Structural analysis of two different stent configurations.

Two different stent configurations (i.e. the well known Palmaz-Schatz (PS) and a new stent configuration) are mechanically investigated. A finite element model was used to study the two geometries under combining loads and a computational fluid dynamic model based on fluid structure interaction was developed investigating the plaque and the artery wall reactions in a stented arterial segment. These models determine the stress and displacement fields of the two stents under internal pressure conditions. Results suggested that stent designs cause alterations in vascular anatomy that adversely affect arterial stress distributions within the wall, which have impact in the vessel responses such as the restenosis. The hemodynamic analysis shows the use of new stent geometry suggests better biofluid mechanical response such as the deformation and the progressive amount of plaque growth.

Behaviour of two typical stents towards a new stent evolution.

This study explores the analysis of a new stent geometry from two typical stents used to treat the coronary artery disease. Two different finite element methods are applied with different boundary conditions to investigate the stenosis region. Computational fluid dynamics (CFD) models including fluid-structure interaction are used to assess the haemodynamic impact of two types of coronary stents implantation: (1) type 1-based on a strut-link stent geometry and (2) type 2-a continuous helical stent. Using data from a recent clinical stenosis, flow disturbances and consequent shear stress alterations introduced by the stent treatment are investigated. A relationship between stenosis and the induced flow fields for the two types of stent designs is analysed as well as the correlation between haemodynamics and vessel wall biomechanical factors during the initiation and development of stenosis formation in the coronary artery. Both stents exhibit a good performance in reducing the obstruction artery. However, stent type 1 presents higher radial deformation than the type 2. This deformation can be seen as a limitation with a long-term clinical impact.

Identification of DVT diseases using numerical simulations.

This research provides useful insights for better diagnosis and understanding the vein blockage induced by a deep venous thrombosis and the occurrence of reverse flow in human veins, allowing a proper detection of serious diseases related to deep venous insufficiency. An arbitrary Lagrangian-Eulerian formulation is used in a coupled model (i.e. fluid and structure equations solved together), considering two domains, specifically the blood flow and the flexible structures (i.e. vein and valves). Computational fluid dynamics mathematical model based on finite element method, with special elements and boundary characterization, is addressed to find the best solution. This research presents a novel model to study the interaction between non-Newtonian laminar fluid flows, the blood, within nonlinear structures, the vein walls. Simulation results are validated using in vivo echo-Doppler measurements.

Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer.

A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.