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Online since: October 2006
Authors: Helena Pálková, Zoltán Lenčéš, Pavol Šajgalík, Miroslav Hnatko, Štefánia Lojanová
.% SiC composite after the carbothermal reduction process.
The reference SNY sample and the nanocomposites C2-0 (as hot-pressed) and C2-4 (HTT for 4 hours) have similar mean grain diameter distributions, however the scatter of data for SNY is wider.
The reference SNY sample and the nanocomposites C2-0 (as hot-pressed) and C2-4 (HTT for 4 hours) have similar mean grain diameter distributions, however the scatter of data for SNY is wider.
Online since: May 2004
Authors: R. Mendoza-Serna, R. Muñoz-Durán, J. Méndez-Vivar, E. Loyo-Arnaud, S.S. Martínez-Fuentes, L. Valdez-Castro
The intensity values, read at intervals ∆2θ = 1/8o from 2θ = 4
o
to 2θ = 70o , were the
input data for the Magini and Cabrini program [12].
The dramatic surface area reduction with calcining temperature and the further size growth of the pores are caused by organic residue oxidation and gradual elimination.
The dramatic surface area reduction with calcining temperature and the further size growth of the pores are caused by organic residue oxidation and gradual elimination.
Online since: September 2018
Authors: Chao Kai Wen, Guo Dong Xu, Yun Zhu, Dong Liu, Jing Chen
Form the table addition data, the content of sugar in the material is between 0.5‰ and 1.0‰.
Based on this criterion or datum, we adjust the ratio of water-cement and the dosage of compound-adjusting retarder to help regulate the setting time.
The data shows that the setting time can be controlled of gradient form, which ranged from 10 minutes to 40 minutes.
Additive Manufacturing (3D Printing) Material and Cost Reduction Algorithm Proof[C]// AIAA SPACE and Astronautics Forum and Exposition. 2017
Based on this criterion or datum, we adjust the ratio of water-cement and the dosage of compound-adjusting retarder to help regulate the setting time.
The data shows that the setting time can be controlled of gradient form, which ranged from 10 minutes to 40 minutes.
Additive Manufacturing (3D Printing) Material and Cost Reduction Algorithm Proof[C]// AIAA SPACE and Astronautics Forum and Exposition. 2017
Online since: January 2014
Authors: Clara Ceppa
Clothing and accessories are manufactured in view of a new mission that considers reduction of waste, a use of high-quality natural materials and improves the general job conditions.
John Thackara [5] said, reporting the statistical data of the Design Council in 2002, that “80% of the environmental impact of a product/service/infrastructure is determined at the planning phase”.
With regard to this aspect, each manufactured product has a label containing data about the actual hours of work used in the design and production phases as well as providing information about all the materials used.
It is desirable, therefore, that in the future new data related to the environment will be added on clothes labels: for example, it would be useful to know the real amount of pollutants that has been used to produce what we buy; or even, how much CO2 has been produced so that a particular product can be finally bought all over the world.
John Thackara [5] said, reporting the statistical data of the Design Council in 2002, that “80% of the environmental impact of a product/service/infrastructure is determined at the planning phase”.
With regard to this aspect, each manufactured product has a label containing data about the actual hours of work used in the design and production phases as well as providing information about all the materials used.
It is desirable, therefore, that in the future new data related to the environment will be added on clothes labels: for example, it would be useful to know the real amount of pollutants that has been used to produce what we buy; or even, how much CO2 has been produced so that a particular product can be finally bought all over the world.
Online since: October 2014
Authors: Saleh Mahdi Qasim, Sahar A. Fattah, Osama M. Jassim
The Nusselt number increases with increasing of Dean number and reduction in pitch of wire coil.
Based on the experimental data, correlations are proposed for Nusselt number and friction factor[6].The present work is focused experimentally on the performance of helical coiled tube heat exchanger with different types of coiled wire inserts placed separately in the tube with nanofluid.
Data deduction Heat transfer through helical coil (hot side) under steady state conditions can be computed from the following equations [7] (figure 1).
Fig.11 Nusselt number versus Dean Number for various volume concentration Fig. 12 Heat transfer coefficient versus Dean number for various volume concentration The following two correlations are developed depending on the present experimental data to predict the Nusselt number of the flow inside the coiled tube heat exchanger with wire coil insert [16].
Based on the experimental data, correlations are proposed for Nusselt number and friction factor[6].The present work is focused experimentally on the performance of helical coiled tube heat exchanger with different types of coiled wire inserts placed separately in the tube with nanofluid.
Data deduction Heat transfer through helical coil (hot side) under steady state conditions can be computed from the following equations [7] (figure 1).
Fig.11 Nusselt number versus Dean Number for various volume concentration Fig. 12 Heat transfer coefficient versus Dean number for various volume concentration The following two correlations are developed depending on the present experimental data to predict the Nusselt number of the flow inside the coiled tube heat exchanger with wire coil insert [16].
Online since: November 2015
Authors: T. Rajmohan, G. Subba Rao, A. Hemantha Kumar
Surface finish is an important parameter in terms of tolerances, it reduces assembly time and avoids the need for secondary operation, thus reduces operation time and leads to overall cost reduction.
The experimental results are used to develop mathematical model and linearized by performing Logarithmic transformations converting into a linear modeling using computational software, from the observed data for surface roughness, the response function has been determined using regression is, Ra = 2.99 + 0.0728 ln(S) + 0.894 ln(F) + 0.076 ln(DOC) (5) i.e Ra = 20.6913*Power(S,0.0728)*Power(F,0.894)*Power(DOC,0.076) (6) Result of ANOVA for the regression model is represented in Table 8.
