A note on computational blood rheology

We briefly present some numerical simulations for a generalized Newtonian model describing the shear-thinning behavior of blood in a realistic 3D geometry. Results are compared with those obtained using the Newtonian model     

Operator splitting for nonlinear reaction-diffusion systems with an entropic structure : singular perturbation and order reduction

Summary. In this paper, we perform the numerical analysis of operator splitting techniques for nonlinear reaction-diffusion systems with an entropic structure in the presence of fast scales in the reaction term. We consider both linear diagonal and quasi-linear non-diagonal diffusion; the entropic structure implies the well-posedness and stability of the system as well as a Tikhonov normal form for the nonlinear reaction term [23]. It allows to perform a singular perturbation analysis and to obtain a reduced and well-posed system of equations on a partial equilibrium manifold as well as an asymptotic expansion of the solution. We then conduct an error analysis in this particular framework where the time scale associated to the fast part of the reaction term is much shorter that the splitting time step t thus leading to the failure of the usual splitting analysis techniques. We define the conditions on diffusion and reaction for the order of the local error associated with the time splitting to be reduced or to be preserved in the presence of fast scales. All the results obtained theoretically on local error estimates are then illustrated on a numerical test case where the global error clearly reproduces the scenarios foreseen at the local level. We finally investigate the discretization of the corresponding problems and its influence on the splitting error in terms of the previously conducted numerical analysis.Mathematics Subject Classification (2000): 65M12, 35K57, 35B25, 35Q80, 34E15, 80A32, 92E20     

Block mesh refinement for incompressible flows in curvilinear domains

A method for the solution of the Navier–Stokes equation for the prediction of flows inside domains of arbitrary shaped bounds by the use of Cartesian grids with block-refinement in space is presented. In order to avoid the complexity of the body fitted numerical grid generation procedure, we use a saw tooth method for the curvilinear geometry approximation. By using block-nested refinement, we achieved the desired geometry Cartesian approximation in order to find an accurate solution of the N–S equations. The method is applied to incompressible laminar flows and is based on a cell-centred approximation. We present the numerical simulation of the flow field for two geometries, driven cavity and stenosed tubes. The utility of the algorithm is tested by comparing the convergence characteristics and accuracy to those of the standard single grid algorithm. The Cartesian block refinement algorithm can be used in any complex curvilinear geometry simulation, to accomplish a reduction in memory requirements and the computational time effort.     

Implementation strategies of a contract-based MRI examination reservation process for stroke patients

Timely imaging examinations are critical for stroke patients due to the potential life threat. We have proposed a contract-based Magnetic Resonance Imaging (MRI) reservation process [1] in order to reduce their waiting time for MRI examinations. Contracted time slots (CTS) are especially reserved for Neural Vascular Department (NVD) treating stroke patients. Patients either wait in a CTS queue for such time slots or are directed to Regular Time Slot (RTS) reservation. This strategy creates “unlucky” patients having to wait for lengthy RTS reservation. This paper proposes and analyzes other contract implementation strategies called RTS reservation strategies. These strategies reserve RTS for NVD but do not direct patients to regular reservations. Patients all wait in the same queue and are served by either CTS or RTS on a FIFO (First In First Out) basis. We prove that RTS reservation strategies are able to reduce the unused time slots and patient waiting time. Extensive numerical results are presented to show the benefits of RTS reservation and to compare various RTS reservation strategies.     

