227,398 research outputs found

    A novel qualitative prospective methodology to assess human error during accident sequences

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    Numerous theoretical models and techniques to assess human error were developed since the 60's. Most of these models were developed for the nuclear, military, and aviation sectors. These methods have the following weaknesses that limit their use in industry: the lack of analysis of underlying causal cognitive mechanisms, need of retrospective data for implementation, strong dependence on expert judgment, focus on a particular type of error, and/or analysis of operator behaviour and decision-making without considering the role of the system in such decisions. The purpose of the present research is to develop a qualitative prospective methodology that does not depend exclusively on retrospective information, that does not require expert judgment for implementation and that allows predicting potential sequences of accidents before they occur. It has been proposed for new (or existent) small and medium- scale facilities, whose processes are simple. To the best of our knowledge, a methodology that meets these requirements has not been reported in literature thus far. The methodology proposed in this study was applied to the methanol storage area of a biodiesel facility. It could predict potential sequences of accidents, through the analysis of information provided by different system devices and the study of the possible deviations of operators in decision-making. It also enabled the identification of the shortcomings in the human-machine interface and proposed an optimization of the current configuration.Fil: Calvo Olivares, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Rivera, Selva Soledad. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Núñez Mc Leod, Jorge Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentin

    Estimating Discrete Markov Models From Various Incomplete Data Schemes

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    The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of individuals over the whole observation period. In such a case, the estimation of transition probabilities is straightforwardly made by counting one-step moves from a given state to another. In many real-life problems, however, the inference is much more difficult as state sequences are not fully observed, namely the state of each individual is known only for some given values of the time variable. A review of the problem is given, focusing on Monte Carlo Markov Chain (MCMC) algorithms to perform Bayesian inference and evaluate posterior distributions of the transition probabilities in this missing-data framework. Leaning on the dependence between the rows of the transition matrix, an adaptive MCMC mechanism accelerating the classical Metropolis-Hastings algorithm is then proposed and empirically studied.Comment: 26 pages - preprint accepted in 20th February 2012 for publication in Computational Statistics and Data Analysis (please cite the journal's paper

    Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System

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    Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative data. However, another type of uncertainty (epistemic uncertainty) must be accounted for in the modeling, due to incomplete knowledge of the phenomena and imprecise evaluation of the related characteristic parameters. In circumstances of few informative data, this type of uncertainty calls for alternative methods of representation, propagation, analysis and interpretation. In this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of DG systems modeling for adequacy assessment. Probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. Evidence theory is used to incorporate the two uncertainties under a single framework. Based on the plausibility and belief functions of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system adapted from the IEEE 34 nodes distribution test feeder. Compared to the pure probabilistic approach, it is shown that the hybrid propagation is capable of explicitly expressing the imprecision in the knowledge on the DG parameters into the final adequacy values assessed. It also effectively captures the growth of uncertainties with higher DG penetration levels

    Certainty Closure: Reliable Constraint Reasoning with Incomplete or Erroneous Data

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    Constraint Programming (CP) has proved an effective paradigm to model and solve difficult combinatorial satisfaction and optimisation problems from disparate domains. Many such problems arising from the commercial world are permeated by data uncertainty. Existing CP approaches that accommodate uncertainty are less suited to uncertainty arising due to incomplete and erroneous data, because they do not build reliable models and solutions guaranteed to address the user's genuine problem as she perceives it. Other fields such as reliable computation offer combinations of models and associated methods to handle these types of uncertain data, but lack an expressive framework characterising the resolution methodology independently of the model. We present a unifying framework that extends the CP formalism in both model and solutions, to tackle ill-defined combinatorial problems with incomplete or erroneous data. The certainty closure framework brings together modelling and solving methodologies from different fields into the CP paradigm to provide reliable and efficient approches for uncertain constraint problems. We demonstrate the applicability of the framework on a case study in network diagnosis. We define resolution forms that give generic templates, and their associated operational semantics, to derive practical solution methods for reliable solutions.Comment: Revised versio

    Machine learning and its applications in reliability analysis systems

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    In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

    Risk analysis and reliability of the GERDA Experiment extraction and ventilation plant at Gran Sasso mountain underground laboratory of Italian National Institute for Nuclear Physics

