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Figure 1: (a) air inlets and outlets of the mound (b) termite mound structure (c) Abstracted termite model 2 Methodology 2.1 Study Area Description The data collection was acquired from constructing the two models; both of them were in the same location and along the same axis (East-West axis).
Since there is a correlation between the outdoor swing and the difference between the indoor and outdoor maximum temperatures, the temperature difference ratio was used to analyze the data.
The longer it takes the heat waves to pass through a surface, the reduction in the cyclical temperature on the inside surface compared to the outside surface.
Data in Fig. 8 displays that the wall orientation has a great effect on the Time Lag, TDR, and the Decrement Factor.
The collected data was divided into four seasons that were defined by compiling the monthly average temperatures and RH readings; where winter is defined from December to February, spring from March to May, summer from June to August, and fall from September to November.

In addition to dynamic recovery, both 3IVM and ALFLOW describe static recovery (RC), but for precise RCkinetics, experimental data is sparse, and accordingly these parts of the models are still under continuous improvement.
However, for a new alloy system, some parameters of the model [8] need to be optimised by comparison with experimental softening data.
As strain rate and temperature may vary along the strip length and in the cooling coil, detailed process input data is required, preferably from FEM models.
Then, using the resulting tandem mill data, the different dislocation density evolutions during hot rolling were simulated with 3IVM (coupled to the GIA deformation texture model) available on SimWeb.
This reduction in particle size increases both the yield stress and the work hardening - and hence steady state flow stress - by about 10%.

This has enabled significant reduction in the cost and time for design and development, and has helped to improve the quality and performance of parts.
It is a non-linear optimization process that uses experimental data (affected by uncontrolled variability) to determine the parameters describing some constitutive simulation model of a material.
An ANOVA (Analysis of Variance) has been conducted on the available material data, using the tensile tests' testing direction as a factor with three levels (0, 45 and 90°) and x as the vector of response variables.
No experimental data is available for the three friction coefficients (x9 x10 x11).
Initial blank diameter 635 mm, initial axial hole diameter 120 mm, initial sheet thickness: 0.81 mm; Young's modulus: 211 GPa; Poisson's coefficient: 0.284; isotropic behaviour; hardening law: σ=2457(0.005+ε) n MPa (data provided by the company).

This new pass sequence is shown in Figure 7 using actual mill data.
T, ºC e, % T1, ms t2, sec F1 1029 40 130 F2 1005 27 60 5.5 F3 978 25 40 4.3 F4 957 23 30 2.8 F5 936 18 20 2.8 F6 915 13 10 2.4 e = Reduction, t1 = Contact Time, t2 = Interpass Time Fig. 6 Rolling data versus pass no. for standard NSB six pass schedule.
As the pass strain increases, more of the poorly oriented grains will show a sufficiently high enough dislocation density that they will exhibit nucleation and recrystallization, grain refinement and subsequent uniform final microstructure. 0.06C-1.5Mn-0.35Si-0.04V-0.025Nb-0.025Ti-0.0045B0.0075N, Final Thickness: 3.25 mm 0 10 20 30 40 50 F1 1092 F2 992 F3 966 F4 939 F5 914 F6 892 Finishing Pass Number and Entry Temperature, °C Relative Units Material Flow Stress Roll Force Rolling Torque Fig. 7 T - ε pass sequence data Kozasu, et al., studied the recrystallization of coarse grained austenite in the early 1970s [12] and showed that recrystallization of coarse grained austenite can occur only with very large reductions, of the magnitude found when stands F3 and F4 are dummied (as shown in Figure 7).
Chirpy V-notch impact data for 12.7mm (0.50 in.) thick X42 and X52 linepipe skelp produced at NUCOR Steel-Berkeley's CSP Plant, Charleston, SC.

As the experimental data shows, to assure efficient operation of the furnace, this parameter should be kept at the maximum level of 60-70 [m3/m2·min] [9].
Comparison of this data reveals that it is possible to improve cupola performance through increase in specific consumption.
Analysis of this data demonstrates that the cupola cross-section is characterized by strongly pronounced nonuniformity of both temperature and velocity fields.
The analysis demonstrated that melting of the cupola mixture in the shaft furnace occurs under different oxidation-reduction conditions.
This leads to the development of reduction reactions in the bed and formation of a metallic phase in the melt.

These data were used to compute the actual density of the samples.
The compression rate was 1mm/min, and the data were collected at 0.01s interval.
The tensile testing rate was 1mm/min, and the data were collected at 0.1s interval.
The cell viability data were shown as mean ± standard error of the mean, and all indirect cytotoxicity tests were conducted with at least 4 biological replicates (n=4).
Such deviations can cause a substantial reduction in the mechanical properties of the actual printed sample and affect the osseointegration of the implant [12].

The electron combines with H+ ion resulting in H2 evolution reduction reaction.
Table 1 Data on corrosion rate of MS from 1M H2SO4/ACW (0% - 6%) solution   ACW Conc. (%) Exp.
Data on corrosion rate of MS from 1M H2SO4/SJA (0% - 6%) solution SJA Conc. (%) Exp.
The data for JLD shows otherwise making the statistical relevance factor for concentration relevant.
Data Collect. 20 (2019) 100214

Replaying The attacker intercepts and captures data, re-transmits data, and thus obtains permission or swindles a reply.
However, data inside a network were not encrypted.
Message authentication code (MAC) is generated by forming new data blocks via the keys from the messages to be authenticated, and then by encrypting the data blocks.
Depending on the user's and data security levels, it decides whether a user has the authority to access to these data.
Check whether the data from the redundant nodes are consistent.

Based on experimental data, the carbon footprint was performed using the Life Cycle Assessment (LCA) methodology.
Based on this kind of data is possible to evaluate the prospect of developing carbon footprint curves.
Life cycle inventory (LCI) For the Life Cycle Inventory (LCI), primary data is collected from the laboratory, while for secondary data, the Ecoinvent v. 3.6 and scientific literature are used.
The electricity consumption of original Ecoinvent data is adapted to the Brazilian energy mix and market transports.
For the Portland cement, there is already available data in Ecoinvent v.3.6, for all these countries.

Caption for Tables Table 1 Summary of data on various physical parameters of Li2O-Na2O-B2O3: Fe2O3 glasses.
Table 2 Summary of data on dielectric constant of Li2O-Na2O-B2O3: Fe2O3 glasses.
Table 3 Summary of data on dielectric loss of Li2O- Na2O-B2O3:Fe2O3 glasses.
Table 4 Summary of data on a.c. conductivity of Li2O-Na2O-B2O3:Fe2O3 glasses.
Table 1 Summary of data on various physical parameters of Li2O-Na2O-B2O3: Fe2O3 glasses.