Comlab

The heart can be described as an electrically driven mechanical pump. This

pump couldn't adapt to beat-by-beat changes in circulatory demand if there

was no feedback from the mechanical environment to the electrical control

processes. Cardiac mechano-electric feedback has been studied at various

levels of functional integration, from stretch-activated ion channels,

through mechanically induced changes in cardiac cells and tissue, to

clinically relevant observations in man, where mechanical stimulation of the

heart may either disturb or reinstate cardiac rhythmicity. The seminar will

illustrate the patho-physiological relevance of cardiac mechano-electric

feedback, introduce underlying mechanisms, and show the utility of iterating

between experimental research and mathematical modelling in studying this

phenomenon.

Semidefinite programming (SDP) techniques have been extremely successful

in many practical engineering design questions. In several of these

applications, the problem structure is invariant under the action of

some symmetry group, and this property is naturally inherited by the

underlying optimization. A natural question, therefore, is how to

exploit this information for faster, better conditioned, and more

reliable algorithms. To this effect, we study the associative algebra

associated with a given SDP, and show the striking advantages of a

careful use of symmetries. The results are motivated and illustrated

through applications of SDP and sum of squares techniques from networked

control theory, analysis and design of Markov chains, and quantum

information theory.

Discontinuous Galerkin methods (DG) use trial and test functions that are continuous within

elements and discontinuous at element boundaries. Although DG methods have been invented

in the early 1970s they have become very popular only recently.

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DG methods are very attractive for flow and transport problems in porous media since they

can be used to solve hyperbolic as well as elliptic/parabolic problems, (potentially) offer

high-order convergence combined with local mass balance and can be applied to unstructured,

non-matching grids.

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In this talk we present a discontinuous Galerkin method based on the non-symmetric interior

penalty formulation introduced by Wheeler and Rivi\`{e}re for an elliptic equation coupled to

a nonlinear parabolic/hyperbolic equation. The equations cover models for groundwater flow and

solute transport as well as two-phase flow in porous media.

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We show that the method is comparable in efficiency with the mixed finite element method for

elliptic problems with discontinuous coefficients. In the case of two-phase flow the method

can outperform standard finite volume schemes by a factor of ten for a five-spot problem and

also for problems with dominating capillary pressure.

The standard airframe industry tool for flutter analysis is based

on linear potential predictions of the aerodynamics. Despite the

limitations of the modelling this is even true in the transonic

range. There has been a heavy research effort in the past decade to

use CFD to generate the aerodynamics for flutter simulations, to

improve the reliability of predictions and thereby reduce the risk

and cost of flight testing. The first part of the talk will describe

efforts at Glasgow to couple CFD with structural codes to produce

a time domain simulation and an example calculation will be described for

the BAE SYSTEMS Hawk aircraft.

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A drawback with time domain simulations is that unsteady CFD is still

costly and parametric searches to determine stability through the

growth or decay of responses can quickly become impractical. This has

motivated another active research effort in developing ways of

encapsulating the CFD level aerodynamic predictions in models which

are more affordable for routine application. A number of these

approaches are being developed (eg POD, system identification...)

but none have as yet reached maturity. At Glasgow effort has been

put into developing a method based on the behaviour of the

eigenspectrum of the discrete operator Jacobian, using Hopf

Bifurcation conditions to formulate an augmented system of

steady state equations which can be used to calculate flutter speeds

directly. The talk will give the first three dimensional example

of such a calculation.

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For background reports on these topics see

http://www.aero.gla.ac.uk/Research/CFD/projects/aeroelastics/pubs/menu…

It is known for elliptic problems with smooth coefficients

that the solution is smooth in the interior of the domain;

low regularity is only possible near the boundary.

The $hp$-version of the FEM allows us to exploit this

property if we use meshes where the element size grows

porportionally to the element's distance to the boundary

and the approximation order is suitably linked to the

element size. In this way most degrees of freedom are

concentrated near the boundary.

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In this talk, we will discuss convergence and complexity

issues of the boundary concentrated FEM. We will show

that it is comparable to the classical boundary element

method (BEM) in that it leads to the same convergence rate

(error versus degrees of freedom). Additionally, it

generalizes the classical FEM since it does not require

explicit knowledge of the fundamental solution so that

it is also applicable to problems with (smooth) variable

coefficients.

Following the framework of Formaggia and Perotto (Numer.

