Abstract: A statistical learning approach for high-dimensional parametric PDEs related to uncertainty quantification is derived. The method is based on the minimization of an empirical risk on a selected model class, and it is shown to be applicable to a broad range of problems. A general unified convergence analysis is derived, which takes into account the approximation and the statistical errors. By this, a combination of theoretical results from numerical analysis and statistics is obtained. Numerical experiments illustrate the performance of the method with the model class of hierarchical tensors. PubDate: 2019-10-05

Abstract: We consider model order reduction based on proper orthogonal decomposition (POD) for unsteady incompressible Navier-Stokes problems, assuming that the snapshots are given by spatially adapted finite element solutions. We propose two approaches of deriving stable POD-Galerkin reduced-order models for this context. In the first approach, the pressure term and the continuity equation are eliminated by imposing a weak incompressibility constraint with respect to a pressure reference space. In the second approach, we derive an inf-sup stable velocity-pressure reduced-order model by enriching the velocity-reduced space with supremizers computed on a velocity reference space. For problems with inhomogeneous Dirichlet conditions, we show how suitable lifting functions can be obtained from standard adaptive finite element computations. We provide a numerical comparison of the considered methods for a regularized lid-driven cavity problem. PubDate: 2019-09-11

Abstract: We present an offline/online computational procedure for computing the dual norm of parameterized linear functionals. The approach is motivated by the need to efficiently compute residual dual norms, which are used in model reduction to estimate the error of a given reduced solution. The key elements of the approach are (i) an empirical test space for the manifold of Riesz elements associated with the parameterized functional and (ii) an empirical quadrature procedure to efficiently deal with parametrically non-affine terms. We present a number of theoretical and numerical results to identify the different sources of error and to motivate the proposed technique, and we compare the approach with other state-of-the-art techniques. Finally, we investigate the effectiveness of our approach to reduce both offline and online costs associated with the computation of the time-averaged residual indicator proposed in Fick et al. (J. Comput. Phys. 371, 214–243 2018). PubDate: 2019-09-11

Abstract: A direct boundary integral equation method for the heat equation based on Nyström discretization is proposed and analyzed. For problems with moving geometries, a weakly and strongly singular Green’s integral equation is formulated. Here the hypersingular integral operator, i.e., the normal trace of the double-layer potential, must be understood as a Hadamard finite part integral. The thermal layer potentials are regarded as generalized Abel integral operators in time and discretized with a singularity-corrected trapezoidal rule. The spatial discretization is a standard quadrature rule for smooth surface integrals. The discretized systems lead to an explicit time stepping scheme and is effective for solving the Dirichlet and Neumann boundary value problems based on both the weakly and/or strongly singular integral equations. PubDate: 2019-08-27

Abstract: In this article, we consider the problems (unsolved in the literature) of computing the nearest normal matrix X to a given non-normal matrix A, under certain constraints, that are (i) if A is real, we impose that also X is real; (ii) if A has known entries on a given sparsity pattern Ω and unknown/uncertain entries otherwise, we impose to X the constraint xij = aij for all entries (i,j) in the pattern Ω. As far as we know, there do not exist in the literature specific algorithms aiming to solve these problems. For the case in which all entries of A can be modified, there exists an algorithm by Ruhe, which is able to compute the closest normal matrix. However, if A is real, the closest computed matrix by Ruhe’s algorithm might be complex, which motivates the development of a different algorithm preserving reality. Normality is characterized in a very large number of ways; in this article, we consider the property that the square of the Frobenius norm of a normal matrix is equal to the sum of the squares of the moduli of its eigenvalues. This characterization allows us to formulate as equivalent problem the minimization of a functional of an unknown matrix, which should be normal, fulfill the required constraints, and have minimal distance from the given matrix A. PubDate: 2019-08-27

Abstract: It is known that wave equations have physically very important properties which should be respected by numerical schemes in order to predict correctly the solution over a long time period. In this paper, the long-time behaviour of momentum and actions for energy-preserving methods is analysed for semi-linear wave equations. A full discretisation of wave equations is derived and analysed by firstly using a spectral semi-discretisation in space and then by applying the adopted average vector field (AAVF) method in time. This numerical scheme can exactly preserve the energy of the semi-discrete system. The main theme of this paper is to analyse another important physical property of the scheme. It is shown that this scheme yields near conservation of a modified momentum and modified actions over long times. The results are rigorously proved based on the technique of modulated Fourier expansions in two stages. First, a multi-frequency modulated Fourier expansion of the AAVF method is constructed, and then two almost-invariants of the modulation system are derived. PubDate: 2019-08-16

Abstract: The image of a polynomial map is a constructible set. While computing its closure is standard in computer algebra systems, a procedure for computing the constructible set itself is not. We provide a new algorithm, based on algebro-geometric techniques, addressing this problem. We also apply these methods to answer a question of W. Hackbusch on the non-closedness of site-independent cyclic matrix product states for infinitely many parameters. PubDate: 2019-08-08

