A 3D discrete model of the diaphragm and human trunk

In this paper, a 3D discrete model is presented to model the movements of the trunk during breathing. In this model, objects are represented by physical particles on their contours. A simple notion of force generated by a linear actuator allows the model to create forces on each particle by way of a geometrical attractor. Tissue elasticity and contractility are modeled by local shape memory and muscular fibers attractors. A specific dynamic MRI study was used to build a simple trunk model comprised of by three compartments: lungs, diaphragm and abdomen. This model was registered on the real geometry. Simulation results were compared qualitatively as well as quantitatively to the experimental data, in terms of volume and geometry. A good correlation was obtained between the model and the real data. Thanks to this model, pathology such as hemidiaphragm paralysis can also be simulated.Comment: published in: "Lung Modelling", France (2006

Diagnostics for magnetically confined high-temperature plasmas

During the last 20 years, magnetically confined laboratory plasmas of steadily increasing temperatures and densities have been obtained, most notably in tokamak configurations, and now approach the conditions necessary to sustain a fusion reaction. Even more important to the goal of understanding the physics of such systems, remarkable advances in plasma diagnostics, the techniques for determining the properties of such plasmas, have accompanied these developments. More parameters can be determined with greater accuracy and finer spatial and temporal resolution. The magnetic configuration, the primary local thermodynamic quantities (density, temperature, and drift velocity), and other necessary quantities can now be measured with sufficient accuracy to determine particle and energy fluxes within the plasma and to characterize the basic transport processes. These plasmas are far from thermodynamic equilibrium. This deviation manifests itself in a variety of instabilities on several spatial and temporal scales, many of which are aptly described as turbulence. Many aspects of the turbulence can also be characterized. This article reviews the current state of diagnostics from an epistemoiogical perspective: the capabilities and limitations for measuring each important physical quantity are presented.Physic

Particle Density Estimation with Grid-Projected Adaptive Kernels

The reconstruction of smooth density fields from scattered data points is a procedure that has multiple applications in a variety of disciplines, including Lagrangian (particle-based) models of solute transport in fluids. In random walk particle tracking (RWPT) simulations, particle density is directly linked to solute concentrations, which is normally the main variable of interest, not just for visualization and post-processing of the results, but also for the computation of non-linear processes, such as chemical reactions. Previous works have shown the superiority of kernel density estimation (KDE) over other methods such as binning, in terms of its ability to accurately estimate the "true" particle density relying on a limited amount of information. Here, we develop a grid-projected KDE methodology to determine particle densities by applying kernel smoothing on a pilot binning; this may be seen as a "hybrid" approach between binning and KDE. The kernel bandwidth is optimized locally. Through simple implementation examples, we elucidate several appealing aspects of the proposed approach, including its computational efficiency and the possibility to account for typical boundary conditions, which would otherwise be cumbersome in conventional KDE