Manuel Tur

The results of the pantograph–catenary interaction benchmark

This paper describes the results of a voluntary benchmark initiative concerning the simulation of pantograph–catenary interaction, which was proposed and coordinated by Politecnico di Milano and participated by 10 research institutions established in 9 different countries across Europe and Asia. The aims of the benchmark are to assess the dispersion of results on the same simulation study cases, to demonstrate the accuracy of numerical methodologies and simulation models and to identify the best suited modelling approaches to study pantograph–catenary interaction. One static and three dynamic simulation cases were defined for a non-existing but realistic high-speed pantograph–catenary couple. These cases were run using 10 of the major simulation codes presently in use for the study of pantograph–catenary interaction, and the results are presented and critically discussed here. All input data required to run the study cases are also provided, allowing the use of this benchmark as a term of comparison for other simulation codes.

PACDIN statement of methods

PAntograph–Catenary Dynamic Interaction (PACDIN) is a code developed by the vehicle technology research centre (CITV) of the Universitat Politècnica de València in collaboration with the railway company Talgo S.L. The model of the catenary is a finite element model using absolute nodal coordinates. It is based on a general formulation that can be applied for analysing a wide range of catenary configurations, including stitch wire, transitions or non-straight path tracks. The formulation is fully non-linear and includes large deformations, dropper slackening and contact interaction. The model is linearised when deformations are small, as in the case of the benchmark dynamic analysis. The results of the PACDIN code show a good agreement with the average results of other benchmark codes.

An approach to geometric optimisation of railway catenaries

ABSTRACT The quality of current collection becomes a limiting factor when the aim is to increase the speed of the present railway systems. In this work an attempt is made to improve current collection quality optimising catenary geometry by means of a genetic algorithm (GA). As contact wire height and dropper spacing are thought to be highly influential parameters, they are chosen as the optimisation variables. The results obtained show that a GA can be used to optimise catenary geometry to improve current collection quality measured in terms of the standard deviation of the contact force. Furthermore, it is highlighted that apart from the usual pre-sag, other geometric parameters should also be taken into account when designing railway catenaries.

Stochastic Monte Carlo simulations of the pantograph–catenary dynamic interaction to allow for uncertainties introduced during catenary installation

ABSTRACT The simulation of the pantograph–catenary dynamic interaction is at present mainly based on deterministic approaches. However, any errors made during the catenary stringing process are sources of variability that can affect the dynamic performance of the system. In this paper, we analyse the influence of dropper length, dropper spacing and support height errors on the current collection quality by applying a classic Monte Carlo method to obtain the probability density functions of several output quantities. The effects of installation errors are also studied for a range of train speeds. Finally, the pre-sag that, on average, produces the best behaviour of the system is identified, allowing for the uncertainty in the catenary installation. The results obtained show the convenience to consider variability in pantograph–catenary dynamic simulations.

Element Stiffness Matrix Integration in Image-Based Cartesian Grid Finite Element Method

Patient specific Finite Element (FE) simulations are usually expensive. Time consuming geometry creation procedures are normally necessary to use standard FE meshing software, while direct pixel-based meshing techniques typically lead to a large number of degrees of freedom hence introducing a high computational cost. Image-based Cartesian grid Finite Element Method (image-based cgFEM) allows accurate models to be automatically obtained with a low computational cost without the necessity of defining geometries. In cgFEM the image is directly immersed into a Cartesian mesh which is h-adapted on the basis of the pixel value distribution. A hierarchical structure of nested Cartesian grids guarantees the efficiency of the process. In each element, the material elastic properties are heterogeneous, therefore a critical aspect of image-based cgFEM is the integration of the element stiffness matrices which homogenize the material elastic behavior at the element level. This paper compares accuracy and computational cost of different integration strategies: pixel direct integration schemes (Riemann sum and subdomain Gauss quadrature) and recovery based schemes (Least Squares fitting and Superconvergent Patch Recovery).

The Use of Bayesian Optimisation Techniques for the Pantograph-Catenary Dynamic Interaction Stochastic Problem

The simulation of the pantograph-catenary dynamic interaction has become an essential tool for the design of the overhead contact line. With the help of an efficient simulation strategy, the geometry of the catenary can be optimised in terms of the current collection quality. This work is a first attempt to obtain robust optimised catenaries in which the uncertainty caused by the installation errors is taken into account in the simulations. The optimisation problem is solved by means of a Bayesian Optimisation algorithm and the stochastic objective function is evaluated via Monte Carlo simulations. The results show, on the one hand, the good performance of the Bayesian Optimisation technique when compared with a Genetic Algorithm, and on the other hand, the coincidence between the deterministic and the robust optimal catenaries.

