The probabilistic risk analysis of external hazards of an interim storage for spent nuclear fuel

Tässä diplomityössä tehtiin Olkiluodon ydinvoimalaitoksella sijaitsevan käytetyn ydinpolttoaineen allasvarastointiin perustuvan välivaraston todennäköisyysperustainen ulkoisten uhkien riskianalyysi. Todennäköisyysperustainen riskianalyysi (PRA) on yleisesti käytetty riskien tunnistus- ja lähestymistapa ydinvoimalaitoksella. Työn tarkoituksena oli laatia täysin uusi ulkoisten uhkien PRA-analyysi, koska Suomessa ei ole aiemmin tehty vastaavanlaisia tämän tutkimusalueen riskitarkasteluja. Riskitarkastelun motiivina ovat myös maailmalla tapahtuneiden luonnonkatastrofien vuoksi korostunut ulkoisten uhkien rooli käytetyn ydinpolttoaineen välivarastoinnin turvallisuudessa. PRA analyysin rakenne pohjautui tutkimuksen alussa luotuun metodologiaan. Analyysi perustuu mahdollisten ulkoisten uhkien tunnistamiseen pois lukien ihmisen aikaansaamat tahalliset vahingot. Tunnistettujen ulkoisten uhkien esiintymistaajuuksien ja vahingoittamispotentiaalin perusteella ulkoiset uhat joko karsittiin pois tutkimuksessa määriteltyjen karsintakriteerien avulla tai analysoitiin tarkemmin. Tutkimustulosten perusteella voitiin todeta, että tiedot hyvin harvoin tapahtuvista ulkoisista uhista ovat epätäydellisiä. Suurinta osaa näistä hyvin harvoin tapahtuvista ulkoisista uhista ei ole koskaan esiintynyt eikä todennäköisesti koskaan tule esiintymään Olkiluodon vaikutusalueella tai edes Suomessa. Esimerkiksi salaman iskujen ja öljyaltistuksen roolit ja vaikutukset erilaisten komponenttien käytettävyyteen ovat epävarmasti tunnettuja. Tutkimuksen tuloksia voidaan pitää kokonaisuudessaan merkittävinä, koska niiden perusteella voidaan osoittaa ne ulkoiset uhat, joiden vaikutuksia olisi syytä tutkia tarkemmin. Yksityiskohtaisempi tietoisuus hyvin harvoin esiintyvistä ulkoisista uhista tarkentaisi alkutapahtumataajuuksien estimaatteja.

Modelling of hydrogen stratification and gas mixing in containment using the APROS code

Hydrogen stratification and atmosphere mixing is a very important phenomenon in nuclear reactor containments when severe accidents are studied and simulated. Hydrogen generation, distribution and accumulation in certain parts of containment may pose a great risk to pressure increase induced by hydrogen combustion, and thus, challenge the integrity of NPP containment. The accurate prediction of hydrogen distribution is important with respect to the safety design of a NPP. Modelling methods typically used for containment analyses include both lumped parameter and field codes. The lumped parameter method is universally used in the containment codes, because its versatility, flexibility and simplicity. The lumped parameter method allows fast, full-scale simulations, where different containment geometries with relevant engineering safety features can be modelled. Lumped parameter gas stratification and mixing modelling methods are presented and discussed in this master’s thesis. Experimental research is widely used in containment analyses. The HM-2 experiment related to hydrogen stratification and mixing conducted at the THAI facility in Germany is calculated with the APROS lump parameter containment package and the APROS 6-equation thermal hydraulic model. The main purpose was to study, whether the convection term included in the momentum conservation equation of the 6-equation modelling gives some remarkable advantages compared to the simplified lumped parameter approach. Finally, a simple containment test case (high steam release to a narrow steam generator room inside a large dry containment) was calculated with both APROS models. In this case, the aim was to determine the extreme containment conditions, where the effect of convection term was supposed to be possibly high. Calculation results showed that both the APROS containment and the 6-equation model could model the hydrogen stratification in the THAI test well, if the vertical nodalisation was dense enough. However, in more complicated cases, the numerical diffusion may distort the results. Calculation of light gas stratification could be probably improved by applying the second order discretisation scheme for the modelling of gas flows. If the gas flows are relatively high, the convection term of the momentum equation is necessary to model the pressure differences between the adjacent nodes reasonably.

