Driver curve speed model and its application to ACC speed control in curved roads

A speed control algorithm for an ACC (Adaptive Cruise Control) system for curved roads is proposed based on driver behavior characteristics. As the foundation of this research, a driver speed model for curved roads is developed using a series of experimental data regarding driver behavior. To adapt the model to each driver’s individual curve speed behavior, the coefficients of the model are identified in real time from the data sequences collected during drivers’ manual operation stage by a self-learning algorithm based on a Recursive Least-Square (RLS) method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data collected in the manual operation phase, and the identification results are applied during the ACC automatic control phase. Based on the developed model, the ACC speed control algorithm is modified to provide each individual driver with a customized speed profile for the scenario of a curved road with no car ahead. Tests verify the applicability of the modified system.     

Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

Computational and experimental investigation of the unsteady flow structures around automotive outside rear-view mirrors

The unsteady flow field around two automotive outside rear-view mirrors is investigated. This study includes comprehensive experimental and computational approaches in order to characterize the complex flow structures in the wake of the mirrors. The experiments were carried out in a wind tunnel which included the measurements of the instantaneous and averaged velocity fields as well as mean and unsteady surface pressure distributions. The simulations were performed using Large Eddy Simulation (LES). The LES approach (particularly with the dynamic subgrid viscosity model) provided good agreements with the experiments for the velocity and the surface pressure distributions. The experimental and the computational results of this study will be used as a benchmark to validate the current and the future CFD development and the subsequent aero-acoustic computations.     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

Public transit subsidies, output effect and total factor productivity

This paper extends previous works on total factor productivity decomposition when firms receive both operating and capital subsidies. It shows that previous works considered either the lump-sum or substitution effects of these subsidies but not together. Using constrained cost minimization as the framework it offers formal proofs to show that cost increases are inevitable if the total effects of the subsidies are considered, and that total factor productivity growth results from increasing amounts of subsidies under economies of scale and in the absence of technical change. Applications of the decomposition equations derived to a sample of transit systems finds near constant returns to scale and negative contributions of these subsidies to total factor productivity growth. Technical change reverses this decline and results in total factor productivity growth. Further, it finds that the lump-sum effects of the subsidies reduce total factor productivity more than does the substitution effect.     

Multiaxial stress creep rupture mechanisms of AZ31 magnesium alloy

The maximum principal stresses, von Mises effective stresses and principal facet stresses at the time of creep rupture were compared in uniaxial, biaxial, and triaxial stress states for AZ31 magnesium alloy. The creep rupture of this alloy was experimentally controlled by cavitation, which was the result of a low damage tolerance, λ. Creep deformation could be correlated with the von Mises effective stress parameter. The failure-mechanism control parameter governing the stress state coincided with the experimental results of the rupture of the materials under multiaxial stress states. Finally, the theoretical prediction based on constrained cavity growth and continuous nucleation agreed with the experimental rupture data to within a factor of three.     

Condition monitoring of wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are to large extent based on visual analysis. In this paper a machine vision based approach has been considered to emulate the visual abilities of the human operator to enable automation of the process. Digital images from either ends (left and right) of the sleepers have been acquired. A pattern recognition approach has been adopted to classify the condition of the sleeper into classes (good or bad) and thereby achieve automation. Appropriate image analysis techniques were applied and relevant features such as the number of cracks on a sleeper, average length and width of the crack and the condition of the metal plate were determined. Feature fusion has been proposed in order to integrate the features obtained from each end for the classification task which follows. The effect of using classifiers like multi-layer perceptron and support vector machines has been tested and compared. Results obtained from the experiments show that multi-layer perceptron and support vector machines have achieved encouraging results, with a classification accuracy of 90%; thereby exhibiting a competitive performance when compared to a human operator.     

Spatial fisheries ecology: Recent progress and future prospects

We review recent progresses made in the study of fish distribution and survival over space — i.e., fisheries spatial ecology. This is achieved by first surveying the most common statistical approaches and relative challenges associated with the analysis of fisheries spatial data, loosely grouped in geostatistical and regression approaches. Then we review a selected number of case-studies implementing the discussed techniques. We conclude by proposing new areas of statistical and ecological research to further our understanding of how fish distribute and survive in space. This review serves a dual purpose by emphasizing the scientific importance of studying spatial interactions to better understand the temporal dynamics of fish abundance, and by promoting the development of new analytical and ecological approaches for the analysis of spatial data. Through our survey we cover different statistical techniques, marine ecosystems and life stages. This analytical, geographic and ontogenetic variety is also purposely selected to highlight the importance of comparative and multidisciplinary studies across diverging ecological disciplines, ecosystems and life stages. Besides having a general ecological relevance this review also bears a more applied significance, owing to the increasing need for protecting renewable marine resources along with their primary habitat.     

德国铁路的内燃牵引

ＤＢ（德国铁路）的电气化铁路占４４％，却完成了８３．７％的牵引任务。内燃牵引主要用在运输量少的线路和调车、车辆的交换输送上。ＤＢ铁路现有的内燃机车最少也有２３年车龄了，最老的机车是１９５５年制造的。有时，机车的维修量很大。列车编组的基础设施的合理化改造改变了机车运用条件。假设总牵引吨位将达到２０００ｔ，而网络２１的技术规范将把干线的最大速度提高到１００ｋｍ／ｈ。如果按总牵引吨位和速度来考虑货运量对