A Unified CFD Based Approach to a Variety of Condensation Processes in a Viscous Turbulent Wet Steam Flow

A family of quasi linear mathematical models is presented and calculations made for viscous turbulent wet steam flow with a variety of condensation phenomena. These models can be applied to the analysis of equilibrium condensation, homogeneous (spontaneous) condensation, heterogeneous condensation on extraneous particles, and condensation of charged dispersed phase moving in an electrostatic field. The unified model is represented by coupled systems of gas dynamic equations for viscous turbulent two-phase flow, kinetic and electro-kinetic equations tracing out combined processes of size and charge growth, and electromagnetic field equations described an electric field with an account of self- induced in-part by a moving electrical cluster. The numerical procedure is time marching, monotone, implicit, of second order accuracy by space and time coordinates, and exhibits high resolution shock capturing ability. Viscous flow field calculations made with this procedure reveal significant influence on condensation by the shear boundary layers and wakes. Distributions of cooling rate, droplet radius and parameters of the bulk flow are predicted. Verification of the codes against known experimental data is presented

Quantification of Hemodynamic Pulse Wave Velocity Based on a Thick Wall Multi-Layer Model for Blood Vessels

Pulse wave velocity (PWV) is an important index of arterial hemodynamics, which lays the foundation for continuous, noninvasive blood pressure automated monitoring. The goal of this paper is to examine the accuracy of PWV prediction based on a traditional homogeneous structural model for thin-walled arterial segments. In reality arteries are described as composite heterogeneous hyperelastic structures, where the thickness dimension cannot be considered small compared to the cross section size. In this paper we present a hemodynamic fluid - structure interaction model accounting for the variation of geometry and material properties in a radial direction. The model is suitable to account for the highly nonlinear orthotropic material undergoing finite deformation for each layer. Numerical analysis of single and two layer arterial segments shows that a single thick layer model provides sufficient accuracy to predict PWV. The dependence of PWV on pressure for three vessels of different thicknesses is compared against a traditional thin wall model of a membrane shell interacting with an incompressible fluid. The presented thick wall model provides greater accuracy in the prediction of PWV, and will be important for blood pressure estimation based on PWV measurements

Variational Approach of Constructing Reduced Fluid-Structure Interaction Models in Bifurcated Networks

Reduced fluid-structure interaction models have received a considerable attention in recent years being the key component of hemodynamic modeling. A variety of models applying to specific physiological components such as arterial, venous and cerebrospinal fluid (CSF) circulatory systems have been developed based on different approaches. The purpose of this paper is to apply the general approach based on Hamilton’s variational principle to create a model for a viscous Newtonian fluid - structure interaction (FSI) in a compliant bifurcated network. This approach provides the background for a correct formulation of reduced FSI models with an account for arbitrary nonlinear visco-elastic properties of compliant boundaries. The correct boundary conditions are specified at junctions, including matching points in a combined 3D/1D approach. The hyperbolic properties of derived mathematical model are analyzed and used, constructing the monotone finite volume numerical scheme, second-order accuracy in time and space. The computational algorithm is validated by comparison of numerical solutions with the exact manufactured solutions for an isolated compliant segment and a bifurcated structure. The accuracy of applied TVD (total variation diminishing) and Lax-Wendroff methods are analyzed by comparison of numerical results to the available analytical smooth and discontinuous solutions

Application of Variational Principle to Form Reduced Fluid-Structure Interaction Models in Bifurcated Networks

Reduced fluid-structure interaction models have received a considerable attention in recent years being the key component of hemodynamic modeling. A variety of models applying to specific physiological components such as arterial, venous and cerebrospinal fluid (CSF) circulatory systems have been developed based on different approaches. The purpose of this paper is to apply the general approach based on Hamilton’s variational principle to create a model for a viscous Newtonian Fluid - Structure Interaction (FSI) in a compliant bifurcated network. This approach provides the background for a correct formulation of reduced FSI models with an account for arbitrary nonlinear visco-elastic properties of compliant boundaries. The correct boundary conditions are specified at junctions, including the interface between 3D and 1D models. The hyperbolic properties of the derived mathematical model are analyzed and used, constructing a monotone finite volume numerical scheme, second-order accuracy in time and space. The computational algorithm is validated by comparison of numerical solutions with the exact manufactured solutions for an isolated compliant segment and a bifurcated structure. The accuracy of applied total variation diminishing (TVD) and Lax-Wendroff schemes are analyzed by comparison of numerical results to the available analytical smooth and discontinuous solutions, demonstrating a superior performance from the TVD algorithm

A neural tracking and motor control approach to improve rehabilitation of upper limb movements

