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Online since: March 2004
Authors: Yun Xia Ye, Yong Kang Zhang, Yin Qun Hua, Rong Fa Chen, Judith C. Yang
On the other hand, under several GPa pressure in LSP, metal or alloy surface layer can gain uniformity stability dislocation, fined grain and surface residual compression stress.
Table 1 Chemical compositions and mechanical properties of ductile iron QT800-2 Chemical composition C Si Mn P S Mg RE Wt [%] 3.7-3.85 1.3-1.4 0.3-0.4 �0.07 �0.05 0.04-0.05 0.015-0.04 E [Mpa] � �b [Mpa] �0.2 [Mpa] � [%] HV Mechanical properties 130 0.291 800 480 2 274 Heat treatment Normalization Journal Title and Volume Number (to be inserted by the publisher) 375 Experiment Equipments and Selection of the Parameters.
The laser power density used during laser shock processing is about 1.86 GW/cm2, the peak value of surface compression stress Journal Title and Volume Number (to be inserted by the publisher) 377 obtained here can reach 426 MPa, and the hardened depth 2.0 mm.
Online since: February 2016
Authors: R.M. Baitimerov, S.D. Vaulin, P.A. Lykov
However SLM process is defined by a large number of parameters: laser power, scanning speed, layer thickness, point distance, exposure time, hatch space, stripe width, scanning strategy, powder bed temperature, building atmosphere and other), this complicates optimization of SLM process for each new metal or alloy.
SLM process is defined by a large number of parameters.
Attallah, The influence of the laser scan strategy on grain structure and cracking behavior in SLM powder-bed fabricated nickel superalloy, Journal of Alloys and Compounds. 615 (2014) 338-347
Online since: May 2012
Authors: Yi Lin Chi, Wei Li, Tao Yong Zhou, Xue Jun Wang
EDEM is a discrete element program that has the ability to model entire boundary value problems directly with a large number of particles.
M. [12] put forward modeling method like the spherical particles stacking, such as the cumulative clouds ten goals of the shape of the grain, and a tetrahedron eight goals in the round state of particles.
The third step is to use the external interface import EDEM tamping bank to the simplified model of the system simulation model, EDEM particles in accord with the requirement of the generation factory number of particle, particle shape as state above.
Online since: March 2015
Authors: Zheng Kun Liu, Hong Liang Wang, Xin Xin Man
The definition of shale gas Jinchuan Zhang defined shale gas and said shale gas refers to the thermal maturation or continuous as well as the interaction between biological effects mainly generated, gathered at the gas source rocks in the body, including a free state (that exists between natural fractures and grain pores), adsorbed (presence of clay mineral particles, kerogen particle surface) and dissolved (found in kerogen and asphaltenes), basically includes all the possible presence of gas phase. 3.
However, according to statistics show that only a small number of well-developed natural fractures can be used in shale gas development and production direct, more than 90% of shale gas well needed fracturing to communicate naturally fractured, improving conductivity near the wellbore. 6.2.1 Water fracturing technology Hydraulic fracturing technology uses water to add the appropriate drag reduction agent, clay stabilizers and necessary surfactants to replace the traditional gel fracturing fluid.
A large number of water supply problems lead to development of new environment-friendly technologies fracturing.
Online since: May 2013
Authors: Fei Liu
Limitations in the number of wood, so it is necessary to the development of new alternative materials.
Wheat straw as agricultural and sideline products, annual output accounts for about half of barley grain crops, the past can only be treated by burning, burning process not only pollute the air, but also easy to cause a fire.
Reduce the number of parts, the size, the weight in the design, the optimization design technology, so that the utilization rate of raw materials the highest.
Online since: April 2011
Authors: Daniel Fruchart, Patricia de Rango, N.E. Skryabina, Salvatore Miraglia, Marina G. Shelyapina
The grain size after hydrogen decrepitation was less than 100 μm easing hydrogenation/dehydrogenation reactions Structural characterization of samples before and after hydrogenation was made using a Siemens D-5000 diffractometer operating CoKa radiation in reflexion mode.
In fact, both the number and strength of each of the endothermic peaks, as well as their temperature strongly depend on metal composition and hydrogen content.
The main difference in between samples is the number of DSC peaks.
