PP Weight (g ) 1125 820 3500 2600 15000 11770 Weight reduction (%) 27 26 22 Table 2.
The weight reduction ranges from 20-30%.
Natural fiber reinforced composites for automobile(Data source[25,26]) Products Main applications Developers Main users Jute/PP Car interior components, noise absorption panel, NVH/Acoustic absorption materials.
As reported in reference [22], the author gives the thermal conductivity data of some kinds of NFRP.