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Online since: October 2010
Authors: Jo Dweck, V. Campos, Leonardo F. Fraceto, Pedro M. Büchler, André H. Rosa, Leandro Cardoso de Morais
Sludge combustion enjoys a combination of several advantages that are not found in other treatment alternatives, including a large reduction of sludge volume to a small stabilized ash, which accounts for only 10% of the volume of mechanically dewatered sludge, and thermal destruction of toxic organic constituents [4].
In Kissinger model, which was originally developed for DTA curve data concerning to reactions of the type solida à solidb + gas, of any order n, the maximum reaction rate temperature is characterized by the DTA peak temperature, which corresponds to the maximum heat effect of the decomposing reaction.
Thus the DTG peaks occurring between 780 and 920oC are probably due to a reduction reaction (N5) of the residual sulphates by the carbonaceous residue and/or by residual sulphides, with simultaneous release of SO2 [19, 20].
From DTA data, the activation energy of step N1 was 108 kJ/mol.
Online since: October 2011
Authors: Chun Ming Xu, Feng He, Peng Cheng Fu
These bacteria were chosen based on a preliminary screening (data not shown) that demonstrated their ability to grow well at a range of higher temperatures and acidity levels, salinity levels.
Given that the fluctuation of the quantity and quality of wastewater is very large at the actual treatment operation, this tank appeared to be necessary at the design stage, and was proven to be effective in subsequent experiments (data not shown).
Because of the gradual reduction of the concentrations of organic compounds in the wastewater, the characteristics of the biofacies of the two stages of this tank differ.
Table 1 Results of the treatment of the wastewater generated by the production of heavy crude oil parameter Before treatment After treatment Reduction(%) Oil content (mg/L) 25.9 5.0 80.6 TSS (mg/L) 110 10 90.9 Sulfides (mg/L) 2.6 0 100.0 CODcr (mg/L) 362 91 74.8 Volatile phenols (mg/·L) 0.37 0 100.0 After the anaerobic and aerobic biological treatments, the fixed-film bioreactors with a 15-h hydraulic retention time (HRT) reduced COD by 74.8%, TSS by 90.9%,oil by 80.6%, and phenols and sulfides by 100%.
Online since: May 2016
Authors: Kazutoshi Kojima, Johji Nishio, Hirokuni Asamizu, Kentaro Tamura, Chiaki Kudou, Keiko Masumoto, Keiichi Yamada
Introduction The reduction of the silicon carbide (SiC) wafer off-angle effectively lowers production costs by decreasing material loss when slicing wafers from a single SiC ingot.
Moreover, increasing demands for chip cost reduction per area and large-size chip production have led to a shift in mainstream SiC wafer size from 100 to 150 mm.
These data were collected for 61 triangular defects observed on three 3-inch wafers with a 5-μm-thick epitaxial layer.
The SBH estimate is in good agreement with reported data for Ni/4H-SiC diodes [7].
Online since: March 2025
Authors: Erwin Oliver V. Fundador, Noreen Grace V. Fundador, Blezzie Desales, Khent Ivan Duerme
The phenolic compounds present in plants are responsible for the reduction of Ag+ to Ag0.
The phenolic compounds found on the surface of AgNPs provide more active sites for the reduction of silver ions and help in stabilizing the mixture [12].
Data on EDX analysis provides the elemental composition of AgNPs.
On the other hand, DLS analysis (data not shown) revealed that AgNPs had an average hydrodynamic size of 140 nm.
Online since: January 2013
Authors: Lan Xun Wang, Dan Fang Li
This model is a blind recognition in no error, and the amount of data for analysis will dramatically increase with code length valuation expansion which results in few practical significances.
Reference [2] estimates code length according to the weight distribution, and then gains generator matrix through the improved matrix reduction.
This method avoids the complex matrix reduction arithmetic.
This is a memoryless channel, that is to say, these mistakes are produced when data sequences transmit are not related to each other.
Online since: August 2013
Authors: Li Yong Jiao, Zheng Jie Wu
The data of Tign, PHRR, and THR are listed in Table 2.
The PHRR of sample 6 was 370kW/m2, a reduction by 48% relative to that of polyacrylate coating.
