Feedback and adaptive finite element solution of one-dimensional boundary value problems

Summary This paper examines the concepts of feedback and adaptivity for the Finite Element Method. The model problem concernsC ⁰ elements of arbitrary, fixed degree for a one-dimensional two-point boundary value problem. Three different feedback methods are introduced and a detailed analysis of their adaptivity is given.Dedicated to F.L. Bauer on the occasion of his 60th birthdayThis research was partially supported by the Office of Naval Research under grant number N00014-77-C-0623     

Error-controlled homogenization for a class of linear elastic composite problems

The research field of model adaptivity is well established, aiming at adaptive selection of mathematical models from a well defined class of models (model hierarchy) to achieve a preset level of accuracy, see e.g. [4, 5]. The present work addresses its application to a class of linear elastic composite problems. In order to adaptively control both macro model and macro discretization errors, we present a coupled adaptive scheme, which is driven by a goal-oriented error estimator based on duality techniques. For efficient computation of the dual solution, we make use of a patch-based recovery technique proposed in [6]. As a possibility for model adaptivity, we propose a model hierarchy based on the classical bounding theories [2, 3], which is established in a natural and theoretically consistent manner, without combination of different methods using a priori knowledge. For illustration, a numerical example is presented. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Error indicators for the mortar finite element discretization of the Laplace equation

The mortar technique turns out to be well adapted to handle mesh adaptivity in finite elements, since it allows for working with nonnecessarily compatible discretizations on the elements of a nonconforming partition of the initial domain. The aim of this paper is to extend the numerical analysis of residual error indicators to this type of methods for a model problem and to check their efficiency thanks to some numerical experiments.

     

Adaptive and Optimal Point-Wise Estimations for Densities in GARCH-Type Model by Wavelets

This paper considers adaptive point-wise estimations of density functions in GARCH-type model under the local Holder condition by wavelet methods.A point-wise lower bound estimation of that model is first investigated;then we provide a linear wavelet estimate to obtain the optimal convergence rate,which means that the convergence rate coincides with the lower bound.The non-linear wavelet estimator is introduced for adaptivity,although it is nearly-optimal.However,the non-linear wavelet one depends on an upper bound of the smoothness index of unknown functions,we finally discuss a data driven version without any assumptions on the estimated functions.     

Multiscale method based on discontinuous Galerkin methods for homogenization problems

We propose a multiscale method for elliptic problems with highly oscillating coefficients based on a coupling of macro and micro methods in the framework of the heterogeneous multiscale method. The macro method, defined on a macroscopic triangulation, aims at recovering the effective (homogenized) solution of an unknown macro model. The unspecified data of this model are computed by micro methods on sampling domains during the macro assembly process. In this Note, we show how to construct such a coupling with a discontinuous macro finite element space. We show that the flux information needed in this formulation in order to impose weak interelement continuity can be recovered from the known micro calculations on the sampling domains. A fully discrete analysis is presented. To cite this article: A. Abdulle, C. R. Acad. Sci. Paris, Ser. I 346 (2008).     

Fast algorithms for computing the Boltzmann collision operator

The development of accurate and fast numerical schemes for the five-fold Boltzmann collision integral represents a challenging problem in scientific computing. For a particular class of interactions, including the so-called hard spheres model in dimension three, we are able to derive spectral methods that can be evaluated through fast algorithms. These algorithms are based on a suitable representation and approximation of the collision operator. Explicit expressions for the errors in the schemes are given and spectral accuracy is proved. Parallelization properties and adaptivity of the algorithms are also discussed.

     

The root–unroot algorithm for density estimation as implemented via wavelet block thresholding

We propose and implement a density estimation procedure which begins by turning density estimation into a nonparametric regression problem. This regression problem is created by binning the original observations into many small size bins, and by then applying a suitable form of root transformation to the binned data counts. In principle many common nonparametric regression estimators could then be applied to the transformed data. We propose use of a wavelet block thresholding estimator in this paper. Finally, the estimated regression function is un-rooted by squaring and normalizing. The density estimation procedure achieves simultaneously three objectives: computational efficiency, adaptivity, and spatial adaptivity. A numerical example and a practical data example are discussed to illustrate and explain the use of this procedure. Theoretically it is shown that the estimator simultaneously attains the optimal rate of convergence over a wide range of the Besov classes. The estimator also automatically adapts to the local smoothness of the underlying function, and attains the local adaptive minimax rate for estimating functions at a point. There are three key steps in the technical argument: Poissonization, quantile coupling, and oracle risk bound for block thresholding in the non-Gaussian setting. Some of the technical results may be of independent interest.     