The graph shows that the data closely follow the straight lines, denoting a normal distribution.
From the observed data for surface roughness, the response function has been determined using regression and fitness function, defined as Minimize Ra = 2.99 + 0.0728 ln(S) + 0.894 ln(F) + 0.076 ln(DOC) i.e Ra = 20.6913*Power(S,0.0728)*Power(F,0.894)*Power(DOC,0.076) (i) Speed min ≤ Speed ≤ Speed max 360 m/min ≤ Speed ≤ 580 m/min (ii) feed min ≤ feed ≤ feed max 0.05 mm/rev ≤ feed ≤ 0.09 mm/rev (iii) doc min ≤ doc ≤ doc max 0.05 mm ≤ doc ≤ 0.15 mm xil ≤ xi ≤ xiu where xil and xiu are the upper and lower bounds of process variables xi . x1, x2, x3 are the cutting speed, feed and depth of cut respectively.
The experimental results are used to develop mathematical model and linearized by performing Logarithmic transformations converting into a linear modeling using computational software, from the observed data for surface roughness, the response function has been determined using regression is, Ra = 2.99 + 0.0728 ln(S) + 0.894 ln(F) + 0.076 ln(DOC) (5) i.e Ra = 20.6913*Power(S,0.0728)*Power(F,0.894)*Power(DOC,0.076) (6) Result of ANOVA for the regression model is represented in Table 8.
The graph shows that the data closely follow the straight lines, denoting a normal distribution.
From the observed data for surface roughness, the response function has been determined using regression and fitness function, defined as Minimize Ra = 2.99 + 0.0728 ln(S) + 0.894 ln(F) + 0.076 ln(DOC) i.e Ra = 20.6913*Power(S,0.0728)*Power(F,0.894)*Power(DOC,0.076) (i) Speed min ≤ Speed ≤ Speed max 360 m/min ≤ Speed ≤ 580 m/min (ii) feed min ≤ feed ≤ feed max 0.05 mm/rev ≤ feed ≤ 0.09 mm/rev (iii) doc min ≤ doc ≤ doc max 0.05 mm ≤ doc ≤ 0.15 mm xil ≤ xi ≤ xiu where xil and xiu are the upper and lower bounds of process variables xi . x1, x2, x3 are the cutting speed, feed and depth of cut respectively.
Online since: March 2022
Authors: Therdsak Prammananan, Sathit Niratisai, Kanawan Pochanakom, Pitikarn Kanjanapruk
These compounds were prepared from corresponding phenyl benzoates through Fries rearrangement and reduction reaction.
The DSC data were effectively applied for the estimation of the optimal reaction temperatures to attain high %yields for the synthesis of benzhydrols.
The DSC data were effectively applied for the estimation of the optimal reaction temperatures to attain high %yields for the synthesis of benzhydrols.
Online since: October 2023
Authors: Mohsin Iqbal, Veeradasan Perumal, Mark Ovinis, Akram Hina, Saravanan Karuppanan
A total of 320 finite element simulations were performed for training data generation.
Once the numerical model was validated, a Design of Experiment (DoE) data set was simulated.
This data was loaded into the nntool module of MATLAB, and a neural network was set.
DoE data generation.
Data availability Supplementary data is available upon request.
Once the numerical model was validated, a Design of Experiment (DoE) data set was simulated.
This data was loaded into the nntool module of MATLAB, and a neural network was set.
DoE data generation.
Data availability Supplementary data is available upon request.
Online since: June 2014
Authors: Ting Yu, Xiang Qi Chang, Wen Qi Lin, Na Yan
Fig.1 Location of Study Areas
Data.
After checking meteorological data in the past 10 years, we selected the LANDSAT-5 Satellite TM images taken on 22 September 2009 (Track No.135949, 10:43am) as our basic research data.
In image data, based on the values of NDVI and MNDWI, vegetation, water bodies and buildings were distinguished from each other.
Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data.
Study on urban heat island of Beijing using ASTER data: A quantative remote sensing perspective.
After checking meteorological data in the past 10 years, we selected the LANDSAT-5 Satellite TM images taken on 22 September 2009 (Track No.135949, 10:43am) as our basic research data.
In image data, based on the values of NDVI and MNDWI, vegetation, water bodies and buildings were distinguished from each other.
Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data.
Study on urban heat island of Beijing using ASTER data: A quantative remote sensing perspective.
Online since: February 2018
Authors: Chun Zhi Zhao, Yan Jiao Zhang, Shi Wei Ren, Yi Liu
Table 1 Inventory data of raw materials and energy.
Site data includes the inventory data regarding raw materials consumption, energy consumption, pollutant discharge, transport and the like of glass wool product at production stage.
Upstream data includes the inventory data regarding raw material exploitation and energy production as well as the inventory data regarding road transportation required for raw material transport; the upstream data of this report is taken from CLCD database.
Table 2 Source of the data adopted in various processes of glass wool product.
The model data in life cycle is based on the production data of enterprise in 2015 and the upstream data is based on 2013.
Site data includes the inventory data regarding raw materials consumption, energy consumption, pollutant discharge, transport and the like of glass wool product at production stage.
Upstream data includes the inventory data regarding raw material exploitation and energy production as well as the inventory data regarding road transportation required for raw material transport; the upstream data of this report is taken from CLCD database.
Table 2 Source of the data adopted in various processes of glass wool product.
The model data in life cycle is based on the production data of enterprise in 2015 and the upstream data is based on 2013.