This paper presents a case study for the strength demonstration of a railway wagon welded node using the probability approach. The design variables were taken from the existing standardization for railway vehicles. The fatigue damage summation method for proving the satisfactory service life as well as the Goodman diagram method for verification of the unlimited service life was used for the node examination. The probability estimation was made using the Monte Carlo SBRA method with the help of the Anthill software. and Obsahuje seznam literatury
Train-induced vibration prediction in multi-story buildings can effectively provide the effect of vibrations on buildings. With the results of prediction, the corresponding measures can be used to reduce the influence of the vibrations. To accurately predict the vibrations induced by train in multi-story buildings, support vector machine (SVM) is used in this paper. Since the parameters in SVM are very vital for the prediction accuracy, shuffled frog-leaping algorithm (SFLA) is used to optimize the parameters for SVM. The proposed model is evaluated with the data from field experiments. The results show SFLA can effectively provide better parameter values for SVM and the SVM models outperform a better performance than artificial neural network (ANN) for train-induced vibration prediction
The effects of sleepiness, sleep loss and fatigue have been the focus of literally hundreds of studies dating back to 1896. Sleep disorders, like any other medical condition potentially affecting the safe performance of essential job functions or the safety of co-workers or the general public, require an individual assessment of the employee diagnosed with the condition to determine medical fitness for service and the necessity of any appropriate reasonable accommodations. The medical fitness assessment is a tool for maximum possible operational safety and the health and safety of all personnel in the railway industry. The article describes relevant international medical fitness standards for railway staff with special rules recommended for mental disorders, disorders of the central nervous system and use of alcohol, drugs, and other psychotropic substances.