A Category Classification Based Safety Risk Assessment Method for Railway Wagon Loading Status

The identification and control of safety risks in the loading state of goods wagon is one of the important tasks to ensure the safety of goods in transit. In view of the problem that the current risk assessment of transportation schemes is mainly based on manual experience and cannot be quantified, which makes it difficult to accurately determine the safety risk of transportation on the way, a risk assessment method for loading status of goods wagon based on scenario classification was proposed. Firstly, based on a detailed analysis of the safety risk points in various stages of railway freight operations, a SHEL influencing factor model based on scenario classification was constructed. Then, considering the characteristics of railway freight transportation, a fuzzy accident tree model (FTA) of goods wagon loading state risk was constructed, and the fault tree was transformed into a Bayesian network structure according to the mapping algorithm of fuzzy fault tree and Bayesian. Furthermore, a triangular fuzzy membership function was introduced to describe the fault probability of nodes, and a BN based fuzzy fault tree inference algorithm was proposed. Finally, taking a railway station and route transporting coil steel goods in China as an example, this paper explained how to integrate expert knowledge through fault tree and Bayesian network to support railway freight scheme designers in conducting risk quantification assessment of freight wagon loading status

Development of methods to increase the efficiency of railway maintenance

Object of research: technology of track maintenance optimization Solved problem: In the development of decisions to optimize the decision-making system in the content of the upper structure of the track used methods of control theory, systems analysis, methodology of optimal control. Main scientific results: An analysis of the degrees of research on improving the efficiency of the technical management of railways showed that there was no systematic approach and that existing developments in the organization, in particular the relative optimization, Separate track repair standards or take into account parameter models, process requirements and conditions. Area of practical use of research results: industrial enterprises, railway stations. Providing the stable support of the railway, sustainable and rhythmic operation of railway traffic is ensured. About 7.3 thousand km are exploited in the ferrous metallurgy of Ukraine. More than 70 % of routes are up to 500 km long and belong to a large company. Consequently, an important task is to maintain the technical state of railways at the production demands level. Innovative technological product: combined transportations that can interact with similar networks of foreign countries. Scope of application of innovative technological product: formation and effective functioning of railway-transport complex, improvement of tariff policy, substantiation of perspective parameters of transportation process and its technical means, creation of advanced technologies, choice of rational structure of transport network, formation of transport corridors, development of fundamentally new management systems

Experimental and modelling study of advanced aqueous ammonia based post combustion capture process

The present thesis focuses on the development of a rigorous, rate-based model for CO2 capture and SO2 removal by aqueous NH3. Using the model, an advanced process design is proposed to realise the NH3 recycling and simultaneous capture of CO2 and SO2. Technical and economic assessment are conducted to evaluate the techno-economic performance of the NH3 process and its process improvements integrated with a 650 MW coal fired power station

How and Why Freight Trains Deviate from the Timetable : Evidence from Sweden

European infrastructure managers (IMs) create annual timetables for trains that will run during a year. Freight trains in Sweden often deviate from this by being added, cancelled, delayed or early, resulting in increased costs for IMs and railway undertakings (RUs). We investigate the frequency of and causes for these deviations, using one year of operational data for 48,000 trains, and 15 stakeholder interviews. We find that about 20% of freight trains are added once the timetable has been created, and that cancellations occur for about 35% of freight trains, mostly at the RUs’ initiative. Delays are common: some 40% of departures, 30% of runtimes, and 20% of dwell times are delayed. Running early is even more common: 80% are ready to depart early, and 60% do so, while 40% of runtimes and 75% of dwell times are shorter than scheduled. We find links and feedback loops between the root causes for these deviations and suggest that IMs reserve more of the capacity that is needed for freight trains and instead distribute it throughout the year. This could lead to more appropriate, attractive, and reliable timetables for freight trains, whilst greatly reducing the amount of planning effort

