Dynamics of railway freight vehicles

This paper summarises the historical development of railway freight vehicles and how vehicle designers have tackled the difficult challenges of producing running gear which can accommodate the very high tare to laden mass of typical freight wagons whilst maintaining stable running at the maximum required speed and good curving performance. The most common current freight bogies are described in detail and recent improvements in techniques used to simulate the dynamic behaviour of railway vehicles are summarised and examples of how these have been used to improve freight vehicle dynamic behaviour are included. A number of recent developments and innovative components and sub systems are outlined and finally two new developments are presented in more detail: the LEILA bogie and the SUSTRAIL bogie

Nonlinear optimal control for aircraft ground manoeuvres

Despite recent advances in flight control systems, aircraft ground manoeuvres are still conducted manually. This thesis aims to improve the efficiency and safety of airport operations by developing a real-time optimal controller forground operations, especially high-speed runway turnoff. A reliable and robust controller is able to improve airport traffic capacity and reduce runway events of incursion, excursion, and confusion. A high-fidelity fully-parameterised aircraft model is developed to capture aircraft ground dynamics. The nonlinearities enter the system via sub-models of tyres and aerodynamics. A numerical continuation method is used to compute and track steady-state solutions under the variation of parameters, providing a global picture of the system stability within a typical operation envelop. Dynamic simulations are carried out to analyse transient behaviourswhich are not captured by the bifurcation analysis. Three controllers are employed to investigate the automation of aircraft runway exit manoeuvres. An Expert Pilot Model is developed to represent manoeuvres that are manually operated by pilots. To evaluate the optimality of the proposed Expert Pilot Model (EPM), Generalised Optimal Control (GOC) is employed to numerically investigate the optimal solutions for aircraft runway exit manoeuvres. A formal solution of real-time optimal steering control problem is desired in light of the gap between the Expert Pilot Modeland Generalised Optimal Control. Therefore, Predictive Steering Control is developed based on Linear Quadratic method with lookahead, which is able to deliver near-optimal manoeuvres.</div

Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination.

BACKGROUND: Parameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus - pathological ocular oscillations that can be subdivided into different waveform classes. By developing appropriate fitness functions, we optimised the model to existing experimental saccade and nystagmus data, using a well-established multi-objective genetic algorithm. This algorithm required the model to be numerically integrated for very large numbers of parameter combinations. To address this computational bottleneck, we implemented a master-slave parallelisation, in which the model integrations were distributed across the compute units of a GPU, under the control of a CPU. RESULTS: While previous nystagmus fitting has been based on reproducing qualitative waveform characteristics, our optimisation protocol enabled us to perform the first direct fits of a model to experimental recordings. The fits to normal eye movements showed that although saccades of different amplitudes can be accurately simulated by individual parameter sets, a single set capable of fitting all amplitudes simultaneously cannot be determined. The fits to nystagmus oscillations systematically identified the parameter regimes in which the model can reproduce a number of canonical nystagmus waveforms to a high accuracy, whilst also identifying some waveforms that the model cannot simulate. Using a GPU to perform the model integrations yielded a speedup of around 20 compared to a high-end CPU. CONCLUSIONS: The results of both optimisation problems enabled us to quantify the predictive capacity of the model, suggesting specific modifications that could expand its repertoire of simulated behaviours. In addition, the optimal parameter distributions we obtained were consistent with previous computational studies that had proposed the saccadic braking signal to be the origin of the instability preceding the development of infantile nystagmus oscillations. Finally, the master-slave parallelisation method we developed to accelerate the optimisation process can be readily adapted to fit other highly parametrised computational biology models to experimental data

