932 resultados para ENERGY FUNCTION
Resumo:
It has been well accepted that over 50% of cerebral ischemic events are the result of rupture of vulnerable carotid atheroma and subsequent thrombosis. Such strokes are potentially preventable by carotid interventions. Selection of patients for intervention is currently based on the severity of carotid luminal stenosis. It has been, however, widely accepted that luminal stenosis alone may not be an adequate predictor of risk. To evaluate the effects of degree of luminal stenosis and plaque morphology on plaque stability, we used a coupled nonlinear time-dependent model with flow-plaque interaction simulation to perform flow and stress/strain analysis for stenotic artery with a plaque. The Navier-Stokes equations in the Arbitrary Lagrangian-Eulerian (ALE) formulation were used as the governing equations for the fluid. The Ogden strain energy function was used for both the fibrous cap and the lipid pool. The plaque Principal stresses and flow conditions were calculated for every case when varying the fibrous cap thickness from 0.1 to 2mm and the degree of luminal stenosis from 10% to 90%. Severe stenosis led to high flow velocities and high shear stresses, but a low or even negative pressure at the throat of the stenosis. Higher degree of stenosis and thinner fibrous cap led to larger plaque stresses, and a 50% decrease of fibrous cap thickness resulted in a 200% increase of maximum stress. This model suggests that fibrous cap thickness is critically related to plaque vulnerability and that, even within presence of moderate stenosis, may play an important role in the future risk stratification of those patients when identified in vivo using high resolution MR imaging.
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A lattice-gas model of multilayer adsorption has been solved in the mean-field approximation by a different numerical method. Earlier workers obtained a single solution for all values of temperature and pressure. In the present work, multiple solutions have been obtained in certain regions of temperature and pressure which give rise to bysteresis in the adsorption isotherm. In addition, we have obtained a parameter which behaves like an order parameter for the transition. The potential-energy function shows a double minimum in the region of bysteresis and a single maximum elsewhere.
Resumo:
The standard free energy of formation of titanium boride (TiB2) Was measured by the Electro Motive Force (EMF) method (by using yttria doped thoria (YDT) as the solid electrolyte). Two galvanic cells viz. Cell (I): Pt, TiB2 (s), TiO2 (s), B (s) vertical bar YDT vertical bar NiO (s), Ni (s), Pt and cell (II): Pt, TiB2 (s), TiO2 (s), B (s) vertical bar YDT vertical bar FeO (s). Fe (s), Pt were constructed in order to determine the Delta(f)G degrees, of TiB2. Enthalpy increments on TiB2 were measured by using inverse drop calorimetry over the temperature range 583-1769 K. The heat capacity, entropy and the free energy function have been derived from these experimental data in the temperature range 298-1800 K. The mean value of the standard enthalpy of formation of TiB2 (Delta H-f(298)degrees (TiB2)) was obtained by combining these Delta(f)G degrees, values and the free energy functions of TiB2 derived from the drop calorimetry data. The mean values of Delta H-f(298)degrees (TiB2) derived from the Delta(f)G degrees, data obtained from cell I and II were -322 +/- 1.2 kJ mol(-1) and -323.3 +/- 2.1 kJ mol(-1), respectively. These values were found to be in very good agreement with the assessed data. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Fugacity coefficients and isothermal changes of enthalpy have been calculated and reported. The calculations cover a temperature range of 0° to 75°C. up to gas densities of 1.0 gram per cc. The generalized Benedict-Webb-Rubin constants evaluated from generalized PVT relations is found to predict the experimental data with an over-all absolute deviation of 3.1%. Second virial coefficients and potential energy parameters for Lennard-Jones (12-6) potential energy function are reported also.
