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Online since: June 2010
Authors: Yong Xiang Zhao, Hai Bin Hu
However, quality
of cast steels is highly relative to fabrication technologies e.g. shrink cavity shapes and sizes were
greatly affected by the cooling velocity of cast process and the wear resistance of high Cr cast steel
was mostly relative to austenite content [5].
Mechanical properties are around 188 GPa for Young's modulus, 254 MPa 0.2% proof strength, 453 MPa ultimate tensile strength, 26 % elongation, and 45 % reduction of area.
In the test process, test loading level of stress intensity factor range, ∆K, is defined as ( ) max1 KRK −=∆ ; ( )WafWBPK maxmax = ; ( ) ( )( ) ( ) 5.1 4 3 2 126.572.1432.1364.4886.0 αααα αα −+ −+−+=Waf ; Wa=α (1) ×100 150µm c ×100 150µm b ×500 50µm ferrite pearlite a Table 1 Specimen geometries and initial loading levels Specimen ∆K0 (MPam 1/2) R a0 (mm) B (mm) W (mm) 1 7.04 0.1 14.119 10.03 50.02 2 6.90 0.1 14.510 10.02 50.00 3 7.24 0.1 15.049 10.04 50.05 4 7.00 0.1 15.186 10.02 50.05 5 7.00 0.1 13.987 10.03 50.02 B W a aO Fig.2 CT specimen for present study a. a - curve 0.0E+00 2.0E+06 4.0E+06 6.0E+06 8.0E+06 1.0E+07 1.2E+07 1.4E+07 1.6E+07 0 1 2 3 4 ∆a (mm) (cycles) b. da /d -∆K data 1.0E-08 2.1E-07 4.1E-07 6.1E-07 8.1E-07 1.0E-06 1.2E-06 0 2 4 6 8 ∆K (MPa.m^0.5) da /d (mm.cycle^-1) da/dN-∆K data ∆Kmin data Fig. 3 Test a- and da/d -∆K data for the present material.
Table 2 Minimum da/d -∆K data from the present tests Specimen da/d min (mm.cycle -1) ∆Kmin (MPa.m 1/2) 1 1.08×10-7 4.7125 2 1.79×10-7 5.0718 3 1.30×10-7 4.7687 4 1.18×10-7 4.3755 5 1.02×10-7 4.2681 where Pmax is maximum value of a cyclic test load; Kmax is maximum value of stress intensity factor with respect to Pmax.
Test data for minimum stress intensity factor range, K∆ min, values and corresponding crack growth rate, da/d min, values of the specimens are given in Table 2.
Mechanical properties are around 188 GPa for Young's modulus, 254 MPa 0.2% proof strength, 453 MPa ultimate tensile strength, 26 % elongation, and 45 % reduction of area.
In the test process, test loading level of stress intensity factor range, ∆K, is defined as ( ) max1 KRK −=∆ ; ( )WafWBPK maxmax = ; ( ) ( )( ) ( ) 5.1 4 3 2 126.572.1432.1364.4886.0 αααα αα −+ −+−+=Waf ; Wa=α (1) ×100 150µm c ×100 150µm b ×500 50µm ferrite pearlite a Table 1 Specimen geometries and initial loading levels Specimen ∆K0 (MPam 1/2) R a0 (mm) B (mm) W (mm) 1 7.04 0.1 14.119 10.03 50.02 2 6.90 0.1 14.510 10.02 50.00 3 7.24 0.1 15.049 10.04 50.05 4 7.00 0.1 15.186 10.02 50.05 5 7.00 0.1 13.987 10.03 50.02 B W a aO Fig.2 CT specimen for present study a. a - curve 0.0E+00 2.0E+06 4.0E+06 6.0E+06 8.0E+06 1.0E+07 1.2E+07 1.4E+07 1.6E+07 0 1 2 3 4 ∆a (mm) (cycles) b. da /d -∆K data 1.0E-08 2.1E-07 4.1E-07 6.1E-07 8.1E-07 1.0E-06 1.2E-06 0 2 4 6 8 ∆K (MPa.m^0.5) da /d (mm.cycle^-1) da/dN-∆K data ∆Kmin data Fig. 3 Test a- and da/d -∆K data for the present material.
