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Introduction Nowadays, in the automotive field the adoption of FE modelling has led to a reduction in time and costs necessary for vehicle design; a full-vehicle FE model usually counts millions of elements, more than one thousand components and hundreds of different properties and card materials.
A maximum deviation (e) of 14% from the experimental data was found at ε/ εmax= 0.83 for the panel 2.5 mm thick subjected to 4-points bending.
This component influences marginally the acceleration peak (ca. 10 per cent, referring to the experimental data), the deceleration peak depends mainly on the stiffness of the metal roof.
As shown in Fig. 6, the components involved into the crash event increase significantly, affecting the acceleration peak value and the HICd index data as previously discussed.

Sample A was symmetrically cold rolled providing a reduction in thickness of 53.35 % (Sample B) by laboratory rolling machine consisting of a roll diameter of 150 mm.
To record the data and operation of this instrument, software coded in MATLAB was used.
The EBSD patterns were captured with an acquisition speed of ⁓20 fpc and during Orientation Imaging Microscopy (OIM) data were recorded with an accelerating voltage of about ⁓17–19 kV.
To post-process the OIM data, the commercial OIM-TSL-8® software was used.

In automotive components, weight reduction is one of the major goals of engineering design and manufacturing section in any automotive industry, so that materials, energy, costs are saved and environmental damage is reduced by reducing the overall weight of the machine.
Comley [4] reported that the determination of superplastic properties of a material, just like any material property was highly dependent on the test method, coupon geometry and analysis from the raw data from the test.
The load –displacement data for every tensile test were monitored continuously by a personal computer equipped with a data acquisition system.

However, the global financial and economic crisis and the decline in production and business activity that took place against it in 2008-2009 led to a decline in the level of development of construction industry and a reduction in amount of housing to be introduced (Table 1).
Housing construction in the largest cities of Russia 2000-2015 Cities Construction of residential buildings, thousand [sq. m of total area] Average annual growth rate for the period 2000-2015 [%] 2000 2005 2010 2015 On average, annually for period 2000-2015 Volgograd 232.5 318.6 325.6 475.1 335.6 8.0 Rostov-on-Don 390.3 605.4 850 1111.1 758.8 8.2 Ufa 243.2 469.9 654.6 824.9 580.1 7.8 Kazan 541.8 632.0 771.8 762.0 753.0 3.3 Perm 160.2 384.8 364.2 565.5 369.4 8.4 Nizhny Novgorod 251.2 361.7 363.1 442.4 428.1 10.0 Samara 262.3 342.5 589.1 831.5 537.4 14.7 Ekaterinburg 295.7 643.1 1026.8 1196.9 763.2 11.0 Chelyabinsk 330.7 440.9 486.9 571.3 573.0 7.2 Novosibirsk 342.3 507.7 1017.1 1735.6 831.6 17.9 Omsk 170.1 595.2 350.2 576.5 453.6 16.3 Calculated by the authors and compiled from the data of [10, 11] The building of new neighborhoods and residential areas in the cities essentially supports the construction industry and in future can strengthen the trend of growth in the volumes of annually
Average annual input of housing per capita in the cities of Russia, 2002-2015, sq. m Compiled according to the data of [10, 11] The integral indicator characterizing the provision of housing for population is the size of area in living quarters that are on average per urban inhabitant (Figure 2).
Total area of living quarters accounting for one urban inhabitant on average for 2002-2015 (at the end of the year), sq. m Compiled according to the data of [9, 10] The priorities of this program are: - stimulating housing construction, increasing the annual volume of new housing by building new residential areas, developing built-up areas; - provision of comfortable housing to privileged categories of the population; - introduction of modern rational and energy-efficient technologies in housing construction and operation of housing; - development and improvement of engineering infrastructure; - ensuring the sustainable operation of utility networks; - improving the reliability and quality of housing and communal services

