Guideline for Selection of Systems, Structures and Components to be considered in Ageing PSA

The guideline intends to provide a practical approach and to recommend the methods to be used in selection/prioritization of components, systems and structures (SSC) sensitive to ageing and important from risk point of view in operating nuclear power plants. The approach intends to ensure that the selection process will be carried out and documented in a uniform and consistent manner. The methods suitable for selection are briefly presented, and their advantages and disadvantages are specified. A list of generic ageing mechanisms, the factors favorable for their occurrence and some sensitive materials are provided in appendices. In the appendices are presented also the specific approaches and criteria used for SSC prioritization and selection in case studies performed in the frame of Ageing PSA task 3 activities. The guideline was developed in the frame of EC JRC Ageing PSA Network (APSA) activities.JRC.DDG.F.5-Safety of present nuclear reactor

Global sensitivity analysis of a one-dimensional ocean biogeochemical model

Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts from fisheries management to carbon dioxide removal and policy-making. These models contain numerous parameters, each coupled with large uncertainties, leading to significant uncertainty in the model outputs. This study performs a global sensitivity analysis (GSA) of an ocean BGC model to identify the uncertain parameters that impact the variability of model outputs most. The BGC model Regulated Ecosystem Model 2 is used in a one-dimensional configuration at two ocean sites in the North Atlantic (BATS) and the Mediterranean Sea (DYFAMED). Variance-based Sobol' indices are computed to identify the most influential parameters for each site for the quantities of interest (QoIs) commonly considered for the calibration and validation of BGC models. The most sensitive parameters are the chlorophyll to nitrogen ratio, chlorophyll degradation rate, zooplankton grazing and excretion parameters, photosynthesis parameters, and nitrogen and carbon remineralization rate. Overall, the sensitivities of most QoIs were similar across the two sites; however, some differences emerged because of different mixed layer depths. The results suggest that implementing multiple zooplankton function types in BGC models can improve BGC predictions. Further, explicitly implementing heterotrophic bacteria in the model can better simulate the carbon export production and CO2 fluxes. The study offers a comprehensive list of the most important BGC parameters that need to be quantified for future modeling applications and insights for BGC model developments.  </jats:p

Utilization of Integer Programming for Scheduling Maintenance at Nuclear Power Plants

This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week. The second chapter addresses the question of whether this simple schedule can be implemented with a long time horizon as the goal. This section delves into the concept of utilizing maintenance task frequencies and extended preventive maintenance frequencies to once again minimize the objective function of cost due to compensation. The third chapter focuses on the ability of the program to respond to adaptive circumstances. One major obstacle in running any large commercial facility is unplanned downtime of required systems or components. Simulating failures of certain components that shorten the overall allowable out-of-service time, the program will be required to still minimize the objective function while navigating these changing timelines

Voltage stability analysis of a power system network comprising a nuclear power plant

As recently as 2016, the performance of South Africa’s power utility has shown that it is not resilient enough to withstand the consequences of a power system blackout. Blackouts are defined as being a form of power system instability that can be brought about by a variety of abnormal network scenarios. The most common modes of failure are grouped under the term power system stability. In this dissertation, the different modes of power stability that can affect a nuclear power station will be investigated and discussed. The particular phenomenon that will be focused on, however, is the effect that voltage instability has on the ability of generators and loads to perform their standard functions, thus ensuring a secure power system. To investigate the effect that voltage instability has on a nuclear power station, this dissertation will look at relevant literature on the topic. In addition, by extracting from common examples of national and international occurrences of voltage stability, this dissertation will record the effects that this phenomenon has on the security of a power system, in particular on nuclear power plants. To model the network containing a nuclear power plant for the evaluation of voltage stability, the different mathematical models of the generation plant are presented, which include: the automatic voltage regulator, power system stabilizer, governor, nuclear reactor, and excitation system. Also presented are mathematical models of network equipment such as under voltage tap changers and the dynamic loads that are of interest when evaluating voltage stability. The models used for evaluation of the voltage stability phenomenon affecting a nuclear power plant and the surrounding integrated power system are built in the Digsilent PowerFactory® software. The scenario for evaluation is based on a voltage stability event that occurred around at the Koeberg nuclear power system situated in the Western Cape province on South Africa on 15 October 2003. It is commonly accepted that voltage stability can be evaluated at a steady state level by performing power versus voltage (PV) analysis to determine the voltage buses vulnerable to voltage collapse, and reactive power versus voltage (QV) analysis to determine the critical reactive devices required to avert a voltage instability event. The scenarios that are evaluated for voltage stability are divided into two sections: i) a PV and QV analysis as per the event that occurred on 15 October 2003 and ii) present-day voltage stability indices for PV and QV if mixed with a generation such as renewable energy sources that include wind, solar, biomass and concentrated solar power (CSPs). The result reveals the vulnerabilities of the nuclear power plant and the surrounding integrated power system due to a voltage instability event. Some of the solutions proposed include a review of the typical power system protection schemes — such as under and overvoltage detection scheme — that are used. In the study, PV and QV curves provide v good indications of the state of critical busbars and the reactive power reserve margins available before instability can potentially settle in. Simulations confirmed the effectiveness of critical equipment installed in the Western Grid and the effect on their electrical parameters such as torque and the slip on motors