Performance Degradation Modelling and Techno-Economic Analysis of Lithium-Ion Battery Energy Storage Systems

Transmission system operators and distribution system operators are experiencing new challenges in terms of reliability, power quality, and cost efficiency. Although the potential of energy storages to face those challenges is recognized, the economic implications are still obscure, which introduce the risk into the business models. This thesis aims to investigate the technical and economic value indicators of lithium-ion battery energy storage systems (BESS) in grid-scale applications. In order to do that, a comprehensive performance lithium-ion BESS model with degradation effects estimation is developed. The model development process implies literature review on lifetime modelling, use, and modification of previous study progress, building the additional system parts and integrating it into a complete tool. The constructed model is capable of describing the dynamic behavior of the BESS voltage, state of charge, temperature and capacity loss. Five control strategies for BESS unit providing primary frequency regulation are implemented, in addition to the model. The questions related to BESS dimensioning and the end of life (EoL) criterion are addressed. Simulations are performed with one-month real frequency data acquired from Fingrid. The lifetime and cost-benefit analysis of the simulation results allow to compare and determine the preferable control strategy. Finally, the study performs the sensitivity analysis of economic profitability with variable size, EoL and system price. The research reports that BESS can be profitable in certain cases and presents the recommendations.

Stress, social support, and health risk behaviours as mediators of the forgiveness-health relation /

The mediating roles of stress, social support, and health risk behaviours in the relationships between dispositional forgiveness and mental and physical health were examined. Participants were 748 undergraduate students (554 women, 194 men) entering their first year of studies at Brock University. Participants, ranging in age from 17 to 25 years, completed the Brock University First Year Health Study and were provided monetary compensation. Dispositional forgiveness, stress, social support, health risk behaviours, mental health, and physical health were measured using self-report methods. The data were analyzed separately for women and men because there were significant mean differences on many of the study'S variables. Analyses revealed that the mediated relationships between dispositional forgiveness and health were generally stronger for women than men. Stress was the most robust mediator of the forgiveness-health relation for both women and men. The only health risk behaviour that mediated the forgivenesshealth relation was physical fitness and this result was found for women only. Social support mediated several of the relationships between forgiveness and health but not others. Results were discussed with reference to the literature on forgiveness and health. Several directions for future research were offered, such as conducting longitudinal research designs to assess the direction of causality better, investigating moderator variables of the forgiveness-health relation, and building models, which incorporate multiple mediators using structural equation modelling techniques.

Numerical modelling of the impact of climate change on the morphology of Saint-Lawrence tributaries