Railway Research

This book focuses on selected research problems of contemporary railways. The first chapter is devoted to the prediction of railways development in the nearest future. The second chapter discusses safety and security problems in general, precisely from the system point of view. In the third chapter, both the general approach and a particular case study of a critical incident with regard to railway safety are presented. In the fourth chapter, the question of railway infrastructure studies is presented, which is devoted to track superstructure. In the fifth chapter, the modern system for the technical condition monitoring of railway tracks is discussed. The compact on-board sensing device is presented. The last chapter focuses on modeling railway vehicle dynamics using numerical simulation, where the dynamical models are exploited

Optimisation and Computational Methods to Model the Oculomotor System with Focus on Nystagmus

Open access. Use it freely but cite it.Infantile nystagmus is a condition that causes involuntary, bilateral and conjugate oscillations of the eyes, which are predominately restricted to the horizontal plane. In order to investigate the cause of nystagmus, computational models and nonlinear dynamics techniques have been used to model and analyse the oculomotor system. Computational models are important in making predictions and creating a quantitative framework for the analysis of the oculomotor system. Parameter estimation is a critical step in the construction and analysis of these models. A preliminary parameter estimation of a nonlinear dynamics model proposed by Broomhead et al. [1] has been shown to be able to simulate both normal rapid eye movements (i.e. saccades) and nystagmus oscillations. The application of nonlinear analysis to experimental jerk nystagmus recordings, has shown that the local dimensions number of the oscillation varies across the phase angle of the nystagmus cycle. It has been hypothesised that this is due to the impact of signal dependent noise (SDN) on the neural commands in the oculomotor system. The main aims of this study were: (i) to develop parameter estimation methods for the Broomhead et al. [1] model in order to explore its predictive capacity by fitting it to experimental recordings of nystagmus waveforms and saccades; (ii) to develop a stochastic oculomotor model and examine the hypothesis that noise on the neural commands could be the cause of the behavioural characteristics measured from experimental nystagmus time series using nonlinear analysis techniques. In this work, two parameter estimation methods were developed, one for fitting the model to the experimental nystagmus waveforms and one to saccades. By using the former method, we successfully fitted the model to experimental nystagmus waveforms. This fit allowed to find the specific parameter values that set the model to generate these waveforms. The types of the waveforms that we successfully fitted were asymmetric pseudo-cycloid, jerk and jerk with extended foveation. The fit of other types of nystagmus waveforms were not examined in this work. Moreover, the results showed which waveforms the model can generate almost perfectly and the waveform characteristics of a number of jerk waveforms which it cannot exactly generate. These characteristics were on a specific type of jerk nystagmus waveforms with a very extreme fast phase. The latter parameter estimation method allowed us to explore whether the model can generate horizontal saccades of different amplitudes with the same behaviour as observed experimentally. The results suggest that the model can generate the experimental saccadic velocity profiles of different saccadic amplitudes. However, the results show that best fittings of the model to the experimental data are when different model parameter values were used for different saccadic amplitude. Our parameter estimation methods are based on multi-objective genetic algorithms (MOGA), which have the advantage of optimising biological models with a multi-objective, high-dimensional and complex search space. However, the integration of these models, for a wide range of parameter combinations, is very computationally intensive for a single central processing unit (CPU). To overcome this obstacle, we accelerated the parameter estimation method by utilising the parallel capabilities of a graphics processing unit (GPU). Depending of the GPU model, this could provide a speedup of 30 compared to a midrange CPU. The stochastic model that we developed is based on the Broomhead et al. [1] model, with signal dependent noise (SDN) and constant noise (CN) added to the neural commands. We fitted the stochastic model to saccades and jerk nystagmus waveforms. It was found that SDN and CN can cause similar variability to the local dimensions number of the oscillation as found in the experimental jerk nystagmus waveforms and in the case of saccade generation the saccadic variability recorded experimentally. However, there are small differences in the simulated behaviour compared to the nystagmus experimental data. We hypothesise that these could be caused by the inability of the model to simulate exactly key jerk waveform characteristics. Moreover, the differences between the simulations and the experimental nystagmus waveforms indicate that the proposed model requires further expansion, and this could include other oculomotor subsystem(s).Engineering and Physical Sciences Research Council (EPSRC