Table 2 Minimum da/d -∆K data from the present tests Specimen da/d min (mm.cycle -1) ∆Kmin (MPa.m 1/2) 1 1.08×10-7 4.7125 2 1.79×10-7 5.0718 3 1.30×10-7 4.7687 4 1.18×10-7 4.3755 5 1.02×10-7 4.2681 where Pmax is maximum value of a cyclic test load; Kmax is maximum value of stress intensity factor with respect to Pmax.
Test data for minimum stress intensity factor range, K∆ min, values and corresponding crack growth rate, da/d min, values of the specimens are given in Table 2.
Online since: January 2012
Authors: Yue Tang, Wen Min Tu
The mechanical properties of WPC are influenced by many factors, such as the moisture content of the raw materials, temperature in processing and molding pressure, When wood powder moisture content is higher, the process is more prone to "bridge" and "hold stem" phenomenon, and this charging discontinuous can make products production down and reduce the performance.
The conveyor plate conveying materials affect analysis Tab.3 The gliding angles of wood powder, PVC, the mixture of wood powder and PVC when they slide from the top surface of the conveyor plate at each heating temperature T /℃ angle/° 40 50 60 70 80 90 100 110 120 130 140 wood powder 25 24 22 20 22 21 20 21 20 22 22 PVC 26 27 29 31 37 glue the mixture 26 20 20 21 23 22 23 23 glue It could be saw that PVC and the mixture of wood powder and PVC glued with conveyor plate respectively at the heating temperature 90 ℃ and 120 ℃from table 3, sticky materials effect as shown in figure 3 and 4. it was just that PVC softened at 82 ℃and adsorbed on conveyor plate, but mixture began to stick material at 110 ℃.
(3)The friction coefficient of the mixture of wood powder and PVC is much smaller than PVC powder alone in the transmission process, because the PVC is easy to soften and sticky, synthesizing every factor, selecting 80 ℃ as the drying temperature of transportation and the effect is best.
The conveyor plate conveying materials affect analysis Tab.3 The gliding angles of wood powder, PVC, the mixture of wood powder and PVC when they slide from the top surface of the conveyor plate at each heating temperature T /℃ angle/° 40 50 60 70 80 90 100 110 120 130 140 wood powder 25 24 22 20 22 21 20 21 20 22 22 PVC 26 27 29 31 37 glue the mixture 26 20 20 21 23 22 23 23 glue It could be saw that PVC and the mixture of wood powder and PVC glued with conveyor plate respectively at the heating temperature 90 ℃ and 120 ℃from table 3, sticky materials effect as shown in figure 3 and 4. it was just that PVC softened at 82 ℃and adsorbed on conveyor plate, but mixture began to stick material at 110 ℃.
(3)The friction coefficient of the mixture of wood powder and PVC is much smaller than PVC powder alone in the transmission process, because the PVC is easy to soften and sticky, synthesizing every factor, selecting 80 ℃ as the drying temperature of transportation and the effect is best.
Online since: May 2011
Authors: Chun Lin He, Cheng Zhong Gong, Yue Xin She, Wen Bin Sun
Physical parameters of the main mechanical rock were shown in table 1.
The side resistance was affected by many factors, including the strength of pile, its diameter, rock characteristics around the pile, initial stress of the rock.
Tip resistance affected not only with the strength of the bearing layer, but also with depth buried in rock, tip diameter, tip displacement and the intensity of rock.
The results show that the bearing property of segment in mud rock area is similar to the friction piles.
The side resistance was affected by many factors, including the strength of pile, its diameter, rock characteristics around the pile, initial stress of the rock.
Tip resistance affected not only with the strength of the bearing layer, but also with depth buried in rock, tip diameter, tip displacement and the intensity of rock.
The results show that the bearing property of segment in mud rock area is similar to the friction piles.
Online since: October 2013
Authors: Xiang Hong Fu
Among the factors affecting concrete durability, permeability responds to the density of concrete and the ability of concrete resisting external medium penetration into the concrete.
Researches showed that multi-step mixing can improve the internal pore structure of concrete and the working performance and mechanical property and durability of concrete without any increase in raw material and without extended mixing time.
