Nonlinear three-dimensional wagon-track model for the investigation of rail corrugation initiation on curved track

A nonlinear wagon-track model on curved track has been developed to characterize rail corrugation formation due to self-excitation of the wheel-rail stick-slip process. In this model, wagon movements were described using up to 78 degrees of freedom (DOFs) to model a three-piece freight bogie. Innovatively, the wheelset movements are described using nine DOFs, including torsional and bending modes about the longitudinal and vertical directions. The track modelling is considered as a one-layer structure (two rail beams on discrete spring and damper elements). The wheel sliding after creepage saturation is considered in the wheel-rail interface modelling. Simulation of a case study shows that the frequencies of the wheel stick-slip process are composed of the basic frequency, which might come from the combined effect of sleeper-passing frequency and one-third of the combined torsional and bending frequency of the wheelset, and the double and triple basic frequencies, which form the wavelengths of rail corrugation at different situations.     

An analysis of the determinants of children’s weekend physical activity participation

This paper examines the out-of-home, weekend, time-use patterns of children aged 5–17 years, with a specific emphasis on their physical activity participation. The impact of several types of factors, including individual and household demographics, neighborhood demographics, built environment characteristics, and activity day variables, on physical activity participation is analyzed using a joint nested multiple discrete–continuous extreme value-binary choice model. The sample for analysis is drawn from the 2000 San Francisco Bay Area Travel Survey. The model developed in the paper can be used to assess the impacts of changing demographics and built environment characteristics on children’s physical activity levels.     

Short-term Hourly Traffic Forecasts using Hong Kong Annual Traffic Census

The need for acquiring the current-year traffic data is a problem for transport planners since such data may not be available for on-going transport studies. A method is proposed in this paper to predict hourly traffic flows up to and into the near future, using historical data collected from the Hong Kong Annual Traffic Census (ATC). Two parametric and two non-parametric models have been employed and evaluated in this study. The results show that the non-parametric models (Non-Parametric Regression (NPR) and Gaussian Maximum Likelihood (GML)) were more promising for predicting hourly traffic flows at the selected ATC station. Further analysis encompassing 87 ATC stations revealed that the NPR is likely to react to unexpected changes more effectively than the GML method, while the GML model performs better under steady traffic flows. Taking into consideration the dynamic nature of the common traffic patterns in Hong Kong and the advantages/disadvantages of the various models, the NPR model is recommended for predicting the hourly traffic flows in that region.     

Optimum design of tilting bogie frame in consideration of fatigue strength and weight

This paper addresses the use of finite-element (FE) analysis to calculate the fatigue strength of a bogie frame, for the development of tilting trains in Korea. A multi-body dynamic analysis was performed to extract the load condition by tilting on curves. Using the results of the multi-body dynamic analysis and the load scenario setout in the UIC standard, FE analysis was performed to obtain the stress distribution and to calculate the fatigue strength. An attempt was made to minimize the weight of the bogie frame using a back-propagation artificial neural network (ANN). The results of this study reveal that the stresses at some nodes are near the fatigue limit in the Goodman diagram and by using back-propagation ANN, the weight of the bogie frame could be reduced by 4.7%.     

Global cutting-path optimization considering the minimum heat effect with microgenetic algorithms

This article considers microgenetic algorithms (GAs), which explore in a small population with a few genetic operators, for cutting-path optimization problems. The major difference between GAs and simple genetic algorithms (SGAs) is how to make a reproductive plan for an improved searching technique because of population choice. It is shown that GAs implementation reaches the near-optimal region much earlier than the SGAs approach, and the GAs give a better solution than simulated annealing (SA). The main objective was to determine what temperature distribution can be obtained from the solution of a travelling distributed heat source. The solution of the travelling heat source on nested raw plate provides information about the vertices of each nested part of the raw plate. From the fact that the initial temperature at a piercing point strongly depends on the heat flow which stems from the previous cutting contour, the temperature of all piercing points must be lower than the critical temperature after each cutting of the components of a part. The critical temperature is identified as the mechanical melting temperature of steels. A heuristic back-tracking method is introduced to find the near-optimum cutting path considering the minimum heat effect on deformation. The heuristic back-tracking method is incorporated with the GAs.     

Seabed scene simulation and its realization in extending Vega

Realistic simulation of underwater scene is always difficult because of the special and complex vision effects in underwater space. Seabed is an important part of underwater environment. This paper describes the methods for seabed scene simulation based on OpenGL. It includes construction of fluetuant terrain based on the random sinusoidal algorithm, simulation of seabed flicker effect by means of circular texture mapping and generation of turbidity effect by using fog techniques. For the application based on the leading high level 3D development environment-Vega, underwater scene simulation is still a difficulty since there is no module for it. Based on the analysis of Vega software and the research on seabed scene simulation methods, a Vega extending module named “Underwater Space” was created through developing module class and extending lynx interface. The module class was designed through developing DLL written in C . The Lynx was extended through developing keyword configure file, GUI configure file and lynx plug-in DLL. The problem that Vega can‘t simulate underwater space, is elementarily resolved. The results show that this module is efficient, easy using, and the seabed scene images am vivid.     

Identity-based threshold decryption on access structure

For the applied limitation of the existing threshold decryption schemes based on the (t, n) structure, an identity-based threshold decryption scheme which can be applied on the access structure is proposed through designing a special distribution algorithm of the private key shares. The generation and distribution of private key shares, the encryption, the decryption and the combination are introduced in detail. The validity and security of the scheme are proved and analyzed. Comparisons with the existing schemes show that the proposed scheme is more flexible.     

Tool sequence optimization based on three logical modes of robot control via CPLEX optimization

Cluster tools have advantages of shorter cycle times, faster process development, and better yield for less contamination. The sequence of dual-arm cluster tools is a complex logistics process during the semiconductor production. Efficient use of cluster tools is naturally very significant to competitive fab operations. Generating an optimized sequence in a computationally efficient manner and assessing the quality of the requirements to improve the fab production are the key factors for semiconductor manufacturing productivity. The Petri net modeling is introduced to minimize the makespan of the process for the three different logical modes and select a better mode after comparing the makespan among the three logical modes. The tool sequence optimization problem is formulated as optimization firing transition sequences based on the Petri net and then the formulation is converted to be linearly solved by the branch-and-cut method in the standard commercial solver CPLEX. Special methods for the linear conversion are highlighted. Due to the limited calculation time requirement for the real production and the large scale of the problem, special methods for the efficiency tuning are applied according to the characteristics of the problem. Numerical testing is supported by one of the most advanced semiconductor enterprises and the computational results show significant improvement compared with the traditional manual sequence results.     

Poisson noise removal based on nonlocal total variation with Euler’s elastica pre-processing

An enhancement-based Poisson denoising method for photon-limited images is presented. The noisy image is firstly pre-processed for enhancing incomplete object information, and then it is denoised while preserving the restored structural details. A variational regularization model based on Euler’s elastica (EE) is proposed for image enhancement pre-processing. A nonlocal total variation (NLTV) regularization model is then employed in the second stage of image denoising. The above two optimization problems are solved by the alternating direction method of multipliers (ADMM). For Poissonian images with low image peak values, experiments demonstrate the validity and efficiency of the proposed method for both restoring geometric structure and removing noise.