Cette thèse examine les impacts sur la morphologie des tributaires du fleuve Saint-Laurent des changements dans leur débit et leur niveau de base engendrés par les changements climatiques prévus pour la période 2010–2099. Les tributaires sélectionnés (rivières Batiscan, Richelieu, Saint-Maurice, Saint-François et Yamachiche) ont été choisis en raison de leurs différences de taille, de débit et de contexte morphologique. Non seulement ces tributaires subissent-ils un régime hydrologique modifié en raison des changements climatiques, mais leur niveau de base (niveau d’eau du fleuve Saint-Laurent) sera aussi affecté. Le modèle morphodynamique en une dimension (1D) SEDROUT, à l’origine développé pour des rivières graveleuses en mode d’aggradation, a été adapté pour le contexte spécifique des tributaires des basses-terres du Saint-Laurent afin de simuler des rivières sablonneuses avec un débit quotidien variable et des fluctuations du niveau d’eau à l’aval. Un module pour simuler le partage des sédiments autour d’îles a aussi été ajouté au modèle. Le modèle ainsi amélioré (SEDROUT4-M), qui a été testé à l’aide de simulations à petite échelle et avec les conditions actuelles d’écoulement et de transport de sédiments dans quatre tributaires du fleuve Saint-Laurent, peut maintenant simuler une gamme de problèmes morphodynamiques de rivières. Les changements d’élévation du lit et d’apport en sédiments au fleuve Saint-Laurent pour la période 2010–2099 ont été simulés avec SEDROUT4-M pour les rivières Batiscan, Richelieu et Saint-François pour toutes les combinaisons de sept régimes hydrologiques (conditions actuelles et celles prédites par trois modèles de climat globaux (MCG) et deux scénarios de gaz à effet de serre) et de trois scénarios de changements du niveau de base du fleuve Saint-Laurent (aucun changement, baisse graduelle, baisse abrupte). Les impacts sur l’apport de sédiments et l’élévation du lit diffèrent entre les MCG et semblent reliés au statut des cours d’eau (selon qu’ils soient en état d’aggradation, de dégradation ou d’équilibre), ce qui illustre l’importance d’examiner plusieurs rivières avec différents modèles climatiques afin d’établir des tendances dans les effets des changements climatiques. Malgré le fait que le débit journalier moyen et le débit annuel moyen demeurent près de leur valeur actuelle dans les trois scénarios de MCG, des changements importants dans les taux de transport de sédiments simulés pour chaque tributaire sont observés. Ceci est dû à l’impact important de fortes crues plus fréquentes dans un climat futur de même qu’à l’arrivée plus hâtive de la crue printanière, ce qui résulte en une variabilité accrue dans les taux de transport en charge de fond. Certaines complications avec l’approche de modélisation en 1D pour représenter la géométrie complexe des rivières Saint-Maurice et Saint-François suggèrent qu’une approche bi-dimensionnelle (2D) devrait être sérieusement considérée afin de simuler de façon plus exacte la répartition des débits aux bifurcations autour des îles. La rivière Saint-François est utilisée comme étude de cas pour le modèle 2D H2D2, qui performe bien d’un point de vue hydraulique, mais qui requiert des ajustements pour être en mesure de pleinement simuler les ajustements morphologiques des cours d’eau.

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 .

Statistical evidences of cyclic changes in volcanic gas chemistry composition by inverse modelling

The identification of compositional changes in fumarolic gases of active and quiescent volcanoes is one of the most important targets in monitoring programs. From a general point of view, many systematic (often cyclic) and random processes control the chemistry of gas discharges, making difficult to produce a convincing mathematical-statistical modelling. Changes in the chemical composition of volcanic gases sampled at Vulcano Island (Aeolian Arc, Sicily, Italy) from eight different fumaroles located in the northern sector of the summit crater (La Fossa) have been analysed by considering their dependence from time in the period 2000-2007. Each intermediate chemical composition has been considered as potentially derived from the contribution of the two temporal extremes represented by the 2000 and 2007 samples, respectively, by using inverse modelling methodologies for compositional data. Data pertaining to fumaroles F5 and F27, located on the rim and in the inner part of La Fossa crater, respectively, have been used to achieve the proposed aim. The statistical approach has allowed us to highlight the presence of random and not random fluctuations, features useful to understand how the volcanic system works, opening new perspectives in sampling strategies and in the evaluation of the natural risk related to a quiescent volcano

Knowledge-based modelling and simulation of operational problems of microbiological origin in wastewater treatment plants

The activated sludge and anaerobic digestion processes have been modelled in widely accepted models. Nevertheless, these models still have limitations when describing operational problems of microbiological origin. The aim of this thesis is to develop a knowledge-based model to simulate risk of plant-wide operational problems of microbiological origin.For the risk model heuristic knowledge from experts and literature was implemented in a rule-based system. Using fuzzy logic, the system can infer a risk index for the main operational problems of microbiological origin (i.e. filamentous bulking, biological foaming, rising sludge and deflocculation). To show the results of the risk model, it was implemented in the Benchmark Simulation Models. This allowed to study the risk model's response in different scenarios and control strategies. The risk model has shown to be really useful providing a third criterion to evaluate control strategies apart from the economical and environmental criteria.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

