Search results

Adsorption isotherm data is obtained by processing Cr (VI) concentration data at initial and at time t.
Freundlich Isotherm Data Mass of adsorbent (g) Freundlich R2 n Kf 1 0.993 -13.3333 0.0759 2 0.977 -14.7059 0.0722 3 0.970 -12.1951 0.0248 The values of n and Kf are displayed in Table 1, which presents the data from the calculation of the Freundlich isotherm.
The data of Ca, ln Ca0/Ca and 1/Ca against t measured and plotted by using equation (4-6).
The data from the calculation of second-order adsorption kinetics are shown in the Table 5.
Data From the Calculation of Second-order Adsorption Kinetics Mass of adsorbent (g) Order 2 R2 K2 1 0.148 0.043 2 0.506 0.182 3 0.751 0.202 Table 5 shows data from the calculation of second-order adsorption kinetics.

Determination of the index weights AHP establishes the subjective materiality judgments between indexes by fuzzy comparison of evaluation indexes, and through the consistency check to determine the value of the index weights；Entropy method is a method which more objective to determine the index weights by processing the original value of the index data and analyzing the information which carried by indexes.
Determines the index of evaluation sets This paper use the reviews set which formed by the five indicators(A,AA,AAA,AAAA,AAAAA),and these respectively represent the credit rating of low, medium, good, high, very high of the security of grid, In which the ranges of Weighted deviation degree of each class and the Ideal value were: A-level (0.8,1.0), AA-level (0.6,0.8), AAA-level(0.4,0.6),AAAA-level(0.2,0.4),AAAAA-level(0,0.2),then use the cloud model to achieve each comments value ,and constitute the qualitative evaluation of the cloud generator as shown below: Fig.2 The cloud generator Empirical Study This paper conducted an investigation in five regional power grids of similar region and got the original data of nine indicators including the aspect of structural safety, operational safety, stability of the 5 grid in a year.
Due to different data standards, it needs to non-dimensionalize the index so that they are comparable.
The data of the index obtained after processing are as follows: Table 1 Index data for the security of grid evaluation Index Grid1 Grid 2 Grid 3 Grid 4 Grid 5 C1 1.00 0.90 1.00 0.97 0.95 C2 0.95 0.87 1.00 0.94 0.92 C3 1.00 0.81 0.97 0.91 0.85 C4 0.60 1.00 0.50 0.70 0.90 C5 0.70 0.90 0.60 0.80 1.00 C6 0.73 0.91 0.68 1.00 0.85 C7 0.74 0.16 1.00 0.59 0.44 C8 1.00 1.00 1.00 1.00 1.00 C9 1.00 1.00 1.00 1.00 1.00 According to data on the table, firstly, the objective weight value for C-index is W1 based on the calculation process of entropy theory; then, through comprehensive comparison of indexes, the subjective weight value for C-index is W2 by the calculation process of AHP.
Table 3 The Grid’s Security Credit Grade Evaluation Results Grid Activated(level) Credit Rate 1 0.2419 AAAA high 2 0.4969 AAA good 3 0.1796 AAAAA very high 4 0.3655 AAAA high 5 0.4328 AAA good Analysis the data table above, the third grid has he highest level of security, reaching the AAAAA level, which indicate that the overall installation is very good.

Handbooks of mechanical properties typically only give data for the as-cast condition [e.g. 2].
Data is presented with the stress axis showing (a) maximum cyclic stress and (b) the ratio of maximum cyclic stress : tensile strength.
Axial S-N data measured at R = 0.1.
Data at 10 7 cycles are run-outs
Although the results quoted here are encouraging, there is considerable scatter in the fatigue data and its cause has yet to be ascertained.

The main purpose of this study is to provide an ANNs model, knowledge and data on Deuterium–Tritium (D–T) fusion neutron induced damage in MOS devices.
In a second step we arrange the data into training, validation, and test subsets.10% of the data are taken for the validation set, 20% the test set, and 70% training set.
The sets are picked as equally spaced points throughout the original data.
In Figure 4, Note that the data loading is: training base, test base, number of layers and neurons, type of the transfer functions, number of iteration and estimate threshold.
Ross Doherty, Incorporation of endf-v neutron cross section data for calculating neutron-induced single event upsets, ieee transactions on nuclear science, vol. 36, no. 6, december 1989

There is a contradiction between high sensitivity for interference monitoring and reduction of the false alarm probability (Pf).
Measured data from experiments verified the validity of the method.
Too small, single segment is made to have too many data points while too few data segments are get, thus unable to obtain a suitable initial noise spectral density value.
Through the previous analysis, in the algorithm, take K equal to 1/32 of N is suitable, where N is the data points of average windowed periodogram power spectral density.
Transmit the collected interference data to a computer, detect interference from the data, record and analyze the test results.