<p>Abstract</p> <p>Background</p> <p>Restoration of upper limb movements in subjects recovering from stroke is an essential keystone in rehabilitative practices. Rehabilitation of arm movements, in fact, is usually a far more difficult one as compared to that of lower extremities. For these reasons, researchers are developing new methods and technologies so that the rehabilitative process could be more accurate, rapid and easily accepted by the patient. This paper introduces the proof of concept for a new non-invasive FES-assisted rehabilitation system for the upper limb, called smartFES (sFES), where the electrical stimulation is controlled by a biologically inspired neural inverse dynamics model, fed by the kinematic information associated with the execution of a planar goal-oriented movement. More specifically, this work details two steps of the proposed system: an <it>ad hoc </it>markerless motion analysis algorithm for the estimation of kinematics, and a neural controller that drives a synthetic arm. The vision of the entire system is to acquire kinematics from the analysis of video sequences during planar arm movements and to use it together with a neural inverse dynamics model able to provide the patient with the electrical stimulation patterns needed to perform the movement with the assisted limb.</p> <p>Methods</p> <p>The markerless motion tracking system aims at localizing and monitoring the arm movement by tracking its silhouette. It uses a specifically designed motion estimation method, that we named Neural Snakes, which predicts the arm contour deformation as a first step for a silhouette extraction algorithm. The starting and ending points of the arm movement feed an Artificial Neural Controller, enclosing the muscular Hill's model, which solves the inverse dynamics to obtain the FES patterns needed to move a simulated arm from the starting point to the desired point. Both position error with respect to the requested arm trajectory and comparison between curvature factors have been calculated in order to determine the accuracy of the system.</p> <p>Results</p> <p>The proposed method has been tested on real data acquired during the execution of planar goal-oriented arm movements. Main results concern the capability of the system to accurately recreate the movement task by providing a synthetic arm model with the stimulation patterns estimated by the inverse dynamics model. In the simulation of movements with a length of ± 20 cm, the model has shown an unbiased angular error, and a mean (absolute) position error of about 1.5 cm, thus confirming the ability of the system to reliably drive the model to the desired targets. Moreover, the curvature factors of the factual human movements and of the reconstructed ones are similar, thus encouraging future developments of the system in terms of reproducibility of the desired movements.</p> <p>Conclusion</p> <p>A novel FES-assisted rehabilitation system for the upper limb is presented and two parts of it have been designed and tested. The system includes a markerless motion estimation algorithm, and a biologically inspired neural controller that drives a biomechanical arm model and provides the stimulation patterns that, in a future development, could be used to drive a smart Functional Electrical Stimulation system (sFES). The system is envisioned to help in the rehabilitation of post stroke hemiparetic patients, by assisting the movement of the paretic upper limb, once trained with a set of movements performed by the therapist or in virtual reality. Future work will include the application and testing of the stimulation patterns in real conditions.</p

Vibration-induced extra torque during electrically-evoked contractions of the human calf muscles

<p>Abstract</p> <p>Background</p> <p>High-frequency trains of electrical stimulation applied over the lower limb muscles can generate forces higher than would be expected from a peripheral mechanism (i.e. by direct activation of motor axons). This phenomenon is presumably originated within the central nervous system by synaptic input from Ia afferents to motoneurons and is consistent with the development of plateau potentials. The first objective of this work was to investigate if vibration (sinusoidal or random) applied to the Achilles tendon is also able to generate large magnitude extra torques in the triceps surae muscle group. The second objective was to verify if the extra torques that were found were accompanied by increases in motoneuron excitability.</p> <p>Methods</p> <p>Subjects (n = 6) were seated on a chair and the right foot was strapped to a pedal attached to a torque meter. The isometric ankle torque was measured in response to different patterns of coupled electrical (20-Hz, rectangular 1-ms pulses) and mechanical stimuli (either 100-Hz sinusoid or gaussian white noise) applied to the triceps surae muscle group. In an additional investigation, M_maxand F-waves were elicited at different times before or after the vibratory stimulation.</p> <p>Results</p> <p>The vibratory bursts could generate substantial self-sustained extra torques, either with or without the background 20-Hz electrical stimulation applied simultaneously with the vibration. The extra torque generation was accompanied by increased motoneuron excitability, since an increase in the peak-to-peak amplitude of soleus F waves was observed. The delivery of electrical stimulation following the vibration was essential to keep the maintained extra torques and increased F-waves.</p> <p>Conclusions</p> <p>These results show that vibratory stimuli applied with a background electrical stimulation generate considerable force levels (up to about 50% MVC) due to the spinal recruitment of motoneurons. The association of vibration and electrical stimulation could be beneficial for many therapeutic interventions and vibration-based exercise programs. The command for the vibration-induced extra torques presumably activates spinal motoneurons following the size principle, which is a desirable feature for stimulation paradigms.</p