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The ability to avoid safely a collision with previously unknown obstacles depends on many factors, first of all on flying object’s manoeuvrability, allocation of obstacles, their sizes, parameters of motion, object  to  obstacle distance in the moment of detection and accuracy of data characterising the obstacle.
This structure covers necessary data sources and units for storing pre  prepared data and executing the most relevant mathematical and logical operations.
Detection and identification of the previously unknown obstacle by the radar detector of obstacles (RDP), as well as the information from data base of obstacles are the necessary data for choosing a safe manoeuvre.
Reduction of turning radius by increasing the roll angle causes the lost of altitude and reduction of longitudinal component of velocity vector.

Also the results of simulation have been compared with the experimental data.
The experimental data are obtained using a Keithley 2361 parameter analyzer by measuring the anode current with respect to the gate/cathode and anode/cathode voltages.
Referred to the experimental data of Fig. 7 (right) at low anode voltages only the gate voltage causes an emission of electrons form the CNT tip.
Right: Experimental data for the effect of gate voltage on the emission current.
Based on the data obtained from the simulation results the best performance is obtained if the distance between nanotubes is set to be the same as the length of nanotubes.

In this study, the three kinetic models namely, the pseudo-first order equation, the pseudo second order equation and the Elovich equation will be used to test experimental data (Table 1).
A decrease in pH probably results in a reduction of the negative charges at the surface of adsorbents [7].
The kinetics of the adsorption data were analyzed using the pseudo-first order, pseudo-second order and Elovich models (Table 1).
Furthermore, the experimental values (qe) do not agree with the calculated ones, which indicate that the pseudo-first-order equation cannot provide an accurate fit of the experimental data.
Even though these results are good, but a comparison with the Elovich model shows that the latter gives a better fit between experimental and calculated data.

Within the data it is possible to recognize two groups of samples: those submitted to the ageing treatments, characterized by high strength and high ductility, and the slowly cooled and annealed specimens, with lower strength.
(ii) Microstructure Figure 5 shows the microstructure of samples 1X and 4X, each heat treated at 170 and 100 oC, and Table III summarizes data on grain size and precipitate apparent length.
Consequently, although they are clearly non-shearable, their low intragranular volume fraction is insufficient for dislocation accumulation, hence the low WH rate showed by the present experimental data.
Double arrows identify the correlations confirmed by the present data.
Conclusions (i) Experimental data shows that ECAP-deformation accelerates the precipitation kinetics of the Al2Cu phase in Al-4%Cu.

The wood bio-concrete (WBC) production is a solution for the advancement of sustainable construction, since it has the potential to recycle waste in the form of shavings generated in wood processing and stock CO2, contributing for climate change reduction.
The environmental modeling was performed by SimaPro, using the Ecoinvent database, and primary data collected in the laboratory.
Fig. 1: System boundaries of the WBC production 2.3 Life cycle inventory analysis Portland Cement CPV-ARI data were obtained from Ecoinvent 3.6, which already has data for the Brazilian context, including the type of cement studied.

Rezaie et al. [10] investigated the possibility of applying topology optimisation methods on fused deposition modelling (FDM) fabricated parts by adopting the weight reduction approach and a successful implementation of the optimisation output files serving as FDM input data was achieved without the strength of the part compromised.
Figure 2 The black cuboid, FDM-PLA fabricated samples Output characteristics and data analysis.
The main effects of the infill density, extrusion temperature and layer thickness were investigated on each of the output characteristics using the S/N ratio data in Table 4.
In order to obtained the unified parameter setting, deviation of the normalised S/N ratios are computed from the normalised S/N data in Table 4 using equation (4).
However, in order to scientifically obtain the weighting factor for each of the output characteristics, the grey relational coefficient data in Table 5 was subjected to principal component analysis (PCA).

Thus an economic production is achieved to reduce the necessary numbers of production steps which often leads to a reduction of capital investment for dies and machinery[4], production costs and the technological risk is reduced as well.
Figure1 Examples of buckling, wrinkling and bursting Software Architecture Tube Hydroforming Analysis Wizard is composed of four parts as below(shown as Figure 2): (1) Database construction Build hydroforming design data, process data and experience data etc. into database

(6) Using the DTA curve data, according to Eq. (6) the reaction progression n can be obtained.
The mensuration condition that rise temperature velocity was 10°C·min-1 and reduction reaction gas is N2 gas.
Fig.2 TG-DTA-DTG curvers of nano-Cr(OH)3 power The DTA-TG-DTG curves data and Eq. (2) allow the calculation for apparent activation energy E and pre-exponential factor A of nano-Cr(OH)3 power.
-E/R E(J·mol-1) LnA A n Cr(OH)3 -30554.166 254.027 84.012 3.062×1036 1.560 Based on all above data, the kinetics decomposition equation of nano-Ni(OH)2 power was: Conclusions The conclusions were as followed: (1) In process of nano-Cr(OH)3powders decomposition, the apparent activation energy of nano-Cr(OH)3is 254.027 kJ·mol-1, the frequency gene is3.062×1036 (2) The reaction progression was as1.560obtained by Kissinger peak sharp factor

The international standard ISO 5807: 1985 "Information processing - Documentation symbols and conventions for data, program and system flow charts" has been used to compile block diagrams of calculation algorithms.
According to the set of rules, the next step is to determine the coefficient of reduction of the load-carrying capacity χd, as in Fig. 2 (a), by which the thickness of the second part of the shelf and the overhang of the shelf is determined.
Zozus The Data Book: Collection and Management of Research Data, by Taylor & Francis Group, LLC, Boca Raton, 2017.

Engineering data models are integrated from all kinds of building information in BIM, providing much coordinating and operational information for architectural design and construction where BIM is an innovation [1,2].
The data base, made up of the computer three-dimensional model, is the core technology of steel structure BIM, and actual structural elements of steel structure are digitally created by visualization methods.
It is better to unify the management of the whole resources and quality to increase efficiency and cost reduction.
It is BIM, one data base rich in engineering information[5], that can solve this problem.