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In this chapter, we discuss one powerful approach to obtain a numerical solution of partial differential equations. The basic approach is to replace derivatives by discrete formulas called finite difference approximations. After these approximations are applied to the given differential equations, the boundary conditions are included by modifying the equations that involve the boundary points. This often results in a large and sparse matrix equation, in which the desired values at the chosen grid points are combined as a vector or a matrix, depending on whether the problem involves one dimension or two dimensions. For steady-state cases, the unknown vector can be obtained by solving an algebraic equation. Conversely, for non–steady-state cases, algebraic iteration is used to obtain a time-marching solution.
Throughout the chapter, we limit our discussion to a discretization based on uniform grids. Under this assumption, different finite difference approximations can be formulated using the Taylor series expansions as discussed in Section 13.1. Several formulations are possible depending on the choice of neighboring points for different order of derivatives. Formulas for various approximations of first-order and second-order derivatives, including their order of accuracy, are given in Tables 13.1 and 13.2, respectively.
Once the derivatives in the differential equations are replaced with their finite difference approximations, the resulting formulas can be recast as matrix algebraic equations. We limit our applications to second-order linear partial differential equations. We first discuss the time-independent cases before moving on to time-dependent cases.
In this chapter, we focus on the case of linear partial differential equations. In general, we consider a partial differential equation to be linear if the partial derivatives together with their coefficients can be represented by an operator L such that it satisfies the property that L (αu + βv) = αLu + βLv, where α and β are constants, whereas u and v are two functions of the same set of independent variables. This linearity property allows for superposition of basis solutions to fit the boundary and initial conditions.
We limit our discussion in this chapter to three approaches: operator factorization of reducible linear operators, separation of variables, and similarity transformations. Another set of solution methods known as integral transforms approach are discussed instead in Chapter 12.
The method using operator factorization is described in Section 11.2, and it is applicable to a class of partial differential equations known as reducible differential equations. We show how this approach can be applied to the one-dimensional wave equation to yield the well-known d'Alembert's solutions. In Section K.1 of the appendix, we consider how the d'Alembert solutions can be applied and modified to fit different boundary conditions, including infinite, semi-infinite, and finite spatial domains.
The separation of variables method is described in Section 11.3. It may not be as general at first glance, but it is an important and powerful approach because it has yielded useful solutions to several important linear problems in science and engineering. These include the linear diffusion, wave, and elliptic problems.
In Chapter 1, we started with the study of matrices based on their composition, structure, and basic mathematical operations such as addition, multiplication, inverses, determinants, and so forth, including matrix calculus operations. Then, in Chapter 2, we focused on the use of matrices to solve simultaneous equations of the form Ax = b, including their applications toward the solution of nonlinear equations via Newton algorithms. Based on linear algebra, we saw that Ax can also be taken to be a linear combination of the columns A with the elements of x acting as the weights. Under this perspective, the least-squares problem shifted the objective to be that of finding x that would minimize the residual error given by r = b − Ax.
In this chapter, we return to the equation Ax = b with a third perspective. Here, we consider matrix A to be an operator that will “transform” (or “map”) an input vector x to yield an output vector b, as shown schematically in Figure 3.1. We call this the matrix operator perspective of the linear equation. The main focus is now on A as a “machine” that needs to be analyzed, constructed, or modified to achieve some desired operational characteristics. For instance, we may want to construct a matrix A that rotates, stretches, or flips various points xi described by vectors. As another example, a stress tensor (to be discussed in Chapter 4) can be represented by a matrix T, which can then be used to find the stress vector s pointing in the direction of a unit vector n by the operation s= Tn.
Existence of a solution to the quasi-variational inequality problem arising in a modelfor sand surface evolution has been an open problem for a long time. Another long-standingopen problem concerns determining the dual variable, the flux of sand pouring down theevolving sand surface, which is also of practical interest in a variety of applications ofthis model. Previously, these problems were solved for the special case in which theinequality is simply variational. Here, we introduce a regularized mixed formulationinvolving both the primal (sand surface) and dual (sand flux) variables. We derive,analyse and compare two methods for the approximation, and numerical solution, of thismixed problem. We prove subsequence convergence of both approximations, as the meshdiscretization parameters tend to zero; and hence prove existence of a solution to thismixed model and the associated regularized quasi-variational inequality problem. One ofthese numerical approximations, in which the flux is approximated by thedivergence-conforming lowest order Raviart–Thomas element, leads to an efficient algorithmto compute not only the evolving pile surface, but also the flux of pouring sand. Resultsof our numerical experiments confirm the validity of the regularization employed.
