Transient analyses at Forsmark nuclear power plant are currently performed using realistic computer models in conjunction with conservative estimates of initial- and boundary conditions. This is known as the combined methodology. Due to the conservative estimates, the methodology runs the risk of sometimes over-estimating certain safety criteria which will negatively affect the optimization of reactor operation. The Best Estimate Plus Uncertainty (BEPU) methodology can provide higher safety margins by using probabilities instead of conservatisms when estimating initial and boundary conditions. The BEPU methodology applies a Monte Carlo method to assess the distribution of one or several key outputs. This study focuses on the lowest dryout margin achieved during each Monte Carlo simulation. The tolerance limits of the output are set with the help of Wilks formula using a one-sided 95% tolerance limit with 95% confidence. A total of 36 unique parameters describing initial and boundary conditions have been sampled for each Monte Carlo simulation. The parameters have been sampled using either Gaussian or Uniform distribution functions. The random nature of the Monte Carlo simulations has uncovered alternative event sequences and end states that are not seen in the combined methodology. Assessing the choice of order statistic in Wilks formula also concludes that there are diminishing returns the higher the order statistic is. When choosing the order statistic, one should consider the trade-off between an increased accuracy in the estimated outputs and the increased computational time required. The conservative methodology uses a mix of conservative and nominal estimations of key parameters. The difference in dryout margin between the conservative and the Monte Carlo results should therefore not be used to draw a conclusion about which methodology out-performs the other. While the Monte Carlo simulations do not result in an improved core optimization, they can act as a complement to the combined methodology by providing a more detailed analysis of possible event pathways for a postulated transient.

Nuclear power is a foundational part of our electrical grid in the present and through our transition towards more sustainable and renewable alternatives. However, given the serious consequences of reckless and/or dangerous operation of nuclear power plants, they are subject to strict regulation and supervision by the Swedish radiation protection authority (SSM) and other regulating bodies (e.g. IAEA). In order to prove that a nuclear power plant is operating in a safe and accident preventative manner, the “Safety Analysis Report” (SAR) is created and submitted. The SAR categorizes and ranks all possible incidents and operation affecting events in terms of risk and available countermeasures to ensure that the radioactive release from the power plant and impact on a third party from any event is at acceptable levels. This projects limits its analysis to flooding of the reactor building or “internal flooding events” as described in the SAR. To determine the affected areas and impacted systems of any flooding event, deterministic safety analyses (DSA) are employed. The goal of this project is to develop a comprehensive thermohydraulic model of the Forsmark 2 reactor building and evaluate its performance with respect to the previously used MATLAB model. The model  should allow for a detailed nodalisation of the reactor building as well as realistic modelling of structural components such as doors, hatches, stairwells and drainage systems. The resulting thermohydraulic model  can be used to evaluate different flooding incidents dynamically and follow the spread of water and/or steam throughout the reactor building. Furthermore, the resulting pressure changes and heat generation in the reactor building can also be evaluated. The model allows for the possibility to couple the thermohydraulic reactor building model with the existing power plant systems model to holistically evaluate the power plant response to flooding related incidents. / Kärnkraft är en grundläggande del av vårt elnät i nuläget och under vår övergång mot mer hållbara och förnybara alternativ. Men med tanke på de allvarliga konsekvenserna av vårdslös och/eller farlig drift av kärnkraftverk, är de föremål för strikt reglering och tillsyn av Strålsäkerhetsmyndigheten (SSM) och andra reglerande organ (t.ex. IAEA). För att bevisa att ett kärnkraftverk drivs på ett säkert och olycksförebyggande sätt, upprättas och inlämnas "Strålsäkerhetsanalysrapport" (SAR). SAR kategoriserar och rangordnar alla möjliga incidenter och händelser som påverkar driften i termer av risk och tillgängliga motåtgärder för att säkerställa att radioaktiva utsläpp från kraftverket och påverkan på tredje person från någon händelse är på acceptabla nivåer. Detta projekt begränsar sin analys till översvämning av reaktorbyggnaden eller "interna översvämningshändelser" enligt beskrivningen i SAR. För att fastställa de påverkade områdena och drabbade systemen vid en översvämningshändelse, används deterministiska säkerhetsanalyser (DSA). Målet med detta projekt är att utveckla en omfattande termohydraulisk modell av Forsmark 2 reaktorbyggnad och utvärdera dess prestanda i förhållande till den tidigare använda MATLAB-modellen. Modellen ska möjliggöra en detaljerad nodalisering av reaktorbyggnaden samt realistisk modellering av strukturella komponenter som dörrar, luckor, trapphus och dräneringssystem. Den resulterande termohydrauliska modellen kan användas för att dynamiskt utvärdera olika översvämningsincidenter och följa spridningen av vatten och/eller ånga genom reaktorbyggnaden. Dessutom kan de resulterande tryckförändringarna och värmegenereringen i reaktorbyggnaden också utvärderas. Modellen möjliggör koppling av den termohydrauliska reaktorbyggnadsmodellen med den befintliga kraftverkssystemmodellen för att holistiskt utvärdera kraftverkets respons på översvämningsrelaterade händelser.

