972 resultados para Reliability prediction
Resumo:
The work aims to analyze the possibilities of utilizing old crane driving AC induction motors in modern pulse-width-modulated variable frequency drives. Bearing currents and voltage stresses are the two main problems associated with modern IGBT inverters, and they may cause premature failure of an old induction motor. The origins of these two problems are studied. An analysis of the mechanism of bearing failure is proposed. Certain types of bearing currents are considered in detail. The most effective and economical means are chosen for bearing currents mitigation. Transient phenomena of cables and mechanism of over voltages occurring at motor terminals are studied in the work. The weakest places of the stator winding insulation system are shown and recommendations are given considering the mitigation of voltage stresses. Only the most appropriate and cost effective preventative methods are chosen for old motor drives. Rewinding of old motors is also considered.
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Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations
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Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.
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Distribution companies are facing numerous challenges in the near future. Regulation defines correlation between power quality and revenue cap. Companies have to take measures for reliability increase to successfully compete in modern conditions. Most of the failures seen by customers originate in medium voltage networks. Implementation of network automation is the very effective measure to reduce duration and number of outages, and consequently, outage costs. Topic of this diploma work is study of automation investments effect on outage costs and other reliability indices. Calculation model have been made to perform needed reliability calculations. Theoretical study of different automation scenarios has been done. Case feeder from actual distribution company has been studied and various renovation plans have been suggested. Network automation proved to be effective measure for increasing medium voltage network reliability.
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Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.
Resumo:
Software faults are expensive and cause serious damage, particularly if discovered late or not at all. Some software faults tend to be hidden. One goal of the thesis is to figure out the status quo in the field of software fault elimination since there are no recent surveys of the whole area. Basis for a structural framework is proposed for this unstructured field, paying attention to compatibility and how to find studies. Bug elimination means are surveyed, including bug knowhow, defect prevention and prediction, analysis, testing, and fault tolerance. The most common research issues for each area are identified and discussed, along with issues that do not get enough attention. Recommendations are presented for software developers, researchers, and teachers. Only the main lines of research are figured out. The main emphasis is on technical aspects. The survey was done by performing searches in IEEE, ACM, Elsevier, and Inspect databases. In addition, a systematic search was done for a few well-known related journals from recent time intervals. Some other journals, some conference proceedings and a few books, reports, and Internet articles have been investigated, too. The following problems were found and solutions for them discussed. Quality assurance is testing only is a common misunderstanding, and many checks are done and some methods applied only in the late testing phase. Many types of static review are almost forgotten even though they reveal faults that are hard to be detected by other means. Other forgotten areas are knowledge of bugs, knowing continuously repeated bugs, and lightweight means to increase reliability. Compatibility between studies is not always good, which also makes documents harder to understand. Some means, methods, and problems are considered method- or domain-specific when they are not. The field lacks cross-field research.
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This thesis concentrates on studying the operational disturbance behavior of machine tools integrated into FMS. Operational disturbances are short term failures of machine tools which are especially disruptive to unattended or unmanned operation of FMS. The main objective was to examine the effect of operational disturbances on reliability and operation time distribution for machine tools. The theoretical part of the thesis covers the fimdamentals of FMS relating to the subject of this study. The concept of FMS, its benefits and operator's role in FMS operation are reviewed. The importance of reliability is presented. The terms describing the operation time of machine tools are formed by adopting standards and references. The concept of failure and indicators describing reliability and operational performance for machine tools in FMSs are presented. The empirical part of the thesis describes the research methodology which is a combination of automated (ADC) and manual data collection. By using this methodology it is possible to have a complete view of the operation time distribution for studied machine tools. Data collection was carried out in four FMSs consisting of a total of 17 machine tools. Each FMS's basic features and the signals of ADC are described. The indicators describing the reliability and operation time distribution of machine tools were calculated according to collected data. The results showed that operational disturbances have a significant influence on machine tool reliability and operational performance. On average, an operational disturbance occurs every 8,6 hours of operation time and has a down time of 0,53 hours. Operational disturbances cause a 9,4% loss in operation time which is twice the amount of losses caused by technical failures (4,3%). Operational disturbances have a decreasing influence on the utilization rate. A poor operational disturbance behavior decreases the utilization rate. It was found that the features of a part family to be machined and the method technology related to it are defining the operational disturbance behavior of the machine tool. Main causes for operational disturbances were related to material quality variations, tool maintenance, NC program errors, ATC and machine tool control. Operator's role was emphasized. It was found that failure recording activity of the operators correlates with the utilization rate. The more precisely the operators record the failure, the higher is the utilization rate. Also the FMS organizations which record failures more precisely have fewer operational disturbances.
Resumo:
Background: Effective treatment for breast cancer requires accurate preoperative planning, developing and implementing a consistent definition of margin clearance, and using tools that provide detailed real-time intraoperative information on margin status. Intraoperative ultrasound (IOUS) may fulfil these requirements and may offer few advantages that other preoperative localization and intraoperative margin assessment techniques may notPurpose: The goal of the present work is to determine how accurate the intraoperative ultrasound should be to acquire complete surgical excision with negative histological margins in patients undergoing Breast Conservative SurgeryDesign: A diagnostic test study with a cross-sectional design carried out in a tertiary referral hospital in Girona within a Breast Pathology UnitParticipants: Women diagnosed with breast cancer undergoing a Breast Conservative Surgery in the Breast Pathology Unit at Hospital Universitari de Girona Dr. Josep Trueta
Resumo:
The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.
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The primary objective of this thesis was to research delivery reliability of mill business unit of a forest industry company, especially timely and quantitative accuracy of sales orders. Delivery reliability is an important factor of customer satisfaction, which has a great influence for success of a company. The secondary objective was to find out reasons for possible problems of delivery reliability and give propositions for improvable performances. The empirical part of the thesis based on reporting database of the forest industry company’s ERP-software and detailed information of the mill system. The delivery reliability results of the mill business unit were compared to delivery reliability of similar mill business unit inside the forest industry company. The research results expressed problems in the supply chain. The delivery reliability reporting should be also developed further. This would advance delivery reliability monitoring. The improvement propositions of the thesis were logistic operation mode estimation, particular benchmarking of the compared mill business unit and more detailed survey on production delivery reliability.
Resumo:
During the process of language development, one of the most important tasks that children must face is that of identifying the grammatical category to which words in their language belong. This is essential in order to be able to form grammatically correct utterances. How do children proceed in order to classify words in their language and assign them to their corresponding grammatical category? The present study investigates the usefulness of phonological information for the categorization of nouns in English, given the fact that it is phonology the first source of information that might be available to prelinguistic infants who lack access to semantic information or complex morphosyntactic information. We analyse four different corpora containing linguistic samples of English speaking mothers addressing their children in order to explore the reliability with which words are represented in mothers’ speech based on several phonological criteria. The results of the analysis confirm the prediction that most of the words to which English learning infants are exposed during the first two years of life can be accounted for in terms of their phonological resemblance
Resumo:
Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.
Resumo:
Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.