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Online since: February 2013
Authors: De Yu Tu, Xu Wang, Ai Hua Xu, Xin Chen, Yun Hu
In this paper, the mechanical characteristics of the die holes were analyzed to set up mathematical model in the briquettes forming process.
Jens etc. [4-5] established the mechanical characteristics model of the ring die pelletizing process and the testing results showed the model accuracy.
The finite element mesh model of the die hole is shown in fig.3 and the object material properties are shown in table 2.
Conclusions In this paper, the mechanical characteristics of die holes were analyzed to set up mathematical model in the briquettes forming process.
So that, the inlet angle should be determined by the overall consideration of various factors. 4) If other structural parameters are determinate and equivalent, the length-diameter ratio could impact on the stress distribution of the die hole in shave-preserving section.
Jens etc. [4-5] established the mechanical characteristics model of the ring die pelletizing process and the testing results showed the model accuracy.
The finite element mesh model of the die hole is shown in fig.3 and the object material properties are shown in table 2.
Conclusions In this paper, the mechanical characteristics of die holes were analyzed to set up mathematical model in the briquettes forming process.
So that, the inlet angle should be determined by the overall consideration of various factors. 4) If other structural parameters are determinate and equivalent, the length-diameter ratio could impact on the stress distribution of the die hole in shave-preserving section.
Online since: May 2011
Authors: Chen Lu Zhang, Ping Li, Pei Gen Zhou, Xiao Rong Pan, Yan Wang
However, there is no further research on how physical structure and properties of composite carriers would affect the kinetic properties of the immobilized enzyme.
Determination of optimum pH The pH is one of the most significant factors that affect the enzyme-catalyzed reaction.
Kinetics of immobilized chitosanase with different carriers The Km value is considered to be as a measure of affinity between the enzyme and the substrate, which would be affected by carrier with electrical properties.
One is the electrical properties of carrier that affect the affinity between the enzyme and the substrate, the other is the spatial three-dimensional obstacles or diffusion resistance of the immobilized enzyme which can lead to Km value increasing.
The results showed that the pH and Km values of immobilized chitosanase were significantly affected by electrical properties and spatial three-dimensional obstacles of carriers, respectively.
Determination of optimum pH The pH is one of the most significant factors that affect the enzyme-catalyzed reaction.
Kinetics of immobilized chitosanase with different carriers The Km value is considered to be as a measure of affinity between the enzyme and the substrate, which would be affected by carrier with electrical properties.
One is the electrical properties of carrier that affect the affinity between the enzyme and the substrate, the other is the spatial three-dimensional obstacles or diffusion resistance of the immobilized enzyme which can lead to Km value increasing.
The results showed that the pH and Km values of immobilized chitosanase were significantly affected by electrical properties and spatial three-dimensional obstacles of carriers, respectively.
Online since: May 2014
Authors: Yan Lin, Jiao Gao
Study on Thermal Conductivities of Composite Adsorbents for Adsorption Refrigeration
Lin Yan1 , Gao Jiao1
The College of Mechanical and Electrical Engineering, QUST University, Qing dao266061 China
Key words: adsorption refrigeration thermal conductivity curing density anisotropy
Abstract.
For this, the development of an adsorbent with low regeneration temperature and high heat-transfer property has become one of the hot topics in the adsorption refrigeration field [1].
This indicates that curing density and quality, the two factors that affect the heat conductivity coefficient of Cacl2/ENG molding compound adsorbent, do not exist in isolation.
(3)The curing density and the mass ratio between calcium chloride and expanded graphite that affect the heat-conducting property of compound adsorbent are coupled with each other.
Experimental Study on Permeability and Heat-conducting Property of Compound Adsorbent [D].
For this, the development of an adsorbent with low regeneration temperature and high heat-transfer property has become one of the hot topics in the adsorption refrigeration field [1].
This indicates that curing density and quality, the two factors that affect the heat conductivity coefficient of Cacl2/ENG molding compound adsorbent, do not exist in isolation.
