Consequence modelling,vulnerability assessment and fuzzy fault tree analysis of hazardous storages in an industrial area

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation .

Dynamic fault tree analysis with PEWMA modeling of event rates and Bayesian updating of material balance parameters using MCMC

This research explores Bayesian updating as a tool for estimating parameters probabilistically by dynamic analysis of data sequences. Two distinct Bayesian updating methodologies are assessed. The first approach focuses on Bayesian updating of failure rates for primary events in fault trees. A Poisson Exponentially Moving Average (PEWMA) model is implemnented to carry out Bayesian updating of failure rates for individual primary events in the fault tree. To provide a basis for testing of the PEWMA model, a fault tree is developed based on the Texas City Refinery incident which occurred in 2005. A qualitative fault tree analysis is then carried out to obtain a logical expression for the top event. A dynamic Fault Tree analysis is carried out by evaluating the top event probability at each Bayesian updating step by Monte Carlo sampling from posterior failure rate distributions. It is demonstrated that PEWMA modeling is advantageous over conventional conjugate Poisson-Gamma updating techniques when failure data is collected over long time spans. The second approach focuses on Bayesian updating of parameters in non-linear forward models. Specifically, the technique is applied to the hydrocarbon material balance equation. In order to test the accuracy of the implemented Bayesian updating models, a synthetic data set is developed using the Eclipse reservoir simulator. Both structured grid and MCMC sampling based solution techniques are implemented and are shown to model the synthetic data set with good accuracy. Furthermore, a graphical analysis shows that the implemented MCMC model displays good convergence properties. A case study demonstrates that Likelihood variance affects the rate at which the posterior assimilates information from the measured data sequence. Error in the measured data significantly affects the accuracy of the posterior parameter distributions. Increasing the likelihood variance mitigates random measurement errors, but casuses the overall variance of the posterior to increase. Bayesian updating is shown to be advantageous over deterministic regression techniques as it allows for incorporation of prior belief and full modeling uncertainty over the parameter ranges. As such, the Bayesian approach to estimation of parameters in the material balance equation shows utility for incorporation into reservoir engineering workflows.

Governmental start-up support in the light of allocative market failure : justification, analysis, and design

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2011

Structures and failure mechanisms analysis of Turtle Mountain

The 30 M m3 rockslide that occurred on the east face of Turtle Mountain in the Crowsnest Pass area (Alberta) in 1903 is one of the most famous landslides in the world. In this paper, the structural features of the South part of Turtle Mountain are investigated in order to understand the present-day scar morphology and to identify the most important failure mechanisms. The structural features were mapped using a high resolution digital elevation model (DEM) in order to have a large overview of the relevant structural features. At the same time, a field survey was carried out and small scale fractures were analyzed in different parts of southern Turtle Mountain in order to confirm the DEM analysis. Results allow to identify six main discontinuity sets that influence the Turtle Mountain morphology. These discontinuity sets were then used to identify the potential failure mechanisms affecting Third Peak and South Peak area.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Are beta-blockers needed in patients receiving spironolactone for severe chronic heart failure? An analysis of the COPERNICUS study

BACKGROUND: The beneficial effects of beta-blockers and aldosterone receptor antagonists are now well established in patients with severe systolic chronic heart failure (CHF). However, it is unclear whether beta-blockers are able to provide additional benefit in patients already receiving aldosterone antagonists. We therefore examined this question in the COPERNICUS study of 2289 patients with severe CHF receiving the beta1-beta2/alpha1 blocker carvedilol compared with placebo. METHODS: Patients were divided post hoc into subgroups according to whether they were receiving spironolactone (n = 445) or not (n = 1844) at baseline. Consistency of the effect of carvedilol versus placebo was examined for these subgroups with respect to the predefined end points of all-cause mortality, death or CHF-related hospitalizations, death or cardiovascular hospitalizations, and death or all-cause hospitalizations. RESULTS: The beneficial effect of carvedilol was similar among patients who were or were not receiving spironolactone for each of the 4 efficacy measures. For all-cause mortality, the Cox model hazard ratio for carvedilol compared with placebo was 0.65 (95% CI 0.36-1.15) in patients receiving spironolactone and 0.65 (0.51-0.83) in patients not receiving spironolactone. Hazard ratios for death or all-cause hospitalization were 0.76 (0.55-1.05) versus 0.76 (0.66-0.88); for death or cardiovascular hospitalization, 0.61 (0.42-0.89) versus 0.75 (0.64-0.88); and for death or CHF hospitalization, 0.63 (0.43-0.94) versus 0.70 (0.59-0.84), in patients receiving and not receiving spironolactone, respectively. The safety and tolerability of treatment with carvedilol were also similar, regardless of background spironolactone. CONCLUSION: Carvedilol remained clinically efficacious in the COPERNICUS study of patients with severe CHF when added to background spironolactone in patients who were practically all receiving angiotensin-converting enzyme inhibitor (or angiotensin II antagonist) therapy. Therefore, the use of spironolactone in patients with severe CHF does not obviate the necessity of additional treatment that interferes with the adverse effects of sympathetic activation, specifically beta-blockade.

Alarm tree analysis using statistical techniques

This work presents a systematic method for the generation and treatment of the alarms' graphs, being its final object to find the Alarm Root Cause of the Massive Alarms that are produced in the dispatching centers. Although many works about this matter have been already developed, the problem about the alarm management in the industry is still completely unsolved. In this paper, a simple statistic analysis of the historical data base is conducted. The results obtained by the acquisition alarm systems, are used to generate a directed graph from which the more significant alarms are extracted, previously analyzing any possible case in which a great quantity of alarms are produced.

