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Online since: November 2020
Authors: Alexey Yu. Trifonov, Radoslaw Ciesielski, Evgeny Kitsyuk, Dmitry Gromov, Andrey Savitskiy, Sergei Dubkov, Roman Ryazanov, Viktor Shatila, Alexey Shkal, Oleksandr Shtyka
Photocatalytic Reduction of CO2 over Metal/BaTiO3 Catalysts
Sergey Dubkov1,a, Andrey Savitskiy1,2,b*, Roman Ryazanov2, Viktor Shatila3, Alexey Trifonov1,4, Alexey Shkal1, Evgeny Kitsyuk2, Oleksandr Shtyka3, Radoslaw Ciesielski3 and Dmitry Gromov1
1National Research University of Electronic Technology, Bld. 1, Shokin Square, Zelenograd, Moscow 124498, Russia
2Scientific-Manufacturing Complex "Technological Centre", 1, Bld. 7, Shokin Square, Zelenograd, Moscow 124498, Russia
3Institute of General and Ecological Chemistry, Lodz University of Technology, Zeromskiego 116, Lodz 90-924, Poland
4F.V.
Data was collected in the 2θ range of 5°– 90° with a step size of 0.0167° and exposure per step of 27 sec.
Because the raw diffraction data contain some noise, the background during the analysis was subtracted using the Sonneveld and Visser algorithm.
The data were then smoothed using a cubic polynomial function.
The activity of the catalyst was estimated by the number of produced products of the CO2 reduction reaction (mainly methanol CH3OH) per unit mass of catalyst per unit time recorded by a flame ionization detector of a gas chromatograph.
Data was collected in the 2θ range of 5°– 90° with a step size of 0.0167° and exposure per step of 27 sec.
Because the raw diffraction data contain some noise, the background during the analysis was subtracted using the Sonneveld and Visser algorithm.
The data were then smoothed using a cubic polynomial function.
The activity of the catalyst was estimated by the number of produced products of the CO2 reduction reaction (mainly methanol CH3OH) per unit mass of catalyst per unit time recorded by a flame ionization detector of a gas chromatograph.
Online since: February 2014
Authors: Wilson B. Musinguzi, Mackay A.E. Okure, Adam Sebbit, Terese Løvås, Izael da Silva
Preliminary validation of the model results using experimental data from literature shows a close relationship.
The characteristic properties form part of the data necessary for modeling the steam gasification phenomena.
Component Composition Mol flow/mol of dry wood Mole (%)/mol of dry producer gas Experimental yield* Mole (%)/mol of producer gas H2 CO CH4 CO2 1.0935 52.23 48.88 0.3645 17.41 22.7 0.1980 9.46 6.22 0.4375 20.90 22.2 H2O 0.4335 *Data taken from Karmakar and Datta [18] The comparison of the model results with experimental data shows comparable gas composition.
The producer gas composition obtained in this study is similar to the literature data published on downdraft gasifiers.
Sharma: Equilibrium modeling of global reduction reactions for a downdraft (biomass) gasifier, Energy Conversion and Management Vol. 49 (2008), p. 832 – 842
The characteristic properties form part of the data necessary for modeling the steam gasification phenomena.
Component Composition Mol flow/mol of dry wood Mole (%)/mol of dry producer gas Experimental yield* Mole (%)/mol of producer gas H2 CO CH4 CO2 1.0935 52.23 48.88 0.3645 17.41 22.7 0.1980 9.46 6.22 0.4375 20.90 22.2 H2O 0.4335 *Data taken from Karmakar and Datta [18] The comparison of the model results with experimental data shows comparable gas composition.
The producer gas composition obtained in this study is similar to the literature data published on downdraft gasifiers.
Sharma: Equilibrium modeling of global reduction reactions for a downdraft (biomass) gasifier, Energy Conversion and Management Vol. 49 (2008), p. 832 – 842
Online since: November 2011
Authors: M.O. Abiodun, Dare Aderibigbe Adetan, Kolawole Adesola Oladejo
The reduction in frictional force brought about by lubrication leads to decrease in cutting force and ultimately reduction in manufacturing cost [5]
Cutting fluids have been used to deal with the problem of high heat generation and reduction of frictional force during machining operations.
Thus, 36 data points were taken for the four experimental fluids.
The experimental run for each data point was done twice and the mean of the resulting two values of each of the measured variables (cutting zone temperature and power consumed in cutting) was obtained.