Resumo:
In order to study the elastic behaviour of matter when subjected to very large pressures, such as occur for example in the interior of the earth, and to provide an explanation for phenomena like earthquakes, it is essential to be able to calculate the values of the elastic constants of a substance under a state of large initial stress in terms of the elastic constants of a natural or stress-free state. An attempt has been made in this paper to derive expressions for these quantities for a substance of cubic symmetry on the basis of non-linear theory of elasticity and including up to cubic powers of the strain components in the strain energy function. A simple method of deriving them directly from the energy function itself has been indicated for any general case and the same has been applied to the case of hydrostatic compression. The notion of an effective elastic energy-the energy require to effect an infinitesimal deformation over a state of finite strain-has been introduced, the coefficients in this expression being the effective elastic constants. A separation of this effective energy function into normal co-ordinates has been given for the particular case of cubic symmetry and it has been pointed out, that when any of such coefficients in this normal form becomes negative, elastic instability will set in, with associated release of energy.
Resumo:
The optimum values of the solution parameters of a multiparameter integral free-energy function have been determined using experimental data from the Ga-Sb system. The equation is represented as DELTAG(xs) = x(1 - x)[(1 - x)(a1 + a2T + a3T ln T) + x(a4 + a5T + a6T ln T) + x(1 - x)(a7 + a8T + a9xT)].The integral and the corresponding partial form of the free energy function have been found to be of use when interpreting the high temperature thermodynamic data, atomic interactions and phase equilibria in the Ga-Sb system.
Resumo:
An important tool in signal processing is the use of eigenvalue and singular value decompositions for extracting information from time-series/sensor array data. These tools are used in the so-called subspace methods that underlie solutions to the harmonic retrieval problem in time series and the directions-of-arrival (DOA) estimation problem in array processing. The subspace methods require the knowledge of eigenvectors of the underlying covariance matrix to estimate the parameters of interest. Eigenstructure estimation in signal processing has two important classes: (i) estimating the eigenstructure of the given covariance matrix and (ii) updating the eigenstructure estimates given the current estimate and new data. In this paper, we survey some algorithms for both these classes useful for harmonic retrieval and DOA estimation problems. We begin by surveying key results in the literature and then describe, in some detail, energy function minimization approaches that underlie a class of feedback neural networks. Our approaches estimate some or all of the eigenvectors corresponding to the repeated minimum eigenvalue and also multiple orthogonal eigenvectors corresponding to the ordered eigenvalues of the covariance matrix. Our presentation includes some supporting analysis and simulation results. We may point out here that eigensubspace estimation is a vast area and all aspects of this cannot be fully covered in a single paper. (C) 1995 Academic Press, Inc.
Resumo:
The present research describes the modeling of the thermodynamic properties of the liquid Al-Ga-In-As alloys at 1073 and 1173 K, and investigates the solid-liquid equilibria in the systems. The isothermal molar excess free energy function for the liquid alloys is represented in terms of 37 parameters pertaining to six of the constituent binaries, four ternaries and the quaternary interactions in the system. The corresponding solid alloys which consist of AlAs, GaAs and InAs are assumed to be quasi-regular ternary solutions. The solidus and liquidus compositions are calculated at 1073 and 1173 K using the derived values of the partial components for the solid and liquid alloys at equilibrium. They are in good agreement with those of the experimentally determined values available in the literature. (C) 1999 Elsevier Science S.A. All rights reserved.
Resumo:
The propagation of axial waves in hyperelastic rods is studied using both time and frequency domain finite element models. The nonlinearity is introduced using the Murnaghan strain energy function and the equations governing the dynamics of the rod are derived assuming linear kinematics. In the time domain, the standard Galerkin finite element method, spectral element method, and Taylor-Galerkin finite element method are considered. A frequency domain formulation based on the Fourier spectral method is also developed. It is found that the time domain spectral element method provides the most efficient numerical tool for the problem considered.
