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Online since: July 2014
Authors: Habib Mohamadian, Zheng Mao Ye
The engine operating modes also affect engine exhaust emission levels directly.
It can capture cycle-to-cycle dynamics affecting exhaust temperature according to thermodynamics.
The temperature factor should be fully taken into account for more accurate LNT storage model and purge models to optimize the powertrain overall performance [8].
Simplified Exhaust Temperature Model Despite the fact that numerous engine parameters affect exhaust temperature, such as engine speed, engine load, A/F ratio, intake air temperature, coolant temperature, spark timing, cylinder pressure, and so on, there is no doubt that engine speed and engine load serve as two key factors of engine exhaust temperature.
Since the Markov chain has properties of ergodic, aperiodic and reversible, it produces a dependent sequence of random variables which eventually reaches the stationary distribution or equilibrium distribution, which is equal to the ergodic limit.
Online since: February 2015
Authors: Lilla Nádai, Bálint Katona, Eszter Bognár
Titanium and its alloys have low density compared to other metals of similar mechanical and thermal properties.
The conclusion was, the titanium surface etched with H2SO4 and HCl according to its topography combines the main properties of roughened titanium surface: glossily micro rough and large waviness.
Major factors for industry appliance are the reproducibility and productivity; therefore, we took into account at the surface treatment the low material decrease and shortest etching time.
Ahossi et al, Biological properties of acid etched titanium implants: effect of sandblasting on bone anchorage, J.
Muller, Relationship between surface properties (roughness,wettability and morphology) of titanium and dental implant removal torque, Journal of the Mechanical Behavior of Biomedical Materials 1 (2008) 234-242
Online since: September 2021
Authors: Svetlana N. Morozkina, Petr P. Snetkov, Roman O. Olekhnovich, Mayya Valerievna Uspenskaya
Hyaluronic acid is one of the most promising polymers for nanofiber formation due to its unique biological and biochemical properties.
Obviously, the composition of the spinning polymer solution can affect both the formation process of nanofibers and the morphological, physico-mechanical, physico-chemical, and biological properties of the resulting polymer nanofibers.
This study eliminates the shortcomings of fundamental knowledge of the relations of technological factors such as applied voltage and flow volume rate and the morphological characteristics of nanofibers obtained from aqueous-organic solutions of hyaluronic acid.
By changing the applied electrical voltage and flow volume rate the nanofiber with required set of properties could be obtained.
Cui, Effects of ambient relative humidity and solvent properties on the electrospinning of pure hyaluronic acid nanofibers, J.
Online since: October 2009
Authors: Yoshio Bando, Atsuro Yokoyama, Fumio Watari, Motohiro Uo, Masato Suzuki, N. Takashi, T. Akasaka, Y. Totsuka, Shigeaki Abe, Yoshinori Kuboki, I.D. Rosca, E. Hirata, M. Matsuoka, K. Ishikawa, S. Itoh, Y. Yawaka, N. Terada, Y. Kitagawa
Imogolite showed the similar properties to CNTs.
Then their feature and difference of properties were investigated.
Then what is the reason that graphite and CNTs show the inverse properties?
On structural view point the fibrous nano-meshwork structure of agglomeration of CNTs contains the large porosity where cells can take nutrient elements or growth factors.
On CNT scaffold, however, cells were going to detach and float up, but could not separate because of the mechanical binding of filopodia with CNT network (Fig.8), which demonstrates the good cell adhesion properties of CNTs.
Online since: August 2014
Authors: Kai Yuan Chen, Meng Xue Yan, Ying Wang, Nan Qiao Zhou
Injection Speed Control of Precision Injection Molding Based on CMAC Neural Network Kaiyuan Chen1 ,Mengxue Yan2 ,Ying Wang3 and Nanqiao Zhou4 1,2,3Department of Mechanical and Electrical Engineering, Foshan Polytechnic College, Foshan 528137, China 4Key Laboratory of Polymer Processing Engineering of Ministry of Education, National Engineering Research Center of Novel Equipment for Polymer Processing, South China University of Technology, Guangzhou 510640, China Keywords: CMAC; neural network; injection speed; PID control Abstract: Injection speed is one of the most important parameters during precision injection molding.
Introduction Precision injection plastic parts are widely used in many fields including machinery, electronics, communication and automobile because they have many advantages such as good mechanical property, high precision and superior dimensional stability, which replace part of high precision metal parts.
When the mathematical model of the controlled object changes and becomes nonlinear, the adjustment of PID controller is difficult according to the actual situation, which affects the control quality.