Incidentally, all the four cutting fluids used in this study gave their lowest cutting zone temperatures and power consumptions at the same data point of 34 m/min cutting speed, 1.0 mm depth of cut, 0.08 mm/rev feed rate and 200 ml/min fluid flow rate.
At the best machining data point, maize-starch based cutting fluid showed reduced cutting zone temperatures and power consumed during cutting compared to the conventional cutting fluids used for the study.
Thus, 36 data points were taken for the four experimental fluids.
The experimental run for each data point was done twice and the mean of the resulting two values of each of the measured variables (cutting zone temperature and power consumed in cutting) was obtained.
Incidentally, all the four cutting fluids used in this study gave their lowest cutting zone temperatures and power consumptions at the same data point of 34 m/min cutting speed, 1.0 mm depth of cut, 0.08 mm/rev feed rate and 200 ml/min fluid flow rate.
At the best machining data point, maize-starch based cutting fluid showed reduced cutting zone temperatures and power consumed during cutting compared to the conventional cutting fluids used for the study.
Online since: September 2005
Authors: Stefan Zaefferer, Dorothée Dorner, Ludger Lahn
A silicon steel single crystal with initial Goss orientation, i.e. the {110}<001>
orientation, was cold rolled up to 89 % thickness reduction.
In 14 passes the sheet was rolled to a thickness of 0.25 mm corresponding to a total engineering thickness reduction of ε = 89 % (true logarithmic strain of ϕ = 2.2).
The strongest components are the two {111}<112> orientations (Fig. 2a), but the data also show that a weak Goss component is still present after 89 % thickness reduction (Fig. 2b).
Shear bands formed in cold rolled samples with thickness reductions of 77 % and higher [4,5].
(1) The texture after cold rolling up to 89 % thickness reduction is characterised by two strong symmetrically equivalent {111}<112> components.
In 14 passes the sheet was rolled to a thickness of 0.25 mm corresponding to a total engineering thickness reduction of ε = 89 % (true logarithmic strain of ϕ = 2.2).
The strongest components are the two {111}<112> orientations (Fig. 2a), but the data also show that a weak Goss component is still present after 89 % thickness reduction (Fig. 2b).
Shear bands formed in cold rolled samples with thickness reductions of 77 % and higher [4,5].
(1) The texture after cold rolling up to 89 % thickness reduction is characterised by two strong symmetrically equivalent {111}<112> components.
Online since: October 2004
Authors: Sergei Ya. Betsofen, A.L. Lapin
Comparison of the data for
superlattice and lattice reflections allows one to estimate the influence of ordering on
recrystallization (Fig 1.e and i).
In Al and АМg6 surface layers have shear components only at small deformations, since the 30% thickness reduction a sheet texture are practically homogeneous on thickness.
In 1420 alloy the surface layers have the shear texture components up to 70 % reduction.
These distinctions take place in the as-received sheet, however with increasing of rolling reduction the difference in lattice distances is increased (Table 1).
The time of each stage is reduced with increasing reduction in thickness and temperature.
In Al and АМg6 surface layers have shear components only at small deformations, since the 30% thickness reduction a sheet texture are practically homogeneous on thickness.
In 1420 alloy the surface layers have the shear texture components up to 70 % reduction.
These distinctions take place in the as-received sheet, however with increasing of rolling reduction the difference in lattice distances is increased (Table 1).
The time of each stage is reduced with increasing reduction in thickness and temperature.
Online since: September 2013
Authors: Zhi Guo He, Ze Min Liu, Yu Dong Cao
ICA
The ICA [10] model can be described as:
(1)
The model describes how the observed data X can be obtained by mixing the signal source S.
All the data can be observed is only the random variable X, so it is necessary to estimate the mixing matrix A and the source S.
As an extension of PCA, ICA focuses on the higher-order statistical characteristics between data, and each of the transformed components is not only unrelated, but also as statistically independent as possible.
Therefore, ICA can be more fully reveal the essential characteristics of the input data.
Bartlett: Face Image Analysis by Unsupervised Learning and Redundancy Reduction.
All the data can be observed is only the random variable X, so it is necessary to estimate the mixing matrix A and the source S.
As an extension of PCA, ICA focuses on the higher-order statistical characteristics between data, and each of the transformed components is not only unrelated, but also as statistically independent as possible.
Therefore, ICA can be more fully reveal the essential characteristics of the input data.
