OECD/NEA ROSA/LSTF project tests are performed on the Large Scale Test Facility (LSTF). LSTF is a full-height, full-pressure and 1/48 volumetrically-scaled two-loop system which aims to simulate Japanese Tsuruga-2 Westinghouse-type 4-loop PWR. ROSA-V Test 6-1 simulates a pressure vessel (PV) upper-head small break loss-of-coolant accident (SBLOCA) with a break size equivalent to 1.9% of the volumetrically scaled cross-sectional area of the reference PWR cold leg.The main objective of present thesis is to build a TRACE calculation model for simulating thermal hydraulic behaviors in LSTF and PV upper-head SBLOCA, so as to assess different modeling options and parameters of TRACE code. The results show that TRACE code well reproduce the complex physical phenomena involved in this type of SBLOCA scenarios. Almost all the events in the experiment are well predicted by the model based on TRACE code. In addition, the sensitivity of different models and parameters are investigated. For example, the code slightly overestimates the break mass flow from upper head which affects the accuracy of the results significantly. The rising of core exit temperature (CET) is significantly influenced by the flow area of leakage between downcomer and hot leg. Besides, the effect of the break location, low pressure injection system (LPIS) and accumulator setup are also studied.

Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence. iv In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type v based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics. In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson- vi lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence. Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear- vii end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level’s diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the singlevehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence. Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an viii extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL’s impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL’s safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.

This study explores the behavior of a Boiling Water Reactor (BWR) during a turbine trip scenario initiated by the abrupt closure of the turbine stop valve. The RELAP5/Mod3.4 code is employed to make calculations using the Laguna Verde Nuclear Power Plant input model provided by Innovative Software Systems Company. The event sequences and initial boundary conditions are sourced from the Boiling Water Reactor Turbine Trip 2 Benchmark created by NEA. Results are subsequently compared against the benchmark values. In order to gauge the risk of a turbine trip event leading to elevated power, which could in turn cause Critical Heat Flux (CHF)-related issues in cladding temperature, a best-estimate case is developed. Our findings indicate that the closure of the turbine stop valve (TSV) resulted in a collapse of the void fraction within the reactor core. Although the core power doubled the initial level, the negative feedback mechanism effectively suppressed the power pulse. Throughout the transient phase, the maximum cladding temperature stayed below the CHF threshold, a fact attributable to the fuel's conductivity and the rapid progression of the transient. We further analyzed three hypothetical scenarios to test the computational boundaries of the plant model. The third scenario, which combines conditions from the first two, produced elevated outcomes (6500MW core power, 598K cladding temperature, and 7900kPa dome pressure) as expected. Notably, while the CHF limit remained unbreached in this scenario, literature reviews suggest potential core meltdown risks in subsequent stages of this calculation. Our sensitivity analyses determined that variations in the gamma heating coefficient or the maximum time step of the calculations have little to no impact on core power or peak cladding temperature. Conversely, we noted a significant reduction, approximately 35\%, in the power peak, underscoring the high sensitivity of the parameters to the initial triggering of the SCRAM mechanism. Our results also recommend rapid and early actuation of the BPV as a measure to dampen the pressure wave, consequently decreasing both the power peak and peak cladding temperatures. / Thesis / Master of Applied Science (MASc) / This research investigates the response of the Laguna Verde Boiling Water Reactor to a turbine trip event using the RELAP5/Mod3.4 thermal-hydraulic analysis code. From reactor safety perspective a best-estimate case is evaluated, as well as three additional hypothetical scenarios. Findings are compared with the Boiling Water Reactor Turbine Trip II Benchmark results. Additionally, sensitivity analyses focusing on plant parameters such as shutdown rod behavior, gamma heating coefficient, turbine stop valve, and steam bypass valve characteristics conducted to determine their impact on the results. Insights from these analyses aim to enhance safety protocols and refine best practices in boiling water reactor management.

Yes / Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example. / DEIS H2020 Project under Grant 732242.

No

No / Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example. / This conference paper is available to view at http://hdl.handle.net/10454/17423.

