22,873 research outputs found
An Analysis of Finite Element Approximation in Electrical Impedance Tomography
We present a finite element analysis of electrical impedance tomography for
reconstructing the conductivity distribution from electrode voltage
measurements by means of Tikhonov regularization. Two popular choices of the
penalty term, i.e., -norm smoothness penalty and total variation
seminorm penalty, are considered. A piecewise linear finite element method is
employed for discretizing the forward model, i.e., the complete electrode
model, the conductivity, and the penalty functional. The convergence of the
finite element approximations for the Tikhonov model on both polyhedral and
smooth curved domains is established. This provides rigorous justifications for
the ad hoc discretization procedures in the literature.Comment: 20 page
Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography
Total variation (TV) is a powerful regularization method that has been widely
applied in different imaging applications, but is difficult to apply to diffuse
optical tomography (DOT) image reconstruction (inverse problem) due to complex
and unstructured geometries, non-linearity of the data fitting and
regularization terms, and non-differentiability of the regularization term. We
develop several approaches to overcome these difficulties by: i) defining
discrete differential operators for unstructured geometries using both finite
element and graph representations; ii) developing an optimization algorithm
based on the alternating direction method of multipliers (ADMM) for the
non-differentiable and non-linear minimization problem; iii) investigating
isotropic and anisotropic variants of TV regularization, and comparing their
finite element- and graph-based implementations. These approaches are evaluated
on experiments on simulated data and real data acquired from a tissue phantom.
Our results show that both FEM and graph-based TV regularization is able to
accurately reconstruct both sparse and non-sparse distributions without the
over-smoothing effect of Tikhonov regularization and the over-sparsifying
effect of L regularization. The graph representation was found to
out-perform the FEM method for low-resolution meshes, and the FEM method was
found to be more accurate for high-resolution meshes.Comment: 24 pages, 11 figures. Reviced version includes revised figures and
improved clarit
Generation of curved high-order meshes with optimal quality and geometric accuracy
We present a novel methodology to generate curved high-order meshes featuring optimal mesh quality and geometric accuracy. The proposed technique combines a distortion measure and a geometric L2-disparity measure into a single objective function. While the element distortion term takes into account the mesh quality, the L2-disparity term takes into account the geometric error introduced by the mesh approximation to the target geometry. The proposed technique has several advantages. First, we are not restricted to interpolative meshes and therefore, the resulting mesh approximates the target domain in a non-interpolative way, further increasing the geometric accuracy. Second, we are able to generate a series of meshes that converge to the actual geometry with expected rate while obtaining high-quality elements. Third, we show that the proposed technique is robust enough to handle real-case geometries that contain gaps between adjacent entities.Peer ReviewedPostprint (published version
Generation of Curved High-order Meshes with Optimal Quality and Geometric Accuracy
We present a novel methodology to generate curved high-order meshes featuring optimal mesh quality and geometric accuracy. The proposed technique combines a distortion measure and a geometric Full-size image (<1 K)-disparity measure into a single objective function. While the element distortion term takes into account the mesh quality, the Full-size image (<1 K)-disparity term takes into account the geometric error introduced by the mesh approximation to the target geometry. The proposed technique has several advantages. First, we are not restricted to interpolative meshes and therefore, the resulting mesh approximates the target domain in a non-interpolative way, further increasing the geometric accuracy. Second, we are able to generate a series of meshes that converge to the actual geometry with expected rate while obtaining high-quality elements. Third, we show that the proposed technique is robust enough to handle real-case geometries that contain gaps between adjacent entities.This research was partially supported by the Spanish Ministerio de EconomĂa y Competitividad under grand contract
CTM2014-55014-C3-3-R, and by the Government of Catalonia under grand contract 2014-SGR-1471. The work of the last author was supported by the European Commission through the Marie Sklodowska-Curie Actions
(HiPerMeGaFlows project).Peer ReviewedPostprint (published version
Generalized Debye Sources Based EFIE Solver on Subdivision Surfaces
The electric field integral equation is a well known workhorse for obtaining
fields scattered by a perfect electric conducting (PEC) object. As a result,
the nuances and challenges of solving this equation have been examined for a
while. Two recent papers motivate the effort presented in this paper. Unlike
traditional work that uses equivalent currents defined on surfaces, recent
research proposes a technique that results in well conditioned systems by
employing generalized Debye sources (GDS) as unknowns. In a complementary
effort, some of us developed a method that exploits the same representation for
both the geometry (subdivision surface representations) and functions defined
on the geometry, also known as isogeometric analysis (IGA). The challenge in
generalizing GDS method to a discretized geometry is the complexity of the
intermediate operators. However, thanks to our earlier work on subdivision
surfaces, the additional smoothness of geometric representation permits
discretizing these intermediate operations. In this paper, we employ both ideas
to present a well conditioned GDS-EFIE. Here, the intermediate surface
Laplacian is well discretized by using subdivision basis. Likewise, using
subdivision basis to represent the sources, results in an efficient and
accurate IGA framework. Numerous results are presented to demonstrate the
efficacy of the approach
A new Sobolev gradient method for direct minimization of the Gross-Pitaevskii energy with rotation
In this paper we improve traditional steepest descent methods for the direct
minimization of the Gross-Pitaevskii (GP) energy with rotation at two levels.
We first define a new inner product to equip the Sobolev space and derive
the corresponding gradient. Secondly, for the treatment of the mass
conservation constraint, we use a projection method that avoids more
complicated approaches based on modified energy functionals or traditional
normalization methods. The descent method with these two new ingredients is
studied theoretically in a Hilbert space setting and we give a proof of the
global existence and convergence in the asymptotic limit to a minimizer of the
GP energy. The new method is implemented in both finite difference and finite
element two-dimensional settings and used to compute various complex
configurations with vortices of rotating Bose-Einstein condensates. The new
Sobolev gradient method shows better numerical performances compared to
classical or gradient methods, especially when high rotation rates
are considered.Comment: to appear in SIAM J Sci Computin
Enhanced error estimator based on a nearly equilibrated moving least squares recovery technique for FEM and XFEM
In this paper a new technique aimed to obtain accurate estimates of the error
in energy norm using a moving least squares (MLS) recovery-based procedure is
presented. We explore the capabilities of a recovery technique based on an
enhanced MLS fitting, which directly provides continuous interpolated fields,
to obtain estimates of the error in energy norm as an alternative to the
superconvergent patch recovery (SPR). Boundary equilibrium is enforced using a
nearest point approach that modifies the MLS functional. Lagrange multipliers
are used to impose a nearly exact satisfaction of the internal equilibrium
equation. The numerical results show the high accuracy of the proposed error
estimator
- …