Bartlett: Face Image Analysis by Unsupervised Learning and Redundancy Reduction.
Online since: March 2010
Authors: Chih Hsiung Shen, Jun Qi Wang, Shu Jung Chen
The offset reduction with CDS technique
enhances the sensitivity of winner-take-all (WTA) circuit and shows a sharp selectivity which makes
it possible to pick up only one winner pixel from each thermal object.
In particular, detection of important features reduces a large amount of image data and hence facilitates higher level processing tasks carried out on a host computer.
Architecture of Thermopile Array with WTA The offset reduction of our proposed design is based on an addition of CDS circuit which improves the comparison capability of WTA circuit and resolve more little temperature difference.
One is the previous research work without CDS noted as APS+WTA and the other is offset reduction with CDS noted as APS+CDS +WTA.
In particular, detection of important features reduces a large amount of image data and hence facilitates higher level processing tasks carried out on a host computer.
Architecture of Thermopile Array with WTA The offset reduction of our proposed design is based on an addition of CDS circuit which improves the comparison capability of WTA circuit and resolve more little temperature difference.
One is the previous research work without CDS noted as APS+WTA and the other is offset reduction with CDS noted as APS+CDS +WTA.
Online since: December 2012
Authors: Xin Hui Wang, Bi Guang Hong, Lin Jia Yang, Lei Rong
Finally, the effective braking force for full scale tugboats was predicted by using the experiment data and the assumptions mentioned above.
Influence of Ship-Tugboat Interaction Reduction of the braking force, The influence of ship-tugboat distance on the total hull resistance is shown in Fig.1.
Although the type of propellers is imperfectly the same, we try to use these data for estimating the influence of scale effect on the braking force of tugboat-self Fb by the following: , where, the Tb is the bollard pull of the tugboat. α is the correction factor on the base of the results of the Fig.4.
In accordance with the measured and analyzed results, the main conclusions are enumerated as the follows: The braking force of tugboats was influenced by ship-tugboat hydrodynamic interaction, even if full scale tugboat; The reduction of the effective braking force for full scale tugboat was about 10% of the capability of tugboat-self in normal ship-tugboat distance; The reduction inclination of the effective braking force slightly differed in both braking methods.
Influence of Ship-Tugboat Interaction Reduction of the braking force, The influence of ship-tugboat distance on the total hull resistance is shown in Fig.1.
Although the type of propellers is imperfectly the same, we try to use these data for estimating the influence of scale effect on the braking force of tugboat-self Fb by the following: , where, the Tb is the bollard pull of the tugboat. α is the correction factor on the base of the results of the Fig.4.
In accordance with the measured and analyzed results, the main conclusions are enumerated as the follows: The braking force of tugboats was influenced by ship-tugboat hydrodynamic interaction, even if full scale tugboat; The reduction of the effective braking force for full scale tugboat was about 10% of the capability of tugboat-self in normal ship-tugboat distance; The reduction inclination of the effective braking force slightly differed in both braking methods.
Online since: November 2012
Authors: Li Zhang, Shuo Zhang, Yuan Yuan Zhang, Yan Miao Ma
The paper provides a scientific reference for the further study on vibration and noise reduction in food refrigeration compressors.
Given the above situation, a comparative analysis of the vibration characteristics based on the harmonic response analysis theory was carried out in this paper, which provides a scientific reference for the further study on vibration and noise reduction in food refrigeration unit.
The collection of the compressor’s key points is established, and the concerned output data, including the field variables (cloud) and the historical variables (curve), are set in the Sinusoidal vibration analysis step.
Data Analysis Acceleration curve analysis of each measured point under the sinusoidal excitation.The acceleration spectrums of each measured point in the X, Y and Z direction under the sinusoidal excitation are shown in Fig.3, Fig.4 and Fig.5.
Given the above situation, a comparative analysis of the vibration characteristics based on the harmonic response analysis theory was carried out in this paper, which provides a scientific reference for the further study on vibration and noise reduction in food refrigeration unit.
The collection of the compressor’s key points is established, and the concerned output data, including the field variables (cloud) and the historical variables (curve), are set in the Sinusoidal vibration analysis step.
Data Analysis Acceleration curve analysis of each measured point under the sinusoidal excitation.The acceleration spectrums of each measured point in the X, Y and Z direction under the sinusoidal excitation are shown in Fig.3, Fig.4 and Fig.5.