(3)The curing density and the mass ratio between calcium chloride and expanded graphite that affect the heat-conducting property of compound adsorbent are coupled with each other.
Experimental Study on Permeability and Heat-conducting Property of Compound Adsorbent [D].
Online since: December 2012
Authors: Jun Tan
Introduction
The product quality which satisfy and exceed even expect of customer is the key factor for enterprise to success in competitive market.
The method can identify the features of producing welded ball defect and determine the notable features of affecting product quality.
Sterjovski [6] proposed a back-propagation neural networks model to predict mechanical property of steel in all kinds of applications.
The purpose of ARMS is to obtain distributed process data from different process, transform data into knowledge in the form of association rules, and propose advices on the correct combination of process parameters for producing active affect on product quality improvement.
Artificial neural networks for modeling the mechanical properties of steels in various applications [J].
The method can identify the features of producing welded ball defect and determine the notable features of affecting product quality.
Sterjovski [6] proposed a back-propagation neural networks model to predict mechanical property of steel in all kinds of applications.
The purpose of ARMS is to obtain distributed process data from different process, transform data into knowledge in the form of association rules, and propose advices on the correct combination of process parameters for producing active affect on product quality improvement.
Artificial neural networks for modeling the mechanical properties of steels in various applications [J].
Online since: January 2010
Authors: M.C.S. Ribeiro, L.F.P. Juvandes, J.D. Rodrigues, António Torres Marques, Antonio Ferreira
Accordingly,
several efforts have been made towards a systematic quest for standardization of test methodologies
and an understanding of factors influencing the resistance of concrete to freezing and thawing.
Mechanical Test Results.
Freeze-Thaw Cycles Freeze-Thaw Cycles Relative Dynamic Modulus of Elasticity (%) Relative Mechanical Strength (%) CM-0 PM-0 a) b) c) Considering a linear variation of relative dynamic modulus of elasticity between 36 and 72 cycles, durability factors of 12.78% or 9.20% were obtained for this cement based composition, depending on the total amount of freeze-thaw cycles considered for the end of experimental program (216 or 300 cycles).
The flexural and compressive strengths were also severely affected.
Mitchell, in: Significance of Tests and Properties of Concrete and Concrete-Making Materials -STP 169C, edited by P.
Mechanical Test Results.
Freeze-Thaw Cycles Freeze-Thaw Cycles Relative Dynamic Modulus of Elasticity (%) Relative Mechanical Strength (%) CM-0 PM-0 a) b) c) Considering a linear variation of relative dynamic modulus of elasticity between 36 and 72 cycles, durability factors of 12.78% or 9.20% were obtained for this cement based composition, depending on the total amount of freeze-thaw cycles considered for the end of experimental program (216 or 300 cycles).
The flexural and compressive strengths were also severely affected.
Mitchell, in: Significance of Tests and Properties of Concrete and Concrete-Making Materials -STP 169C, edited by P.
Online since: August 2016
Authors: Waddah Al Hawat, Osama Ahmed Mohamed
Mohamed, Rens K L, Stalnaker J J Factors Affecting Resistance of Concrete to Freezing and Thawing Damage.
Marian, Comparing the performance of fine fly ash and silica fume in enhancing the properties of concrete containing fly ash, J.
Supit, Compressive strength and durability properties of high volume fly ash (HVFA) concretes containing ultrafine fly ash (UFFA), J.
Gołaszewski J, The effect of high-calcium fly ash on selected properties of self-compacting concrete, Archives in Civil and Mechanical Engineering, Elsevier 2014; 14: pp. 455-465
Siddique, Properties of self-compacting concrete containing class F fly ash.
Marian, Comparing the performance of fine fly ash and silica fume in enhancing the properties of concrete containing fly ash, J.
Supit, Compressive strength and durability properties of high volume fly ash (HVFA) concretes containing ultrafine fly ash (UFFA), J.