Researches showed that multi-step mixing can improve the internal pore structure of concrete and the working performance and mechanical property and durability of concrete without any increase in raw material and without extended mixing time.
Online since: August 2014
Authors: Yun Peng, Ai Min Gong, Hai Yan Huang
To solve this problem, system-level equality constraints are modified with a relax factor [5], the penalty-function method [6].
(1) Design Variables Main independent design parameters affecting the spring’s working performance are the spring wire diameter d, mean diameter of coil D, number of effective coils n .Therefore, in the spring optimization model, the variables are (2) (2) Objective function Optimal design object of spring should be maximizing the economic benefit.
In order to guarantee the spring’s normal work, spring working stress should be less than or equal to the allowable shear stress, namely (6) Where F is the applied load; k is the curvature correction factor .
(3) In a word, the whole mechanical characters of the MOCO final design case are better than the initial design and the other three design case. 5 Conclusions A multi-objective collaborative optimization model was used to optimize a spring structure.
Multi-objective Optimum Design of Structural and Property Parameters for Spring[J].
(1) Design Variables Main independent design parameters affecting the spring’s working performance are the spring wire diameter d, mean diameter of coil D, number of effective coils n .Therefore, in the spring optimization model, the variables are (2) (2) Objective function Optimal design object of spring should be maximizing the economic benefit.
In order to guarantee the spring’s normal work, spring working stress should be less than or equal to the allowable shear stress, namely (6) Where F is the applied load; k is the curvature correction factor .
(3) In a word, the whole mechanical characters of the MOCO final design case are better than the initial design and the other three design case. 5 Conclusions A multi-objective collaborative optimization model was used to optimize a spring structure.
Multi-objective Optimum Design of Structural and Property Parameters for Spring[J].
Online since: March 2011
Authors: Ling Hui Sun, Wei Dong Liu
However, the adsorption process is hard to be observed under current lab technique; also the adsorption time at the liquid-solid interface is the key factor of wetting efficiency.
In addition, according to kinetic parameters, the property changes of quartz particles surface after having adsorbed CTAB has been analyzed, the adsorption behavior of CTAB at the liquid-solid interface, and the microscopic essentials of wettability alteration have been further understood.
First of all, took 10mL CTAB solution with certain concentration into the stainless steel safety bottle, then added 0.1g quartz, the quartz and CTAB were mixed to disperse system by 60r·min-1 mechanical stir, then the heat effect curve and thermal effect data were tracked and collected by the Digitam4.1 software.
Fig.2 Fitting plot of the kinetic model Table 1 T/K 293 303 313 323 qe/(mmol·g-1) 0.036 0.028 0.019 0.016 W/mJ 12.4 9.6 8.4 8.1 k 0.312 0.256 0.236 0.224 Effects of CTAB solution on the quartz surface Zeta potential:The electrical properties of quartz surface directly affect the adsorption of CTAB solutions on its surface and the wettability of CTAB solution Zeta potentials of quartz in CTAB solution at different temperatures are shown in Figure 3.
In addition, according to kinetic parameters, the property changes of quartz particles surface after having adsorbed CTAB has been analyzed, the adsorption behavior of CTAB at the liquid-solid interface, and the microscopic essentials of wettability alteration have been further understood.
First of all, took 10mL CTAB solution with certain concentration into the stainless steel safety bottle, then added 0.1g quartz, the quartz and CTAB were mixed to disperse system by 60r·min-1 mechanical stir, then the heat effect curve and thermal effect data were tracked and collected by the Digitam4.1 software.
Fig.2 Fitting plot of the kinetic model Table 1 T/K 293 303 313 323 qe/(mmol·g-1) 0.036 0.028 0.019 0.016 W/mJ 12.4 9.6 8.4 8.1 k 0.312 0.256 0.236 0.224 Effects of CTAB solution on the quartz surface Zeta potential:The electrical properties of quartz surface directly affect the adsorption of CTAB solutions on its surface and the wettability of CTAB solution Zeta potentials of quartz in CTAB solution at different temperatures are shown in Figure 3.
