Towards Resilience to Nuclear Accidents:Financing Nuclear Liabilities via Catastrophe Risk Bonds

In light of the 2011 Fukushima disaster, recent discussion has focused on finding the best nuclear storage options, maximizing the oversight power of global institutions, and strengthening safety measures. In addition to these, the development of dependable liability coverage that can be tapped in an emergency is also needed and should be considered thoughtfully. To succeed, financing is essential using special-purpose instruments from the global bond market, which is as big as US$175 trillion. Thus, in this paper, for the first time, a two-coverage-type trigger nuclear catastrophe (N-CAT) risk bond for potentially supplementing the covering of U.S. commercial nuclear power plants (NPPs) beyond the coverage per the Price Anderson Act as amended, and potentially other plants are proposed and designed worldwide. The N-CAT peril is categorized by three risk layers: incident, accident, and major accident. The pricing formula is derived by using a semi-Markovian dependence structure in continuous time. A numerical application illustrates the main findings of the paper.</jats:p

The role of the reactor size for an investment in the nuclear sector: an evaluation of not-financial parameters

The literature presents many studies about the economics of new Nuclear Power Plants (NPPs). Such studies are based on Discounted Cash Flow (DCF) methods encompassing the accounts related to Construction, Operation & Maintenance, Fuel and Decommissioning. However the investment evaluation of a nuclear reactor should also include not-financial factors such as siting and grid constraints, impact on the national industrial system, etc. The Integrated model for the Competitiveness Assessment of SMRs (INCAS), developed by Politecnico di Milano cooperating with the IAEA, is designed to analyze the choice of the better Nuclear Power Plant size as a multidimensional problem. In particular the INCAS’s module “External Factors” evaluates the impact of the factors that are not considered in the traditional DCF methods. This paper presents a list of these factors, providing, for each one, the rationale and the quantification procedure; then each factor is quantified for the Italian case. The IRIS reactor has been chosen as SMR representative. The approach and the framework of the model can be applied to worldwide countries while the specific results apply to most of the European countries. The results show that SMRs have better performances than LRs with respect to the external factors, in general and in the Italian scenario in particular

Evaluating airborne and ground based gamma spectrometry methods for detecting particulate radioactivity in the environment: a case study of Irish Sea beaches

In several places, programmes are in place to locate and recover radioactive particles that have the potential to cause detrimental health effects in any member of the publicwho may encounter them. A model has been developed to evaluate the use of mobile gamma spectrometry systems within such programmes, with particular emphasis on large volume (16 l) NaI(Tl) detectors mounted in low flying helicopters. This model uses a validated Monte Carlo code with assessment of local geochemistry and natural and anthropogenic background radiation concentrations and distributions. The results of the model, applied to the example of particles recovered from beaches in the vicinity of Sellafield, clearly show the ability of rapid airborne surveys conducted at 75 m ground clearance and 120 kph speeds to demonstrate the absence of sources greater than 5 MBq 137Cs within large areas (10–20 km2 h−1), and identify areas requiring further ground based investigation. Lowering ground clearance for airborne surveys to 15 m whilst maintaining speeds covering 1–2 km2 h−1 can detect buried 137Cs sources of 0.5 MBq or greater activity. A survey design to detect 100 kBq 137Cs sources at 10 cm depth has also been defined, requiring surveys at b15 m ground clearance and b2 m s−1 ground speed. The response of airborne systems to the Sellafield particles recovered to date has also been simulated, and the proportion of the existing radiocaesium background in the vicinity of the nuclear site has been established. Finally the rates of area coverage and sensitivities of both airborne and ground based approaches are compared, demonstrating the ability of airborne systems to increase the rate of particle recovery in a cost effective manner. The potential for equipment and methodological developments to improve performance are discussed

Support Vector Machines and Generalisation in HEP

5 pages, 6 figures. Contribution to the proceedings of the 17th International workshop on Advanced Computing and Analysis Techniques in physics research - ACAT 2016, 18 - 22 January 2016, Valpara\'iso, ChileInternational audienceWe review the concept of support vector machines (SVMs) and discuss examples of their use. One of the benefits of SVM algorithms, compared with neural networks and decision trees is that they can be less susceptible to over fitting than those other algorithms are to over training. This issue is related to the generalisation of a multivariate algorithm (MVA); a problem that has often been overlooked in particle physics. We discuss cross validation and how this can be used to improve the generalisation of a MVA in the context of High Energy Physics analyses. The examples presented use the Toolkit for Multivariate Analysis (TMVA) based on ROOT and describe our improvements to the SVM functionality and new tools introduced for cross validation within this framework