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The results showed reduction in density, compressive strength and consistency and an increase in setting time, and flexural strength.
Mostly, the data in this regard pertains to the hardened state of the material.
Both Needle test and flow table test authenticate the reduction in consistency. 2.
Reduction in consistency indicates that the particles absorb water and thus enhance water requirements. 3.
Reduction in density is attributed to lower density of the particle. 4.

Two options for the speed reduction are a gearbox and a screw driven slider-crank mechanism.
A constant reduction ratio means that some design redundancy is unavoidable in order to meet both requirements.
Other limitations include permitted rotational speed of the motor and the speed limit of the reduction system.
With careful design, a factor of 1.5 in the reduction ratio can be reached in a slider-crank mechanism.
Since a redundant reduction system is heavy and it is hard to switch from one reduction system to another smoothly, the redundant driver is not chosen to solve the problem.

Slight reduction in density were observed across all T1 as the Y-TZP content increases up to 10 vol%.
Above 10 vol% Y-TZP content, the sharp decrease in HV might be effects of significant reduction in density.
The reduction of HV in the alumina-Y-TZP composite could also be the effect of porosity formation which caused reduction in density hence leading to reduction in HV.
Furthermore, according to Eq.2, the Young’s modulus is directly proportional to density hence reduction in density would lead to reduction in Young’s modulus of the composite.
According to previous literature data [13,15], the most ideal amount of ZrO2 content is found to be 10 vol% hence these finding are in agreement with previous literature.

A second mesh, which is fine over the entire volume of the workpiece, is used to store the nodal data and simulation results, which get transferred to the simulation mesh every time a remeshing operation becomes necessary.
In combination with an adopted data transfer algorithm, this second mesh is used to minimize the loss of accuracy, if a previously finely meshed area becomes a coarsely meshed area.
The time saving is lower than the reduction of the number of the degrees of freedom to be simulated because of the additional data transfer operations and the additional memory required by the multimesh method.
Based on these data, the microstructure changes i.e. recrystallized volume fraction and grain size, as well as the microstructure dependent flow stress are calculated by Strucsim.
With this flow stress, the forming data for the next step is calculated by the LARSTRAN [4].

The measurement of the experimental data was conducted using a static data logger and a computer at a sampling rate of 1 Hz.
Fig. 9 compares the data measured at the top of the lateral concrete (①) and at the bottom of FRP (②) of Fig. 7 with the analytic values.
Fig. 10 compares the data measured at the bottom of the FRP upper flange (③) and at the top of the FRP bottom flange (④) with the analytic values.
However, the data measured at the upper flange show some difference with the analytic values.
Since the measured and computed values of the strain at the FRP upper flange (④) and the bottom of the lateral FRP (②) are similar and can be interpreted as a result indicating perfect bond behavior of FRP and concrete, this difference can be assumed as an error in the data measured in the FRP upper flange.

Narrowly speaking, low-carbon industry refers to industries directly related to carbon elimination and reduction, the core is clean energy and energy saving technology; broadly speaking, low-carbon industry may include all industries which is helpful to contribute to energy saving and emission reduction.
In one word, low-carbon industry is the basis of low-carbon economy, measured by carbon emission reductions, based on carbon reduction technology and involved collection of low-carbon production and service industries.
Table 2 summarizes the data of the level of energy consumption of the whole society, Shenzhen are much higher than the national average in primary energy consumption and non-fossil energy sources.
Data of public transportation from 2005 to 2012 is shown in Table 3, and Table 4 shows the environmental protection investment in recent years.
According to statistics data of Municipal Bureau of Statistics, the added value of new energy industry was 25.41 billion yuan, increased by 20.7% in 2011.

From map data analysis and satellite images of Google Earth, we find the presence of large-scale over-reclamation at Taiwan’s main mountain ranges.
Research Methods and Purpose Our methods include literature review, map and data analysis, semi-structured interviews, sample analysis and depth interviews.
The supplementary data collected from experts and policy officials during the interviews would help create a better understanding on the planning decisions of climate change reduction issue.
Based on statistical data of the Water Resources Agency, the agricultural water use had amounted to 12.205 billion cubic meters in 2015, accounting for 71.53% of the island’s total water consumption.
Rubin, Qualitative interviewing: The art of hearing data.

This paper adopts the existing experiments data of the freeze-thaw [1,2].
This paper adopts the existing experimental method and data [4].
In order to obtain the relation between the concrete damage and chloride penetration depth, all data was analyzed by nonlinear regression method.
Fig. 1 Freeze-thawing damage model of concrete pier Data that must be surveyed on the spot are as follows
If this qualification cannot be reached, the engineer can use the data of Tab. 2 to estimate the times.

The effect of extrusion process on the quality of AZ31 magnesium extrudate was performed, by data mining from 3DFEM simulation and Rough Set Theory(RST).
So by using of RST, the data mining from the numerical simulation results of AZ31 extrusion processes was performed to quantitative analysis.
Attributes reduction is the main tooling for data analysis[6].
In reality the data are mostly continuous so that these data must be scattered.
The scattered data decision table ),,,( fVDCUS ∪= can be obtained after attributes scattered.

Also, the reduction of plastic collapse pressure with ovality is small for a thick tube bend when compared with that for a thin tube bend.
When data are assumed to fit a mathematical distribution, we are adding information that helps us to model the available data.
ANN models the data that are presented to it during the training stage without assuming a particular distribution.
After the network is trained it is used to simulate or predict plastic collapse pressures using the tube dimensions and ovality data as input.
[6] Zarrabi K, Estimating the plane-strain fracture toughness under mode I from the uniaxial tensile data, Proceedings of the Structural Integrity & Failure conference, CD-ROM, Sydney, Australia, 27 - 29 September (2006), ISBN: 1 876855 26 6.