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Publisher: Springer-Verlag (Total: 2352 journals)

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 Advances in Computational MathematicsJournal Prestige (SJR): 0.812 Citation Impact (citeScore): 1Number of Followers: 19      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1572-9044 - ISSN (Online) 1019-7168 Published by Springer-Verlag  [2352 journals]
• On continuous inkjet systems: a printer driver for expiry date labels on
cylindrical surfaces
• 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: 2019-05-17

• Multiscale finite element calculations in Python using SfePy
• 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: 2019-05-14

• Kolmogorov n -widths for linear dynamical systems
• Abstract: Kolmogorov n-widths and Hankel singular values are two commonly used concepts in model reduction. Here, we show that for the special case of linear time-invariant (LTI) dynamical systems, these two concepts are directly connected. More specifically, the greedy search applied to the Hankel operator of an LTI system resembles the minimizing subspace for the Kolmogorov n-width and the Kolmogorov n-width of an LTI system equals its (n + 1)st Hankel singular value once the subspaces are appropriately defined. We also establish a lower bound for the Kolmorogov n-width for parametric LTI systems and illustrate that the method of active subspaces can be viewed as the dual concept to the minimizing subspace for the Kolmogorov n-width.
PubDate: 2019-05-14

• Efficient alternating minimization methods for variational edge-weighted
colorization models
• Abstract: Alternating minimization algorithms are developed to solve two variational models, for image colorization based on chromaticity and brightness color system. Image colorization is a task of inpainting color from a small region of given color information. While the brightness is defined on the entire image domain, the chromaticity components are only given on a small subset of image domain. The first model is the edge-weighted total variation (TV) and the second one is the edge-weighted harmonic model that proposed by Kang and March (IEEE Trans. Image Proc. 16(9):2251–2261, 2007). Both models minimize a functional with the unit sphere constraints. The proposed methods are based on operator splitting, augmented Lagrangian, and alternating direction method of multipliers, where the computations can take advantage of multi-dimensional shrinkage and fast Fourier transform under periodic boundary conditions. Convergence analysis of the sequence generated by the proposed methods to a Karush-Kahn-Tucker point and a minimizer of the edge-weighted TV model are established. In several examples, we show the effectiveness of the new methods to colorize gray-level images, where only small patches of colors are given. Moreover, numerical comparisons with quadratic penalty method, augmented Lagrangian method, time marching, and/or accelerated time marching algorithms demonstrate the efficiency of the proposed methods.
PubDate: 2019-05-14

• Convergence of subdivision schemes on Riemannian manifolds with
nonpositive sectional curvature
• Abstract: This paper studies well-definedness and convergence of subdivision schemes which operate on Riemannian manifolds with nonpositive sectional curvature. These schemes are constructed from linear ones by replacing affine averages by the Riemannian centre of mass. In contrast to previous work, we consider schemes without any sign restriction on the mask, and our results apply to all input data. We also analyse the Hölder continuity of the resulting limit curves. Our main result states that if the norm of the derived scheme (resp. iterated derived scheme) is smaller than the corresponding dilation factor then the adapted scheme converges. In this way, we establish that convergence of a linear subdivision scheme is almost equivalent to convergence of its nonlinear manifold counterpart.
PubDate: 2019-05-02

• Sparse power factorization: balancing peakiness and sample complexity
• Abstract: In many applications, one is faced with an inverse problem, where the known signal depends in a bilinear way on two unknown input vectors. Often at least one of the input vectors is assumed to be sparse, i.e., to have only few non-zero entries. Sparse power factorization (SPF), proposed by Lee, Wu, and Bresler, aims to tackle this problem. They have established recovery guarantees for a somewhat restrictive class of signals under the assumption that the measurements are random. We generalize these recovery guarantees to a significantly enlarged and more realistic signal class at the expense of a moderately increased number of measurements.
PubDate: 2019-04-30

• Boundary integral analysis for non-homogeneous, incompressible Stokes
flows
• Abstract: A regular-grid volume-integration algorithm has been previously developed for solving non-homogeneous versions of the Laplace and the elasticity equations. This note demonstrates that the same approach can be successfully adapted to the case of non-homogeneous, incompressible Stokes flow. The key observation is that the Stokeslet (Green’s function) can be written as $$\mathcal {U}=\mu \nabla ^{2}\mathcal {H}$$ , where $$\mathcal {H}$$ has a simple analytical expression. As a consequence, the volume integral can be reformulated as an easily evaluated boundary integral, together with a remainder domain integral that can be computed using a regular cuboid grid covering the domain.
PubDate: 2019-04-29