Online since: September 2007
Authors: Li Yang Xie, Xue Hong He
A Statistical Load Weighted Average Fatigue Reliability Model for
uncertain constant amplitude cyclic load
Liyang Xiea and Xuehong Heb
Dept. of Mechanical Engineering, Northeastern University, Shenyang, 110004, China
a
lyxie@me.neu.edu.cn, bxhhe@me.neu.edu.cn
Keywords: Fatigue reliability; Life distribution; Cyclic load; Statistical average model.
Let f(n,y*) denotes the pdf of the fatigue life under a deterministic cyclic stress with constant amplitude y*, then the probability that the fatigue life n is greater than a specified value N, i.e. the fatigue reliability to life N is ∫∞= N dnynfyNR *),(*),( (6) Evidently, the only uncertainty in Eq.6 is in the fatigue life arising from material property.
On the other hand, the uncertainty in cyclic stress is one of the most important factors to affect fatigue reliability.
Let f(n,y*) denotes the pdf of the fatigue life under a deterministic cyclic stress with constant amplitude y*, then the probability that the fatigue life n is greater than a specified value N, i.e. the fatigue reliability to life N is ∫∞= N dnynfyNR *),(*),( (6) Evidently, the only uncertainty in Eq.6 is in the fatigue life arising from material property.
On the other hand, the uncertainty in cyclic stress is one of the most important factors to affect fatigue reliability.
Online since: March 2010
Authors: Ju Yan Liu, Zhi Xia He, Qian Wang, Jian Ping Yuan
During the
working progress, the change of the lubricant's temperature can heavily affect its viscidity and further
the lubricate performance of the whole journal bearings [1-4], so it's necessary to couple the Reynolds
equation, energy equation and thermal balance equation to perform a THD computation.
Fig.1 shows the dynamic loads in direction of x and y acted upon the main shaft bearing .The basic computational parameters of the journal bearing and physical property data of lubricant are shown in fig.2.
Besides, the visualization of software is gradually certain to be one of the important factors in developing the computation software.
Maneshian: Proceedings of the Institution of Mechanical Engineers.
Fig.1 shows the dynamic loads in direction of x and y acted upon the main shaft bearing .The basic computational parameters of the journal bearing and physical property data of lubricant are shown in fig.2.
Besides, the visualization of software is gradually certain to be one of the important factors in developing the computation software.
Maneshian: Proceedings of the Institution of Mechanical Engineers.
Online since: December 2014
Authors: Chao Yu, Zi Ning Tang, Zhi Guo Kong
The results of the busses route operating shows that the optimization method works well and the busses have good performances in fuel economy, dynamic property and comfort.
The working points of the engine are affected by the generator.
The response of the engine is restricted not only by the ability, but also by the temperature, the smoke density, and other possible factors [10].
Improvement in fuel economy for a parallel hybrid electric vehicle by continuously variable transmission ratio control, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 219, pp. 43-51, 2005 [2] Lukic, SM, Emadi A.
The working points of the engine are affected by the generator.
The response of the engine is restricted not only by the ability, but also by the temperature, the smoke density, and other possible factors [10].
Improvement in fuel economy for a parallel hybrid electric vehicle by continuously variable transmission ratio control, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 219, pp. 43-51, 2005 [2] Lukic, SM, Emadi A.
Online since: July 2014
Authors: P. Parthiban, C. Arumugam, T.G. Arul
Plant size is one of the key factors that influence the implementation of lean manufacturing.
The fuzzy measure makes monotonicity instead of additive property.
This study deals with the identification of critical factors that affect the implementation of lean manufacturing in Indian MSMEs and evaluating the performance of MSMEs with respect to these criteria.
Identification of factors The factors the affect the implementation of lean manufacturing was identified through extensive literature review and expert consultation.
This implies that E is the most consistent with the performance factors.
The fuzzy measure makes monotonicity instead of additive property.
This study deals with the identification of critical factors that affect the implementation of lean manufacturing in Indian MSMEs and evaluating the performance of MSMEs with respect to these criteria.
Identification of factors The factors the affect the implementation of lean manufacturing was identified through extensive literature review and expert consultation.
This implies that E is the most consistent with the performance factors.