Table 2 Cone calorimetric data for IFR coating samples at an incident heat flux of 35 kW/m2 Sample Tign (s) PHRR (kW/m−2) THR (MJ/m−2) 1 34±3 717±37 78.98±2.4 2 31±2 494±21 57.15±1.2 3 34±2 478±30 52.52±2.3 4 35±3 466±35 54.86±1.9 5 33±2 418±28 48.84±2.6 6 34±2 370±24 41.06±2.8 Fig. 3 Heat release rate curves of the IFR coatings during cone calorimeter test Conclusions Compared with the traditional APP/PER/MEL IFR system, influence of AL as the carbonization agent of APP/AL/MEL IFR coating on the thermal degradation properties and flame retardant performances were investigated under the air environment.
AL as the carbonization agent could benefit for the formation of charred layer and increase the char residue ratio, which led to the reduction in PHRR and enhanced the flame retardancy of the coating.
Online since: July 2017
Authors: Farid Z. Utyashev, Shamil Mukhtarov, Vener Valitov, Marsel Nagimov, Artem Ganeev, Ruslan Shakhov
Critical factors that reduce costs and fabricating time by superplastic roll forming are metal utilization factor increase up to 0.8, reduction of the labor cost and metal consumption for tools manufacturing.
A significant reduction in the deformation load is an undoubted advantage of roll forming process over isothermal closed die forging.
Mechanical testing results show in Table 3 a significant increase in tensile strength and toughness in comparison with data of material specification.
Superplastic roll forming provides processing precise complex shape components with uniform structure and strength properties which are 15-20% higher than those of material specification data after conventional heat treatment. 2.
Online since: October 2011
Authors: Gwangmin Park, Seonghun Lee, Sung Ho Jin, Sangshin Kwak
Individual components of the model are constructed based on real vehicle data and mathematical dynamic model equations.
The relation for motor torque (Tm), drive shaft torque (Tdr), and motor angular acceleration (ώm) is given as (1) The torque of drive axle (Taxle) is amplified by the differential gear ratio (Gdf) with slight reduction due to the inertia as (2) Furthermore, the vehicle drive acceleration is dependent, based on the 2nd law of Newton, on the motor angular acceleration, the wheel radius (Rw), power transmission efficiency (κ), and the gear ratios as (3) From the equation (1), (2), and (3), the final wheel torque (Tw) is obtained as: (4) Using (1)-(4), the vehicle
For the high precision design in simulations and analyses, the SimPowerSystem / SimDriveline model was configured with real vehicle calibration data.
Online since: May 2012
Authors: J. Gul, S. Mirza
Moreover, no significant reduction in density of EPDM was obtained instead of compounding with lower specific gravity cork powder.
BEM result of ablation data ID Weight (g) Thickness, mm Ablation Before test After test Without char Char Before test After test mm 25 Phr asbestos 82.395 78.71 77.99 3.7 6.5 5.84 0.72 10 Phr cork 79.03 69.5 68.2 1.3 6.06 5.28 0.78 20 Phr cork 78.32 67.2 66.4 0.8 6.13 5.29 0.84 50 Phr cork 77.74 66.4 65.4 0.6 6.14 5.17 0.96 Fig. 6.
No significant reduction in specific gravity of silica-EPDM composite was observed upon compounding with cork.
Online since: December 2011
Authors: Justyna Rozwadowska, Katsuyuki Kida, Edson Costa Santos, Takashi Honda, Hitonobu Koike, Kenji Kanemasu
Due to an increasingly high requirements regarding energy saving, higher power machinery and emission reduction, a need for bearing weight reduction has arisen.
It is expected that once sufficient amount of test data is collected, it will be possible to correlate the inclusion depth, their minimum size and shape factors with the crack initiation process much easier than through conventional testing. 104 5μm 5μm 5μm 65 mm 250 mm 570 mm 106 5μm 5μm 5μm 110 mm 280 mm 445 mm 4.5 * 107 5μm 5μm 5μm 160 mm 280 mm 373 mm Figure 3 Cracks after one-point RCF testing (a) number of cycles = 104 (b) number of cycles = 106 and (c) number of cycles = 4.5 * 107.
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