• Coupling the algebraic model of bypass transition with EARSM model of
turbulence
• 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: 2019-04-26

• Numerical simulation of two-phase flow of immiscible fluids by the finite
element, discontinuous Galerkin and level-set methods
• Abstract: The subject of the paper is the numerical simulation of two-phase flow of immiscible fluids. Their motion is described by the incompressible Navier-Stokes equations with different constant density and viscosity for different fluids. The interface between the fluids is defined with the aid of the level-set method using a transport first-order hyperbolic equation. The Navier-Stokes system is equipped with initial and boundary conditions and transmission conditions on the interface between the two fluids. This system is discretized by the Taylor-Hood P2/P1 conforming finite elements in space and the second-order BDF method in time. The transport level-set problem is solved with the aid of the space-time discontinuous Galerkin method. Numerical experiments demonstrate that the developed method is accurate and robust.
PubDate: 2019-04-26

• Mathematical analysis to optimize crystal growth
• Abstract: For the production of sodium sulfate, a brine is crystallized and crystals of glauber salt are generated by this process. The phase data related to the most common sodium sulfate minerals are as follows: mirabilite (Na2SO4 ⋅ 10H2O), tenardite (Na2SO4), glauberite (Na2SO4 ⋅ CaSO4), astrakanite (Na2SO4 ⋅ MgSO4 ⋅ 4H2O). The units commonly used to express the phases are moles of salt per 1000 moles of water. These latter units simplify the construction of the commonly employed four-sided Janecke phase diagrams. The cooling temperature or the speed with which the solution is cooled has an effect on the size and purity, as well as the amount of crystals produced. We seek to establish, through the population balance equations (PBE), which process variables can be modified to obtain a specific crystal size, as well as to validate the mathematical model that best predicts the amount of crystals precipitated as a function of temperature. The adjustment by least squares, cubic splines, pitzer equations and Lagrange interpolation is tested. The experimental results agree with the characteristics of the proposed models.
PubDate: 2019-04-26

• Optimal approximation with exponential sums by a maximum likelihood
modification of Prony’s method
• Abstract: We consider a modification of Prony’s method to solve the problem of best approximation of a given data vector by a vector of equidistant samples of an exponential sum in the 2-norm. We survey the derivation of the corresponding non-convex minimization problem that needs to be solved and give its interpretation as a maximum likelihood method. We investigate numerical iteration schemes to solve this problem and give a summary of different numerical approaches. With the help of an explicitly derived Jacobian matrix, we review the Levenberg-Marquardt algorithm which is a regularized Gauss-Newton method and a new iterated gradient method (IGRA). We compare this approach with the iterative quadratic maximum likelihood (IQML). We propose two further iteration schemes based on simultaneous minimization (SIMI) approach. While being derived from a different model, the scheme SIMI-I appears to be equivalent to the Gradient Condition Reweighted Algorithm (GRA) by Osborne and Smyth. The second scheme SIMI-2 is more stable with regard to the choice of the initial vector. For parameter identification, we recommend a pre-filtering method to reduce the noise variance. We show that all considered iteration methods converge in numerical experiments.
PubDate: 2019-04-23

• Two directional Laplacian pyramids with application to data imputation
• 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: 2019-04-22

• Convergent tangent plane integrators for the simulation of chiral magnetic
skyrmion dynamics
• Abstract: We consider the numerical approximation of the Landau–Lifshitz–Gilbert equation, which describes the dynamics of the magnetization in ferromagnetic materials. In addition to the classical micromagnetic contributions, the energy comprises the Dzyaloshinskii–Moriya interaction, which is the most important ingredient for the enucleation and the stabilization of chiral magnetic skyrmions. We propose and analyze three tangent plane integrators, for which we prove (unconditional) convergence of the finite element solutions towards a weak solution of the problem. The analysis is constructive and also establishes existence of weak solutions. Numerical experiments demonstrate the applicability of the methods for the simulation of practically relevant problem sizes.
PubDate: 2019-04-22

