Search results

The molecular in the degradation process has good fit with the experiment data.
In this study the evolution rules of cellular automata are not simple data structure model, instead, we make the combination of the chemical reaction of polymer materials degradation and degradation products - oligomer diffusion, the cellular evolution rules is developed by the molecular weight and the strength of the material.
Example calculation Example of DLPLA plate degradation of cellular automata simulation’s specific experiment data can be seen in the literature [7].
The comparison of molecular weight simulated in the degradation process and experimental data is shown in Fig.2.
In simulation results, the hollow phenomenon is appeared, which is consistent with experimental observations, and the cellular molecular weight data fit well with the experimental data.

The functions of the remanufacturing system comprise calibration of system, part reversing measurement, data processing, defective model reconstruction, welding remanufacturing prototyping path layout and etc.
The functions of system include the acquirement and treatment of "point cloud" data of the worn metal part, reconstruction of defective model, remanufacturing prototyping path layout, prototyping simulation, and etc.
Its work interface shows as Fig.2. 2) Reversing measurement module This module is mainly used to set measurement parameter and mode, as well as collect and storage data.
Its work interface is shown as Fig.3. 3) Data processing module The main task of this module is smoothing, reduction, noise removing, combination and segmentation of data.
Its work interface shows as Fig.4. 4) Defective model reconstruction module Fig.5 shows that the defective model reconstruction module comprises the triangularization of "point cloud" data and the comparison of defective module and normal part model. 5) Weld prototyping module Fig.6 is the work interface of the remanufacturing prototyping path layout module.

The results of the previous research showed, gasification technology can not only realize volume reduction and reduction of the sludge, also can make heavy metals fixed in ash to leaching toxicity to meet safety standards.
Fig. 1 The pyrolysis curve of the various components Pyrolysis data of sludge show as in Tab. 2.
Then according to formula (11) calculate the kinetic parameters of sludge samples, shown as Tab. 3: Tab. 3 The apparent activation energy and the frequency factor experimental data of the various components Sample Apparent activation energy ( E ) / kJ/mol Frequency factor ( A ) / s-1 Sludge 27.713 91.54 Paper scraps 28.918 128.854 Peel 35.883 176.398 Starch 27.200 163.30 Experimental results show that starch, orange peel and paper scraps have absorbed little heat to evaporate moisture at about 70 degrees Celsius.
(2) This study provided data can be used to describe steady state and dynamic characteristics of the sludge or the sludge and MSW mixture in a fixed bed, moving bed, fluidized bed pyrolysis and gasification process, for guide engineering design and operation process to optimization.
Kinetic parameters from thermo gravimetric data Nature, 1964, 201: 68-69 [4] Zhaojun Ding, Xinqian Shu, Guangbin Bai.The sludge pyrolysis to producte hydrogen experimental study in city sewage plant [J].

Table 2 and Table 3 summarize the data of neutron cross-section for recoil atom (n, a) and (n, p) reaction, respectively.
The data were taken from the ENDF/B-VI data library.
Table 2 The ENDF/B-VI cross-section data of the (n, a) reaction in silicon crystal.
Q-value (MeV) Cross section (barn) E (Alpha) (MeV) E (Mg) (MeV) 1 2.65 0.09306 10.81 1.54 2 3.24 0.00262 10.29 1.47 3 3.63 0.00488 9.95 1.42 4 4.26 0.00762 9.4 1.34 5 4.61 0.00676 9.09 1.34 6 5.21 0.00253 8.57 1.22 7 5.39 0.0069 8.41 1.2 8 5.45 0.00443 8.36 1.19 9 6.05 0.00667 7.83 1.12 10 6.06 0.00421 7.82 1.12 11 6.56 0.00545 7.39 1.05 12 6.62 0.00589 7.33 1.05 Table 3 The ENDF/B-VI cross-section data of the (n, p) reaction in silicon crystal.
Defense Threat Reduction Agency Fort Belvoir VA (2010) No.

Micro analytical (C, H, N) data were obtained with a FLASH EA 1112 Series CHNS Analyzer.
The crystal data were collected on a Bruker axs kappa APEXII CCD Diffractometer.
The crystal data are shown in Table 1.
Crystallographic data for L1 Empirical formula Formula weight Temperature Wavelength Crystal system Unit cell dimensions a (Å) b (Å) c (Å) α β γ Volume Z Density (calculated) Absorption coefficient F(000) Crystal size Theta range for data collection C18H19NO4 313.34 293 K 0.71073 Å Monoclinic, Cc 15.5870 (9) 12.6447 (7) 7.9620 (4) 90.000(3) ° 93.928 (2)° 90.000(3) ° 1565.57 (15) Å3 4 1.329 Mg m−3 0.09 mm−1 664 0.3 × 0.3 × 0.2 mm 2.1–27.5° The crystal structure of the hetero-bicyclic compound consists of six membered morpholine and five membered oxazolidine rings fused together.
ESI mass spectrum of hetero bicyclic compound (L1) For preparing metal nanoparticles using chemical reduction method, it is very important to decide appropriate stabilizer.

