21 resultados para Mathematical Modeling


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Thrombotic stroke, which is caused by blood clot in the cerebral artery, is a major source of increased mortality and morbidity. Considering as efficient and fastest methods, mathematical approaches have gained significant importance for analyzing and understanding the biological events like thrombosis. This paper presents a computational model to analyze the effects of thrombosis using the theory of coupled fluid dynamics-structure interaction. The finite element method is used for the modeling of thrombosis (blood clot) of different stages in the middle cerebral artery with physiological compliance. The developed model is used to investigate the consequences that occur due to the various sizes of clots in the artery in the form of blood flow velocity, blood pressure, and artery wall stress. Such numerical assessment will facilitate better understanding of the biophysical process in case of thrombosis and thus would support medical practitioners to take faster curing steps.

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Smartphones are pervasively used in society, and have been both the target and victim of malware writers. Motivated by the significant threat that presents to legitimate users, we survey the current smartphone malware status and their propagation models. The content of this paper is presented in two parts. In the first part, we review the short history of mobile malware evolution since 2004, and then list the classes of mobile malware and their infection vectors. At the end of the first part, we enumerate the possible damage caused by smartphone malware. In the second part, we focus on smartphone malware propagation modeling. In order to understand the propagation behavior of smartphone malware, we recall generic epidemic models as a foundation for further exploration. We then extensively survey the smartphone malware propagation models. At the end of this paper, we highlight issues of the current smartphone malware propagation models and discuss possible future trends based on our understanding of this topic. © © 2014 IEEE.

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Ionic polymers have attracted considerable attention due to their interesting sensing and actuating behavior which make them a proper choice for use in a wide range of applications including biomimetic robots and biomedical devices. The complicated electro-chemo-mechanical dynamics of ionic polymer actuators is a drawback for their applications in functional devices. Therefore, establishing a mathematical model which could effectively predict the actuators' dynamic behavior is of great interest. In this paper, a mathematical model, named equivalent dynamic thermoviscoelastic (EDT) model, based on thermal analogy and beam theory is proposed for dynamic analysis of bending-type ionic polymer actuators. Then, the developed model is extended for analyzing the performance of the actuator in finite element software. The finite element analysis of the actuator enables consideration of material and geometric nonlinearities and facilitates modeling of functional devices based on the ionic polymer actuators. The proposed modeling approach is validated using experimental data.

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This research analyses the mathematical model of the PV array with all the parameters involved, in the sequential steps. Then it is going to simulate the I-V and P-V characteristics of PV array in different climatology conditions, by using both MATLAB M-file and Simulink. Finally the capability of this method is demonstrated in simulated results, which are performed for both Single and Double Array PV system.

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The production of carbon fiber, particularly the oxidation/stabilization step, is a complex process. In the present study, a non-linear mathematical model has been developed for the prediction of density of polyacrylonitrile (PAN) and oxidized PAN fiber (OPF), as a key physical property for various applications, such as energy and material optimization, modeling, and design of the stabilization process. The model is based on the available functional groups in PAN and OPF. Expected functional groups, including [Formula presented], [Formula presented], –CH2, [Formula presented], and [Formula presented], were identified and quantified through the full deconvolution analysis of Fourier transform infrared attenuated total reflectance (FT-IR ATR) spectra obtained from fibers. These functional groups form the basis of three stabilization rendering parameters, representing the cyclization, dehydrogenation and oxidation reactions that occur during PAN stabilization, and are used as the independent variables of the non-linear predictive model. The k-fold cross validation approach, with k = 10, has been employed to find the coefficients of the model. This model estimates the density of PAN and OPF independent of operational parameters and can be expanded to all operational parameters. Statistical analysis revealed good agreement between the governing model and experiments. The maximum relative error was less than 1% for the present model.

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An inverse model is proposed to construct the mathematical relationship between continuous cooling transformation (CCT) kinetics with constant rates and the isothermal one. The kinetic parameters in JMAK equations of isothermal kinetics can be deduced from the experimental CCT kinetics. Furthermore, a generalized model with a new additive rule is developed for predicting the kinetics of nucleation and growth during diffusional phase transformation with arbitrary cooling paths based only on CCT curve. A generalized contribution coefficient is introduced into the new additivity rule to describe the influences of current temperature and cooling rate on the incubation time of nuclei. Finally, then the reliability of the proposed model is validated using dilatometry experiments of a microalloy steel with fully bainitic microstructure based on various cooling routes.