HILBERT — a MATLAB implementation of adaptive 2D-BEM

We report on the Matlab program package HILBERT. It provides an easily-accessible implementation of lowest order adaptive Galerkin boundary element methods for the numerical solution of the Poisson equation in 2D. The library was designed to serve several purposes: The stable implementation of the integral operators may be used in research code. The framework of Matlab ensures usability in lectures on boundary element methods or scientific computing. Finally, we emphasize the use of adaptivity as general concept and for boundary element methods in particular. In this work, we summarize recent analytical results on adaptivity in the context of BEM and illustrate the use of HILBERT. Various benchmarks are performed to empirically analyze the performance of the proposed adaptive algorithms and to compare adaptive and uniform mesh-refinements. In particular, we do not only focus on mathematical convergence behavior but also on the usage of critical system resources such as memory consumption and computational time. In any case, the superiority of the proposed adaptive approach is empirically supported.     

带合作行为的平均场模型的依全变差稳定性

该文考虑一个带合作行为的平均场模型的稳定性问题. 应用耦合方法, 建立了相应于这个平均场模型的扩散过程的依全变差稳定性.     

On Dimensional Adaptivity For Mixed Beam‐Shell‐Structures

A hierarchical model for dimensional adaptivity, using mixed beam‐shell structures, is presented. Thin‐walled beam structures are often calculated on the base of beam theories. Parts of the global structure, like framework corners, are usually analyzed with shell elements in a separate model. To minimize the modeling and calculation expense, a transition element to couple beam and shell structures is used. A dimensional adaptiv algorithm is introduced to automate this the procedure of modeling and calculation. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive nested implicit Runge–Kutta formulas of Gauss type

This paper deals with a special family of implicit Runge–Kutta formulas of orders 2, 4 and 6. These methods are of Gauss type; i.e., they are based on Gauss quadrature formulas of orders 2, 4 and 6, respectively. However, the methods under discussion have only explicit internal stages that lead to cheap practical implementation. Some of the stage values calculated in a step of the numerical integration are of sufficiently high accuracy that allows for dense output of the same order as the Runge–Kutta formula used. On the other hand, the methods developed are A-stable, stiffly accurate and symmetric. Moreover, they are conjugate to a symplectic method up to order 6 at least. All of these make the new methods attractive for solving nonstiff and stiff ordinary differential equations, including Hamiltonian and reversible problems. For adaptivity, different strategies of error estimation are discussed and examined numerically.     

Multiscale Coupling through Locally Enriched Finite Elements

Multiscale modeling helps us to focus our limited computational power into those special places where traditional models based on continuum mechanics will fail while not losing the big picture of the macro scale behavior. An hourglass shaped development can be observed in today's simulation technologies. Simulation tools in the macroscale category and that for the micro phenomenons are both relatively well developed. Many algorithms and methods have been proposed in recent years to fill the gap between them. However, rather than trying to bridging different techniques, many tend to replace them completely and become independent simulation tools. Since many single–scale models have already been widely adopted by both the industry and the academy, it would be more beneficial to concentrate just on coupling techniques which can be applied without significant modifications of the original simulation framework. In this work, we present a multiscale idea of coupling the fine–scale model with the coarse–scale model through local enrichment within the elements at the coupling boundary. Higher order shape functions have been used to ‘enrich’ the coarse–scale model, allowing softer transition of the displacement field from the fine–scale model to the coarse–scale model. A least–square process has been used to fit the displacement gradients of different models at the coupling region. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A fully adaptive hybrid optimization of aircraft engine blades

A new fully adaptive hybrid optimization method (AHM) has been developed and applied to an industrial problem in the field of the aircraft engine industry. The adaptivity of the coupling between a global search by a population-based method (Genetic Algorithms or Evolution Strategies) and the local search by a descent method has been particularly emphasized. On various analytical test cases, the AHM method overperforms the original global search method in terms of computational time and accuracy. The results obtained on the industrial case have also confirmed the interest of AHM for the design of new and original solutions in an affordable time.     

