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This approach was then validated against numerical method and experimental data available in literatures, proving its effectiveness and reliability.
In phase 2 (linear softening phase), similarly: s2x2=eβx2C1sinαx2+C2cosαx2-1-K1KK1τmax (0≤x2≤L) (20) Only in this case, β=12(1-K1K)tanϕR (21) Validation Validation against experimental data.
This can be attributed to the simplifications in the mathematical model that could lead to a reduction in the ductility of the strengthened system, such as the omission of interlocking effect provided by the mortar joints, the damage diffusion in the substrate, and for intrados case, the interface residual friction.
The obtained results are validated against experimental data and numerical approach proposed by the authors before, showing a good performance in predicting the trend and peak of load-slip curves, as well confirming some experimental observations.

This is why data feedback from current and previous projects in this field is vital.
Data feedback can help in further developing these devices in order to meet specific requirements, on long-and short-term basis.
Hybrid Systems.To build a hybrid system, as in the case of any type of DG energy system, information and data will be required.
This kind of design will achieve the optimum in the usage of energy and reduction in total cost.
Remote viewing via satellite with continuous data and information feeding/upgrading is one of the best ways to speed up present and future development in this field.

Both pressure contours show that the static pressure profiles from CFD simulations are in reasonable agreement with available experimental data and are like those presented in the literature [1].
The results from the simulations presented in Figs. 9 (a and b) and 10 (a and b) are representative of the level of agreement achieved in the other operating conditions where corresponding experimental data were available for comparison.
Both contours agree with the experimental data in the literature [1].
The velocity XY plots, Figs. 11(a) and 12(b), illustrate the trend in velocity reduction through the nozzle length.
Data Availability Statement The authors affirm that the data that supports the results of the current investigation is present in this article.

In recent years, fatigue properties and fatigue strength design have been approached from a multidimensional perspective using data science and artificial intelligence (AI) technology [5,6].
The accumulation of extensive data is necessary for the application of data science and AI in fatigue strength design.
Applications of data-driven approaches in prediction of fatigue and fracture.
Notches, nominal stresses, fatigue strength reduction factors and constant/ variable amplitude multiaxial fatigue loading.
Estimating the Median Fatigue Limit for Very Small Up-and-Down Quantal Response Tests and for Data with Runouts.

Qualitative research was undertaken with a literature study as the primary source of data collection by using accredited articles, journals and case studies to answer the research and sub-research questions.
The secondary method of data collection consisted of interviewing an expert in this field, as well as an accredited green star building professional in South Africa, knowledgeable in construction (names withheld).
The pie chart in figure 1 below indicates the prominence of each theme throughout the data.
Scope of Nanotechnology: The pie chart in figure 1 above indicates that the scope of the various uses of nanoparticles accounts for the most significant theme which emerged from the data.
Had Covid-19 not impacted the world the way it did, the data collection would have consisted of more in depth interviews with experts in the field.

The physical process included size reduction and calcination process which aimed to evaporate the water trapped in the zeolite pores.
The Fe-zeolite diffraction pattern was compared to the data from this software.
Diffraction pattern of Fe-Zeolite In addition to data interpretation using software, the diffraction pattern of Fe-zeolite was also compared with JCPDS data (Joint Committee on Powder Diffraction Standard).
In Table 3, Fe-zeolite was compared with existing JCPDS data from some references.
In the isomerization temperature of 40℃ and 60℃, the increase of acidity environment caused the reduction of fructose yield level.

A non-volatile memory is a solid-state device that can retain data even when power supply is terminated.
It is an essential data storage device that serves as a backbone for the advancement of Internet-of-Things.
Introduction As modern civilization reaches the big data revolution, huge data retention and energy-efficient information processing devices are in high demand.
ROMs are nonvolatile, which means that the stored data retains even if the power is switched off.
Lee, Flexible Multistate Data Storage Devices Fabricated Using Natural Lignin at Room Temperature, ACS Appl.

Validation data comparing results from conventional strain gauge data and FE models is also presented.
Residual Stress Data Analysis The DIC analysis was carried out using the LaVision Strainmaster software [20].
The displacement data was then converted into polar coordinates, and the x, y and radial components calculated.
There is reasonable agreement between the DIC and strain gauge data, but rather surprisingly the strain gauge data shows differences between the profiles measured in the two principal stress directions.
[15] Steinzig, M., Hayman, G. and Rangaswamy, P., Data Reduction Methods for Digital Holographic Residual Stress Measurement, Proc. 2001 SEM Conf.

AM refers to a group of technologies that build physical objects directly from 3D Computer-Aided Design (CAD) data.
After the brief introduction of each technique, the published data was presented and discussed.
A Pie chart (Fig. 19) is used to show NP % usage in to AM based on the data collected for the present study.
Comparative chart for AM processes employing nanocomposites based on the data used in this study.
The studies conducted in the past can be used as preliminary data to print parts that can benefit society.

Data analysis.
Statistical analysis of the data was performed using analysis of variance and mean values were compared by the least significant difference (LSD) at the 5% level using the Version 16.0 of the SPSS software package.
The data from all graphs were expressed as the arithmetic mean (n=3) with standard error.
Nitrate reduction of no fertilization treatment CK and low amount of organic fertilizer treatment M1and M2 was extremely significant (P<0.01), high amount of organic fertilizer treatment (M3 and M4) also decreased by 53%~75%.