Accurate reconstruction of a known HIV-1 transmission history by phylogenetic tree analysis.

Phylogenetic analyses are increasingly used in attempts to clarify transmission patterns of human immunodeficiency virus type 1 (HIV-1), but there is a continuing discussion about their validity because convergent evolution and transmission of minor HIV variants may obscure epidemiological patterns. Here we have studied a unique HIV-1 transmission cluster consisting of nine infected individuals, for whom the time and direction of each virus transmission was exactly known. Most of the transmissions occurred between 1981 and 1983, and a total of 13 blood samples were obtained approximately 2-12 years later. The p17 gag and env V3 regions of the HIV-1 genome were directly sequenced from uncultured lymphocytes. A true phylogenetic tree was constructed based on the knowledge about when the transmissions had occurred and when the samples were obtained. This complex, known HIV-1 transmission history was compared with reconstructed molecular trees, which were calculated from the DNA sequences by several commonly used phylogenetic inference methods [Fitch-Margoliash, neighbor-joining, minimum-evolution, maximum-likelihood, maximum-parsimony, unweighted pair group method using arithmetic averages (UPGMA), and a Fitch-Margoliash method assuming a molecular clock (KITSCH)]. A majority of the reconstructed trees were good estimates of the true phylogeny; 12 of 13 taxa were correctly positioned in the most accurate trees. The choice of gene fragment was found to be more important than the choice of phylogenetic method and substitution model. However, methods that are sensitive to unequal rates of change performed more poorly (such as UPGMA and KITSCH, which assume a constant molecular clock). The rapidly evolving V3 fragment gave better reconstructions than p17, but a combined data set of both p17 and V3 performed best. The accuracy of the phylogenetic methods justifies their use in HIV-1 research and argues against convergent evolution and selective transmission of certain virus variants.

Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.

Käyttövarmuusanalyysin tuottama tärkeysjärjestys elintarviketeollisuuden prosessilaitteille – Suuntaviivat kustannustietoisen kunnossapitostrategian luomiselle

Hallitsematon ja reaktiivinen kunnossapito on eräs tuotannon suurimpia kustannustekijöistä. Suunnitelmallisesti ja systemaattisesti johdettuna kunnossapito on tuotantotehokkuuden suurin vaikuttaja. Merkittävä osa tuotannon tehokkuuden ylläpidosta saavutetaan laitteiden käyttövarmuudella. Käyttövarmuuden saaminen hallintaan perustuu ennakoivan kunnossapidon määrän kasvattamiseen. Samalla korjaavan kunnossapidon kustannusriski laskee ja siihen käytetty panos vähenee. Huonolla kunnossapidon suunnitelmallisuudella on päinvastaiset vaikutukset. Tavoitteena on määritellä prosessilaitteiden käyttövarmuuksiin perustuva laitekriittisyys. Tutkimuksessa yhdistetään riskien arviointimenetelmiä, joilla keskimääräiset vikavälit ja seuraukset valmistukseen mallinnetaan. Kriittisyystekijöitä ovat käytettävyys, luotettavuus, kustannustekijät, turvallisuus ja ympäristövaikutukset. Tekijöiden arvottamiseen kehitettiin riksianalyysitaulukko. Kriittisyysluokat jaettiin kolmeen kategoriaan, joista A on kriittisin, B keskinkertainen ja C on matalin luokka. Lähtötietojen keräys toteutettiin triangulaatiomenetelmää soveltaen. Empiirisessä osassa HKScan Oy:n lihanjalostustehtaan jauheliha- ja kestomakkaraosastojen laitteet jaettiin A-, B- ja C-luokkiin. Kriittisimpiä laitteita oli 20 prosenttia analysoidusta laitemäärästä. Nämä A-luokkaan sijoitetut laitteet aiheuttavat 80 prosenttia kustannusriskeistä. B-luokkaan kuuluu 50 prosenttia ja C-luokkaan 30 prosenttia laitteista. Luokittelusta erotettiin havaitut turvallisuusriskit riskienhallinnan toimenpiteitä varten. Kustannustietoinen kriittisyysluokittelu on pohja kunnossapitostrategian rakentamiselle. Tämän avuksi esitettiin taulukot huolto-ohjelman luomiseen ja luokituksien hyödyntämiseen päivittäisessä toiminnassa.

Availability analysis of heat recovery steam generators used in thermal power plants

The combined-cycle gas and steam turbine power plant presents three main pieces of equipment: gas turbines, steam turbines and heat recovery steam generator (HRSG). In case of HRSG failure the steam cycle is shut down, reducing the power plant output. Considering that the technology for design, construction and operation of high capacity HRSGs is quite recent its availability should be carefully evaluated in order to foresee the performance of the power plant. This study presents a method for reliability and availability evaluation of HRSGs installed in combined-cycle power plant. The method`s first step consists in the elaboration of the steam generator functional tree and development of failure mode and effects analysis. The next step involves a reliability and availability analysis based on the time to failure and time to repair data recorded during the steam generator operation. The third step, aiming at availability improvement, recommends the fault-tree analysis development to identify components the failure (or combination of failures) of which can cause the HRSG shutdown. Those components maintenance policy can be improved through the use of reliability centered maintenance (RCM) concepts. The method is applied on the analysis of two HRSGs installed in a 500 MW combined-cycle power plant. (C) 2010 Elsevier Ltd. All rights reserved.