We review the optimal design of an arterial bypass graft following either a (i) boundaryoptimal control approach, or a (ii) shape optimization formulation. The main focus isquantifying and treating the uncertainty in the residual flow when the hosting artery isnot completely occluded, for which the worst-case in terms of recirculation effects isinferred to correspond to a strong orifice flow through near-complete occlusion.Aworst-case optimal control approach is applied to the steady Navier-Stokes equations in 2Dto identify an anastomosis angle and a cuffed shape that are robust with respect to apossible range of residual flows. We also consider a reduced order modelling frameworkbased on reduced basis methods in order to make the robust design problem computationallyfeasible. The results obtained in 2D are compared with simulations in a 3D geometry butwithout model reduction or the robust framework.
We consider the solution of second order elliptic PDEs in Rdwith inhomogeneous Dirichlet data by means of an h–adaptive FEM withfixed polynomial order p ∈ N. As model example serves the Poissonequation with mixed Dirichlet–Neumann boundary conditions, where the inhomogeneousDirichlet data are discretized by use of an H1 / 2–stableprojection, for instance, the L2–projection forp = 1 or the Scott–Zhang projection for general p ≥ 1.For error estimation, we use a residual error estimator which includes the Dirichlet dataoscillations. We prove that each H1 / 2–stable projectionyields convergence of the adaptive algorithm even with quasi–optimal convergence rate.Numerical experiments with the Scott–Zhang projection conclude the work.
We analyze a numerical model for the Signorini unilateral contact, based on the mortarmethod, in the quadratic finite element context. The mortar frame enables one to usenon-matching grids and brings facilities in the mesh generation of different components ofa complex system. The convergence rates we state here are similar to those alreadyobtained for the Signorini problem when discretized on conforming meshes. The matching forthe unilateral contact driven by mortars preserves then the proper accuracy of thequadratic finite elements. This approach has already been used and proved to be reliablefor the unilateral contact problems even for large deformations. We provide however somenumerical examples to support the theoretical predictions.
Consider time-harmonic electromagnetic wave scattering from a biperiodic dielectricstructure mounted on a perfectly conducting plate in three dimensions. Given thatuniqueness of solution holds, existence of solution follows from a well-known Fredholmframework for the variational formulation of the problem in a suitable Sobolev space. Inthis paper, we derive a Rellich identity for a solution to this variational problem undersuitable smoothness conditions on the material parameter. Under additional non-trappingassumptions on the material parameter, this identity allows us to establish uniqueness ofsolution for all positive wave numbers.
In this article, we propose an integrated model for oxygen transfer into the blood,coupled with a lumped mechanical model for the ventilation process. Objectives.We aim at investigating oxygen transfer into the blood at rest or exercise. Thefirst task consists in describing nonlinear effects of the oxygen transfer under normalconditions. We also include the possible diffusion limitation in oxygen transfer observedin extreme regimes involving parameters such as alveolar and venous blood oxygen partialpressures, capillary volume, diffusing capacity of the membrane, oxygen binding byhemoglobin and transit time of the red blood cells in the capillaries. The second taskconsists in discussing the oxygen concentration heterogeneity along the path length in theacinus. Method. A lumped mechanical model is considered: a double-balloonmodel is built upon physiological properties such as resistance of the branches connectingalveoli to the outside air, and elastic properties of the surrounding medium. Then, wefocus on oxygen transfer: while the classical [F.J. Roughton and R.E. Forster, J.Appl. Physiol. 11 (1957) 290–302]. approach accounts for thereaction rate with hemoglobin by means of an extra resistance between alveolar air andblood, we propose an alternate description. Under normal conditions, the Hill’s saturationcurve simply quantifies the net oxygen transfer during the time that venous blood stays inthe close neighborhood of alveoli (transit time). Under degraded and/or exerciseconditions (impaired alveolar-capillary membrane, reduced transit time, high altitude)diffusion limitation of oxygen transfer is accounted for by means of the nonlinearequation representing the evolution of oxygen partial pressure in the plasma during thetransit time. Finally, a one-dimensional model is proposed to investigate the effects oflongitudinal heterogeneity of oxygen concentration in the respiratory tract during theventilation cycle, including previous considerations on oxygen transfer. Results.This integrated approach allows us to recover the right orders of magnitudes interms of oxygen transfer, at rest or exercise, by using well-documented data, without anyparameter tuning or curve fitting procedure. The diffusing capacity of thealveolar-capillary membrane does not affect the oxygen transfer rate in the normal regimebut, as it decreases (e.g. because of emphysema) below a critical value,it becomes a significant parameter. The one-dimensional model allows to investigate thescreening phenomenon, i.e. the possibility that oxygen transfer might besignificantly affected by the fact that the exchange area in the peripheral acinus poorlyparticipates to oxygen transfer at rest, thereby providing a natural reserve of transfercapacity for exercise condition. We do not recover this effect: in particular we showthat, at rest, although the oxygen concentration is slightly smaller in terminal alveoli,transfer mainly occurs in the acinar periphery.