• A bilinear ℋ 2 $\mathcal {H}_{2}$ model order reduction approach to
linear parameter-varying systems
• Abstract: This paper focuses on the model reduction problem for a special class of linear parameter-varying systems. This kind of systems can be reformulated as bilinear dynamical systems. Based on the bilinear system theory, we give a definition of the $$\mathcal {H}_{2}$$ norm in the generalized frequency domain. Then, a model reduction method is proposed based on the gradient descent on the Grassmann manifold. The merit of the method is that by utilizing the gradient flow analysis, the algorithm is guaranteed to converge, and further speedup of the convergence rate can be achieved as well. Two numerical examples are tested to demonstrate the proposed method.
PubDate: 2019-04-18

• A probabilistic extension to Conway’s Game of Life
• 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: 2019-04-11

• A shared memory parallel multi-mesh fast marching method for re-distancing
• Abstract: A common problem arising in expanding front simulations is to restore the signed distance field property of a discretized domain (i.e., a mesh), by calculating the minimum distance of mesh points to an interface. This problem is referred to as re-distancing and a widely used method for its solution is the fast marching method (FMM). In many cases, a particular high accuracy in specific regions around the interface is required. There, meshes with a finer resolution are defined in the regions of interest, enabling the problem to be solved locally with a higher accuracy. Additionally, this gives rise to coarse-grained parallelization, as such meshes can be re-distanced in parallel. An efficient parallelization approach, however, has to deal with interface-sharing meshes, load-balancing issues, and must offer reasonable parallel efficiency for narrow band and full band re-distancing. We present a parallel multi-mesh FMM to tackle these challenges: Interface-sharing meshes are resolved using a synchronized data exchanges strategy. Parallelization is introduced by applying a pool of tasks concept, implemented using OpenMP tasks. Meshes are processed by OpenMP tasks as soon as threads become available, efficiently balancing out the computational load of unequally sized meshes over the entire computation. Our investigations cover parallel performance of full and narrow band re-distancing. The resulting algorithm shows a good parallel efficiency, if the problem consists of significantly more meshes than the available processor cores.
PubDate: 2019-04-11

• Optimal convergence orders of fully geometric mesh one-leg methods for
neutral differential equations with vanishing variable delay
• Abstract: The purpose of this paper is to obtain the error bounds of fully geometric mesh one-leg methods for solving the nonlinear neutral functional differential equation with a vanishing delay. For this purpose, we consider Gq-algebraically stable one-leg methods which include the midpoint rule as a special case. The error of the first-step integration implemented by the midpoint rule on [0,T0] is first estimated. The optimal convergence orders of the fully geometric mesh one-leg methods with respect to T0 and the mesh diameter $$h_{\max }$$ are then analyzed and provided for such equation. Numerical studies reported for several test cases confirm our theoretical results and illustrate the effectiveness of the proposed method.
PubDate: 2019-04-10

• A cardioid-parametric model for the Magnus effect in baseballs
• 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: 2019-04-04

• New integer-order approximations of discrete-time non-commensurate
fractional-order systems using the cross Gramian
• Abstract: This paper presents a new approach to modeling of linear time-invariant discrete-time non-commensurate fractional-order single-input single-output state space systems by means of the Balanced Truncation and Frequency Weighted model order reduction methods based on the cross Gramian. These reduction methods are applied to the specific rational (integer-order) FIR-based approximation to the fractional-order system, which enables to introduce simple, analytical formulae for determination of the cross Gramian of the system. This leads to significant decrease of computational burden in the reduction algorithm. As a result, a rational and relatively low-order state space approximator for the fractional-order system is obtained. A simulation experiment illustrates an efficiency of the introduced methodology in terms of high approximation accuracy and low time complexity of the proposed method.
PubDate: 2019-04-01

• On the discontinuity of images recovered by noncovex nonsmooth regularized
isotropic models with box constraints
• Abstract: Nonconvex nonsmooth regularizations have exhibited the ability of restoring images with neat edges in many applications, which has been provided a mathematical explanation by analyzing the discontinuity of the local minimizers of the variational models. Since in many applications the pixel intensity values in digital images are restricted in a certain given range, box constraints are adopted to improve the restorations. A similar property of nonconvex nonsmooth regularization for box-constrained models has been proved in the literature. While many theoretical results are available for anisotropic models, we investigate the isotropic case. We establish similar theoretical results for isotropic nonconvex nonsmooth models with box constraints. Numerical experiments are presented to validate our theoretical results.
PubDate: 2019-04-01

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