Marc Molinari

Adaptive mesh refinement techniques for electrical impedance tomography

Adaptive mesh refinement techniques can be applied to increase the efficiency of electrical impedance tomography reconstruction algorithms by reducing computational and storage cost as well as providing problem-dependent solution structures. A self-adaptive refinement algorithm based on an a posteriori error estimate has been developed and its results are shown in comparison with uniform mesh refinement for a simple head model.

Optimal imaging with adaptive mesh refinement in electrical impedance tomography

In non-linear electrical impedance tomography the goodness of fit of the trial images is assessed by the well-established statistical chi2 criterion applied to the measured and predicted datasets. Further selection from the range of images that fit the data is effected by imposing an explicit constraint on the form of the image, such as the minimization of the image gradients. In particular, the logarithm of the image gradients is chosen so that conductive and resistive deviations are treated in the same way. In this paper we introduce the idea of adaptive mesh refinement to the 2D problem so that the local scale of the mesh is always matched to the scale of the image structures. This improves the reconstruction resolution so that the image constraint adopted dominates and is not perturbed by the mesh discretization. The avoidance of unnecessary mesh elements optimizes the speed of reconstruction without degrading the resulting images. Starting with a mesh scale length of the order of the electrode separation it is shown that, for data obtained at presently achievable signal-to-noise ratios of 60 to 80 dB, one or two refinement stages are sufficient to generate high quality images.

Delivering data management for engineers on the grid

We describe the design and implementation of a database toolkit for engineers, which has been incorporated into the Matlab environment, to help manage the large amount of data created in distributed applications. The toolkit is built using Grid and Web services technologies, and exchanges XML metadata between heterogeneous Web services, databases and clients using open standards. We show an application exemplar of how this toolkit may be used in a grid-enabled Computational Electromagnetics design search.

Comparison of algorithms for non-linear inverse 3D electrical tomography reconstruction

Non-linear electrical impedance tomography reconstruction algorithms usually employ the Newton-Raphson iteration scheme to image the conductivity distribution inside the body. For complex 3D problems, the application of this method is not feasible any more due to the large matrices involved and their high storage requirements. In this paper we demonstrate the suitability of an alternative conjugate gradient reconstruction algorithm for 3D tomographic imaging incorporating adaptive mesh refinement and requiring less storage space than the Newton-Raphson scheme. We compare the reconstruction efficiency of both algorithms for a simple 3D head model. The results show that an increase in speed of about 30% is achievable with the conjugate gradient-based method without loss of accuracy.

Earth system modelling with Windows Workflow Foundation

The GENIE project has built a Grid-enabled Earth system modelling framework that facilitates the integration, execution and management of component models for the study of the Earth system over millennial timescales. The existing framework supports collaborative study of GENIE models across heterogeneous compute grids through scripted workflows in the Matlab environment. While the scripting approach achieves simplicity and flexibility, it suffers from an essentially passive approach to work unit management and from a heavy reliance on a central database to provide fault tolerance. The Windows Workflow Foundation (WF) technology provides a rich set of features to support the authoring and execution of workflows, tracking services that enable the monitoring of a running workflow, and state persistence services that allow workflows to be recovered and resumed upon failure. We demonstrate how the Windows Workflow Foundation has been applied to build a complementary simulation management system which provides rapid composition, event driven logic and reliable hosting of the scientific workflows while interfacing to existing infrastructure. We also describe how the adoption of WF enables the application of a number of associated technologies to provide better interoperability and accessibility for the simulation system. These improvements are demonstrated through a parametric study of the bi-stability of the oceanic thermohaline circulation in a GENIE model where the effects of a new carbon cycle are studied.

Building Scientific Workflows for Earth System Modelling with Windows Workflow Foundation

The GENIE project has built a Grid enabled framework that facilitates the integration, execution and management of component models for the study of the Earth system over millennial timescales. The existing framework supports collaborative study of GENIE models across heterogeneous compute grids through scripted workflows in the Matlab environment. In this paper, Windows Workflow Foundation technologies are applied to demonstrate the benefits of an environment that provides rapid composition, event driven logic and reliable hosting of scientific workflows. These improvements are demonstrated through a parametric study of bi-stability of the oceanic thermohaline circulation in a GENIE model.

Treatment of boundary conditions in the analysis of PBG structures.

Floquet theory is used in the analysis of periodic structures such as photonic crystals. We argue in this paper, that we can use the first form of the Floquet transform to treat the boundary conditions. The advantage is that we can use standard (nonperiodic) software for the analysis by the finite-element method. We give an example of this technique to the electromagnetic Kronig-Penny model in three space dimensions, where the use of vector elements is essential.

Efficient non-linear 3D electrical tomography and finite element optimizations for functional source imaging

An essential factor in functional source imaging is the accurate knowledge of the conducitvity dostribution inside the body. Current models for electrophysiological forward and inverse problems use tabulated conductivity values obtained from experiments. This article shows how EIT-derived conductivities can be used in EEG reconstructions of a head slice.