Robert Bouzerar

A New Lumped-Parameter Model of Cerebrospinal Hydrodynamics During the Cardiac Cycle in Healthy Volunteers

Our knowledge of cerebrospinal fluid (CSF) hydrodynamics has been considerably improved with the recent introduction of phase-contrast magnetic resonance imaging (phase-contrast MRI), which can provide CSF and blood flow measurements throughout the cardiac cycle. Key temporal and amplitude parameters can be calculated at different sites to elucidate the role played by the various CSF compartments during vascular brain expansion. Most of the models reported in the literature do not take into account CSF oscillation during the cardiac cycle and its kinetic energy impact on the brain. We propose a new lumped-parameter compartmental model of CSF and blood flows in healthy subjects during the cardiac cycle. The system was divided into five submodels representing arterial blood, venous blood, ventricular CSF, cranial subarachnoid space, and spinal subarachnoid space. These submodels are connected by resistances and compliances. The model developed was used to reproduce certain functional characteristics observed in seven healthy volunteers, such as the distribution (amplitude and phase shift) of arterial, venous, and CSF flows. The results show a good agreement between measured and simulated intracranial CSF and blood flows

Dynamics of hydrocephalus: a physical approach

As brain ventricles lose their ability to regulate the cerebrospinal fluid (CSF) pressure, serious brain conditions collectively named hydrocephalus can appear. By modelling ventricular dynamics with the laws of physics, dynamical instabilities are evidenced, caused by either CSF transport dysregulations or abnormal properties of the elasticity of the ependyma. We show that these instabilities would lead, in most cases, to dilation of the ventricles, establishing a close connection to hydrocephalus, or in some other cases to a ventricular contraction as observed in the slit ventricle syndrome. Signs seem to indicate the possibility of phase transitions occurring as a result of these instabilities, which might have important clinical consequences, such as the inability to recover a healthy state. Even so, our dynamical approach could allow the development of a unified view of these complex intracranial conditions along with a classification that might be clinically relevant.

Electrodynamics of Magnetic Pulse Welding Machines: Global and Local Electrical Analogues

In this paper, a theoretical, experimental and numerical study of MPW machines is carried out. While it is known that such machines are very complex by nature because of the coupling between different parts, we used simple electrical analogues to describe its dynamics. A RLC circuit modeling the whole machine is depicted and experimental results are shown. A further study including numerical simulations allows to compute the current distribution and estimate the magnetic field within the coil but also the magnetic pressure generated in the process, all using a 2D model and reasonable assumptions. A late theoretical study opens the way for innovative experimental measurements regarding the kinetics of the deformations of metallic tubes, but also their mechanical behavior before the welding process, making use of their capacitive properties.

A physical model for brain ventricle dynamics

Brain ventricles (Rouvière and Delmas 2002) are four cavities filled with a liquid which they secrete, the cerebrospinal fluid (CSF). This fluid flows from ventricles to both the spinal cord and the subarachnoid spaces (around the brain) to eventually return to the bloodstream. As ventricles lose their ability to regulate the CSF pressure, serious brain pathologies called hydrocephalus can occur (Greenberg 1990). Characterised by a dilation of the ventricular space, these diseases can be deadly if not treated. The work of our team consists in a physical study of intracranial mechanics, taking into account the coupling of ventricular dynamics to the brain and surrounding compartments, be it of mechanical nature, or through fluid exchanges. We first address the problem from a theoretical view, making use of the fundamental laws of thermodynamics, hydrodynamics and the theory of elasticity. We then numerically assess the leading equations with a homemade code written on MATLAB. Dynamical instabilities are revealed, inducing an ‘explosion’ or a contraction of the ventricular space, making a possible link with the causes of hydrocephalus and the slit ventricle syndrome (Greenberg 1990).

Multi-contacts Interface: Electrical Properties of Dynamical Interface

Signal transfer systems are used in some industrial or transport applications. These systems have to transmit, through a sliding (pantograph/catenary) or a rolling (wheel/rail) multi-contact interface (MCI), power currents, measurements signals or control signals using specific communication protocols. In the interface are generated electromechanical couplings between solid surfaces of a device in motion, sometimes at high-speed. Whatever the condition of implementation, the quality of the contact must be understood to be optimized. The study of the performance indicators of these systems thus requires the physical understanding and the modeling of the mechanisms at the contact interface.

Multi-Scale and Multi-Physics Modeling of the Contact Interface Using DEM and Coupled DEM-FEM Approach

Abstract: This chapter presents the description of physical phenomena in the context of the modeling of the contact interface behavior based on discrete element method (DEM) and coupled DEM–finite element method (DEM–FEM) approach. Our interest in this area, which is related to several engineering applications where the contact interface plays a significant role, is prompted by the desire to understand the mechanisms that involved multi-physics coupling and how these influence the studied system from mechanical, thermal or electrical behavior point of view. Obviously, it is not easy to summarize all applications involving the contact interfaces, nevertheless, through those given as examples in the following sections, we have tried to highlight the relevance of a multi-scale and multi-physics approach with the aim of a modeling as close as possible to the microscale.