A mixed hp FEM for the approximation of fourth‐order singularly perturbed problems on smooth domains

We consider fourth‐order singularly perturbed problems posed on smooth domains and the approximation of their solution by a mixed Finite Element Method on the so‐called Spectral Boundary Layer Mesh. We show that the method converges uniformly, with respect to the singular perturbation parameter, at an exponential rate when the error is measured in the energy norm. Numerical examples illustrate our theoretical findings.     

Prediction of an outcome using NETwork Clusters (NET-C)

Birth weight is a key consequence of environmental exposures and metabolic alterations and can influence lifelong health. While a number of methods have been used to examine associations of trace element (including essential nutrients and toxic metals) concentrations or metabolite concentrations with a health outcome, birth weight, studies evaluating how the coexistence of these factors impacts birth weight are extremely limited. Here, we present a novel algorithm NETwork Clusters (NET-C), to improve the prediction of outcome by considering the interactions of features in the network and then apply this method to predict birth weight by jointly modelling trace element and cord blood metabolite data. Specifically, by using trace element and/or metabolite subnetworks as groups, we apply group lasso to estimate birth weight. We conducted statistical simulation studies to examine how both sample size and correlations between grouped features and the outcome affect prediction performance. We showed that in terms of prediction error, our proposed method outperformed other methods such as (a) group lasso with groups defined by hierarchical clustering, (b) random forest regression and (c) neural networks. We applied our method to data ascertained as part of the New Hampshire Birth Cohort Study on trace elements, metabolites and birth outcomes, adjusting for other covariates such as maternal body mass index (BMI) and enrollment age. Our proposed method can be applied to a variety of similarly structured high-dimensional datasets to predict health outcomes.     

Adaptive discretization for signal detection in statistical inverse problems

We discuss statistical tests in inverse problems when the original equation is replaced by a discretized one, i.e. a linear system of equations. Previous studies revealed that using the discretization level as regularizing procedure is possible, but its application is limited unless discretization is restricted to the singular value decomposition, see C. Marteau and P. Mathé, General regularization schemes for signal detection in inverse problems, 2013. General linear regularization may circumvent this, and we propose a regularization of the discretized equations. The discretization level may be chosen adaptively, which may save computational budget. This results in tests which are known to yield the optimal separation rate up to some constant in many cases.     

New representation and factorizations of the higher-order ultraspherical-type differential equations

The paper deals with the class of linear differential equations of any even order 2α+4$2\alpha +4$, α∈_N0$\alpha \in {\mathbb{N}}_0$, which are associated with the so-called ultraspherical-type polynomials. These polynomials form an orthogonal system on the interval [−1,1]$[-1,1]$ with respect to the ultraspherical weight function (1−x²)^α${(1-x^2)}^{\alpha }$ and additional point masses of equal size at the two endpoints. The differential equations of “ultraspherical-type” were developed by R. Koekoek in 1994 by utilizing special function methods. In the present paper, a new and completely elementary representation of these higher-order differential equations is presented. This result is used to deduce the orthogonality relation of the ultraspherical-type polynomials directly from the differential equation property. Moreover, we introduce two types of factorizations of the corresponding differential operators of order 2α+4$2\alpha +4$ into a product of α+2$\alpha +2$ linear second-order operators.     

FINITE ELEMENT ANALYSIS OF ANISOTROPIC FLUID SUSPENSIONS

The orientation tensor L is introduced to construct a modified Leslie–Ericksen model for the viscous, incompressible flow of anisotropic suspensions (including electric field effects). This is then utilized to develop a weak variational formulation and finite element scheme for computing the flow and orientation fields. Numerical results are presented for exploratory test problems.     

AN ENTROPY VARIABLE FORMULATION AND APPLICATIONS FOR THE TWO-DIMENSIONAL SHALLOW WATER EQUATIONS

A new symmetric formulation of the two-dimensional shallow water equations and a streamline upwind Petrov–Galerkin (SUPG) scheme are developed and tested. The symmetric formulation is constructed by means of a transformation of dependent variables derived from the relation for the total energy of the water column. This symmetric form is well suited to the SUPG approach as seen in analogous treatments of gas dynamics problems based on entropy variables. Particulars related to the construction of the upwind test functions and an appropriate discontinuity-capturing operator are included. A formal extension to the viscous, dissipative problem and a stability analysis are also presented. Numerical results for shallow water flow in a channel with (a) a step transition, (b) a curved wall transition and (c) a straight wall transition are compared with experimental and other computational results from the literature.     

A PIECEWISE–LINEARIZED METHOD FOR ORDINARY DIFFERENTIAL EQUATIONS: TWO–POINT BOUNDARY–VALUE PROBLEMS

Piecewise-linearized methods for the solution of two-point boundary value problems in ordinary differential equations are presented. These problems are approximated by piecewise linear ones which have analytical solutions and reduced to finding the slope of the solution at the left boundary so that the boundary conditions at the right end of the interval are satisfied. This results in a rather complex system of non-linear algebraic equations which may be reduced to a single non-linear equation whose unknown is the slope of the solution at the left boundary of the interval and whose solution may be obtained by means of the Newton–Raphson method. This is equivalent to solving the boundary value problem as an initial value one using the piecewise-linearized technique and a shooting method. It is shown that for problems characterized by a linear operator a technique based on the superposition principle and the piecewise-linearized method may be employed. For these problems the accuracy of piecewise-linearized methods is of second order. It is also shown that for linear problems the accuracy of the piecewise-linearized method is superior to that of fourth-order-accurate techniques. For the linear singular perturbation problems considered in this paper the accuracy of global piecewise linearizat ion is higher than that of finite difference and finite element methods. For non-linear problems the accuracy of piecewise-linearized methods is in most cases lower than that of fourth-order methods but comparable with that of second-order techniques owing to the linearization of the non-linear terms.     

MULTILEVEL SCHEMES FOR SOLVING UNSTEADY EQUATIONS

In this paper we propose and study various multilevel schemes for solving unsteady equations. Numerical comparisons between the choices of discretization and discussions are made on the Burgers equation in one and two dimensions. In particular we prove the advantage of using a hierarchical ADI solver.