Alice Innocenti

Development of a wear model for the wheel profile optimisation on railway vehicles

The modelling and the reduction of wear due to wheel–rail interaction is a fundamental aspect in the railway field, mainly correlated to safety, maintenance interventions and costs. In this work, the authors present two innovative wheel profiles, specifically designed with the aim of improving the wear and stability behaviour of the standard ORE S1002 wheel profile matched with the UIC60 rail profile canted at 1/20 rad, which represents the wheel–rail combination adopted in the Italian railway line. The two wheel profiles, conventionally named CD1 and DR2, have been developed by the authors in collaboration with Trenitalia S.p.A. The CD1 profile has been designed with the purpose of spreading the contact points in the flange zone on a larger area in order to reduce wear phenomena and having a constant equivalent conicity for small lateral displacements of the wheelset with respect to the centred position in the track. The DR2 wheel profile is instead designed to guarantee the same kinematic characteristics of the matching formed by ORE S1002 wheel profile and UIC60 rail profile with laying angle α p equal to 1/40 rad, widely common in European railways and characterised by good performances in both wear and kinematic behaviour. The evolution of wheel profiles due to wear has been evaluated through a wear model developed and validated by the authors in previous works. The wear model comprises two mutually interactive units: a vehicle model for the dynamic simulations and a model for the wear assessment. The whole model is based on a discrete process: each discrete step consists in one dynamic simulation and one profile update by means of the wear model while, within the discrete step, the profiles are supposed to be constant. The choice of an appropriate step is crucial in terms of precision and computational effort: the particular strategy adopted in the current work has been chosen for its capacity in representing the nonlinear wear evolution and for the low computational time required. In the present research, the investigated trainset is the passenger vehicle ALSTOM ALn 501 ‘Minuetto’, which is usually equipped with the standard ORE S1002 wheel profile in Italian railways. The entire model has been simulated on a virtual track specifically developed to represent a statistical description of the whole Italian line. The data necessary to build the virtual track and the vehicle model were provided by Trenitalia S.p.A. and Rete Ferroviaria Italiana. The CD1 and DR2 wheel profiles, matched to the UIC60 rail with cant 1/20 rad, have shown a good behaviour in terms of wear resistance if compared with the old ORE S1002 wheel profile, consequently assuring a more uniform distribution of the removed material and a prolongation of the mean time between two subsequent re-profiling interventions.

A numerical procedure for the wheel profile optimisation on railway vehicles

The reduction of wear due to wheel–rail interaction is a fundamental aspect in the railway field, mainly correlated to safety, maintenance interventions and costs. In this work, the authors present an innovative wheel profile optimisation procedure, specifically designed with the aim of improving the wear and stability behaviour of the standard ORE S1002 wheel profile matched with the UIC60 rail profile canted at 1/20 rad, which represents the wheel–rail combination adopted in Italian railway line; this matching shows poor wear performance due to the non-conformal contact. A new wheel profile, conventionally named DR2, has been developed by the authors in collaboration with Trenitalia S.p.A. The DR2 wheel profile is designed to guarantee the same kinematic characteristics of the matching formed by ORE S1002 wheel profile and UIC60 rail profile with inclination angle α p equal to 1/40 rad, widely common in European railways and characterised by good performances in both wear and kinematic behaviour. The evolution of wheel profiles due to wear has been evaluated through a wear model developed and validated by the authors in previous works. In the present research the investigated trainset is the passenger vehicle ALSTOM ALn 501 “Minuetto”, which is usually equipped with wheelsets having the standard ORE S1002 wheel profile in Italian railways. The entire model has been simulated on a virtual track specifically developed to represent a statistical description of the whole Italian line; the innovative statistical approach has been employed to obtain accurate results in reasonable computational times. The data necessary to build the virtual track and the vehicle model were provided by Trenitalia S.p.A. and Rete Ferroviaria Italiana (RFI).