Evaluation of modelling approaches for predicting the spatial distribution of soil organic carbon stocks at the national scale

Soil organic carbon (SOC) plays a major role in the global carbon budget. It can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Improving the tools that model the spatial distributions of SOC stocks at national scales is a priority, both for monitoring changes in SOC and as an input for global carbon cycles studies. In this paper, we compare and evaluate two recent and promising modelling approaches. First, we considered several increasingly complex boosted regression trees (BRT), a convenient and efficient multiple regression model from the statistical learning field. Further, we considered a robust geostatistical approach coupled to the BRT models. Testing the different approaches was performed on the dataset from the French Soil Monitoring Network, with a consistent cross-validation procedure. We showed that when a limited number of predictors were included in the BRT model, the standalone BRT predictions were significantly improved by robust geostatistical modelling of the residuals. However, when data for several SOC drivers were included, the standalone BRT model predictions were not significantly improved by geostatistical modelling. Therefore, in this latter situation, the BRT predictions might be considered adequate without the need for geostatistical modelling, provided that i) care is exercised in model fitting and validating, and ii) the dataset does not allow for modelling of local spatial autocorrelations, as is the case for many national systematic sampling schemes

System dynamics modeling for human performance in nuclear power plant operation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006.Includes bibliographical references (p. 62).Perfect plant operation with high safety and economic performance is based on both good physical design and successful organization. However, in comparison with the affection that has been paid to technology research, the effort that has been exerted to enhance NPP management and organization, namely human performance, seems pale and insufficient. There is a need to identify and assess aspects of human performance that are predictive of plant safety and performance and to develop models and measures of these performance aspects that can be used for operation policy evaluation, problem diagnosis, and risk-informed regulation. The challenge of this research is that: an NPP is a system that is comprised of human and physics subsystems. Every human department includes different functional workers, supervisors, and managers; while every physical component can be in normal status, failure status, or a being-repaired status. Thus, an NPP's situation can be expressed as a time-dependent function of the interactions among a large number of system elements. The interactions between these components are often non-linear and coupled, sometime there are direct or indirect, negative or positive feedbacks, and hence a small interference input either can be suppressed or can be amplified and may result in a severe accident finally. This research expanded ORSIM (Nuclear Power Plant Operations and Risk Simulator) model, which is a quantitative computer model built by system dynamics methodology, on human reliability aspect and used it to predict the dynamic behavior of NPP human performance, analyze the contribution of a single operation activity to the plant performance under different circumstances, diagnose and prevent fault triggers from the operational point of view, and identify good experience and policies in the operation of NPPs.(cont.) Regarding the human reliability analysis function, the partial Standardized Plant Analysis Risk Human Reliability Analysis (SPAR-H) method was applied. Performance Shaping Factors (PSFs) were employed to analyze the influence of human performance indicators already existing in ORSIM. Based on the human performance model, an operation case study was investigated. A series of carefully chosen candidate policies were tested on a computerized model that represents the structure, processes, and interactions of the underlying target NPP systems. These candidates included: (1) New management system application; (2) Personnel population change, (3) Planning delay, and (4) Tolerance to surprise workload.by Xinyuan Chu.S.M

Information for Meeting Africa’s Agricultural Transformation and Food Security Goals (IMAAFS)

The organizers of this international Conference on Information for Meeting Africa’s Agricultural Transformation and Food Security Goals (IMAAFS) included the African Union, the UN Economic Commission for Africa, and the European Commission (through the Joint Research Center). The Conference took place at the UN Conference Centre in Addis Ababa from 1 to 3 October 2014, to widen the availability and use of evidence-based information for agricultural growth and improved food and nutrition security. With over 180 international participants, the event brought together scientists and policy makers from a wide range of institutions and research organizations from Africa, Europe and the United States, as well as major UN agencies. The Conference took place over the course of three days and included nine presentation and discussion sessions (each with a chairperson and a rapporteur), executive morning briefs, break-out working groups, and a final decision-grid exercise to summarize the expert opinion of participants regarding the most promising strategies.JRC.H.4-Monitoring Agricultural Resource