Gołaszewski J, The effect of high-calcium fly ash on selected properties of self-compacting concrete, Archives in Civil and Mechanical Engineering, Elsevier 2014; 14: pp. 455-465
Siddique, Properties of self-compacting concrete containing class F fly ash.
Online since: February 2014
Authors: Ravikant Gupta, J. Prasanna, T. Monisha, V. Ranjithabala, E. Vijayakumar, D. Sangeetha
This enhanced property combined with its biodegradable nature, makes it a fascinating polymer to produce nanofibers.
Taguchi method is one of the best methods to arrive at an optimum solution to a particular problem, given the influence of various factors at different levels [3].
Since voltage, flow rate, distance and concentration are the major process parameters that affect the diameter of the fiber, they were chosen for the study [4-6].
Voltage proves to be the second most significant parameter in affecting the diameter of the polymer fiber.
Concentration appears to be the most significant parameter in affecting the diameter of the polymer fiber.
Taguchi method is one of the best methods to arrive at an optimum solution to a particular problem, given the influence of various factors at different levels [3].
Since voltage, flow rate, distance and concentration are the major process parameters that affect the diameter of the fiber, they were chosen for the study [4-6].
Voltage proves to be the second most significant parameter in affecting the diameter of the polymer fiber.
Concentration appears to be the most significant parameter in affecting the diameter of the polymer fiber.
Online since: September 2011
Authors: M. Zadshakoyan, E.Abdi Sobbouhi, H. Jafarzadeh
Throughout a specific analysis a constant friction factor was considered on the die-workpiece contacting surface and the initial diameter of the billet was equal to that of the root circle of the gear.
Experimental 3.1Material properties Compression tests were performed on commercial lead billets using workpieces of 20 mm in diameters and 30 mm in height (h/d=1.5) to obtain true stress-strain data.
For instance, in the numerical simulation the friction factor is considered to be constant during the process while in the real condition the friction factor varies during the forming and it will affect the differences between two results.
This result shows that the teeth and specially the root area are the most affected area of the forged gears. 4.
[3] N.R.Chitkara, M.A.Butta, “Forging and heading of hollow spur gear forms: an analysis and some experiments”, International Journal of Mechanical sciences 41, 1999, pp. 1159-1189
Experimental 3.1Material properties Compression tests were performed on commercial lead billets using workpieces of 20 mm in diameters and 30 mm in height (h/d=1.5) to obtain true stress-strain data.
For instance, in the numerical simulation the friction factor is considered to be constant during the process while in the real condition the friction factor varies during the forming and it will affect the differences between two results.
This result shows that the teeth and specially the root area are the most affected area of the forged gears. 4.
[3] N.R.Chitkara, M.A.Butta, “Forging and heading of hollow spur gear forms: an analysis and some experiments”, International Journal of Mechanical sciences 41, 1999, pp. 1159-1189
Online since: November 2012
Authors: Yoshihiko Uematsu, Toshifumi Kakiuchi, Yasunari Tozaki
The onion structure could be crack initiation sites and crack growth paths resulting in the harmful affect on the fatigue behavior.
The chemical composition and the mechanical properties are shown in Table 1 and Table 2.
Table 2 Mechanical properties of A356-T6 aluminum alloy.
intensity factor Kmax.
(b) Relationship between crack growth rate da/dN and maximum stress intensity factor Kmax.
The chemical composition and the mechanical properties are shown in Table 1 and Table 2.
Table 2 Mechanical properties of A356-T6 aluminum alloy.
intensity factor Kmax.
(b) Relationship between crack growth rate da/dN and maximum stress intensity factor Kmax.
Online since: August 2013
Authors: Xu Li Liang, Fei Wang, Gang Li Hao
But in practical engineering,rock mass is in three- dimension stress state.So it is essential to establish the three- dimension constitutive model of unloading rock mass throughout the study on the relationship between load variety and rock mass property.
The mortar is simulated material.Mortar mix ratio, mechanical parameters and model similarity constants are shown in Table.1~Table.2.