Resumo:
Arterial walls have a regular and lamellar organization of elastin present as concentric fenestrated networks in the media. In contrast, elastin networks are longitudinally oriented in layers adjacent to the media. In a previous model exploring the biomechanics of arterial elastin, we had proposed a microstructurally motivated strain energy function modeled using orthotropic material symmetry. Using mechanical experiments, we showed that the neo-Hookean term had a dominant contribution to the overall form of the strain energy function. In contrast, invariants corresponding to the two fiber families had smaller contributions. To extend these investigations, we use biaxial force-controlled experiments to quantify regional variations in the anisotropy and nonlinearity of elastin isolated from bovine aortic tissues proximal and distal to the heart. Results from this study show that tissue nonlinearity significantly increases distal to the heart as compared to proximally located regions (). Distally located samples also have a trend for increased anisotropy (), with the circumferential direction stiffer than the longitudinal, as compared to an isotropic and relatively linear response for proximally located elastin samples. These results are consistent with the underlying tissue histology from proximally located samples that had higher optical density (), fiber thickness (), and trend for lower tortuosity () in elastin fibers as compared to the thinner and highly undulating elastin fibers isolated from distally located samples. Our studies suggest that it is important to consider elastin fiber orientations in investigations that use microstructure-based models to describe the contributions of elastin and collagen to arterial mechanics.
Resumo:
We use enzymatic manipulation methods to investigate the individual and combined roles of elastin and collagen on arterial mechanics. Porcine aortic tissues were treated for differing amounts of time using enzymes elastase and collagenase to cause degradation in substrate proteins elastin and collagen and obtain variable tissue architecture. We use equibiaxial mechanical tests to quantify the material properties of control and enzyme treated tissues and histological methods to visualize the underlying tissue microstructure in arterial tissues. Our results show that collagenase treated tissues were more compliant in the longitudinal direction as compared to control tissues. Collagenase treatment also caused a decrease in the tissue nonlinearity as compared to the control samples in the study. A one hour collagenase treatment was sufficient to cause fragmentation and degradation of the adventitial collagen. In contrast, elastase treatment leads to significantly stiffer tissue response associated with fragmented and incomplete elastin networks in the tissue. Thus, elastin in arterial walls distributes tensile stresses whereas collagen serves to reinforce the vessel wall in the circumferential direction and also contributes to tissue anisotropy. A microstructurally motivated strain energy function based on circumferentially oriented medial fibers and helically oriented collagen fibers in the adventitia is useful in describing these experimental results.
Resumo:
Thoracic aortic dissections are associated with a significant risk of morbidity and mortality, and currently challenge our understanding of the biomechanical factors leading to their initiation and propagation. We quantified the biaxial mechanical properties of human type A dissections (n = 16) and modeled the stress-strain data using a microstructurally motivated form of strain energy function. Our results show significantly higher stiffness for dissected tissues as compared to control aorta without arterial disease. Higher stiffness of dissected tissues did not, however, correlate with greater aortic diameter measured prior to surgery nor were there any age dependent differences in the tissue properties.
Resumo:
In this paper, we propose a technique for video object segmentation using patch seams across frames. Typically, seams, which are connected paths of low energy, are utilised for retargeting, where the primary aim is to reduce the image size while preserving the salient image contents. Here, we adapt the formulation of seams for temporal label propagation. The energy function associated with the proposed video seams provides temporal linking of patches across frames, to accurately segment the object. The proposed energy function takes into account the similarity of patches along the seam, temporal consistency of motion and spatial coherency of seams. Label propagation is achieved with high fidelity in the critical boundary regions, utilising the proposed patch seams. To achieve this without additional overheads, we curtail the error propagation by formulating boundary regions as rough-sets. The proposed approach out-perform state-of-the-art supervised and unsupervised algorithms, on benchmark datasets.
Resumo:
The thermal expansion coefficient (TEC) of an ideal crystal is derived by using a method of Boltzmann statistics. The Morse potential energy function is adopted to show the dependence of the TEC on the temperature. By taking the effects of the surface relaxation and the surface energy into consideration, the dimensionless TEC of a nanofilm is derived. It is shown that with decreasing thickness, the TEC can increase or decrease, depending on the surface relaxation of the nanofilm.
Resumo:
A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.
Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.
Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.