On the one hand, the chemical bonding and mechanical joining in interface decline at elevated Vf, and this results in a reduction in interface strength, namely decreasing the ILSS.
Table 3 provides the burst test data with PBO/epoxy listed for reference purposes.
Based on limited data available, it is apparent that the PBO/epoxy vessel offers higher PV/Wc values and best-delivered strength performance than that of F-12/epoxy composites.
Fig.3 The effects of Vf in composites on the ILSS Fig.4 ILSS and tensile strength of unidirectional and tensile strength composites versus winding tension Table 3 Comparison of Φ150mm vessels burst test data SN01 SN02 F-12/epoxy (n=5 bottles) Burst pressure [MPa] 34.5 35.0 / Vessel performance factor, PV/Wc [km] 57.7 60.4 38-41 Translation of delivered hoop strength [%] 89.3 91.5 >71 Failure section Hoop mode Hoop mode Hoop mode Summary (1) It is suitable that the preheating temperature of mandrel of fiber winding is taken by 60-70°C and the penetration temperature of resin as 45°C

The connection of COMSOL data and MATLAB toolboxes enabled the realization of changes in the coils dimensions.
In order to enhance the graph legibility, data representing the same number of coil layers were joined into lines (Θ functions).
Results According to the observations mentioned previously, gathered data were investigated.
The comparison of Figs 6 and 7 clearly reveals the inductance reduction.

Introduction According to the data from the China association of automobile manufacturers, the scale of new energy vehicles in China was 17600, and rose 37.9% year-on-year, including 14604 electric vehicles in 2013[1].With the popularity of EVs(electric vehicles), large-scale electric vehicles charging will trigger the growth of the burden on the grid.
The 6th national population census data show that the total number of population in Guilin City is 49,884 million, so the number of private cars can be estimated as 124,700.
Department of Transportation of domestic family car driving data show that the daily mileage can approximate lognormal distribution using the maximum likelihood estimation[4].Its probability density function can be described as equation(4)
“Use of National surveys for estimating ‘Full’ PHEV potential for Oil Use Reduction”.

This modelling method presents an easy and uniform way to prepare appropriate data for computer DTFM algorithm.
The Jeffcott model (Fig. 2) parameters are equal: I=0.03 [kgm2], I1=I4=0.02488 [kgm2], I5=0.5 [kgm2], I2=I3=5.981 [kgm2], C=C4=3141.59 [Nm/rad], C1=C3=154625.263 [N/m], C2=2·108 [N/m], TF=TF1=Dg/2=0.1 and they have been calculated for the following data: E=2.1·1011 [MPa], G=8·1010 [MPa], l=0.8 m, dg=dp=0.02 [m], Dg=Dp=0.2 [m], h=0.02 [m].
These were prepared for the same data as above.
References [1] Orlikowski C., Hein R.: Modal reduction and analysis of gyroscopic systems.

An evident solution is the reduction of thickness, which is usually achieved by polymer pre-stretching.
Computer Function Generator Data Acquisition LVDT Voltage Amplifier 50mm 10mm Computer Function Generator Data Acquisition LVDT Voltage Amplifier 50mm 10mm Electro-mechanical Experimental Set-up.
The synchronized vertical displacements of the actuator (measured by a linear variable differential transformer, LVDT), together with the electrical input data were acquired and analyzed in a computer.

After annealing at 970K for 1 hour, the X-ray diffraction data indicated the formation of Ti5Si3 alongside with NiSi and Ni3Ti (see Fig. 2a).
From data of X-ray diffraction, we found that the annealing at 870K for 8 hours did not cause essential changes of their phase structure.
Results of resistivity measurement have confirmed the phase changes discussed in the above (Fig. 3). 0 2 4 6 8 10 12 14 16 18 20 270K 670K,1h 870K,1h 1070K,1h 1070K,2h 1270K,1h Annealing Specific resistance, µµµµΩΩΩΩ-cm Fig. 3 Change of electrical resistivity of 200 nm Ti/200 nm Ni/(001)Si after annealing After annealing at 870K the samples showed a sharp reduction of electrical resistance, which can be explained by the formation of NiSi.
These data testify that the thermal stability of NiSi phase formed in the ternary system of Ti/Ni/Si as studied here, is better than the NiSi formed in the binary system of Ni/Si.