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    The aim of this study is the risk analysis evaluation about argon release from the GERDA experiment in the Gran Sasso underground National Laboratories (LNGS) of the Italian National Institute for Nuclear Physics (INFN). The GERDA apparatus, located in Hall A of the LNGS, is a facility with germanium detectors located in a wide tank filled with about 70 m3 of cold liquefied argon. This cryo-tank sits in another water-filled tank (700 m3) at atmospheric pressure. In such cryogenic processes, the main cause of an accidental scenario is lacking insulation of the cryo-tank. A preliminary HazOp analysis has been carried out on the whole system. The risk assessment identified two possible top-events: explosion due to a Rapid Phase Transition - RPT and argon runaway evaporation. Risk analysis highlighted a higher probability of occurrence of the latter top event. To avoid emission in Hall A, the HazOp, Fault Tree and Event tree analyses of the cryogenic gas extraction and ventilation plant have been made. The failures related to the ventilation system are the main cause responsible for the occurrence. To improve the system reliability some corrective actions were proposed: the use of UPS and the upgrade of damper opening devices. Furthermore, the Human Reliability Analysis identified some operating and management improvements: action procedure optimization, alert warnings and staff training. The proposed model integrates the existing analysis techniques by applying the results to an atypical work environment and there are useful suggestions for improving the system reliability

    Padronização de uma bateria para a avaliação de fatores de risco psicossociais trabalhistas em trabalhadores colombianos

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    A battery of questionnaires to assess psychosocial risk factors at work was developed in 2010 in response to Resolution 2646 created by the Colombian Ministry of Social Protection. However, this battery presents some theoretical and practical limitations. A new battery of instruments has been designed and validated that includes instruments and risk indicators of the demand-control-social support and the effort-reward imbalance models. Other factors, not included in these models, but that Resolution 2646 suggests should be assessed, have also been added, and with this additional information, the new battery allows us to also calculate a “global indicator” of demand, control, and social support; family and social risk conditions, coping and personality; and health and wellbeing. The new battery was administered to a sample of 16,095 workers from different occupations and representative Colombian regions. An analysis of the various domains indicates that internal consistency of the various scales is high. The new battery has the following properties: it is simple to use in paper format or when administered by computer, it enables comparison between occupations, it offers unified scores for each variable, and provides information to assess the risk factors suggested by Resolution 2646. In addition, it will make it possible to compare the results obtained when analyzing Colombian workers with those obtained from studies of workers from other countries.Em 2010, desenvolveu-se uma bateria de instrumentos para avaliar fatores psicossociais trabalhistas de risco para a saúde, em resposta à Resolução 2 646 do Ministério da Proteção Social da Colômbia. Contudo, esta conta com algumas limitações que, a partir da construção e da validação de uma nova bateria, neste estudo se pretendem superar. Além disso, a nova bateria oferece recursos adicionais para a avaliação desses fatores: a presente bateria incorpora os instrumentos e os indicadores centrais dos modelos demanda-controle-apoio social e desiquilíbrio esforço-recompensa e os fatores internos do trabalho não considerados nesses modelos, mas que a Resolução considera necessários, mediram-se com testes preexistentes ou desenvolvidos pelos autores. Com os dados coletados, é possível calcular indicadores globais de demanda, controle e apoio social; além de condições familiares e sociais de risco, enfrentamento, personalidade e indicadores de saúde e bem-estar. Para a validação, a bateria foi aplicada a uma amostra de 16 095 trabalhadores de diferentes cargos e municípios colombianos. As anál i ses de consistência interna e validade permitem afirmar que a bateria é simples de aplicar em papel ou digital, permitirá comparar cargos, obter pontuações unificadas por variável, oferecer um diagnóstico de um número importante das variáveis sugeridas na Resolução bem como permitirá comparar os resultados dos trabalhadores colombianos com os de outros países. Palavras-chave: fatores trabalhistas de risco psicossocial, Resolução 2 646 de 2008, modelo demanda-controle-apoio social, modelo desiquilíbrio esforço-recompensa, estresse profissional, avaliação.En 2010 se desarrolló una batería de instrumentos para evaluar factores psicosociales laborales de riesgo para la salud, en respuesta a la Resolución 2646 de 2008 del Ministerio de la Protección Social de Colombia. Sin embargo, esta cuenta con algunas limitaciones que, a partir de la construcción y validación de una nueva batería, en el presente estudio se buscan superar. La nueva batería ofrece recursos adicionales para la evaluación de estos factores: incorpora los instrumentos e indicadores centrales de los modelos demanda-control-apoyo social y desequilibrio esfuerzo-recompensa, y los factores intralaborales no contemplados en dichos modelos, pero que la Resolución considera necesarios, se midieron con pruebas preexistentes o desarrolladas por los autores. Con los datos recolectados es posible calcular indicadores globales de demanda, control y apoyo social; además de condiciones familiares y sociales de riesgo, afrontamiento, personalidad e indicadores de salud y bienestar. Para la validación, la batería se aplicó a una muestra de 16.095 trabajadores de diferentes ocupaciones y municipios colombianos. Los análisis de consistencia interna y validez permiten afirmar que la batería es sencilla de aplicar en papel o por computador, permitirá comparar ocupaciones, obtener puntuaciones unificadas por variable, ofrecer un diagnóstico de un número importante de las variables sugeridas en la Resolución y comparar los resultados de los trabajadores colombianos con los de otros países
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