Modelling the hydraulics of the Carlisle 2005 flood event

The performance of a 2D numerical model of flood hydraulics is tested for a major event in Carlisle, UK, in 2005. This event is associated with a unique data set, with GPS surveyed wrack lines and flood extent surveyed 3 weeks after the flood. The Simple Finite Volume (SFV) model is used to solve the 2D Saint-Venant equations over an unstructured mesh of 30000 elements representing channel and floodplain, and allowing detailed hydraulics of flow around bridge piers and other influential features to be represented. The SFV model is also used to corroborate flows recorded for the event at two gauging stations. Calibration of Manning's n is performed with a two stage strategy, with channel values determined by calibration of the gauging station models, and floodplain values determined by optimising the fit between model results and observed water levels and flood extent for the 2005 event. RMS error for the calibrated model compared with surveyed water levels is ~±0.4m, the same order of magnitude as the estimated error in the survey data. The study demonstrates the ability of unstructured mesh hydraulic models to represent important hydraulic processes across a range of scales, with potential applications to flood risk management.

Modelling European winter wind storm losses in current and future climate

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

Transport and distribution of lindane and simazine in a riverine environment: measurements in bed sediments and modelling

Aquatic sediments often remove hydrophobic contaminants from fresh waters. The subsequent distribution and concentration of contaminants in bed sediments determines their effect on benthic organisms and the risk of re-entry into the water and/or leaching to groundwater. This study examines the transport of simazine and lindane in aquatic bed sediments with the aim of understanding the processes that determine their depth distribution. Experiments in flume channels (water flow of 10 cm s(-1)) determined the persistence of the compounds in the absence of sediment with (a) de-ionised water and (b) a solution that had been in contact with river sediment. In further experiments with river bed sediments in light and dark conditions, measurements were made of the concentration of the compounds in the overlying water and the development of bacterial/algal biofilms and bioturbation activity. At the end of the experiments, concentrations in sediments and associated pore waters were determined in sections of the sediment at 1 mm resolution down to 5 mm and then at 10 mm resolution to 50 mm depth and these distributions analysed using a sorption-diffusion-degradation model. The fine resolution in the depth profile permitted the detection of a maximum in the concentration of the compounds in the pore water near the surface, whereas concentrations in the sediment increased to a maximum at the surface itself. Experimental distribution coefficients determined from the pore water and sediment concentrations indicated a gradient with depth that was partly explained by an increase in organic matter content and specific surface area of the solids near the interface. The modelling showed that degradation of lindane within the sediment was necessary to explain the concentration profiles, with the optimum agreement between the measured and theoretical profiles obtained with differential degradation in the oxic and anoxic zones. The compounds penetrated to a depth of 40-50 rum over a period of 42 days. (C) 2004 Society of Chemical Industry.

Measuring and modelling mixture toxicity of imidacloprid and thiacloprid on Caenorhabditis elegans and Eisenia fetida

While the standard models of concentration addition and independent action predict overall toxicity of multicomponent mixtures reasonably, interactions may limit the predictive capability when a few compounds dominate a mixture. This study was conducted to test if statistically significant systematic deviations from concentration addition (i.e. synergism/antagonism, dose ratio- or dose level-dependency) occur when two taxonomically unrelated species, the earthworm Eisenia fetida and the nematode Caenorhabditis elegans were exposed to a full range of mixtures of the similar acting neonicotinoid pesticides imidacloprid and thiacloprid. The effect of the mixtures on C. elegans was described significantly better (p<0.01) by a dose level-dependent deviation from the concentration addition model than by the reference model alone, while the reference model description of the effects on E. fetida could not be significantly improved. These results highlight that deviations from concentration addition are possible even with similar acting compounds, but that the nature of such deviations are species dependent. For improving ecological risk assessment of simple mixtures, this implies that the concentration addition model may need to be used in a probabilistic context, rather than in its traditional deterministic manner. Crown Copyright (C) 2008 Published by Elsevier Inc. All rights reserved.

Towards a nutrient export risk matrix approach to managing agricultural pollution at source

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and is intended to persuade them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk Of Pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers' ability to obtain sound economic returns from their crop and livestock.