Around the world, countries are increasingly considering carbon-free energy generation options as the threat of climate change grows. Small modular reactor designs, promising such carbon-free energy generation, are thriving worldwide with novel and innovative technologies that improve safety as well as economic performance. Canada is also considering small modular reactors (SMRs) as a means of achieving net zero carbon emissions by 2050. Some of these reactor designs utilize pressurized water for cooling and moderator. Reactors with pressurized water have been subjected to steam generator tube ruptures in the past, and a detailed investigation into the possible consequences of such incidents in SMRs should be conducted. In this research, a model for one of the newer designs, the NuScale Integrated Small Modular Reactor, was developed with the RELAP5-3D code for assessing safety related transients. The NuScale Small Modular Reactor incorporates helical coil steam generators within its reactor pressure vessel, which are more efficient in terms of heat transfer than the U-tube steam generators that are widely used in nuclear reactors. In the first part of the research, a detailed model is created and used to obtain steady state conditions with parameters collected from NuScale’s Final Safety Analysis Report (FSAR). The Steam Generator Tube Rupture event is analyzed in the second part of the work. Slight differences in the broken and intact steam generator pressures as well as decay heat removal system flow rates are seen in the comparison of reference values and calculated results. Among the reasons for those differences could be that the correlations used by the RELAP5-3D code for heat transfer coefficient and pressure drop in the helical coil steam generators are different than those of the NuScale proprietary code NRELAP5, with which the analyses have been performed in the FSAR. Also, post-dryout heat transfer at the exit of helical coil steam generators and evaporator sections could cause differences in the outlet conditions of the steam, resulting in different mass flow rates as well. The final section of the research simulates a comparable but more severe tube rupture incident without the availability of decay heat removal systems in order to assess the reactor’s emergency core cooling system reaction. Passive decay heat removal systems are crucial components for removing heat after reactor shutdown through heat exchangers that are submerged in the reactor pool and connected to steam generators by a closed loop. The containment pressures, the containment wall temperatures, and the peak fuel clad temperatures are considered to be the key design constraints that must be observed. Future work on this subject could include modifying the source code, adding specific correlations for helical coil steam generators, and comparing the results, as well as quantifying uncertainties in the SGTR event. Main parameters in the quantification of uncertainties would be reactor power, single phase and two-phase discharge coefficients from the break, trip signals and delays as well as break size and location. / Thesis / Master of Applied Science (MASc)

<p>The reprocessing of spent fuel is a key component in reducing the end waste from nuclear power plant operations and creating a sustainable closed fuel cycle. Central to this effort is the extraction and reprocessing of actinide materials to be recycled into fast or thermal reactors. Reprocessed actinides can contribute additional energy and may be partially transmuted in current thermal systems using mixed oxide fuels before being sent to fast reactors. The use of current thermal reactors as an intermediary step significantly reduces the fast reactor infrastructure needed to handle the spent fuel inventory in the long term, and also provides a source of additional energy from existing mined resources in the short term. An optimization of the fast and thermal systems in a closed fuel cycle reduces the end cycle waste to primarily fission products which have little residual value and manageable disposal and monitoring demands. The dissertation explores the design and analysis of an actinide transmutation solution utilizing a current thermal reactor design. The TRUMOX-30 CANDU-900 system defined herein uses a mixed oxide fuel containing 3.1% transuranic actinides extracted from 30 year cooled spent fuel from a prototypical Pressurized Water Reactor (PWR) and mixed with natural uranium. A significant constraint imposed on the design is that the actinide burning is to occur in an existing CANDU design without major changes or infrastructure replacement. Hence the standard CANDU design and analysis methodology was employed to produce and evaluate the system. The phased approach includes extensive neutron transport modeling of the lattice and control device super-cell configurations, which feed forward in to a detailed full core diffusion model of the TRUMOX-30 CANDU-900 design. Suitable fuel burnup and significant actinide conversion was achieved while remaining within the prescribed operational envelope of the CANDU reactor. The design was evaluated against existing operational constraints and limits, performing well and achieving the goal of actinide transmutation with no changes to the reactor design. This effort demonstrated the adaptation of a current CANDU-900 reactor as a platform for intermediary actinide transmutation which may form part of a sustainable and efficient fuel cycle.</p> / Doctor of Philosophy (PhD)