Online since: November 2012
Authors: Helmo Käerdi, Priit Kulu, Valdek Mikli, Dmitri Goljandin, Heikki Sarjas
Table 2 TiC-NiMo cermet powder particles angularity parameter at different milling cycles Parameter Number of milling cycles, N 1 2 3 4 5 16 SPQmean1 0.619 ± 0.042 0.526 ± 0.056 0.416 ± 0.039 0.316 ± 0.047 0.366 ± 0.048 0.179 ± 0.032 SPQmedian2 0.619 0.549 0.384 0.293 0.366 0.152 SD3 0.145 0.192 0.134 0.156 0.154 0.101 n4 46 46 46 43 39 39 1 SPQmean – the mean value of the SPQ data set 2 SPQmedian – the median value of the SPQ data set 3 SD – standard deviation of SPQ data set 4 n – number of studied particles (data set size) On Figure 3, dependence on SPQmean from milling cycles and uncertainties of measurements of TiC-NiMo powder particles is shown.
Grain defectivity of used powder particles is low.
Online since: January 2010
Authors: Dagmar Mikulová, Ivo Černý
Water jet used abrasive particles of natural garnet of 150 - 300 µm grain size, 3800 bar pressure, 1.02 mm nozzle diameter and 81 mm/min cutting speed.
Individual points in Fig. 6 were amended with corresponding specimen marking to enable further more detailed analysis of fatigue life and crack initiation mechanisms. 290 300 310 320 330 340 350 360 370 10000 100000 1000000 10000000 100000000 Number of cycles Stress range (MPa) Milled - failed Milled - run out H1 H3 H2 H4 H5 D4 S4 D6 D5 S1 H6 D2 S2 S3H7 D3 H8 D1 H2 Fig. 6: Fatigue S-N curve of specimens with milled surface. 200 220 240 260 280 300 320 340 360 380 10000 100000 1000000 10000000 100000000 Number of cycles Stress range (MPa) Water jet impact Center Jet outfall Milled Electroerosion Regression - water Impact Regression - center Regression - jet outfall Fig. 7: Results of fatigue tests of specimens with water jet and electroerosive cutting surface, respectively, in comparison with milled specimens.
Online since: September 2013
Authors: Long Sheng Bao, Ling Yu, Guang Shan Zhu, Wen Jing Wu
granular material lime replacemen 2×20cm two-kinds ash subgrade 6cm coarse graded asphalt concrete 4cm medium grain of asphalt concrete 1550 cm 20cm three-kinds ash subgrade Fig. 6: The recommendation of road construction Table 5 On-site detecting of the compaction, deflection and unconfined compressive strength mark pile on-site detecting 7d unconfined compressive strength [MPa] deflection /[0.01mm] compaction degree[%] K0+040 3.06 10 98.8 K0+060 2.97 8 99.8 K0+080 3.17 9 97.0 K0+100 3.03 10 97.4 K0+120 3.12 13 97.7 K0+140 3.35 13 98.2 According to the information in the Table 5, the 7d unconfined compressive strength meet the 3.0 [MPa] constructing standard, the representative deflection 19.92[0.01mm] is lower than the controlled deflection 32.5[0.01mm], and the compaction degree is higher than the 97% quality standard.
Acknowledgements This work was financially supported by the national natural science fund, the number of funded project is 51078242, and the ‘Young and Middle –Aged Specialist of the Nation with Prominent Contribution’, the number is 2012921047.
Online since: October 2014
Authors: Muhammad Hanif Zainal Abidin, Jamal Hazri Zakaria, Sulastri Sabudin, Mohd Faizal Mohideen Batcha
They reported that Page model was found to agree with the experimental data with less than 1.4% of RMSE while effective moisture diffusivity, Deff value of millet is found to be approximately three times lower than that of ragi (food grain) and corn.
These parameters may be expressed as: N i=1 x2 = Σ (MRexp,i – MRpre,i) N – P (1) 1 Σ (MRexp,i – MRpre,i)2 1/2 N RMSE = N i=1 (2) MRexp,i – MRpre,i MRexp,i 100 N P = (3) (MRexp,i – MRpre,i) Residuals = (4) where MRexp,i and MRpre,i are the i experimental and predicted moisture ratios, respectively. the number of observations is N, and the number of constants is p.
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