Rotor design optimization using a free wake analysis

The aim of this effort was to develop a comprehensive performance optimization capability for tiltrotor and helicopter blades. The analysis incorporates the validated EHPIC (Evaluation of Hover Performance using Influence Coefficients) model of helicopter rotor aerodynamics within a general linear/quadratic programming algorithm that allows optimization using a variety of objective functions involving the performance. The resulting computer code, EHPIC/HERO (HElicopter Rotor Optimization), improves upon several features of the previous EHPIC performance model and allows optimization utilizing a wide spectrum of design variables, including twist, chord, anhedral, and sweep. The new analysis supports optimization of a variety of objective functions, including weighted measures of rotor thrust, power, and propulsive efficiency. The fundamental strength of the approach is that an efficient search for improved versions of the baseline design can be carried out while retaining the demonstrated accuracy inherent in the EHPIC free wake/vortex lattice performance analysis. Sample problems are described that demonstrate the success of this approach for several representative rotor configurations in hover and axial flight. Features that were introduced to convert earlier demonstration versions of this analysis into a generally applicable tool for researchers and designers is also discussed

Impact of COVID-19 pandemic restrictions in urban mobility and air pollution in Lisbon, Portugal

The present work reports the impacts on urban mobility and air quality in Lisbon, Portugal as a consequence of the imposed restrictions to curb the transmission of SARS-CoV-2 virus which causes COVID-19 disease. During the first national emergency period (18-03-2020 to 03-05-2020) the sharp reductions in anthropogenic activities, most importantly road traffic, resulted in generally reduced criteria air pollutant concentration when compared to a homologous baseline from 2013-2019 measured in the six air quality monitoring stations throughout the city. The most negatively impacted air pollutant was No2 with a reduction of 54.35% in traffic stations and 28.62% reduction in background stations. An exception to this trend was the observed O3 concentration increase of 12.89% in traffic stations which is potentially due to changes in the Nox:VOC ratio and reduced O3 titration by NO as a result of sharp decrease of NOx emissions in the usually most polluted city hotspots. This phenomenon raises the need of additional measures to mitigate O3 pollution increases as part of the Lisbon and Tagus Valley air quality improvement plan which aims to reduce NO2 concentrations, namely specific measures for VOC management. Google mobility indicator for local commerce was found to be the main anthropogenic activity indicator for Lisbon with a moderate and positive correlation with NO2 concentration (r=+0.54), whereas the average wind speed was the most relevant natural phenomena contributing to NO2 concentration with a moderate and negative correlation (r=-0.53). A regressor ML pipeline was trained to predict NO2 concentration with the available anthropogenic activity, weather, and air pollutant inputs from March/2020 to March/2021, achieving R2=0.925 on the test set and subsequent feature importance analysis uncovered that anthropogenic features contribute to 41.19% of NO2 concentrations and natural phenomena features contribute to 58.81%.O presente trabalho relata os impactos na mobilidade urbana e qualidade do ar em Lisboa, Portugal, como consequência das restrições impostas para conter a transmissão do vírus SARS-CoV-2, causador da doença COVID-19, onde durante o primeiro período de emergência nacional (18-03-2020 a 03-05-2020) as reduções acentuadas nas atividades antropogénicas, nomeadamente o tráfego rodoviário, resultaram na redução generalizada das concentrações dos principais poluentes atmosféricos medidos nas seis estações de monitorização da qualidade do ar em Lisboa quando comparados ao período homólogo de 2013-2019, sendo o NO2 o poluente atmosférico mais impactado com uma redução média de 54.35% nas estações de tráfego e 28.62% nas estações de fundo. Uma exceção a esta tendência foi o aumento observado na concentração de O3 de 12.89% nas estações de tráfego potencialmente devido a mudanças na relação NOx:COV e redução da ação de redução de O3 por reação com NO como resultado da redução acentuada da concentração de NOx nas zonas habitualmente mais poluídas da cidade. Este fenómeno reforça a necessidade de medidas que mitiguem o aumento da poluição de O3 no âmbito do plano de melhoria da qualidade do ar de Lisboa e Vale do Tejo que visa a redução das concentrações de NO2, nomeadamente medidas específicas de gestão de COV. O indicador de mobilidade da Google para o comércio local em Lisboa foi identificado como a atividade antropogénica mais relevante com uma correlação moderada e positiva com a concentração NO2 (r=+0.54). A velocidade média do vento foi identificada como a atividade natural mais relevante com uma correlação moderada e negativa com a concentração NO2 (r=-0.53). Foi treinada uma ML pipeline para prever a concentração NO2 que teve como entradas os dados de atividade antropogénica, meteorológica e qualidade do ar desde Março/2020 a Março/2021, obtendo R2=0.925 no conjunto de teste. A análise de importância dos atributos identificam as variáveis antropogénicas como responsáveis por 41.19% da concentração NO2 enquanto que as variáveis naturais respondem por 58.81%