Uncertainty quantification of brake squeal Iistability via surrogate modelling

Noise, vibration and Harshness (NVH) of automotive disc brakes have been an active research topic for several decades. The environmental concerns, on one hand, and the rising customer expectations of their car quality, on the other hand, have made NVH of brakes an important issue for car manufacturers. Of different types of noise and vibration that a brake system may generate, squeal is the main focus of the current study. Brake squeal is an irritating high-frequency noise causing a significant warranty cost to car manufacturers. There are a number of reasons leading to squeal noise either at the end of production or during usage and services. Of these reasons, it is believed that manufacturing variability, several sources of uncertainty (such as friction and contact) and diverse loading cases have the most contribution in this problem. Car manufacturers are then recently encouraged to look into the uncertainty analysis of the brake systems in order to cover the influence of these variations on brake designs. The biggest hurdle in the uncertainty analysis of brakes is the computational time, cost and data storage. In general, stochastic studies are done on the premise of deterministic analyses of a system. As the deterministic analyses of brake squeal instability essentially involve a great deal of computational workload, their stochastic (non-deterministic) analyses will be consequently very expensive. To overcome this issue, the method of surrogate modelling is proposed in this study. Briefly speaking, surrogate modelling replaces an expensive simulation code with a cheap-to-evaluate mathematical predictor. As a result, instead of using the actual finite element model of a brake for statistical analyses, its replacement model will be used alternatively. There are three main advantages in surrogate modelling of brakes. First of all, it paves the way of structural modification of brakes, which are conventionally done for reducing squeal propensity. Secondly, structural uncertainties of a brake design can cost-effectively be propagated onto the results of the stability analysis. Thereafter, instead of making a single design point stable, a scatter of points should meet the stability criteria. Finally, the reliability and robustness of a brake design can be quantified efficiently. These two measures indicate the probability of unstable vibration leading to squeal noise for a brake design. Accordingly, car manufacturers will be able to estimate the cost of warranty claims which may be filed due to this particular issue. If the probability of failure which is calculated for squeal propensity is significant, surrogate modelling helps come up with a solution during the design stage, before cars go into production. In brief, two major steps must be taken toward constructing a surrogate model: making a uniform sampling plan and fitting a mathematical predictor to the observed data. Of different sampling techniques, Latin hypercube sampling (LHS) is used in this study in order to reduce the amount of computational workload. It is worth mentioning that the original LHS does not enforce the uniformity condition when making samples. However, some modifications can be applied to LHS in order to improve the uniformity of samples. Note that the uniformity of samples plays a crucial role in the accuracy of a surrogate model. A surrogate model, in fact, is built on the premise of the observations which are made over a design space. Depending on the nonlinearity of the outputs versus the input variables and also depending on the dimensions of a design space, different mathematical functions may be used for a surrogate predictor. The results of this study show that Kriging function brings about a very accurate surrogate model for the brake squeal instability. In order to validate the accuracy of surrogate models, a number of methods are reviewed and implemented in the current study. Finally, the validated surrogate models are used in place of the actual FE model for uncertainty quantification of squeal instability. Apart from surrogate modeling, a stochastic study is conducted on friction-induced vibration. Statistics of complex eigenvalues of a simplified brake models are studied under the influence of variability and uncertainty. For this purpose, the 2nd order perturbation method is extended to be applicable on an asymmetric system with non-proportional damping. The main advantage of this approach is that the statistics of complex eigenvalues can be calculated in just one run, which is massively more efficient than the conventional techniques of uncertainty propagation that use a large number of simulations to determine the results

