936 resultados para PROPORTIONAL HAZARD AND ACCELERATED FAILURE MODELS
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Fault tree analysis is used as a tool within hazard and operability (Hazop) studies. The present study proposes a new methodology for obtaining the exact TOP event probability of coherent fault trees. The technique uses a top-down approach similar to that of FATRAM. This new Fault Tree Disjoint Reduction Algorithm resolves all the intermediate events in the tree except OR gates with basic event inputs so that a near minimal cut sets expression is obtained. Then Bennetts' disjoint technique is applied and remaining OR gates are resolved. The technique has been found to be appropriate as an alternative to Monte Carlo simulation methods when rare events are countered and exact results are needed. The algorithm has been developed in FORTRAN 77 on the Perq workstation as an addition to the Aston Hazop package. The Perq graphical environment enabled a friendly user interface to be created. The total package takes as its input cause and symptom equations using Lihou's form of coding and produces both drawings of fault trees and the Boolean sum of products expression into which reliability data can be substituted directly.
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High velocity oxyfuel (HVOF) thermal spraying is one of the most significant developments in the thermal spray industry since the development of the original plasma spray technique. The first investigation deals with the combustion and discrete particle models within the general purpose commercial CFD code FLUENT to solve the combustion of kerosene and couple the motion of fuel droplets with the gas flow dynamics in a Lagrangian fashion. The effects of liquid fuel droplets on the thermodynamics of the combusting gas flow are examined thoroughly showing that combustion process of kerosene is independent on the initial fuel droplet sizes. The second analysis copes with the full water cooling numerical model, which can assist on thermal performance optimisation or to determine the best method for heat removal without the cost of building physical prototypes. The numerical results indicate that the water flow rate and direction has noticeable influence on the cooling efficiency but no noticeable effect on the gas flow dynamics within the thermal spraying gun. The third investigation deals with the development and implementation of discrete phase particle models. The results indicate that most powder particles are not melted upon hitting the substrate to be coated. The oxidation model confirms that HVOF guns can produce metallic coating with low oxidation within the typical standing-off distance about 30cm. Physical properties such as porosity, microstructure, surface roughness and adhesion strength of coatings produced by droplet deposition in a thermal spray process are determined to a large extent by the dynamics of deformation and solidification of the particles impinging on the substrate. Therefore, is one of the objectives of this study to present a complete numerical model of droplet impact and solidification. The modelling results show that solidification of droplets is significantly affected by the thermal contact resistance/substrate surface roughness.
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Formative measurement has seen increasing acceptance in organizational research since the turn of the 21st Century. However, in more recent times, a number of criticisms of the formative approach have appeared. Such work argues that formatively-measured constructs are empirically ambiguous and thus flawed in a theory-testing context. The aim of the present paper is to examine the underpinnings of formative measurement theory in light of theories of causality and ontology in measurement in general. In doing so, a thesis is advanced which draws a distinction between reflective, formative, and causal theories of latent variables. This distinction is shown to be advantageous in that it clarifies the ontological status of each type of latent variable, and thus provides advice on appropriate conceptualization and application. The distinction also reconciles in part both recent supportive and critical perspectives on formative measurement. In light of this, advice is given on how most appropriately to model formative composites in theory-testing applications, placing the onus on the researcher to make clear their conceptualization and operationalisation.
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This paper analyses corporate and government strategies during the purchase, period of control and divestment by BMW of the car manufacturer Rover over the period 1994 to 2000. This paper examines three types of ‘failure’. It views BMW’s purchase of Rover as a ‘corporate failure’, with British Aerospace keen to sell Rover to raise cash and with BMW not realising the real condition of Rover. It then moves on to examine BMW’s ‘divide and rule’ strategies with regard to working conditions and subsidy-seeking and its decision to sell Rover as an example of ‘strategic failure’. Finally, it considers the ‘hands-off’ nature of British policy towards such transnational firms, and BMW in particular, as an example of ‘government failure’. This paper concludes by raising the possibility of an EU-wide policy towards transnationals, especially in terms of monitoring the activities of such firms.
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Cardiac remodelling occurs in response to stress, such as chronic hypertension or myocardial infarction, and forms the substrate for subsequent development of heart failure. Key pathophysiological features include ventricular hypertrophy, interstitial fibrosis, contractile dysfunction, and chamber dilatation. Although the molecular mechanisms are complex and not fully defined, substantial evidence now implicates increased oxidative stress as being important. The NADPH oxidase ('Nox') enzymes are a particularly important source of reactive oxygen species that are implicated in redox signalling. This article reviews the evidence for an involvement of NADPH oxidases in different aspects of adverse cardiac remodelling. A better understanding of the roles of this complex enzyme family may define novel therapeutic targets for the prevention of heart failure. Copyright © 2007 S. Karger AG.
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Reactive oxygen species play important roles in the pathophysiology of chronic heart failure secondary to chronic left ventricular hypertrophy or myocardial infarction. Reactive oxygen species influence several components of the phenotype of the failing heart, including contractile function, interstitial fibrosis, endothelial dysfunction and myocyte hypertrophy. Recent studies implicate the production of reactive oxygen species by a family of NADPH oxidases in these effects. NADPH oxidases are activated in an isoform-specific manner by many pathophysiological stimuli and exert distinct downstream effects. Understanding NADPH oxidase activation and regulation, and their downstream effectors, could help to develop novel therapeutic targets.
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The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994–2006 period. Moving beyond standard ARCH type models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:727–754, 2011
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This paper presents the main achievements of the author’s PhD dissertation. The work is dedicated to mathematical and semi-empirical approaches applied to the case of Bulgarian wildland fires. After the introductory explanations, short information from every chapter is extracted to cover the main parts of the obtained results. The methods used are described in brief and main outcomes are listed. ACM Computing Classification System (1998): D.1.3, D.2.0, K.5.1.
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A szerzők célja, hogy megvizsgálják, milyen kölcsönhatásban áll az ellátási láncban elfoglalt pozíció, valamint a szolgálatosodás szintje az európai termelővállalatoknál. Vizsgálatuk azt mutatja, hogy a globalizáció és a termelés nemzetközivé válása mindkét tényezőt jelentős mértékben befolyásolja. A termelés globalizációs trendjeinek megfelelően így a kelet-európai (fejlődő), illetve a nyugat-európai (fejlett) országokban eltérő üzleti modellek válnak dominánssá, amelyek különböző ellátásilánc-pozícióval és más-más szintű szolgáltatásnyújtással jellemezhetőek. A domináns üzleti modellek mellett természetesen más üzleti modellek is működőképesnek bizonyulhatnak a két vizsgált régióban. A létesítmények elhelyezésére, valamint az üzleti eredményességre vonatkozó mutatók elemzésbe történő bevonásával cikkük az Európában működő üzleti modellek kialakításának okára, valamint jövőbeli fenntarthatóságára is megpróbál választ adni. __________ The objective of this paper is to examine the relationship between supply chain position and level of servitization in European manufacturing companies. The analysis shows that globalization and internationalization of production has dramatic impact on both phenomena. Due to the globalization trends different business models became dominant in the less developed Eastern-European and the more developed Western European countries, which can be characterized by different supply chain position and servitization level. Certainly other business models can also be successful in the two regions. Involving facility location motivations and business performance indicators the article shed light on the reasons of why these business models came alive and how sustainable they can be.
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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.
Resumo:
Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.
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Funding — Forest Enterprise Scotland and the University of Aberdeen provided funding for the project. The Carnegie Trust supported the lead author, E. McHenry, in this research through the award of a tuition fees bursary.