Prediction of wheel and rail profile wear on complex railway networks

The modelling and the reduction of wear due to wheel-rail contact represents a crucial issue in railway applications, mainly correlated to safety, maintenance interventions and definition of strategies aimed at wheel profile optimization. A model for evaluating wheel and rail profile evolution due to wear developed for complex railway networks is presented in this paper. The model layout is composed of two mutually interacting but separate parts: a vehicle model (composed of multibody model and global contact model) for the dynamical simulations and a unit for wear computation (composed of the local contact model, the wear evaluation procedure and the profile update strategy). In order to achieve general significant accuracy results in reasonable computational effort, a suitable statistical approach for the railway track description is used, aimed at studying complex railway lines: in fact, the exhaustive analysis of vehicle dynamics and wear evolution on all the railway network is too expensive in terms of computational time for each practical purpose. The wear model has been validated in collaboration with Trenitalia S.P.A and Rete Ferroviaria Italiana (RFI), which have provided technical documentation and experimental data relative to some tests performed on a environment exhibiting serious problems in terms of wear: the vehicle ALn 501 Minuetto operated on the Aosta-Pre Saint Didier Italian line.

Obsessive compulsive disorder comorbidity in DBA

Diamond-Blackfan Anemia (DBA) is a congenital erythroid aplasia characterized as a normochromic macrocytic anemia with a selective deficiency in red blood cell precursors in otherwise normocelullar bone marrow. DBA is known to be associated with mental retardation and learning disabilities. Although comorbidities with other psychiatric conditions have not been reported in the existing literature, we report in this paper a case of a DBA patient with previously undiagnosed comorbidity of obsessive compulsive disorder (OCD), successfully treated with sertaline 200 mg/day and valproic acid 600 mg/day. This case of comorbid presentation has clinical, therapeutic and pathophysiological implications. Given the difficulty of distinguishing among mental retardation, learning disabilities and OCD and the importance of precocious diagnosis in treating OCD especially since there are treatment methods interfering with anemia symptoms, physicians should adapt an adequate screening tool treating a child with DBA and comorbid mental disorder.

An innovative algorithm for train detection

Train detection is a very important research issue affecting vehicles and line safety. Currently, the European Train Control System ETCS (a signalling, control and train protection system) Level 1 and 2 provide the train localization functionalities by using track circuits and/or axle counter systems: the problem of these solutions is represented by the high cost of track circuit and axle counter installation and of the related equipment management. This paper presents an innovative train detection algorithm, able to perform the train localization, by estimating its speed, crossing time instants and axle number. The aim of the proposed solution is to use the same processing approach to evaluate all these quantities, starting from the knowledge of the vertical loads on the sleepers directly measured on the track. The inputs are processed through cross-correlation operations to extract the required information in terms of speed, crossing time instants and axle counter. A suitable model of railway vehicle and track has been also developed to test the algorithm when experimental data are not available. The railway vehicle chosen as benchmark is the Manchester Wagon, implemented in the Adams VI-Rail environment. The physical model of the flexible track has been implemented in the Matlab and Comsol Multiphysics environments. A simulation campaign has been performed in order to verify the performance of the proposed algorithm, under different operative conditions. The research has been carried out in cooperation with Ansaldo STS and ECM.

An Innovative Rotordynamical Model for Coupled Flexural-Torsional Vibrations in Rotating Machines

Flexural and lateral coupled vibrations usually exist in rotordynamics applications, as it is caused by common malfunction conditions and complex distributed inertial elements connected to the shaft may determine the coupling as well. In the paper, the authors present an accurate, innovative and fully coupled finite element (FE) rotordynamics formulation with 6 DOFS for each node for the evaluation of the dynamic behaviour of multi-rotor systems that has been conceived with the goal of investigating the flexural-torsional interaction. The model is able to model long rotors of complex topology, such as rotor with distributed inertias or connected simultaneously in several points, couplings and gear-boxes and it uses coupled shape-functions. The model proposed represents a systematic and practical approach to the rotordynamics modeling issue and its main contribution to the research topic of coupled flexural-torsional vibration in rotors is due to its general topology. The effectiveness of the model in predicting the critical behaviour of the a flywheel masses test bench has been preliminary tested by means of experimental data of vibration tests campaign, performed in collaboration with Politecnico di Milano.