Two Way Coupled Micro/Meso Scale Method for Wind Farms

Wind turbines extract energy from the approaching flow field resulting in reduced wind speeds, increased turbulence and a wake downstream of the wind turbine. The wake has a multitude of negative effects on downstream wind turbines. This includes reduced efficiency and increased unsteadiness resulting in vibrations and potentially in material fatigue. Moreover, the maintenance can increase compared to non-interfering wind turbines. The simulation of these effects is challenging. Computational fluid dynamics (CFD) simulations of these large and complex geometries requires exceedingly large computational resources. With present Reynolds Averaged Navier-Stokes (RANS) or Large Eddy Simulation (LES) based CFD methods it is virtually impossible to perform such simulations of the interaction between individual wind turbines in a complete wind turbine farm. Coupling to the mesoscale accounting for local weather situations becomes yet more challenging. This is due to the wide range of length and time scales that have to be considered for these simulations and therefore the tremendous computational power needed to perform such simulations. To investigate these effects we propose to combine ideas from existing methods, the Coarse-Grid-CFD (CGCFD) ( [1]) developed at the KIT and the meso-/ micro scale method developed at the University of Thessaloniki ( [2]). Goal of the proposed methodology is to provide a numerical method that allows to implement a wind farm in a meso-scale weather simulation which includes two-way coupling. Thus both the micro and the meso scale wind and energy production of wind farms can be addressed. This proposed multi scale coupling strategy can also be applied in two hierarchies reducing the numerical effort of the global approach yet more. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Numerical stochastic model for the magnetic relaxation time of the fine particle system with dipolar interactions

This paper presents the results obtained by numerical simulations, the magnetic relaxation time simulation for a fine particle system with dipolar magnetic interaction. We used a 3D simulation model for fine magnetic particles with spherical shape and lognormal distribution for their diameters. Starting from Dormann–Bessais–Fiorani model, the 3D model we used is more realistic if we consider that the particles are randomly arranged into a preset volume, following a Gaussian distribution generated with the Box–Mueller transformation.     

An explicit staggered-grid method for numerical simulation of large-scale natural gas pipeline networks

We present an explicit second order staggered finite difference (FD) discretization scheme for forward simulation of natural gas transport in pipeline networks. By construction, this discretization approach guarantees that the conservation of mass condition is satisfied exactly. The mathematical model is formulated in terms of density, pressure, and mass flux variables, and as a result permits the use of a general equation of state to define the relation between the gas density and pressure for a given temperature. In a single pipe, the model represents the dynamics of the density by propagation of a non-linear wave according to a variable wave speed. We derive compatibility conditions for linking domain boundary values to enable efficient, explicit simulation of gas flows propagating through a network with pressure changes created by gas compressors. We compare our staggered grid method with an explicit operator splitting method and a lumped element scheme, and perform numerical experiments to validate the convergence order of the new discretization approach. In addition, we perform several computations to investigate the influence of non-ideal equation of state models and temperature effects on pipeline simulations with boundary conditions on various time and space scales.     

Optimal proportional reinsurance and investment for stochastic factor models

In this work we investigate the optimal proportional reinsurance-investment strategy of an insurance company which wishes to maximize the expected exponential utility of its terminal wealth in a finite time horizon. Our goal is to extend the classical Cramér–Lundberg model introducing a stochastic factor which affects the intensity of the claims arrival process, described by a Cox process, as well as the insurance and reinsurance premia. The financial market is supposed not influenced by the stochastic factor, hence it is independent on the insurance market. Using the classical stochastic control approach based on the Hamilton–Jacobi–Bellman equation we characterize the optimal strategy and provide a verification result for the value function via classical solutions to two backward partial differential equations. Existence and uniqueness of these solutions are discussed. Results under various premium calculation principles are illustrated and a new premium calculation rule is proposed in order to get more realistic strategies and to better fit our stochastic factor model. Finally, numerical simulations are performed to obtain sensitivity analyses.     

Explicit-implicit schemes for convection-diffusion-reaction problems

Boundary value problems for time-dependent convection-diffusion-reaction equations are basic models of problems in continuum mechanics. To study these problems, various numerical methods are used. With a finite difference, finite element, or finite volume approximation in space, we arrive at a Cauchy problem for systems of ordinary differential equations whose operator is asymmetric and indefinite. Explicit-implicit approximations in time are conventionally used to construct splitting schemes in terms of physical processes with separation of convection, diffusion, and reaction processes. In this paper, unconditionally stable schemes for unsteady convection-diffusion-reaction equations are constructed with explicit-implicit approximations used in splitting the operator reaction. The schemes are illustrated by a model 2D problem in a rectangle.     

