Fernando Sánchez

Soil evaluation for Castanea sativa afforestation in Northeastern Spain

This paper is focused on the soil characterisation of forest sites where Castanea sativa wood stands are located in Catalonia (NE of Spain) as a former and essential requirement to future afforestation programs with this species. From 28 sample plots field survey, several soil indexes have been calculated and, their central and marginal values have been established, defining a range of soil conditions where this species can successfully live in Catalonia. So, we can see that soils are developed on acid bedrock as parent material, basically igneous rocks such as granodiorite and granite, but they occur on schist as well. Their predominant texture is loamy-sand. Soils have low water holding capacity, mainly due to their high stoniness and steep slopes. Nevertheless, regular rainfall distribution all year around, avoids meteorological drought as well as reduces physiological drought. Annual rainfall distribution and steep slopes are responsible for the dwarf development of argic horizons. Soils are relatively poor in organic matter, and despite being generally very acid they have forest mull humus forms.

Improving Computational Efficiency in LCM by Using Computational Geometry and Model Reduction Techniques

LCM simulation is computationally expensive because it needs an accurate solution of flowequations during the mold filling process. When simulating large computing times are not compatiblewith standard optimization techniques (for example for locating optimally the injection nozzles)or with process control that in general requires fast decision-makings. In this work, inspired by theconcept of medial axis, we propose a numerical technique that computes numerically approximatedistance fields by invoking computational geometry concepts that can be used for the optimal locationof injection nozzles in infusion processes. On the other hand we also analyze the possibilities thatmodel order reduction offers to fast and accurate solutions of flow models in mold filling processes.

Towards a 2.5D geometric model in mold filling simulation

Resin Infusion (RI) process is frequently used for large composite parts production. This Liquid Composite Molding method uses vacuum pressure to shape a plastic bag as a counter mold. Once a complete vacuum is achieved, the resin is sucked into a dry preform textile laminate via placed tubing. In this note we introduce a 2.5D model for a Liquid Composite Molding LCM process starting from a recent one introduced by Besson and Poussin in Besson and Pousin (2005) for the Resin Transfer Molding RTM process. Moreover for 2.5D models defined over quadrilateral reference domains, we show the effectiveness of the use of the Proper Generalized Decomposition. Finally, we propose a procedure, for a particular class of 2.5D model, in order to perform a numerical simulation of a mold filling process.

A Computational Approach Based on Flow Front Shape Dynamic Behavior for the Process Characterization during Filling in Liquid Resin Infusion

Resin Infusion (RI) process is one of the common techniques used in the industry for large composite parts production. This technique uses vacuum pressure to drive the resin into a laminate. Preform is laid dry into the mold and the vacuum is applied before the resin is introduced. Once a complete vacuum is achieved, resin is sucked into the laminate via placed tubing. Fig.1 shows a diagram of this process.An appropriate modeling of flow front’s shapes constrained by LRI process during filling can be based on the continuous deformation of the vent oriented flow pattern due to the driving pressure from the inlet. One of the main objectives is that the flow achieves the contour vent uniformly to avoid pressure drop and ensuring complete filling. In LRI, the flow front shape progression is mainly conditioned by the initial arrangement of the injection line allocation and the permeability of the preform that can evolve along the mold

Meshless methods with application to Resin Transfer Molding simulation

In this work it is studied and analyzed the possible advantages to simulate the mold filling process in Resin Transfer Molding (RTM) with an updated Lagrangian formulation. For this purpose, the well known meshless natural element method (NEM) was implemented to simulate the mold filling process. In this approach, nodes are distributed in the calculation domain, however no mesh is needed to interpolate the unknown functions. This technique presents some advantages over classical finite element simulations (FEM): (1) no remeshing of the transient saturated domain is required at each calculation step; (2) the accuracy of the interpolation is not significantly affected by the nodal distribution. The use of meshless techniques also prevents from having to cope with the numerical instabilities generally associated with the numerical resolution of the transport equations that arise in RTM, such as in the heat balance during mold filling or in the equations giving the position of the fluid front or the incubatio...

MESTRIMAN: An expert system for medical triage and clinical management of patients in catastrophes

Abstract Providing appropriate medical assistance in catastrophes is not an easy problem to cope with. Some of the problems involved in the task are the diversity of catastrophes and medical emergencies, the insufficient number of experts usually available during a given catastrophe, the necessity of improving medical performace time, and the lack of coordination of the resources that may be used. In this respect, the application of both communication and computer technologies may provide important and useful support in most of the different phases involved in the management of catastrophes. In this paper we describe “MESTRIMAN,” an expert system designed to provide medical assistance in catastrophes. “MESTRIMAN” is a module of SIAC, a computer system designed to manage relevant information and data about a wide range of different catastrophes and capable of performing as the central coordinator of the available resources.