Finite element methods for problems with solid-liquid-solid phase transitions and free melt surface

Modeling and computation of a process with solid-liquid-solid phase transitions and a free capillary surface is discussed. The main components of the model are heat conduction, a free melt surface, a moving phase boundary, and its coupling with the Navier-Stokes equations. We present two different approaches for handling the phase transitions by applying in a FE method, namely an energy conservation based approach, and a sharp interface approach with moving mesh. By combining both methods, we benefit from the advantages of the respective approach. The methods are applied to a problem where material is accumulated by melting the tip of thin steel wires using laser heating. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On a hierarchical error estimator combined with a stabilized method for the Navier–Stokes equations

This work combines two complementary strategies for solving the steady incompressible Navier–Stokes model with a zeroth‐order term, namely, a stabilized finite element method and a mesh–refinement approach based on an error estimator. First, equal order interpolation spaces are adopted to approximate both the velocity and the pressure while stability is recovered within the stabilization approach. Also designed to handle advection dominated flows under zeroth‐order term influence, the stabilized method incorporates a new parameter with a threefold asymptotic behavior. Mesh adaptivity driven by a new hierarchical error estimator and built on the stabilized method is the second ingredient. The estimator construction process circumvents the saturation assumption by using an enhancing space strategy which is shown to be equivalent to the error. Several numerical tests validate the methodology. © 2011 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2011     

Parallel anisotropic mesh adaptivity with dynamic load balancing for cardiac electrophysiology

Simulations in cardiac electrophysiology generally use very fine meshes and small time steps to resolve highly localized wavefronts. This expense motivates the use of mesh adaptivity, which has been demonstrated to reduce the overall computational load. However, even with mesh adaptivity performing such simulations on a single processor is infeasible. Therefore, the adaptivity algorithm must be parallelised. Rather than modifying the sequential adaptive algorithm, the parallel mesh adaptivity method introduced in this paper focuses on dynamic load balancing in response to the local refinement and coarsening of the mesh. In essence, the mesh partition boundary is perturbed away from mesh regions of high relative error, while also balancing the computational load across processes. The parallel scaling of the method when applied to physiologically realistic heart meshes is shown to be good as long as there are enough mesh nodes to distribute over the available parallel processes. It is shown that the new method is dominated by the cost of the sequential adaptive mesh procedure and that the parallel overhead of inter-process data migration represents only a small fraction of the overall cost.     

Explicit and Implicit Solver Coupling: Stability Analysis Based on an Eight-Parameter Test Model

Coupling different solvers via co-simulation is frequently applied in the field of multi-physical simulation. The numerical stability and accuracy of the coupled problem strongly depends on the coupling technique used for the co-simulation. In the current work, different co-simulation approaches are analytically investigated based on a linear eight-parameter test model. The test model is formulated in state-space form containing input and output variables so that the results may directly be applied to practical coupling interfaces. For the test model, recurrence formulas are derived for explicit and implicit coupling techniques of Jacobian and Gauss-Seidel type. The numerical stability of the co-simulation approach is examined by an eigenvalue analysis of the corresponding recurrence equation. Three-dimensional stability plots can be analyzed for different coupling methods and for arbitrary order of the extrapolation/interpolation polynomial. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Optimal control for supply network models: Mixed integer programming

The aim of our investigations is the optimization of a continuous model for a special class of supply networks. We focus on the underlying fundamentals and show the relation to mixed-integer programming. This is done by applying numerical discretization schemes to the dynamics of the continuous equations and by approximations to the cost functional. One benefit of the MIP model is the adaptivity to real-world situations by adding reasonable extensions such as bounded queues. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive first integral preserving methods for PDEs

We present a method for constructing first integral preserving numerical schemes for time-dependent partial differential equations on non-uniform grids, using a finite difference approach for spatial discretization and discrete gradients for time stepping. The method is extended to accommodate spatial adaptivity. A numerical experiment is carried out where the method is applied to the Sine-Gordon equation with moving mesh adaptivity. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive Fourier tester for statistical estimation

Based on Takenaka–Malmquist (TM) system, a new nonparametric estimator for probability density function is proposed. The TM estimation method is completely different from the existent density estimation methods in that the estimator depends on an approximate system with poles in a complex plane. Compared with the classic Fourier estimator, the TM estimator will offer more flexibility and adaptivity for real data due to the poles and nonlinearity of the phase of TM system. We compare the TM estimator with kernel, wavelet, and spline estimators by simulations. It shows that the introduced TM estimator is a more promising method than the existing and commonly used methods. Copyright © 2016 John Wiley & Sons, Ltd.