Fast direct solver for Poisson equation in a 2D elliptical domain

In this article, we extend our previous work 3 for developing some fast Poisson solvers on 2D polar and spherical geometries to an elliptical domain. Instead of solving the equation in an irregular Cartesian geometry, we formulate the equation in elliptical coordinates. The solver relies on representing the solution as a truncated Fourier series, then solving the differential equations of Fourier coefficients by finite difference discretizations. Using a grid by shifting half mesh away from the pole and incorporating the derived numerical boundary value, the difficulty of coordinate singularity can be elevated easily. Unlike the case of 2D disk domain, the present difference equation for each Fourier mode is coupled with its conjugate mode through the numerical boundary value near the pole; thus, those two modes are solved simultaneously. Both second‐ and fourth‐order accurate schemes for Dirichlet and Neumann problems are presented. In particular, the fourth‐order accuracy can be achieved by a three‐point compact stencil which is in contrast to a five‐point long stencil for the disk case. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 20: 72–81, 2004     

Dynamics of SIS Epidemic Model with Varying Total Population and Multivaccination Control Strategies

In this paper, two susceptible‐infected‐susceptible epidemic models with varying total population size, continuous vaccination, and state‐dependent pulse vaccination are formulated to describe the transmission of infectious diseases, such as diphtheria, measles, rubella, pertussis, and so on. The first model incorporates the proportion of infected individuals in population as monitoring threshold value; we analytically show the existence and orbital asymptotical stability of positive order‐1 periodic solution for this control model. The other model determines control strategy by monitoring the proportion of susceptible individuals in population; we also investigate the existence and global orbital asymptotical stability of the disease‐free periodic solution. Theoretical results imply that the disease dies out in the second case. Finally, using realistic parameter values, we carry out some numerical simulations to illustrate the main theoretical results and the feasibility of state‐dependent pulse control strategy.     

Operator-splitting methods via the Zassenhaus product formula

In this paper, we contribute an operator-splitting method improved by the Zassenhaus product. Zassenhaus products are of fundamental importance for the theory of Lie groups and Lie algebras. While their applications in physics and physical chemistry are important, novel applications in CFD (computational fluid dynamics) arose based on the fact that their sparse matrices can be seen as generators of an underlying Lie algebra. We apply this to classical splitting and the novel Zassenhaus product formula. The underlying analysis for obtaining higher order operator-splitting methods based on the Zassenhaus product is presented. The benefits of dealing with sparse matrices, given by spatial discretization of the underlying partial differential equations, are due to the fact that the higher order commutators are very quickly computable (their matrix structures thin out and become nilpotent). When applying these methods to convection-diffusion-reaction equations, the benefits of balancing time and spatial scales can be used to accelerate these methods and take into account these sparse matrix structures.The verification of the improved splitting methods is done with numerical examples. Finally, we conclude with higher order operator-splitting methods.     

Wave simulations of Gray‐Scott reaction‐diffusion system

In this work, we study the numerical simulation of the one‐dimensional reaction‐diffusion system known as the Gray‐Scott model. This model is responsible for the spatial pattern formation, which we often meet in nature as the result of some chemical reactions. We have used the trigonometric quartic B‐spline (T4B) functions for space discretization with the Crank‐Nicolson method for time integration to integrate the nonlinear reaction‐diffusion equation into a system of algebraic equations. The solutions of the Gray‐Scott model are presented with different wave simulations. Test problems are chosen from the literature to illustrate the stationary waves, pulse‐splitting waves, and self‐replicating waves.     

Existence and global stability of almost automorphic solutions for shunting inhibitory cellular neural networks with time-varying delays in leakage terms on time scales

In this paper, shunting inhibitory cellular neural networks(SICNNs) with time-varying delays in leakage terms on time scales are investigated. With the aid of the existence of the exponential dichotomy of linear dynamic equations on time scales, fixed point theorem and the theory of calculus on time scales, we establish some sufficient conditions to ensure the existence and exponential stability of almost automorphic solutions for the model. An example with its numerical simulations is given to illustrate the feasibility and effectiveness of the theoretical findings.     