Table.1 Ratio and mechanical parameters for mortar model sample ratio Unit weight (kN/m3) elastic modulus (Gpa) compressive strength (MPa) tensile strength (MPa) cohesive force (MPa) internal frictional angle (°) cement water Sand HC 1.33 1 5.96 2.03 6.67 14.3 1 0.21 54 Table.2 Similarity ratio for mortar model physical quantity length (m) elastic modulus (GPa) stress (MPa) strain cohesive force (MPa) similarity ratio 9 9 9 2.9 9 Geometric Parameters of Test Model (1) A group of structural surface Structural plane is divided into three groups: NWW(included angel )group ; NEE(included angel)group ; EW(included angel)group .Characteristics of the structural plane is shown in table 3
Table4.Correlative data of EW joint stage 1 2 3 4 5 6 7 8 9 10 11 Et 25.904 25.116 18.234 15.255 12.884 9.978 7.409 6.669 5.953 5.756 5.379 J2/MPa 6.363 2.216 0.473 0.485 0.996 1.481 2.078 2.884 3.796 4.710 5.341 T/MPa 4.931 3.426 2.289 1.531 0.889 0.497 0.165 -0.166 -0.491 -0.774 -0.957 P/MPa 6.928 5.423 4.286 3.528 2.886 2.494 2.162 1.831 1.507 1.223 1.040 D(area density) 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 θ -0.637 -0.321 0.322 0.409 0.179 0.323 0.423 0.504 0.566 0.608 0.631 Et/E0 1.000 0.970 0.704 0.589 0.497 0.385 0.286 0.257 0.230 0.222 0.208 Unloading Parameter Illustration Many factors affect unloading constitutive relation.According to test results and sensitivity analysis,some main factors were considered,such as the second invariant of deviatoric stress tensor, lode parameter, normal stress and shear stress of structure surface, initial deformation modulus etc,The symbols of parameters are as follows: the second invariant of deviatoric stress
The mortar is simulated material.Mortar mix ratio, mechanical parameters and model similarity constants are shown in Table.1~Table.2.
Table.1 Ratio and mechanical parameters for mortar model sample ratio Unit weight (kN/m3) elastic modulus (Gpa) compressive strength (MPa) tensile strength (MPa) cohesive force (MPa) internal frictional angle (°) cement water Sand HC 1.33 1 5.96 2.03 6.67 14.3 1 0.21 54 Table.2 Similarity ratio for mortar model physical quantity length (m) elastic modulus (GPa) stress (MPa) strain cohesive force (MPa) similarity ratio 9 9 9 2.9 9 Geometric Parameters of Test Model (1) A group of structural surface Structural plane is divided into three groups: NWW(included angel )group ; NEE(included angel)group ; EW(included angel)group .Characteristics of the structural plane is shown in table 3
Table4.Correlative data of EW joint stage 1 2 3 4 5 6 7 8 9 10 11 Et 25.904 25.116 18.234 15.255 12.884 9.978 7.409 6.669 5.953 5.756 5.379 J2/MPa 6.363 2.216 0.473 0.485 0.996 1.481 2.078 2.884 3.796 4.710 5.341 T/MPa 4.931 3.426 2.289 1.531 0.889 0.497 0.165 -0.166 -0.491 -0.774 -0.957 P/MPa 6.928 5.423 4.286 3.528 2.886 2.494 2.162 1.831 1.507 1.223 1.040 D(area density) 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 4.500 θ -0.637 -0.321 0.322 0.409 0.179 0.323 0.423 0.504 0.566 0.608 0.631 Et/E0 1.000 0.970 0.704 0.589 0.497 0.385 0.286 0.257 0.230 0.222 0.208 Unloading Parameter Illustration Many factors affect unloading constitutive relation.According to test results and sensitivity analysis,some main factors were considered,such as the second invariant of deviatoric stress tensor, lode parameter, normal stress and shear stress of structure surface, initial deformation modulus etc,The symbols of parameters are as follows: the second invariant of deviatoric stress