Partitioned Algorithms for Fluid-Structure Interaction Problems in Haemodynamics

We consider the fluid-structure interaction problem arising in haemodynamic applications. The finite elasticity equations for the vessel are written in Lagrangian form, while the Navier-Stokes equations for the blood in Arbitrary Lagrangian Eulerian form. The resulting three fields problem (fluid/ structure/ fluid domain) is formalized via the introduction of three Lagrange multipliers and consistently discretized by p-th order backward differentiation formulae (BDFp). We focus on partitioned algorithms for its numerical solution, which consist in the successive solution of the three subproblems. We review several strategies that all rely on the exchange of Robin interface conditions and review their performances reported recently in the literature. We also analyze the stability of explicit partitioned procedures and convergence of iterative implicit partitioned procedures on a simple linear FSI problem for a general BDFp temporal discretization

Personal Career Development Plans for all ESRs : Deliverable number: D1.1 - Version 1.1

In the ROMSOC project continuous career development strategies for the Early Stage Researchers (ESRs) are set up in order to enhance the career perspectives and employability of the recruited fellows to many public and private sectors (involving industry and research institutes). An intensive and highly qualified supervision and mentoring program, as well as the network-wide training activities contribute to the development of task-oriented research skills, generic research skills and transferable skills. The goal of the ROMSOC project is that the ESRs experience a wide range of interdisciplinary and intersectoral training to enable them to become professional workers and to take responsibility for their project and career management, while reflecting on their own skills and actively pursuing their own training needs.EC/H2020/765374/EU/Reduced Order Modelling, Simulation and Optimization of Coupled Systems/ROMSO

Análisis estadístico de las causas de accidentes de transito en la ciudad de Guayaquil

El trabajo que se presenta a continuación, consiste en un estudio estadístico de las causas de accidentes de transito que se registraron en la ciudad de Guayaquil, tomando como base para este estudio las publicaciones que realiza la Comisión de Transito del Guayas, con el cual se busca estudiar el comportamiento de las causas y sus consecuencias en la sociedad, mediante el uso de herramientas estadísticas. Este trabajo en su desarrollo presenta cuatro capítulos; Estudio histórico del transporte y transito de la ciudad de Guayaquil; en este capitulo se analiza antecedentes del transporte; El estudio de los accidentes en la ciudad de Guayaquil y sus consecuencias; en esta parte se analizan todos los factores que intervienen en los accidentes de transito como sus causa, tipos, condiciones del conductor y las consecuencias de los mismos; El siguiente capitulo de basa en el Marco teórico del trabajo; Análisis univariado y multivariado de las causas de accidentes de transito en la ciudad de Guayaqui

Coovar: Co-Occurring Variant Analyzer

Background Evaluating the impact of genomic variations (GV) on protein-coding transcripts is an important step in identifying variants of functional significance. Currently available programs for variant annotation depend on external databases or annotate multiple variants affecting the same transcript independently, which limits program use to organisms available in these databases or results in potentially incorrect or incomplete annotations. Findings We have developed CooVar (Co-occurring Variant Analyzer), a database-independent program for assessing the impact of GVs on protein-coding transcripts. CooVar takes GVs, reference genome sequence, and protein-coding exons as input and provides annotated GVs and transcripts as output. Other than similar programs, CooVar considers the combined impact of all GVs affecting the same transcript, generating biologically more accurate annotations. CooVar is operated from the command-line and supports standard file formats VCF, GFF/GTF, and GVF, which makes it easy to integrate into existing computational pipelines. We have extensively tested CooVar on worm and human data sets and demonstrate that it generates correct annotations in only a short amount of time. Conclusions CooVar is an easy-to-use and lightweight variant annotation tool that considers the combined impact of GVs on protein-coding transcripts. CooVar is freely available at http://genome.sfu.ca/projects/coovar/ webcite

Robin-Robin preconditioned Krylov methods for fluid-structure interaction problems

In this work, we propose a Robin–Robin preconditioner combined with Krylov iterations for the solution of the interface system arising in fluid–structure interaction (FSI) problems. It can be seen as a partitioned FSI procedure and in this respect it generalizes the ideas introduced in [S. Badia, F. Nobile, C. Vergara, J. Comput. Phys. 227 (2008) 7027–7051]. We analyze the convergence of GMRES iterations with the Robin–Robin preconditioner on a model problem and compare its efficiency with some existing algorithms. The method is shown to be very efficient for many challenging fluid–structure interaction problems, such as those characterized by a large added-mass effect or by enclosed fluids. In particular, the possibility to solve balloon-type problems without any special treatment makes this algorithm very appealing compared to the computationally intensive existing approaches

Fluid-structure partitioned procedures based on Robin transmission conditions

In this article we design new partitioned procedures for fluid–structure interaction problems, based on Robin-type transmission conditions. The choice of the coefficient in the Robin conditions is justified via simplified models. The strategy is effective whenever an incompressible fluid interacts with a relatively thin membrane, as in hemodynamics applications. We analyze theoretically the new iterative procedures on a model problem, which represents a simplified blood-vessel system. In particular, the Robin–Neumann scheme exhibits enhanced convergence properties with respect to the existing partitioned procedures. The theoretical results are checked using numerical experimentatio

Aplicación de membranas dinámicas auto-formantes para el tratamiento biológico de aguas residuales.

Si bien los precios de las membranas han experimentado una reducción notable, estas siguen siendo parte importante del costo asociado a la implementación de biorreactores de membrana (BRM) para el tratamiento de aguas residuales. La operaciónde BRM con membranas dinámicas auto-formantes permitiría una reducción considerable en los costos de inversión y operación asociados. Una membrana autoformante requiere solo de un soporte sobre el cual se forma un queque de filtración, el que actúa como membrana, rechazando los sólidos contenidos en el biorreactor. Durante la presente investigación se probaron mallas de tamizado de 20 y 100 μm como soportes para la formación de membranas dinámicas. Los resultados muestran que es posible sostener la operación del reactor en el tiempo y obtener un permeado de elevada calidad, con niveles de turbiedad inferiores a 3 NTU. El empleo de una malla de 100 μm permite aumentar el flujo, pero compromete la retención de sólidosy la remoción de materia orgánica

The Implementation of Monetary Policy in an Emerging Economy: The Case of Chile

Central bank authorities base implementation of monetary policy on an analysis of multiple variables known as monetary policy indicators. In a small open economy such as Chile, these indicators may include inflation misalignments, unemployment, GDP growth, money growth, the current account balance, exchange rate volatility and international reserves. A neural network approach is used to establish the corresponding weights considered by the Board of the Central Bank of Chile during the period 1995-2003. GDP growth and the difference between the actual and the target inflation were found to be among the variables of greatest weight in the monetary policy decision-making process of the Central Bank of Chile during this period.Monetary Policy, Neural Network