The advective motion of seawater governs the transport of almost everything, animate or inanimate, present in the ocean and those lacking the ability to outswim the currents have to follow the flow. This makes modelling of advective ocean transports a powerful tool in various fields of science where a displacement of something over time is studied. The present thesis comprises four different applications of ocean-transport modelling, ranging from large-scale heat transports to the dispersion of juvenile marine organisms. The aim has been to adapt the method not only to the object of study, but also to the available model-data sets and in situ-observations. The first application in the thesis is a study of the oceanic heat transport. It illustrates the importance of wind forcing for not only the heat transport from the Indian to the Atlantic Ocean, but also for the net northward transport of heat in the Atlantic. In the next study focus is on the particle-transport differences between an open and a semi-enclosed coastal area on the Swedish coast of the Baltic Sea. The modelled patterns of sedimentation and residence times in the two basins are examined after particles having been released from a number of prescribed point sources. In the two final studies the transport-modelling framework is applied within a marine-ecology context and the transported entities are larvae of some Scandinavian sessile and sedentary species and non-commercial fishes (e.g. the bay barnacle, the blue mussel, the shore crab and the gobies). The effects of depth distribution of dispersing larvae on the efficiency of the Marine Protected Areas in the Baltic Sea are examined. Further, the diversity in dispersal and connectivity depending on vertical behaviour is modelled for regions with different tidal regimes in the North Sea, the Skagerrak and the Kattegat. The spatial scales dealt with in the studies varied from global to a highly resolved 182-metres grid. The model results, excepting those from the global study, are based on or compared with in situ-data. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 3: Submitted. 4: Manuscript.</p>

Nuclear power plants are inherently complex systems. While the technology has been used to generate electrical power for many decades, process monitoring continuously evolves. There is always room for improvement in terms of maximizing the availability by reducing the risks of problems and errors. In this context, automated monitoring systems have become important tools – not least with the rapid progress being made in the field of data analytics thanks to ever increasing amounts of processing power. There are many different types of models that can be utilized for identifying anomalies. Some rely on physical properties and theoretical relations, while others rely more on the patterns of historical data. In this thesis, a data-driven approach using a hierarchical autoencoder framework has been developed for the purposes of anomaly detection at the Swedish nuclear power plant Forsmark. The model is first trained to recognize normal operating conditions. The trained model then creates reference values and calculates the deviations in relation to real data in order to identify any issues. This proof-of-concept has been evaluated and benchmarked against a currently used hybrid model with more physical modeling properties in order to identify benefits and drawbacks. Generally speaking, the created model has performed in line with expectations. The currently used tool is more flexible in its understanding of different plant states and is likely better at determining root causes thanks to its physical modeling properties. However, the created autoencoder framework does bring other advantages. For instance, it allows for a higher time resolution thanks to its relatively low calculation intensity. Additionally, thanks to its purely data-driven characteristics, it offers great opportunities for future reconfiguration and adaptation with different signal selections.