993 resultados para Operational safety


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Uma ocorrência ferroviária tem danos imprevisíveis, desde um simples atraso do horário do trem enquanto o socorro ferroviário encarrilha o vagão, até prejuízos milionários com grande perda de ativos (material rodante e via permanente) e, em casos extremos, até vidas humanas. Portanto, as ferrovias nacionais sempre buscam maneiras de programar ações que minimizam este risco. Uma das principais ações é estabelecer critérios de manutenção sempre justos. Entretanto, estes critérios geralmente não contemplam de maneira conjunta a dinâmica veicular e a geometria da via permanente. Neste sentido, este trabalho elabora um modelo matemático de um vagão ferroviário de alta capacidade em conjunto com a flexibilidade do suporte da via permanente. O modelo matemático foi validado e considerado satisfatório, a partir da comparação das frequências naturais obtidas no vagão real e na comparação de seu resultado produzido a partir de uma entrada medida com equipamentos de controle de geometria de linha e de medições dinâmicas realizadas por vagão instrumentado. Um método estratégico para análise da segurança do veículo foi sugerida e utilizada mostrando-se capaz de determinar os comprimentos de onda da via permanente que devem ser priorizados na manutenção, bem como na análise da segurança do vagão quando na adoção de restrições de velocidades.

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The need of the oil industry to ensure the safety of the facilities, employees and the environment, not to mention the search for maximum efficiency of its facilities, makes it seeks to achieve a high level of excellence in all stages of its production processes in order to obtain the required quality of the final product. Know the reliability of equipment and what it stands for a system is of fundamental importance for ensuring the operational safety. The reliability analysis technique has been increasingly applied in the oil industry as fault prediction tool and undesirable events that can affect business continuity. It is an applied scientific methodology that involves knowledge in engineering and statistics to meet and or analyze the performance of components, equipment and systems in order to ensure that they perform their function without fail, for a period of time and under a specific condition. The results of reliability analyzes help in making decisions about the best maintenance strategy of petrochemical plants. Reliability analysis was applied on equipment (bike-centrifugal fan) between the period 2010-2014 at the Polo Petrobras Guamaré Industrial, situated in rural Guamaré municipality in the state of Rio Grande do Norte, where he collected data field, analyzed historical equipment and observing the behavior of faults and their impacts. The data were processed in commercial software reliability ReliaSoft BlockSim 9. The results were compared with a study conducted by the experts in the field in order to get the best maintenance strategy for the studied system. With the results obtained from the reliability analysis tools was possible to determine the availability of the centrifugal motor-fan and what will be its impact on the security of process units if it will fail. A new maintenance strategy was established to improve the reliability, availability, maintainability and decreased likelihood of Moto-Centrifugal Fan failures, it is a series of actions to promote the increased system reliability and consequent increase in cycle life of the asset. Thus, this strategy sets out preventive measures to reduce the probability of failure and mitigating aimed at minimizing the consequences.

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The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

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Federal Highway Administration, Office of Research and Development, Washington, D.C.

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In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

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Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

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Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations. However, people have limited knowledge on this complex topic. In this research, 1) the impact of traffic oscillations on freeway crash occurrences has been measured using the matched case-control design. The results consistently reveal that oscillations have a more significant impact on freeway safety than the average traffic states. 2) Wavelet Transform has been adopted to locate oscillations' origins and measure their characteristics along their propagation paths using vehicle trajectory data. 3) Lane changing maneuver's impact on the immediate follower is measured and modeled. The knowledge and the new models generated from this study could provide better understanding on fundamentals of congested traffic; enable improvements to existing traffic control strategies and freeway crash countermeasures; and instigate people to develop new operational strategies with the objective of reducing the negative effects of oscillatory driving.

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Variable Speed Limits (VSL) is a control tool of Intelligent Transportation Systems (ITS) which can enhance traffic safety and which has the potential to contribute to traffic efficiency. This study presents the results of a calibration and operational analysis of a candidate VSL algorithm for high flow conditions on an urban motorway of Queensland, Australia. The analysis was done using a framework consisting of a microscopic simulation model combined with runtime API and a proposed efficiency index. The operational analysis includes impacts on speed-flow curve, travel time, speed deviation, fuel consumption and emission.