Multi-scale Spatial Analysis of the Water-Food-Climate Nexus in the Nile Basin using Earth Observation Data

Securing enough water and food for everyone is a great challenge that the humanity faces today. This challenge is aggravated by many external drivers such as population growth, climate variability, and degradation of natural resources. Solutions for weak water and food securities require holistic knowledge of the different involved drivers through a nexus approach that looks at the interlinkages and the multi-directional synergies to be promoted and increased and trade-offs to be reduced or eliminated. In particular, the interlinkages between water, food, and climate, the so-called Water-Food-Climate Nexus (WFC Nexus) is critical for the given challenge in many regions around the world such as the Nile Basin (NB). Studying the WFC Nexus synergies and trade-offs might provide entry points for the required interventions that are potential to induce positive impacts on water and food securities. However, these synergies and trade-offs are not well known due to factors such as the complexity of the interactions which involve many dimensions within and across spatial and temporal domains and unavailability of reliable ground observations that could be used for such analysis. Therefore, multidisciplinary research that encompasses different methodologies and employs datasets with adequate spatial and temporal resolutions is required. The recent advancement in Earth Observation (EO) sensors and data processing algorithms have resulted in the accumulation of big data that are produced in rates faster than their usage in solving real challenges such as the one that is in the focus of the current research. The availability of public-domain datasets for several parameters with spatial and temporal coverage offers an excellent opportunity to discover the WFC Nexus interlinkages. To this end, the main goal of the current research is to employ EO data derived from public-domain datasets and supplemented with other primary and secondary data to identify WFC Nexus synergies and trade-offs in the NB region, taking the agricultural systems in Sudan as a central focus of this assessment. By concentrating mainly on the agricultural systems in Sudan, which are characterized by low performance and efficiency despite the huge potentials for food production, the current research provides a representative case study that could deliver helpful and transferrable knowledge to many areas within and outside the NB region. In the current research, multi-scale analysis of the WFC Nexus synergies and trade-offs was conducted. The assessment involved investigations on a country scale as a strategic level, and on river basin, agricultural scheme (both irrigated and rainfed systems) and field scales as operational levels. On a country scale, a general analysis of the vegetation’s Net Primary Productivity (NPP) and Water and Carbon Use Efficiencies (WUE and CUE, respectively) in different land cover types was carried out. A comparison between the land cover types in Sudan and Ethiopia was conducted to understand and compare the impact of inter-annual climate variability on the NPP, WUE and CUE indicators of these different land cover types under relatively different climate regimes. The results of this analysis indicate low magnitude of the three indicators in the land cover types that are in Sudan compared to their counterparts in Ethiopia. Moreover, the response of these indicators to climate variability varies widely among the land cover types. In addition, land cover types such as forests and woody savannah represent important natural sinks for the atmospheric CO2 that need to be protected. These observations suggest the need for effective policies that enhance crop productivity, especially in Sudan, and at the same time ensure preserving the land cover types that are important for climate change mitigation. On a river basin scale, which represented by the Blue Nile Basin (BNB), precipitation estimation is of utmost importance, as it is not only the main source of water in the basin but also because precipitation variability is controlling food production in the agricultural systems, especially in the rainfed schemes. The high spatial and temporal variation in precipitation within the BNB suggests the need for water storage and water harvesting be promoted and practiced. This would ensure water transfer spatially from wet to dry areas and temporally from wet to dry seasons. As a major staple cereal crop in Sudan, the performance of sorghum production in irrigated and rainfed schemes was investigated on agriculture schemes and field scales. A noticeable low and unstable sorghum yield is detected under both agricultural systems. This low performance represents a serious challenge, not only for food production but also for water availability. The current low performance was found to be controlled by many factors of physical, socio-economic and management nature. As many of these factors are closely linked, effectively addressing some of them might induce positive impacts on the other controlling factors. To conclude, the identified synergies and trade-offs of the WFC Nexus could be used as entry points to increase the efficiency of water use and bridge the crop yield gap. Even simple interventions in the field might induce positive effects to the total crop production of the agricultural schemes and water use efficiency. The increase of water availability in the river basin and improved production in the schemes would enhance the overall water and food security in the country and would minimize the need to convert land covers that are important for climate change mitigation into croplands. This paradigm shift needs to be done through a comprehensive sustainable intensification (SI) framework that is not only aimed at increasing crop yield but also targets promoting a healthy environment, improved livelihood, and a growing economy