An efficient hybrid numerical method based on an additive scheme for solving coupled systems of singularly perturbed linear parabolic problems

We construct an efficient hybrid numerical method for solving coupled systems of singularly perturbed linear parabolic problems of reaction-diffusion type. The discretization of the coupled system is based on the use of an additive or splitting scheme on a uniform mesh in time and a hybrid scheme on a layer-adapted mesh in space. It is proven that the developed numerical method is uniformly convergent of first order in time and third order in space. The purpose of the additive scheme is to decouple the components of the vector approximate solution at each time step and thus make the computation more efficient. The numerical results confirm the theoretical convergence result and illustrate the efficiency of the proposed strategy.     

Quasi-interpolation operators based on a cubic spline and applications in SAMR simulations

In this paper, we consider the properties of monotonicity-preserving and global conservation-preserving for interpolation operators. These two properties play important role when interpolation operators used in many real numerical simulations. In order to attain these two aspects, we propose a one-dimensional (1D) new cubic spline, and extend it to two-dimensional (2D) using tensor-product operation. Based on discrete convolution, 1D and 2D quasi-interpolation operators are presented using these functions. Both analysis and numerical results show that the interpolation operators constructed in this paper are monotonic and conservative. In particular, we consider the numerical simulations of 2D Euler equations based on the technique of structured adaptive mesh refinement (SAMR). In SAMR simulations, effective interpolators are needed for information transportation between the coarser/finer meshes. We applied the 2D quasi-interpolation operator to this environment, and the simulation result show the efficiency and correctness of our interpolator.     

Asymptotic Formulas for Thermography Based Recovery of Anomalies

We start from a realistic half space model for thermal imaging, which we then use to develop a mathematical asymptotic analysis well suited for the design of reconstruction algorithms. We seek to reconstruct thermal anomalies only through their rough features. With this way our proposed algorithms are stable against measurement noise and geometry perturbations. Based on rigorous asymptotic estimates, we first obtain an approximation for the temperature profile which we then use to design nonit-erative detection algorithms. We show on numerical simulations evidence that they are accurate and robust. Moreover, we provide a mathematical model for ultrasonic temperature imaging, which is an important technique in cancerous tissue ablation therapy.AMS subject classifications: 35R20, 35B30     

Symmetric spaces and Lie triple systems in numerical analysis of differential equations

A remarkable number of different numerical algorithms can be understood and analyzed using the concepts of symmetric spaces and Lie triple systems, which are well known in differential geometry from the study of spaces of constant curvature and their tangents. This theory can be used to unify a range of different topics, such as polar-type matrix decompositions, splitting methods for computation of the matrix exponential, composition of selfadjoint numerical integrators and dynamical systems with symmetries and reversing symmetries. The thread of this paper is the following: involutive automorphisms on groups induce a factorization at a group level, and a splitting at the algebra level. In this paper we will give an introduction to the mathematical theory behind these constructions, and review recent results. Furthermore, we present a new Yoshida-like technique, for self-adjoint numerical schemes, that allows to increase the order of preservation of symmetries by two units. The proposed techniques has the property that all the time-steps are positive.     

A distributed combustion solver for engine simulations on grids

Multi-dimensional models for predictive simulations of modern engines are an example of multi-physics and multi-scale mathematical models, since lots of thermofluiddynamic processes in complex geometrical configurations have to be considered. Typical models involve different submodels, including turbulence, spray and combustion models, with different characteristic time scales. The predictive capability of the complete models depends on the accuracy of the submodels as well as on the reliability of the numerical solution algorithms. In this work we propose a multi-solver approach for reliable and efficient solution of the stiff Ordinary Differential Equation (ODE) systems arising from detailed chemical reaction mechanisms for combustion modeling. Main aim was to obtain high-performance parallel solution of combustion submodels in the overall procedure for simulation of engines on distributed heterogeneous computing platforms. To this aim we interfaced our solver with the CHEMKIN-II package and the KIVA3V-II code and carried out multi-computer simulations of realistic engines. Numerical experiments devoted to test reliability of the simulation results and efficiency of the distributed combustion solver are presented and discussed.