A distributed-parameter (one-dimensional) anatomically detailed model for the arterialnetwork of the arm is developed in order to carry out hemodynamics simulations. This workfocuses on the specific aspects related to the model set-up. In this regard, stringentanatomical and physiological considerations have been pursued in order to construct thearterial topology and to provide a systematic estimation of the involved parameters. Themodel comprises 108 arterial segments, with 64 main arteries and 44 perforator arteries,with lumen radii ranging from 0.24 cm – axillary artery- to 0.018 cm – perforatorarteries. The modeling of blood flow in deformable vessels is governed by a well-known setof hyperbolic partial differential equations that accounts for mass and momentumconservation and a constitutive equation for the arterial wall. The variationalformulation used to solve the problem and the related numerical approach are described.The model rendered consistent pressure and flow rate outputs when compared with patientrecords already published in the literature. In addition, an application todimensionally-heterogeneous modeling is presented in which the developed arterial networkis employed as an underlying model for a three-dimensional geometry of a branching pointto be embedded in order to perform local analyses.
In vivo visualization of cardiovascular structures ispossible using medical images. However, one has to realize that the resulting 3Dgeometries correspond to in vivo conditions. This entails an internalstress state to be present in the in vivo measured geometry ofe.g. a blood vessel due to the presence of the blood pressure. In orderto correct for this in vivo stress, this paper presents an inverse methodto restore the original zero-pressure geometry of a structure, and to recover thein vivo stress field of the final, loaded structure. The proposedbackward displacement method is able to solve the inverse problem iteratively using fixedpoint iterations, but can be significantly accelerated by a quasi-Newton technique inwhich a least-squares model is used to approximate the inverse of the Jacobian. The hereproposed backward displacement method allows for a straightforward implementation of thealgorithm in combination with existing structural solvers, even if the structural solveris a black box, as only an update of the coordinates of the mesh needs to beperformed.
We consider optimal control problems for the bidomain equations of cardiacelectrophysiology together with two-variable ionic models, e.g. theRogers–McCulloch model. After ensuring the existence of global minimizers, we provide arigorous proof for the system of first-order necessary optimality conditions. The proof isbased on a stability estimate for the primal equations and an existence theorem for weaksolutions of the adjoint system.
The reliable and effective assimilation of measurements and numerical simulations inengineering applications involving computational fluid dynamics is an emerging problem assoon as new devices provide more data. In this paper we are mainly driven by hemodynamicsapplications, a field where the progressive increment of measures and numerical toolsmakes this problem particularly up-to-date. We adopt a Bayesian approach to the inclusionof noisy data in the incompressible steady Navier-Stokes equations (NSE). The purpose isthe quantification of uncertainty affecting velocity and flow related variables ofinterest, all treated as random variables. The method consists in the solution of anoptimization problem where the misfit between data and velocity - in a convenient norm -is minimized under the constraint of the NSE. We derive classical point estimators, namelythe maximum a posteriori – MAP – and the maximum likelihood – ML – ones.In addition, we obtain confidence regions for velocity and wall shear stress, a flowrelated variable of medical relevance. Numerical simulations in 2-dimensional andaxisymmetric 3-dimensional domains show the gain yielded by the introduction of a completestatistical knowledge in the assimilation process.
A second-order in time finite-difference scheme using a modified predictor–corrector method is proposed for the numerical solution of the generalized Burgers–Fisher equation. The method introduced, which, in contrast to the classical predictor–corrector method is direct and uses updated values for the evaluation of the components of the unknown vector, is also analysed for stability. Its efficiency is tested for a single-kink wave by comparing experimental results with others selected from the available literature. Moreover, comparisons with the classical method and relevant analogous modified methods are given. Finally, the behaviour and physical meaning of the two-kink wave arising from the collision of two single-kink waves are examined.
This paper is concerned with the initial boundary value problem of a class of nonlinear wave equations and reaction–diffusion equations with several nonlinear source terms of different signs. For the initial boundary value problem of the nonlinear wave equations, we derive a blow up result for certain initial data with arbitrary positive initial energy. For the initial boundary value problem of the nonlinear reaction–diffusion equations, we discuss some probabilities of the existence and nonexistence of global solutions and give some sufficient conditions for the global and nonglobal existence of solutions at high initial energy level by employing the comparison principle and variational methods.