<p>Analiza frekvencije saobraćajnih nezgoda predstavlja važan predmet<br />istraživanja mnogih autora. Jedno od ključnih pitanja koje se<br />postavlja pred upravljača puta je gde da prvo deluje, odnosno koje<br />deonica puta treba da se tretiraju kako bi se postigao željeni nivo<br />pouzdanosti određenog puta. Disertacija pokazuje da se teorija<br />pouzdanosti sistema može koristiti za analizu frekvencija<br />saobraćajnih nezgoda. Nakon analize frekvencije saobraćajnih<br />nezgoda, sledeći korak predstavlja primena teorije realokacije<br />pouzdanosti. Predloženi modeli razvijeni su za izbor deonica za<br />tretman na osnovu precizno definisanog povećanja nivoa pouzdanosti<br />određenog puta.</p> / <p>Analysis of traffic accident frequency represents an important subject of<br />research of many authors. One of the essential questions placed before a<br />road authority is where to act first, i.e. which road sections should be treated<br />in order to achieve the desired level of reliability. Dissertation shows that the<br />system reliability theory can be used to analyze traffic accident frequency.<br />After analysis of the traffic accident frequency, further step is application of<br />the reliability reallocation theory Tools have been developed for selecting<br />road sections for treatment on the basis of a precisely defined increase in the<br />level of reliability of a particular road.</p>

O licenciamento de uma instalação nuclear é motivado pela necessidade de proteger os seres humanos e o meio ambiente das radiações ionizantes e, ao mesmo tempo, define as bases para a concepção e a determinação da aceitabilidade da planta. Uma parte importante no processo de licenciamento é a realização de uma análise de acidentes, a qual deve estar documentada no Relatório Final de Análise de Segurança (RFAS). Existem diferentes opções de cálculo na área de acidentes, combinando a utilização de códigos computacionais e dados de entrada, para fins de licenciamento. Uma delas é a Best Estimate Plus Uncertainty (BEPU), que considera dados de entrada realistas e as incertezas associadas. As aplicações de abordagens BEPU em processos de licenciamento iniciaram-se nos anos 2000, primeiro para análise de Acidente de Perda de Refrigerante (Loss of Coolant Accident - LOCA), e depois para a análise de acidentes como um todo, documentados no Capítulo 15 do RFAS. O presente trabalho tem como objetivo principal demonstrar que é possível a aplicação da metodologia BEPU em todas as análises contidas no RFAS, identificando as disciplinas-chave do processo de licenciamento e os códigos computacionais utilizados. Este trabalho foi desenvolvido em conjunto com a Universidade de Pisa, Itália, com a colaboração do Prof. Dr. Francesco D\'Áuria. A principal motivação desse trabalho é o aprimoramento da metodologia BEPU para sua implementação em reatores do tipo PWR (Pressurized Water Reactor) no Brasil e no mundo, especialmente para fins de licenciamento, uma vez que as plantas nucleares brasileiras têm pouca experiência na área de cálculo de incertezas. / The licensing process of a nuclear power plant is motivated by the need to protect humans and the environment from ionizing radiation and, at the same time, sets out the basis for the design and determining the acceptability of the plant. An important part of the licensing process is the realization of accident analysis, which should be documented in the Final Safety Analysis Report (FSAR). There are different options on accidents calculation area by combining the use of computer codes and data entry for licensing purposes. One is the Best Estimate Plus Uncertainty (BEPU), which considers realistic input data and associated uncertainties. Applications of BEPU approaches in licensing procedures were initiated in the 2000s, first to analysis of Loss of Coolant Accident (LOCA), and then to the accident analysis as a whole, documented in Chapter 15 of the FSAR. This work has as main objective demonstrate the implementation of BEPU methodology in all analyses contained in FSAR is possible, identifying the key disciplines of the licensing process and the computer codes. This work was done in conjunction with the University of Pisa, Italy, with the collaboration of Professor Francesco D\'Auria. The main motivation of this work is the improvement of BEPU methodology for its implementation in PWR (Pressurized Water Reactor) reactors in Brazil and the world, especially for licensing purposes, since the Brazilian nuclear plants have little experience in the regulatory area, and specifically in calculation uncertainties.