An innovative high speed Weigh in Motion system for railway vehicles

The accurate estimation of the axle loads and the correct detection of overloads and imbalances, represent a primary concern for railways management companies, since they are strictly related to traffic safety and maintenance planning of the track. Weigh in Motion (WIM) systems aim at the dynamic weighing of railway vehicles through a reasonable number of measurement stations placed along the track. Such systems may overcome disadvantages in terms of costs and traffic management exhibited by conventional static weighing systems. In this paper the authors present an innovative algorithm for high speed WIM applications to estimate the wheel loads of trains by means of indirect track measurements. The formulation of the algorithm is quite general and it can be customized for several track measurements; consequently it can be employed in different typologies of measurement stations. The WIM algorithm processes the set of experimental physical quantities chosen as track inputs by means of estimation procedures based on least square (LSQ) minimization techniques. The vertical loads on the train wheels are computed from the measurements according to the assumption that the effects of the single wheel loads on the track are approximately superimposable. The whole WIM architecture has been developed in cooperation with Ansaldo STS and ECM SpA.

Weigh in Motion systems for railway vehicles: Performance and robustness analysis

One of the most important issue in the railway research is represented by the accurate estimation of the axle loads of railway vehicles. Weigh in Motion (WIM) devices are designed to measure loads with the vehicle in motion, making the weighing process more efficient. This paper is focused on an innovative algorithm for high speed WIM applications able to estimate the wheel loads of trains by means of indirect track measurements. The novelty of the proposed estimation method are its generality, the possibility to be used with different layouts and its robustness against numerical and measure noise. The main estimation procedure is based on least square (LSQ) minimization techniques, used to process the set of experimental physical input. The whole WIM architecture has been developed in cooperation with Ansaldo STS and ECM SpA.

Development and Validation of Efficient Rotordynamical Models for Complex Rotating Systems

A correct prediction of the dynamic behaviour of rotors represents a critical issue in the rotating machines field. A large amount of research work dealing with rotor-dynamics modelling can be found in literature and nowadays both traditional simple and complex models may be adopted to investigate the vibration behaviour of rotating equipments. In this paper, the authors introduce an accurate and general-purpose model for the evaluation of the dynamic behaviour of multi-rotor systems, that has been conceived with the purpose of modelling complex rotors through a systematic and practical approach. The model, which aims at overcoming the modelling limitations characterising commercial dedicated softwares and which is based on a finite element rotor-dynamics formulation, is able to deal with long rotors characterised by complex topology, such as rotor with distributed inertias or connected simultaneously in several points. The investigated rotor test case is a flywheel masses test bench for railway brakes that is formed of several rotors with complex topology (distributed inertias). The model has been validated in a preliminary step by means of experimental data coming from a test campaign for the vibration assessment, performed in collaboration with Politecnico di Milano.

An Innovative Procedure for High Speed Weighing in Motion of Railway Vehicles

In the present work the authors propose an innovative estimation algorithm for Weigh-in-motion (WIM) applications with the aim of estimating the axle or wheel loads of a generic train composition, starting from indirect track measurements. The WIM algorithm elaborates the set of experimental physical quantities chosen as track inputs, making use of estimation procedures based on least square minimization techniques. To perform an accurate estimation, the algorithm uses a flexible multibody model of the track and the vehicle. The novelty of the proposed solution is the general approach that allows to manage different kinds of measurement station and signal inputs (both experimental data and simulated ones) and the good robustness against numerical noise. The algorithm has been tested under any operating conditions through a wide simulation campaign, obtaining good results. Future developments will be based on the experimental data provided by Ansaldo STS and ECM SpA that supported the research activity.Copyright