Math. 2001 and 2003), anisotropic a posteriori error estimates have been

proposed for various elliptic and parabolic problems. The error in the

energy norm is bounded above by an error indicator involving the matrix

of the error gradient, the constant being independent of the mesh aspect

ratio. The matrix of the error gradient is approached using

Zienkiewicz-Zhu error estimator. Numerical experiments show that the

error indicator is sharp. An adaptive finite element algorithm which

aims at producing successive triangulations with high aspect ratio is

proposed. Numerical results will be presented on various problems such

as diffusion-convection, Stokes problem, dendritic growth.

While the average settling velocity of particles in a suspension has been successfully predicted, we are still unsuccessful with the r.m.s velocity, with theories suggesting a divergence with the size of

the container and experiments finding no such dependence. A possible resolution involves stratification originating from the spreading of the front between the clear liquid above and the suspension below. One theory describes the spreading front by a nonlinear diffusion equation

$\frac{\partial \phi}{\partial t} = D \frac{\partial }{\partial z}(\phi^{4/5}(\frac{\partial \phi}{\partial z})^{2/5})$.

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Experiments and computer simulations find differently.

An essential first step in many problems of numerical analysis and

computer graphics is to cover a region with a reasonably regular mesh.

We describe a short MATLAB code that begins with a "distance function"

to describe the region: $d(x)$ is the distance to the boundary

(with d

In recent years, there has been considerable interest, especially in the context of

fluid-dynamics, in nonconforming finite element methods that are based on discontinuous

piecewise polynomial approximation spaces; such approaches are referred to as discontinuous

Galerkin (DG) methods. The main advantages of these methods lie in their conservation properties, their ability to treat a wide range of problems within the same unified framework, and their great flexibility in the mesh-design. Indeed, DG methods can easily handle non-matching grids and non-uniform, even anisotropic, polynomial approximation degrees. Moreover, orthogonal bases can easily be constructed which lead to diagonal mass matrices; this is particularly advantageous in unsteady problems. Finally, in combination with block-type preconditioners, DG methods can easily be parallelized.

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In this talk, we introduce DG discretizations of mixed field and potential-based formulations of

eddy current problems in the time-harmonic regime. For the electric field formulation, the

divergence-free constraint within non-conductive regions is imposed by means of a Lagrange

multiplier. This allows for the correct capturing of edge and corner singularities in polyhedral domains; in contrast, additional Sobolev regularity must be assumed in the DG formulation, and their conforming counterparts, when regularization techniques are employed. In particular, we present a mixed method involving discontinuous $P^\ell-P^\ell$ elements, which includes a normal jump stabilization term, and a non-stabilized variant employing discontinuous $P^\ell-P^{\ell+1}$ elements.The first formulation delivers optimal convergence rates for the vector-valued unknowns in a suitable energy norm, while the second (non-stabilized) formulation is designed to yield optimal convergence rates in both the $L^2$--norm, as well as in a suitable energy norm. For this latter method, we also develop the {\em a posteriori} error estimation of the mixed DG approximation of the Maxwell operator. Indeed, by employing suitable Helmholtz decompositions of the error, together with the conservation properties of the underlying method, computable upper bounds on the error, measured in terms of the energy norm, are derived.

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Numerical examples illustrating the performance of the proposed methods will be presented; here,

both conforming and non-conforming (irregular) meshes will be employed. Our theoretical and

numerical results indicate that the proposed DG methods provide promising alternatives to standard conforming schemes based on edge finite elements.

The satisfiability (SAT) problem is a central problem in mathematical

logic, computing theory, and artificial intelligence. We consider

instances of SAT specified by a set of boolean variables and a

propositional formula in conjunctive normal form. Given such an instance,

the SAT problem asks whether there is a truth assignment to the variables

such that the formula is satisfied. It is well known that SAT is in

general NP-complete, although several important special cases can be

solved in polynomial time. Extending the work of de Klerk, Warners and van

Maaren, we present new linearly sized semidefinite programming (SDP)

relaxations arising from a recently introduced paradigm of higher

semidefinite liftings for discrete optimization problems. These

relaxations yield truth assignments satisfying the SAT instance if a

feasible matrix of sufficiently low rank is computed. The sufficient rank

values differ between relaxations and can be viewed as a measure of the

relative strength of each relaxation. The SDP relaxations also have the

ability to prove that a given SAT formula is unsatisfiable. Computational

results on hard instances from the SAT Competition 2003 show that the SDP

approach has the potential to complement existing techniques for SAT.