Abstract: The main purpose of this study is to show differences between the numerical solution of the flow through the artificial heart valve using Newtonian or non-Newtonian fluid. The simulation was carried out by a commercial computational fluid dynamics (CFD) package based on finite-volume method. An aortic bileaflet heart valve (Sorin Bicarbon) was used as a pattern for model of real heart valve replacement. Computed tomography (CT) was used to gain the accurate parameters of the valve. Data from CT were transferred in the commercial 3D designer, where the model for CFD was made. Carreau rheology model was applied as non-Newtonian fluid. Physiological data of cardiac cycle were used as boundary conditions. Outputs were taken the leaflets excursion from opening to closure and the fluid dynamics through the valve. This study also includes experimental measurement of pressure fields in ambience of valve for verification numerical outputs. Results put in evidence a favorable comparison between the computational solutions of flow through the mechanical heart valve using Newtonian and non-Newtonian fluid.
Abstract: A mathematical model of the additional effects of the
liquid in the hydrodynamic gap is presented in the paper. An
incompressible viscous fluid is considered. Based on computational
modeling are determined the matrices of mass, stiffness and damping.
The mathematical model is experimentally verified.
Abstract: Nanoscale thermites such as the composite mixture of
nano-sized aluminum and molybdenum trioxide powders possess
several technical advantages such as much higher reaction rate and
shorter ignition delay, when compared to the conventional energetic
formulations made of micron-sized metal and oxidizer particles. In this
study, the self-propagation of combustion wave in compacted pellets
of nanoscale thermite composites is modeled and computationally
investigated by utilizing the activation energy reduction of aluminum
particles due to nanoscale particle sizes. The present computational
model predicts the speed of combustion wave propagation which is
good agreement with the corresponding experiments of thermite
reaction. Also, several characteristics of thermite reaction in nanoscale
composites are discussed including the ignition delay and combustion
wave structures.
Abstract: This paper describes a computer model of Quantum Field Theory (QFT), referred to in this paper as QTModel. After specifying the initial configuration for a QFT process (e.g. scattering) the model generates the possible applicable processes in terms of Feynman diagrams, the equations for the scattering matrix, and evaluates probability amplitudes for the scattering matrix and cross sections. The computations of probability amplitudes are performed numerically. The equations generated by QTModel are provided for demonstration purposes only. They are not directly used as the base for the computations of probability amplitudes. The computer model supports two modes for the computation of the probability amplitudes: (1) computation according to standard QFT, and (2) computation according to a proposed functional interpretation of quantum theory.
Abstract: Mathematical and computational modeling of calcium
signalling in nerve cells has produced considerable insights into how
the cells contracts with other cells under the variation of biophysical
and physiological parameters. The modeling of calcium signaling in
astrocytes has become more sophisticated. The modeling effort has
provided insight to understand the cell contraction. Main objective
of this work is to study the effect of voltage gated (Operated)
calcium channel (VOC) on calcium profile in the form of advection
diffusion equation. A mathematical model is developed in the form
of advection diffusion equation for the calcium profile. The model
incorporates the important physiological parameter like diffusion
coefficient etc. Appropriate boundary conditions have been framed.
Finite volume method is employed to solve the problem. A program
has been developed using in MATLAB 7.5 for the entire problem
and simulated on an AMD-Turion 32-bite machine to compute the
numerical results.
Abstract: Well-developed strategic marketing planning is the essential
prerequisite for establishment of the right and unique competitive
advantage. Typical market, however, is a heterogeneous
and decentralized structure with natural involvement of individual
or group subjectivity and irrationality. These features cannot be
fully expressed with one-shot rigorous formal models based on,
e.g. mathematics, statistics or empirical formulas. We present an
innovative solution, extending the domain of agent based computational
economics towards the concept of hybrid modeling in service
provider and consumer market such as telecommunications. The
behavior of the market is described by two classes of agents -
consumer and service provider agents - whose internal dynamics
are fundamentally different. Customers are rather free multi-state
structures, adjusting behavior and preferences quickly in accordance
with time and changing environment. Producers, on the contrary,
are traditionally structured companies with comparable internal processes
and specific managerial policies. Their business momentum is
higher and immediate reaction possibilities limited. This limitation
underlines importance of proper strategic planning as the main
process advising managers in time whether to continue with more
or less the same business or whether to consider the need for future
structural changes that would ensure retention of existing customers
or acquisition of new ones.
Abstract: Temperature, relative humidity and overhygroscopic
moisture fields in a sandstone wall provided with interior thermal
insulation were calculated in order to assess the hygric performance
of the retrofitted wall. Computational simulations showed that during
the time period of 10 years which was subject of investigation no
overhygroscopic moisture appeared in the analyzed building
envelope so that it performed in a satisfactory way from the hygric
point of view.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: Stochastic models of biological networks are well established in systems biology, where the computational treatment of such models is often focused on the solution of the so-called chemical master equation via stochastic simulation algorithms. In contrast to this, the development of storage-efficient model representations that are directly suitable for computer implementation has received significantly less attention. Instead, a model is usually described in terms of a stochastic process or a "higher-level paradigm" with graphical representation such as e.g. a stochastic Petri net. A serious problem then arises due to the exponential growth of the model-s state space which is in fact a main reason for the popularity of stochastic simulation since simulation suffers less from the state space explosion than non-simulative numerical solution techniques. In this paper we present transition class models for the representation of biological network models, a compact mathematical formalism that circumvents state space explosion. Transition class models can also serve as an interface between different higher level modeling paradigms, stochastic processes and the implementation coded in a programming language. Besides, the compact model representation provides the opportunity to apply non-simulative solution techniques thereby preserving the possible use of stochastic simulation. Illustrative examples of transition class representations are given for an enzyme-catalyzed substrate conversion and a part of the bacteriophage λ lysis/lysogeny pathway.
Abstract: NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.