Numerical data, describing the microstructure of the cementitious material both in terms of pore structure and mineralogy, are necessary input parameters for such model.
Data were collected in the angular range 5–80° 2θ, at 40 kV and 40 mA.
ImageJ software was employed for visualizing the obtained data.
Volumes of interest (VOIs) were selected for each data set, paying attention to exclude large defects (pores), in order to perform quantitative image analysis of the cement matrix.
The quantitative data obtained are supposed to be employed in the development of a micromechanical model for the prediction of mechanical properties of cementitious systems exposed to thaumasite sulfate attack.

Thus, the conclusion was made about the necessary reduction in the value of this parameter.
Based on data from the last two models we can conclude that for better flow of combined process "helical rolling – pressing" need to set the matrix at the minimum possible distance from the deformation zone of the rolls.
Similar data were obtained in work [7] with the combined process "rolling-pressing".
For this research specialized database of the microstructure of the Matilda programwas used, which uses the data of stress-strain state, strain rate and temperature of ready designed models to Simufact.Forming, complements them with the data of physic-chemical properties and their behavior for a given material and its structure from the database, then using the algorithm Yada [8], calculates the process parameters of static and dynamic recrystallization that may cause changes in grain size.
As a result the following data were obtained (Fig. 5).

Under optimum conditions, Matrox Solios can exchange data with the host at a peak transfer rate of up to 1 Gbyte/sec.
Tab. 1 Parameters of the AVIIVA ® M2 CL Parameters Value Senor High Sensitivity and High SNR Performance Linear CCD Number of Pixels 2048 pixels Pixel Size 56×60×39.4 mm Maximum Line Rate 28 KHz Data rate 60 Mpixels/s Linearity ＜1% Anti blooming ×150 Core Sample Rotation Platform.
The platform that drives the core sample rotation with different speed is mainly composed of a frequency turner, an electrical motor, reduction box, bearing and the core sample tray.
It extracts characteristics such as area, perimeter, fitting ellipse and minFeret of each particle and save the data into a database table (Table 2).
According to the data above, the particle was classified to 2.36mm to 4.75mm, 4.75mm to 9.5mm, 9.5mm to 13.2mm, 13.2mm to 16.0mm and 16.0mm to 19.0mm.

In order to achieve energy-saving and emission-reduction targets requested from the central and local governments, most companies in continuous industries emphasized on the device-level, the traditional energy-saving mode, to improve the main energy consumption devices, or to improve the production process, and thereby achieved considerable economic benefits.
Currently many factories are investigating a new solution with an idea that integrates the industrialization and informationization, they turn to focus on the enterprise-level process optimization considering not only the product order, the material balance, but also the energy-saving and emission-reduction, represented by various enterprise-energy-management systems (EMS), this systematic energy-saving is getting more and more attention from the big enterprises or big factories.
Most current enterprise-energy-management systems can meet the requirements mainly about energy data sampling, data display, data recording, partial data analysis, while not about the energy-saving-oriented production optimization.
All material lines with arrows reflect the material flow in this model, in the same production mechanism with traditional production description documents; In information flow, all the blue lines shown in Fig.1, all the production states sampled by DCS or the central controller, including the data about liquid flow value (F symbol in Fig.1), the inner-pressure (P symbol in Fig.1), the inner-temperature (T symbol in Fig.1), the electrical current (I symbol in Fig.1), also the switch-state or opening-value of different valves, are transferred in any kind of communication wires, or wireless networks, and abstracted into information flow.

Simulation model Runs Initial Model and Data Analysis.
Table 2.Data validation Items Actual data Simulated data Achievement Ratio Number of input 410225 403086 98.2% Number of output 205506 191150 93% Average of total production time 9002.39 8532.37 94.8% Conduct What-if Analysis After simulating the production line of this company, the obtained result indicated the lack of proper balance and production control in production line.
Afterwards the results were evaluated with real data and its validity was tested.
Average price of the products in this scenario declined from initial 18005$ to 16020$ that is mostly because of the reduction in production time of total orders.
Three scenarios were analysed and assessed and finally the first scenario was selected as the best scenario since this scenario by increasing the production speed caused a rise in output and more reduction in total cost in respect of other scenarios.