On the effect of the contact surface definition in the Cartesian grid finite element method

The definition of the surface plays an important role in the solution of contact problems, as the evaluation of the contact force is based on the measure of the gap between the solids. In this work three different methods to define the surface are proposed for the solution of contact problems within the framework of the 3D Cartesian grid finite element method. A stabilized formulation is used to solve the contact problem and details of the kinematic description for each surface definition are provided. The three methods are compared solving some numerical tests involving frictionless contact with finite and small deformations.

Simulación estructural de espumas de aluminio a partir de imágenes 2D mediante la combinación de técnicas de homogeneización y machine learning

espanolEn la industria actual, el uso de materiales resistentes, rigidos, de bajo peso y con buenas propiedades tanto acusticas como termicas es de gran interes. Entre estos materiales encontramos las espumas de aluminio. Para su uso, es necesario conocer su comportamiento estructural. Para la obtencion de la geometria de una espuma de aluminio se pueden plantear diversas tecnicas, todas ellas basadas en que la informacion inicial proviene de una imagen obtenida mediante una Tomografia Axial Computarizada (TAC). Una posible metodologia, conocida comunmente como segmentacion, consiste en generar un CAD a partir de la imagen y de ahi el modelo de Elementos Finitos (EF). Otra opcion es usar tecnicas como el CellFEM o el cgFEM, donde cierta cantidad de pixeles, que definen las propiedades del material, son embebidos en cada elemento. De entre los diversos metodos que existen para evaluar la matriz de propiedades del material, en este trabajo se propone el uso de tecnicas de homogeneizacion aceleradas mediante tecnicas de machine learning. Dicha tecnica se ha aplicado a problemas reales obteniendo un elevado speed up sin sacrificar la precision. EnglishThe use of resistant, rigid, low-weight materials with good both acoustic and thermal properties is very interesting in today’s industry. Among these materials, one can find aluminium foams, whose mechanical behaviour is necessary for their application. In order to obtain the geometry of an aluminium foam, several techniques can be applied, and all of them are based in the fact that information is initially obtained by a Computed Axial Tomography (CAT). One of these techniques, known as segmentation, involves a CAD being generated from an image in order to build the Finite Element (FE) model. Another option is to use techniques such as CutFEM or cgFEM, in which a certain amount of pixels, which define the properties of the material, are embedded in each element. Among the existing methods for evaluating the material properties matrix, this study proposes the use of homogenization techniques, sped up by the use of machine learning techniques. This method has been applied to real problems obtaining a high speed up, conserving precision.

Diseño de actividades y uso de la coevaluación para fomentar el desarrollo de competencias transversales en ingeniería mecánica y de materiales

En esta comunicacion se presentan las actividades de evaluacion desarrolladas en el marco de un Proyecto de Innovacion y Mejora Educativa, junto con algunos resultados preliminares. El principal objetivo de este proyecto es el diseno de actividades de evaluacion que fuercen a los estudiantes a desarrollar sus competencias transversales, al mismo tiempo que permitan a los profesores evaluar su desempeno en las competencias cientifico-tecnicas. Se emplea un enfoque de evaluacion formativa, de forma que las actividades de evaluacion sean utiles a los estudiantes para mejorar su aprendizaje. Palabras clave: competencias transversales, actividades de evaluacion, coevaluacion

Numerical Simulation from Medical Images: Accurate Integration by Means of the Cartesian Grid Finite Element Method

Nowadays, when it comes to generation of patient-specific Finite Element model, there are two main alternatives. On the one hand, it is possible to generate geometrical models through segmentation, whereupon FE models would be obtained using standard mesh generators. On the other hand, we can create a Cartesian grid of uniform hexahedra in which the elements fit each pixel/voxel perfectly. In both cases, geometries will take part during the analysis either as complete models, in the first case, or as auxiliary entities, to apply boundary conditions properly for instance, in the second case. In any case, once the geometrical entities have been obtained from the medical image, the efficient generation of an accurate Finite Element model for numerical simulation in not trivial. The aim of this paper is to propose an efficient integration strategy, using Cartesian meshes, of 3D geometries defined by parametric surfaces, i.e. NURBS, obtained from medical images.