Abstract: The following paper describes a numerical simulation of a complete bypass of a stenosed human artery. The considered geometry consists of the narrowed host tube and the bypass graft with a 45-degree angle of connection. Different diameters of the narrowing are tested. Blood is the fluid with shear rate–dependent viscosity; therefore, various rheology mathematical models for generalized Newtonian fluids are considered, namely Cross model, modified Cross model, Carreau model, and Carreau-Yasuda model. The fundamental system of equations is based on the system of generalized Navier-Stokes equations. Generalized Newtonian fluids flow in a bypass tube is numerically simulated by using a SIMPLE algorithm included in the open-source CFD tool, OpenFOAM. The aim of this work is to compare the numerical results for the different mathematical models of the viscosity with the changing diameter of the narrowed channel. PubDate: 2019-08-01

Abstract: This paper discusses a discrete-time queueing system in which an arriving customer may adopt four different strategies; two of them correspond to a LCFS discipline where displacements or expulsions occur, and in the other two, the arriving customer decides to follow a FCFS discipline or to become a negative customer eliminating the customer in the server, if any. The different choices of the involved parameters make this model to enjoy a great versatility, having several special cases of interest. We carry out a thorough analysis of the system, and using a generating function approach, we derive analytical results for the stationary distributions obtaining performance measures for the number of customers in the queue and in the system. Also, recursive formulae for calculating the steady-state distributions of the queue and system size has been developed. Making use of the busy period of an auxiliary system, the sojourn times of a customer in the queue and in the system have also been obtained. Finally, some numerical examples are given. PubDate: 2019-08-01

Abstract: Continuous inkjet systems are commonly used to print expiry date labels for food products. These systems are designed to print on flat surfaces; however, a lot of food products package have a cylindrical shape (e.g., bottled and canned products) which causes an enlargement in characters at the ends of the label. In this work, we present an algorithm to correct this defect by calculating the extra-distance that an ink drop travels when the printing surface approaches an elliptic cylinder. Each charged ink drop is modeling as a solid particle which is affected by the air drag, Earth’s gravitation, and voltage due to the electrical field that causes the perturbation in the ink drop path. Numerical results show the correction of the enlargement mentioned above by varying the electric field along the width of the label. In addition, the equation and the values of a second electric field to correct the printing’s inclination caused by the method of the system’s operation are presented. PubDate: 2019-08-01

Abstract: The “Game of life” model was created in 1970 by the mathematician John Horton Conway using cellular automata. Since then, different extensions of these cellular automata have been used in many applications. In this work, we introduce probabilistic cellular automata which include non-deterministic rules for transitions between successive generations of the automaton together with probabilistic decisions about life and death of the cells in the next generation of the automaton. Different directions of the neighbours of each cell are treated with the possibility of applying distinct probabilities. This way, more realistic situations can be modelled and the obtained results are also non-deterministic. In this paper, we include a brief state of the art, the description of the model and some examples obtained with an implementation of the model made in Java. PubDate: 2019-08-01

Abstract: This paper focuses on the generalization ability of a dendritic neuron model (a model of a simple neural network). The considered model is an extension of the Hodgkin-Huxley model. The Markov kinetic schemes have been used in the mathematical description of the model, while the Lagrange multipliers method has been applied to train the model. The generalization ability of the model is studied using a method known from the regularization theory, in which a regularizer is added to the neural network error function. The regularizers in the form of the sum of squared weights of the model (the penalty function), a linear differential operator related to the input-output mapping (the Tikhonov functional), and the square norm of the network curvature are applied in the study. The influence of the regularizers on the training process and its results are illustrated with the problem of noise reduction in images of electronic components. Several metrics are used to compare results obtained for different regularizers. PubDate: 2019-08-01

Abstract: The article deals with the numerical simulation of unsteady flows through the turbine part of the turbocharger. The main focus of the article is the extension of the in-house CFD finite volume solver for the case of unsteady flows in radial turbines and the coupling to an external zero-dimensional model of the inlet and outlet parts. In the second part, brief description of a simplified one-dimensional model of the turbine is given. The final part presents a comparison of the results of numerical simulations using both the 3D CFD method and the 1D simplified model with the experimental data. The comparison shows that the properly calibrated 1D model gives accurate predictions of mass flow rate and turbine performance at much less computational time than the full 3D CFD method. On the other hand, the more expensive 3D CFD method does not need any specific calibration and allows detailed inspections of the flow fields. PubDate: 2019-08-01

Abstract: In a previous paper, the authors developed new rules for computing improper integrals which allow computer algebra systems (Cas) to deal with a wider range of improper integrals. The theory used in order to develop such rules where Laplace and Fourier transforms and the residue theorem. In this paper, we describe new rules for computing symbolic improper integrals using extensions of the residue theorem and analyze how some of the most important Cas could improve their improper integral computations using these rules. To achieve this goal, different tests are developed. The Cas considered have been evaluated using these tests. The obtained results show that all Cas involved, considering the new developed rules, could improve their capabilities for computing improper integrals. The results of the evaluations of the Cas are described providing a sorted list of the Cas depending on their scores. PubDate: 2019-08-01

