VERIFICATION OF NUMERICAL MODEL OF FIRE AND SMOKE DEVELOPMENT IN RAILWAY TUNNEL

Simulation of fire spread and development of toxic gases during a fire accident in a railway tunnel allows prepare and validate models of safe evacuation of people. Highly complex problem of fire dynamics in a tunnel can be solved by the aid of numerical models based on CFD method. In order to check the quality of prediction models the procedure of verification is used. A relatively simple model of a single track railway tunnel is solved in two independent codes - FDS and Smart Fire. Accuracy of the model prediction is verified by the aid of gas temperature resolution along the tunnel length. To estimate an error based on different mesh resolutions of numerical model, calculation of the same model is carried out using different mesh density

Verification and validation of a numerical model of fire and smoke development in a railway tunnel

The paper describes the verification and validation of a numerical model of the development of fire and smoke in a railway tunnel carried out in the Fire Dynamic Simulator numerical code. To evaluate the correctness of a numerical solution of the model with respect to the mathematical model, the results are compared with a solution executed in the SmartFire numerical code. The influence of mesh size on the gas temperature results in the vicinity of the fire source is studied. The level of agreement between the numerical model and a physical model is validated by comparing the calculated data with data measured during a fire test in the Valik road tunnel in the Czech Republic

Seasonal Variability of Resuspension

Particulate air pollution in cities is caused by a variety of sources. One of the less-studied contributors is wind-induced particle resuspension. As the wind speed increases, particles are removed from surfaces. These particles cause an increase in the total concentration in the air. It is known that particles of 10-2.5 m in size can be resuspended (PM10-2,5). Modern emission monitoring in cities also allows the monitoring of fine particles of 10, 2.5 and 1 m in size. The size fractions can then be sorted into PM10-2,5, PM2,5-1 and PM1. When breathed in, particles of different sizes cause various serious health risks. This paper focuses on the identification of the resuspension process of different particle size fractions by a data processing method. Data measured by automatic emission monitoring are used. It is confirmed that the concentration increase can be dominated by the fraction PM10-2,5. However, a concentration increase of fractions PM2,5-1 and PM1 is also evident with increasing wind speed. Although the increase in the PM1 fraction is smaller than PM10-2,5, it is more severe due to the respiratory deposition dose. The resuspension of particles of different fractions has different behaviours during the year. PM10-2,5 particles are dominantly resuspended in the summer months. In winter, on the other hand, the proportion of PM2.5-1 and PM1 particles increases, which may be related to the heating seaso

Train Type Identification at S&C

The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such system requires a robust and efficient train type identification. Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool. For design and validation of the system, real on-site acceleration data were used. The resulting theoretical and practical challenges are discussed

Statistical characteristics of the traffic flow microstructure

The actual traffic flow theory assumes interactions only between neighbouring vehicles within the traffic. This assumption is reasonable, but it is based on the possibilities of science and technology available decades ago, which are currently overcome. Obviously, in general, there is an interaction between vehicles at greater distances (or between multiple vehicles), but at the time, no procedure has been put forward to quantify the distance of this interaction. This work introdukce a method, which use mathematical statistics and precise measurement of time distances of individual vehicles, which allows to determine these interacting distances (between several vehicles) and its validation for narrow densities of traffic flow. It has been revealed that at high traffic flow densities there is an interaction between at least three consecutive vehicles and four and five vehicles at lower densities. Results could be applied in the development of new traffic flow models and its verification

Statistical characteristics of the traffic flow microstructure

The actual traffic flow theory assumes interactions only between neighbouring vehicles within the traffic. This assumption is reasonable, but it is based on the possibilities of science and technology available decades ago, which are currently overcome. Obviously, in general, there is an interaction between vehicles at greater distances (or between multiple vehicles), but at the time, no procedure has been put forward to quantify the distance of this interaction. This work introdukce a method, which use mathematical statistics and precise measurement of time distances of individual vehicles, which allows to determine these interacting distances (between several vehicles) and its validation for narrow densities of traffic flow. It has been revealed that at high traffic flow densities there is an interaction between at least three consecutive vehicles and four and five vehicles at lower densities. Results could be applied in the development of new traffic flow models and its verification

Analýza křižovatek pomocí bezpilotních prostředků

This paper presents a new approach to simultaneous detection and tracking of vehicles moving through an intersection in aerial images acquired by an unmanned aerial vehicle (UAV). Detailed analysis of spatial and temporal utilization of an intersection is an important step for its design evaluation and further traffic inspection. Traffic flow at intersections is typically very dynamic and requires continuous and accurate monitoring systems. Conventional traffic surveillance relies on a set of fixed cameras or other detectors, requiring a high density of the said devices in order to monitor the intersection in its entirety and to provide data in sufficient quality. Alternatively, a UAV can be converted to a very agile and responsive mobile sensing platform for data collection from such large areas. However, manual vehicle annotation in aerial images would involve tremendous effort. In this paper, the proposed combination of vehicle detection and tracking aims to tackle the problem of automatic traffic analysis at an intersection from visual data. The presented method has been evaluated in several real-life scenarios.Článek představuje nový přístup k detekování vozidel a sledování jejich trajektorie při pohybu v křižovatce pomocí snímků pořízených bezpilotním letounem. Prostorové a časové využití křižovatky je klíčové pro budoucí přístupy v návrhu křižovatek