Studying the effects of various parameters on the behavior of velocity, temperature and thus the entropy generation rate in the microfluidic systems to reduce loss power is very important. Minimization of entropy generation in the flow system enables us for the parametric optimization of the MHD micropumps operation. In the present study, a transient, laminar and fully developed electrically conductive fluid flow in MHD micropumps has been investigated and the temperature distribution and effects of dimensionless influencing parameters on the entropy generation rate has been presented. Pumping operator in MHD micropumps are the Lorentz forces, which is produced as a result of the interaction between magnetic and electric fields. Governing equations have been solved numerically using finite-difference (ADI) method. The results of simulation have shown good agreement with analytical results by ei-genfunction expansion method. In addition, the results are compared with experimental data from literature which confirms the accuracy of the model. The obtained results showed that aspect ratio, Hartman, Prandtl, Eckert numbers and Joule heating parameter have significant influences on the flow and temperature distribution as well as entropy generation rate in MHD micropumps that controlling them can lead us for optimized operation of MHD micropumps.
The most common index for representing structural condition of the pavement is the structural number. The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests, recording pavement surface deflections, and analyzing recorded deflections by back-calculation manners. This procedure has two drawbacks: falling weight deflectometer and ground-penetrating radar are expensive tests; back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach. In this study, three machine learning methods entitled Gaussian process regression, M5P model tree, and random forest used for the prediction of structural numbers in flexible pavements. Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes “structural number” as output and “surface deflections and surface temperature” as inputs. The accuracy of results was examined based on three criteria of R, MAE, and RMSE. Among the methods employed in this paper, random forest is the most accurate as it yields the best values for above criteria (R=0.841, MAE=0.592, and RMSE=0.760). The proposed method does not require to use ground penetrating radar test, which in turn reduce costs and work difficulty. Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy. 相似文献
The flux diffusion into a superconducting long rod of square cross-section in the flux flow regime is investigated numerically
for sinusoidal variations of the external magnetic field. The real and imaginary parts of first harmonic as well as its penetration
depth are determined in function of the field frequency. This penetration depth, which decreases exponentially in function
of the frequency, is influenced by the change of the flux front shape from square to circular at low frequencies and seems
to be a scaling length for both components of the first harmonic. 相似文献
The influence of nanoconfinement on segmental relaxation behavior of poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile) miscible blend and its nanocomposites with spherical and layered nanoparticles have been investigated. Dynamic mechanical analysis was employed to examine the effect of geometry of nanoparticles on the temperature dependence and relaxation function breadth of segmental dynamics (α-relaxation) in the glass transition region. The maxima of the loss modulus curves were used to fit to the Vogel–Fulcher–Tamman equation to describe the temperature dependence of the characteristic relaxation times. Furthermore, the Tg-normalized semi-logarithmic Arrhenius plots (fragility plots) were exploited to indicate the changes in cooperative segmental motions across the glass transition. The master curves for relaxation modulus were also constructed for each sample as a function of time using the time–temperature superposition principle. The investigated nanocomposites showed a narrower segmental dispersion in the glass transition region compared to the neat systems. The relaxation modulus master curves were fitted by the Kohlrausch–Williams–Watts (KWW) function. It was observed that the distribution parameter of segmental relaxation time increased with addition of nanoparticles which was correlated with a decrease in fragility index. In addition, the increase of the KWW distribution parameter (βKWW) for spherical silica nanocomposites was less than that for nanocomposites prepared with layered silicates (organoclay). 相似文献
Power line communication technology is used in various applications, from high voltage network to the low voltage network, as it is the only wired communication technology that is comparable with wireless communication network. It works by injecting a modulated carrier wave into the electric cables from one transceiver to another. But still, the noise level and impedance mismatch are still the main concern of this technology, particularly in the low voltage network in residential area. Power line has additive non-white noise and extremely harsh environment for communication. At the same time, there is signal attenuation along the power line caused by the impedance mismatch in the power line network. Even though these problems can be controlled using a band-pass filter and an impedance matching circuit respectively, but the impedances in the power line are time and location variant and it is rather difficult to design a circuit that allows maximum power transfer in the system all the time. Thus in this paper, a new adaptive impedance matching circuits is proposed for narrowband power line communication. This methodology is derived based on the RLC band-pass filter circuit. This concept is designed to achieve simpler configuration and higher matching resolution. 相似文献
In the present work, a mathematical model was developed based on finite difference method to predict the microporosity distribution in A356 aluminum alloy casting. Heat, mass, and gas conservation equations were solved in this model. Moreover, Darcy’s equation was considered in the mushy zone. Results show that the distribution and concentration of microporosities in cast parts vary with both cooling rate and initial gas content. Simulation results were compared with experimental data where proportionally good agreement with experimental results was found. Finally, a complex cast part was simulated presenting the ability of the model to predict the porosities in industrial cast parts. 相似文献