To keep safe operation of power grid, effective harmonic reduction methods must be taken.
Some systems are based on PC associated with off-the-shelf data acquisition component[5,6].
This kinds of system provides abundant memory space for captured data, powerful data processing and analysis ability as well as visual GUI (Graphical User Interface).
The Synchronous Sampling When performing the FFT, all data for the operation is required to be included in a integer cycle, otherwise spectral leakage will occur[8].
The Design of the System Software The software system of the harmonic analyzer mainly includes AC sampling control, FFT, high-precision frequency measurement, parameters computing and data communications.

First, few aquatic physiochemical and distribution data are available for aquatic species, and strongly predictive environmental variables for establishment are unknown for many (or most) aquatic species.
The initial risk management The mediate risk management The final risk management decision policy Risk Assessment (on the information which we have understood) Risk Assessment The overall Risk Assessment Risk Assessment Risk management decision New data and information ssinformati Alternatives Assessment New data and information Fig.1 The management processes of applying the precautionary principle In this management processes, the precautionary principle runs through the risk management.
Using the new data and information in the risk assessment, we can overcome obstacles due to insufficient information on the risk management of invasive species.
Using the new data and information in the risk assessment, we can overcome obstacles due to insufficient information on the traditional risk management of invasive species.
“long-term changes in zooplankton biomass concentration and mean size over the nnorthwest European shelf inferred from continuous plankton recorder data.

The measured data can not be compared with the results by finite element method.
The ultrasonic velocity data indicate that the computed plastic zone, denoted by shaded area shown in Fig. 5(a), is reasonable.
When other αand κof D-P yield criterion is used to model the excavation of the problem, the results deviate more from the measured data than those computed by Eq. (4).
Table 2 The deformation by the extensometers( data in the bracket are obtained by finite element method).
Zheng, S.Y.Zhao and W.D.Deng: Numerical simulation on failure mechanism of rock slope by strength reduction FEM.

As there are less data for mining, processing and transportation of raw materials and fuel, the construction stage was expressed with relatively accurate life cycle cost.
That is, providing the weighting of various environmental impact types, and then further processing and analyzing the data.
Therefore, the reduction of industrial boiler resource consumption should start with the coal resource.
Economic data in the collected inventory can be classified, non-environmental impact data to internal costs and environmental impact data to external costs.
According to the model and determined data, the external costs in the boiler life cycle were calculated, as shown in Fig. 4.

Firstly, select the alloy categories, set the rough castings and gating riser system’s density, viscosity, radiation coefficient, latent heat, liquids temperature, solidus temperature, coagulation factor, liquid shrinkage and other physical parameters, set the cold iron, the density of insulation cap, heat capacity, thermal conductivity and other physical parameters; set the weight factor, relaxation factor, the initial time step, casting parameters, etc. flow parameters, enter the calculation, generate FLD flow field data files, TEM temperature data files and DFC gravity feeding defect files
(4) Post Processing: based on the calculated FLD flow field generated data files, TEM temperature data files, use the volume filling, fill color temperature, the critical solid-phase analysis, and make comprehensive analysis of the bubble models during casting, mixture, pouring inadequacy, cold shut defects, as shown in Figure 3,the immediate image of filled steel.
Fig. 1 Schematic diagram of valve body casting Fig. 2 The Process Schematic of valve body casting Fig. 3 Schematic diagram of filled steel reference Fig. 4 The liquid Schematic diagram of casting solidification Fig. 5 Schematic diagram of quantitative analysis of shrinkage Fig. 6 Schematic diagram of Niyama shrinkage According to TEM temperature data files, observed and analyzed whether the casting solidification process forms isolated liquids, isolated liquids changes and the disappearance at castings as shown in Figure 4, the liquid schematic diagram of casting solidification, and found no apparent isolated liquid areas; According to DFC gravity feeding defects file, the Figure 5, schematic diagram of quantitative analysis of shrinkage, there is no shrinkage phenomenon for 14 shrinkage holes.
Take TEM files, extract the time data and associated temperature data of each casting unit from the liquid into the solid moment, and generate TIM, NYM documentation recording the solidification time sequence, analysis the casting shrinkage probability, as shown in Figure 6, the shrinkage rate is 1.95%.
Table 2 Mechanical test results and ASTM standards Project Proof strength Rp0.2(MPa) Tensile strength Rm(MPa) Tensile stretch A(%) Reduction of cross section Z(%) Standards ≥250 485-655 ≥22 ≥35 Original product 310 515 32 53 Compared product 260 470 24 30 Conclusions (1) Make software design as a link between the process design and non-destructive testing.