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One of the more important tasks which are realized in the integration process of the design and technological production preparation functions is the translation task it is mapping of the design information into data which is important from the need of the process planning point of view – manufacturing data.
In this case the product description it is the input data for process planning functions is introduced by the user in the shape of the text file.
The input data for this process was the shaft solid model (see: the Fig. 2).
Dzitkowski, Passive reduction of system vibrations to the desired amplitude value, Journal of Vibroengineering. 15/3 (2013) 1254-1264

The temperature effects on the preparation and the coating tribological properties are investigated, and furthermore, the friction reduction and wear mitigation are analyzed and discussed.
Analysis and computation results for data of preheating temperature are listed in Tab. 1, wherein the values listed are averaged from triple tests.
Tab. 1 Preheating Temperature Data Factors Test No.
The symbols Ⅰ, Ⅱ, and Ⅲ represent the sum of the data of ‘1’, ‘2’, and ‘3’ in each line.
The superior combination A2B1is determined, based on the wear rate data.

Three-high skew rolling process allows a large reduction in the diameter of the rod rolled in one pass, while keeping high quality of the surface and roundness of the finished product.
Flow curves for aluminum 1050A on temperatures: a) 300 °C; b) 400 °C; c) 500 °C Based on the data presented in Figure 1, a high effect of strain rate, strain and temperature on the yield stress values was found.
From the data shown at Figure 3a, it can be found that the highest stress intensity magnitudes occur at the locations of bimetallic strip contact with the rolls and are equal to approx. 70 MPa.
Distribution of stress intensity during the 20 mm aluminum bar skew rolling The data in Figure 3b indicate that at the moment of roll bite the strip only contacts pointiest with each of the working rolls.
While analyzing the data presented in Figure 5, it can be seen that a strong increase in temperature occurs during the rolling.

The experimental data was carried out from spectroscopic ellipsometry measurement and processed using Drude-Lorentz model to get the optical properties.
For the analysis purpose, we present the optical properties of Cu doped ZnO such as n and k curve, Neff, and second derivative of dielectric function in 0.5-6.3 eV spectral range to see the effect of Cu Fig. 1 Y and D data measurements were taken by Spectroscopic Ellipsometry (SE).
To verify our measurement, Y and D data SE measurements were taken at several spot on the samples with multiple incident angles (55ᴼ, 70ᴼ, and 80ᴼ).
Then, the optical properties are obtained by fitting the experimental data SE measurement using Drude-Lorentz optical model following this equation
Shifting spectra Y and D by introducing Cu dopant are also shown in Fig. 1 that signifies reduction of bandgap (or the samples become more metallic).

Several factors which had a great effect on unit economy were investigated through comparing design conditions data with actual operating data, and then an energy saving method of ultra-supercritical unit operation was putted forward.
(4) Comparison between the Actual and the Design Conditions Three typical operation conditions were got from the vast running data of the power plant, which correspond to the 50%, 75% and 100% of the rated load respectively.
Another reason for efficiency reduction is the regulation method of reheat steam temperature makes it inaccurate.
Data comparison between designed and actual motion condition revealed the existence of inaccuracy in superheated steam, i.e., about 20℃~40℃ insufficient.

Introduction High speed cutting offers several advantages such as reduction of finishing operations, elimination of part distortion, achievement of high metal removal rates and lower machining costs as well as improved surface integrity which makes it outweigh conventional cutting speed.
In all simulation, based on the stabilization of cutting force and chip-tool contact length, the steady-state was achieved prior to gather data from the results.
The values from Merchant and Experiments are from [3], while other data is predicted by the three softwares.
It is worth mentioning that shear predicted through Merchant`s model are always the highest, followed by experimental data.
However, when Advantage is utilized, compared to experimental data, all errors are less than 6% and the trend that cutting force decreases slightly with cutting speeds can be both witnessed in experiment and Advantage prediction.

This reduction in stiffness can lead to increased tire damage during operation [7] and raises concerns about the durability and performance of the tires.
The model was rigorously validated against experimental data, including vertical stiffness and footprint testing.
This comparison demonstrated that the finite element model of the tractor tire was in good agreement with the experimental data.
The comparison results demonstrate good agreement between the finite element method (FEM) and experimental data, with an average error of less than 12.22%.
The FEM effectively captured the complex composite structure of the tires, with the simulation results demonstrating strong agreement with experimental data, as evidenced by the low average errors for vertical displacement (7.019%), vertical stiffness (6.609%), and contact coefficient (12.222%).

Additionally, they significantly contribute to the reduction of building energy demand for cooling during summertime, by improving both indoor air quality and thermal comfort conditions [3-5].
According to this study, such materials may be considered as common diffusive surfaces by introducing a reduction factor.
On the other hand, the use of phase change materials in reflective coatings leads to further reduction and delay of heat loads given their latent heat storage capability.
UNI EN ISO 13501 [55] classifies materials on a scale according to their fire reaction: from A1, which labels non combustible materials, to E and F, connotating poor behavior with fire or not available data.
(i) heating-cooling energy savings, (ii) global warming mitigation, and (iii) waste reduction, will be presented.

This paper takes high-tech transfer projects as a data source, considers the key words and new words extracted by NLPIR from the projects, and proposes a high-tech word similarity calculating method based on morphological similarity, word length similarity and individual character similarity.
High-tech transfer ontology takes the transferred high and new technical achievements as registered in NAST as data source, applies NLPIR new word identification function to identity high and new technical new words and phrases, and the integrate key words on scientific and technical achievements to shape high-tech lexicon.
The Paper takes high and new technology transfer projects as data source, and applies Regex to extract high-tech monitoring indicators.
Table 2　High-Tech Monitoring Indicators (Take Briquette Technology as Example) Economic Indicators Environmental Indicators Resources Indicators Low-load combustion stabilizing rated power N0x emission Total coal saving rate Annual output value SO2 emission Total Sulfur reduction rate Total investment Fume emission Thermal efficiency of boiler Equipment investment Fume blackness Boiler efficiency Major equipment life Strong carcinogen benzopyrene emission Carbon content of slag Operating expense Sulfur capture rate Annual coal consumption Power consumption 　 　 Annual output 　 　 Equipment fee of industrial briquette plant 　 　 Total area of factory building 　 　 Briquette price 　 　 Anthracite slime 　 　 Binder cost 　 　 Administrative fee 　 　 Payroll 　 　 Cost of production 　 　 Annual benefits 　 　 Number of employee Power fee Ontology Monitoring.
Fig.4 Monitoring Ontology Schematic (Take Pulverized Coal Boiler for example) Conclusion The paper takes the transferred high and new technical achievements as registered in NAST as data source, considers the keywords and NLPIR new words extracted from the projects, and constructs high-tech lexicon.

Eight thermocouples were connected with the casting and the time-temperature data were recorded automatically.
Experimental Procedure During the solidification process, temperatures at different positions in the casting were measured and the data were acquired automatically.
The temperature measurements were performed using a set of eight fine type K thermocouples previously calibrated, accurately located with respect to the metal-mold interface, connected by coaxial cables to a data acquisition system controlled by a computer.
The TR profile was calculated by considering the thermal data recorded immediately after the passing of the liquidus front by each thermocouple whose values are compared with theoretical predictions furnished by the numerical model [30] in Fig. 3b.
From this time until 50 s of the process, a gradual reduction of the hi values occurs.