W refer to the CMAC network link weight matrix, and the parameter can be adjusted, then the i number of output can be described as (2) The learning algorithm for the CMAC network link weight matrix can be shown below: (3) where k is learning cycle, i is the number of output variable, j is the number of CMAC neuron, is learning factor with a value between 0 and 1, is desired output, is its actual output., and is vector of correlation space.
When the nozzle temperature decreases to 220℃, which affects the melt flowability, and the parameters of the control object change, from Fig. 5 it can be seen that the adjustment time of step response of injection speed using conventional PID control algorithm delays significantly, but the adjustment time using compound control algorithm of CMAC and PID almost remains unchanged.
Online since: April 2012
Authors: Sujoy S. Hazra, Azdiar Gazder, Vladimir Bata, Elena V. Pereloma
Pereloma1,c 1School of Mechanical, Materials and Mechatronic Engineering, University of Wollongong, Wollongong, Australia 2 Previously with the Department of Materials Engineering, Monash University, Clayton, Australia aazdiar@uow.edu.au, bssh755@uow.edu.au, celenap@uow.edu.au Keywords: Low carbon steels, Cr addition, annealing, recrystallization, texture.
Compared to the unalloyed steel, Cr addition significantly delays the time for recrystallisation and increases the JMAK pre-exponential factor (k) by an order of magnitude.
Both ageing processes adversely affect the final properties of LC steels such as the strength-ductility balance, formability and surface quality.
It is clear that Cr addition delays recrystallisation and significantly alters the pre-exponential factor (k) of the JMAK fit by an order of magnitude.
Summary Studies of recrystallisation behaviour in cold rolled low carbon steel with and without Cr addition shows that Cr delays recrystallisation and affects the texture and morphology of recrystallised grains.
Online since: August 2007
Authors: Masanori Kikuchi
Mechanical properties and chemical compositions of this material are shown in Table 1 and Table 2.
Table 1 Chemical Component Of A533B Steel C Si Mn P S Ni Mo 0.22 0.32 1.46 0.01 0.01 0.60 0.57 Table 2 Mechanical Property of A533B Steel Young's modulus Yield stress Tensile strength E � ys � B 206[GPa] 599[MPa] 720[MPa] � � � � Fig.1 Three point bend specimen Fracture surface observation Fracture surface is observed after dimple fracture test.
It means that shear stress affects the growth of voids near specimen surface.
In these numerical simulations void growth is assumed to be due to two factors.
J.Fracture, 47(1991), 105 [7] JSME Standard S 001-1992 (1992), Japan Society of Mechanical Engineer [8] Koers R.
Online since: July 2016
Authors: Liborio Cavaleri, Maurizio Papia, Fabio di Trapani
The latter represents an attractive and practical solution but a conspicuous number of uncertainties affect the identification of the struts.
Description of the building and modelling assumptions Building features and adopted mechanical properties.
The same reduction factor was applied to the determination of the strength of the struts in presence of openings.
According to [13] the actual shear VC on the generic column can be expressed instant by instant as function of the axial load (FS) acting on the adjacent infill-equivalent strut as: (7) where the coefficient aCSE, called shear distribution coefficient for the base cross-section of a column, has the following expressions, depending on the aspect ratio of the panel: ; (8) The parameter y appearing in Eq. (8) (whose definition can be found in [13]), identifies each specific infill-frame system accounting simultaneously for the geometrical and mechanical relative properties.
Mollaioli, Strength and Stiffness Reduction Factors for Infilled Frames with Openings, Earthquake Engineering and Engineering Vibrations 13-3 (2014) 437–54
Online since: January 2017
Authors: Derce Recouvreux, Ricardo Brandes, Alexandre Mikowski, Claudimir Carminatti, Hazim Al-Qureshi
However, it provides a material with lower mechanical properties compared to static culture.
Production of BC by stirred medium form spheres whose mechanical properties are lower when compared to properties of membranes produced in a static environment.
The BC has some limitations regarding their properties.
The primary purpose of the addition of reinforcing materials is the modification of the original properties of BC, for instance, the increase in mechanical properties.
Vogler, Factors Impacting the Formation of Sphere-Like Bacterial Cellulose, Biomacromolecules, 14 (10) (2013) 3444-3452
Online since: December 2014
Authors: Peter Hlaváč, Monika Božiková
Introduction In the quality evaluation of food material, it is important to know the physical properties, particularly mechanical, rheological and thermophysical [1–3].
The knowledge about physical properties of packaging materials is also important [4].
Values of dynamic viscosity are influenced by other factors, i.e. by the amount of fat content (for milk) and also by structure (acidophilus milk) in this case.
Zeman, Mechanical properties of polyethylene foils, Journal of Central European Agriculture, 15 (2014) 138–145
Sumnu, Physical properties of foods, Springer, USA, 2006
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