Brake-clutch squeal prediction and supression

This work studies the high frequency noise in brake–clutch systems known as squeal. The work is divided into two parts, the first is focused on the development of both a theoretical and experimental simplified model of a brake–clutch and the second is centred on squeal modelling in the real system. For the simple model, on the theoretical side, a FE model was developed including anisotropic material properties, pressure and speed dependent friction coefficient and friction damping. The pertinent characterisation tests were performed as needed. On the experimental side, squeal tests were performed in the test bench in order to check the ability of the system for squeal prediction. Once the model was thought as accurate enough, a methodology to decide over point structural modifications for squeal suppression based on the receptance function was designed. Using this process squeal was successfully eliminated from the simplified model both theoretically and experimentally. In the second part the modelling of squeal in a real brake–clutch system was tackled. With this objective a FE model of the whole system was developed and its validity was checked first by EMA and after, comparing the experimental squeal frequencies with the ones predicted by simulation. To finish, the methodology for structural modifications previously designed was applied to the system and several theoretical modifications were proposed and studied.Lan honetan balazta–enbrage unitate konbinatuetan agertzen den squeal izeneko frekuentzia altuko zarata aztertzen da. Lana bi zatitan banatuta dago: alde batetik, balazta–enbragearen eredu sinplifikatu bat garatu da, bai teorikoa zein esperimentala; bestetik, squeala sistema errealean modelizatu da. Eredu sinplean, alde teorikoari dagokionez, elementu finitutako eredu bat garatu da. Eredu honek marruskadura materialaren propietate anisotropoak, presio eta abiaduraren menpeko marruskadura koefizientea eta marruskadurak eragindako moteltzea kontutan hartzen ditu. Propietate hauek saiakuntza independentetan neurtu dira. Alde esperimentalean, squeal saiakuntzak burutu dira ereduak squeala aurreikusteko duen gaitasuna balioztatzeko asmoz. Behin eredua nahiko zehatza izanik, zarata kentzeko aldaketa estrukturalak proposatu eta baloratzeko metodologia bat diseinatu da. Proposatutako metodoa errezeptantzia funtzioan oinarrituta dago. Metodo honi esker squeala eredu teorikoan lehenengo eta ondoren saiakuntza bankuan kentzea posible izan da. Bigarren atalean, balazta–enbragearen modelizazioari ekin zaio squealari dagokionez. Helburu honekin, sistema osoaren eredu bat garatu da eta lehengo AME bidez eta gero squeal frekuentzia esperimentalak ereduak aurreikusitakoekin konparatuz balioztatu da. Azkenik, aldaketa estrukturalak proposatzeko metodologia sistema errealari aplikatu zaio eta aldaketa teoriko batzuk planteatu eta aztertu dira.El presente trabajo estudia el ruido de alta frecuencia que se da en los freno-embragues conocido como squeal. El trabajo se divide en dos partes, la primera enfocada en el desarrollo de un modelo simple tanto teórico como experimental del freno–embrague y la segunda centrada en la modelización del squeal en el sistema real. En lo referente al modelo simple, en la parte teórica se desarrolló un modelo de elementos finitos que incluía propiedades anisótropas para el material de fricción, un coeficiente de fricción dependiente de la presión y la velocidad y amortiguamiento por fricción. Estas propiedades se caraterizaron en los correspondientes ensayos independientes cuando fue necesario. En la parte experimental, se llevaron a cabo ensayos de squeal en banco con la idea de verificar la capacidad del modelo para predecir el squeal. Una vez que el modelo se consideró lo suficientemente exacto, se desarrolló una metodología para proponer y valorar modificaciones estructurales para la supresión de squeal. El método propuesto está basado en la función de receptancia. Gracias a este proceso fue posible eliminar el squeal del modelo primero en la teoría y a continuación en el banco de ensayos. En la segunda parte se aborda la modelización de squeal en un freno–embrague real. Con esto en mente se desarrolló un modelo de elementos finitos del sistema completo y se validó en primer lugar mediante AME y a continuación comparando las frecuencias experimentales de squeal con las predichas por la simulación. Por último, la metodología desarrollada para modificaciones estructurales se aplicó al sistema real y se propusieron y analizaron varias modificaciones teóricas