Abstract: SfePy (simple finite elements in Python) is a software for solving various kinds of problems described by partial differential equations in one, two, or three spatial dimensions by the finite element method. Its source code is mostly (85%) Python and relies on fast vectorized operations provided by the NumPy package. For a particular problem, two interfaces can be used: a declarative application programming interface (API), where problem description/definition files (Python modules) are used to define a calculation, and an imperative API, that can be used for interactive commands, or in scripts and libraries. After outlining the SfePy package development, the paper introduces its implementation, structure, and general features. The components for defining a partial differential equation are described using an example of a simple heat conduction problem. Specifically, the declarative API of SfePy is presented in the example. To illustrate one of SfePy’s main assets, the framework for implementing complex multiscale models based on the theory of homogenization, an example of a two-scale piezoelastic model is presented, showing both the mathematical description of the problem and the corresponding code. PubDate: 2019-08-01

Abstract: The Magnus effect is responsible for deflecting the trajectory of a spinning baseball. The deflection at the end of the trajectory can be estimated by simulating some similar trajectories or by clustering real paths; however, previous to this study, there are no reports for a detailed connection between the initial throw conditions and the resulting deflection by using. The only approximation about this is the PITCHf/x algorithm, which uses the kinematics equations. In this work, deflections from simulated spinning throws with random linear and angular velocities and spin axis parallel to the horizontal plane are analyzed in their polar representation. A cardioid function is proposed to express the vertical deflection as response of the angular velocity. This is based on both theoretical arguments from the ball movement equations and from the numerical solution of such equations. We found that the vertical deflection fits a cardioid model as function of the Magnus coefficient and the spin angle, for a set of trajectories with initial linear velocities symmetrically distributed around the direction of motion. A variation of the model can be applied to estimate the radial deflection whereas an extended model should be explored for trajectories with velocities asymmetrically distributed. The model is suitable for many applications: from video games to pitching machines. In addition, the model approaches to the results obatined with the kinematic equations, which serves as validation of the PITCHf/x algorithm. PubDate: 2019-08-01

Abstract: The article deals with numerical solution of the laminar-turbulent transition. A mathematical model consists of the Reynolds-averaged Navier-Stokes equations, which are completed by the explicit algebraic Reynolds stress model (EARSM) of turbulence. The algebraic model of laminar-turbulent transition, which is integrated to the EARSM, is based on the work of Kubacki and Dick (Int. J. Heat Fluid Flow 58, 68–83, 2016) where the turbulent kinetic energy is split in to the small-scale and large-scale parts. The algebraic model is simple and does not require geometry data such as wall-normal distance and all formulas are calculated using local variables. A numerical solution is obtained by the finite volume method based on the HLLC scheme and explicit Runge-Kutta method. PubDate: 2019-08-01

Abstract: This paper describes the usage of the finite element library CFEM for solution of boundary value problems for partial differential equations. The application of the finite element method is shown based on the weak formulation of a boundary value problem. A unified approach for solution of linear scalar, linear vector, and nonlinear vector problems is presented. A direct link between the mathematical formulation and the design of the computer code is shown. Several examples and results are shown. PubDate: 2019-08-01

Abstract: Modeling and analyzing high-dimensional data has become a common task in various fields and applications. Often, it is of interest to learn a function that is defined on the data and then to extend its values to newly arrived data points. The Laplacian pyramids approach invokes kernels of decreasing widths to learns a given dataset and a function defined over it in a multi-scale manner. Extension of the function to new values may then be easily performed. In this work, we extend the Laplacian pyramids technique to model the data by considering two-directional connections. In practice, kernels of decreasing widths are constructed on the row-space and on the column space of the given dataset and in each step of the algorithm the data is approximated by considering the connections in both directions. Moreover, the method does not require solving a minimization problem as other common imputation techniques do, thus avoids the risk of a non-converging process. The method presented in this paper is general and may be adapted to imputation tasks. The numerical results demonstrate the ability of the algorithm to deal with a large number of missing data values. In addition, in most cases, the proposed method generates lower errors compared to existing imputation methods applied to benchmark dataset. PubDate: 2019-08-01

Abstract: This paper deals with the numerical solution of an ionization wave propagation in air, described by a coupled set of convection-diffusion-reaction equations and a Poisson equation. The standard three-species and more complex eleven-species models with simple chemistry are formulated. The PDEs are solved by a finite volume method that is theoretically second order in space and time on an unstructured adaptive grid. The upwind scheme and the diamond scheme are used for the discretization of the convective and diffusive fluxes, respectively. The Poisson equation is also discretized by the diamond scheme. The results of both models are compared in details for a test case. The influence of physically pertinent boundary conditions at electrodes is also presented. Finally, we deal with numerical accuracy study of implicit scheme in two variants for simplified standard model. It allows us in the future to compute simultaneously and efficiently a process consisting of short time discharge propagation and long-term after-discharge phase or repetitively pulsed discharge. PubDate: 2019-06-20