Simulation of Co-60 uptake on stainless steel and alloy 690 using the OSCAR V1.4 code integrating an advanced dissolution-precipitation model

International audienceThe contamination of a nuclear cooling system by activated corrosion products (ACPs) is a process that involves many different mechanisms all interacting with each other. One of the most important mechanisms is dissolution-precipitation. This governs the transfer of soluble corrosion products between the circulating water and the immobile oxidized surfaces, and is strongly dependent on the water chemistry. The dissolution-precipitation model was improved in version 1.4 of the OSCAR computer code, which simulates the ACPs transfer in nuclear reactor systems. The OSCAR v1.4 code is now able to better calculate the incorporation of minor species (e.g., a cobalt isotope) into oxides using the chemistry module, PHREEQCEA, which determines the composition of an ideal solid solution and the equilibrium concentrations of elements in the aqueous solution. This model was challenged by comparing the results obtained using OSCAR v1.4 with the experimental results of a test performed in a dedicated loop by Studsvik Nuclear AB. Finally, with this model, the OSCAR v1.4 code accurately reproduces soluble $^{60}$Co uptake on stainless steel and alloy 690 under various experimental conditions (pH, Zn injection and flow rate)

Modeles bas-Reynolds appliques a une couche limite compressible

Theme 4 - Simulation et optimisation des systemes complexes. Projet SinusAvailable at INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.1996 n.2837 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

The OSCAR code: a simulation tool to assess the PWR contamination for decommissioning

International audienceKnowing the contamination state of the end-of-life nuclear reactor systems by Long-Lived RadioNu-clides (LLRNs) is a key stage for the decommissioning process. Indeed, the initial state is necessary to optimize the decommissioning works and to manage the radioactive waste as well. To address this issue, the contamination state is usually characterized using different types of techniques: in-situ gamma spectrometry, gamma camera scanning, dose rate measurements, , , measurements of samples obtained by smears or scrapings and then chemical separation processes, scaling factor approach… To reduce the amount of these measurements and thus the Occupational Radiation Ex-posure (ORE) and the decommissioning costs, a method is to assess the level of contamination by simulation. Furthermore, at the design stage of a new reactor, its decommissioning has to be taken into account and a simulation tool, such as the OSCAR code, can predict the radioactive source term at the end of life of a future reactor.The OSCAR code (Outil de Simulation de la ContAmination en Réacteur - tOol of Simulation of Con-tAmination in Reactor) has been developed by the CEA in collaboration with EDF and Framatome since the 1970s. The OSCAR code simulates the production and transfer of Activated Corrosion Products (ACPs) and Actinides and Fission Products and (AFPs) in the reactor systems and thus calculates the masses and activities of radionuclides deposited inside piping and heat exchangers of different circuits. As the OSCAR code has been originally devoted to mainly an industrial objective, which is the reduction of the Occupational Radiation Exposure (ORE) for operating PWRs, it deals with the main ACPs, 60Co, 58Co, 54Mn…, which are short-lived radionuclides. Nevertheless, it also cal-culates LLRNs of interest for decommissioning, such as 55Fe, 63Ni, 90Sr, 239Pu…, most of which are difficult to measure. The OSCAR code is validated through on-site measurements, including the EMECC campaigns, an operational experience feedback unique in the world, that consist of measur-ing the gamma surface activities mainly of the PWR primary system but also of auxiliary systems.After a presentation of the features and modeling of the OSCAR code, the paper will present some OSCAR simulation results of long-lived ACPs and AFPs deposited inside PWR circuits and their comparison with measurements. Perspectives of the OSCAR code on the decommissioning pro-grams will also be discussed

The OSCAR code package : A unique tool for simulating PWR contamination

International audienceUnderstanding the PWR primary circuit contamination by corrosion products, fission productsand actinides is a crucial issue for reactor operation and design. The main challenges aredecreasing the impact on personnel exposure to radiation, optimizing the plant operation,limiting the activity of the wastes produced during the reactor lifetime and preparingdecommissioning.In cooperation with EDF and AREVA NP, CEA has developed the OSCAR code package, aunique tool for simulating PWR contamination. The OSCAR package results from the mergingof two codes, which simulate PWR contamination by fission products and actinides (PROFIPcode) and by activated corrosion products (PACTOLE code).These two codes have been validated separately against an extensive set of data obtained over 40years from in-situ gamma spectrometry measurements, sampling and analysing campaigns ofprimary coolant, as well as experiments in test loops or experimental reactors, which arerepresentative of PWR conditions.In this paper, a new step is presented with the OSCAR code package, combining the features ofthe two codes and motivated by the fact that, wherever they originate from, the contaminationproducts are subject to the same severe conditions (300 °C, 150 bar, neutron flux, water velocityup to 15 m.s-1) and follow the same transport mechanisms in the primary circuit. The main processes involved are erosion/deposition, dissolution/precipitation, adsorption/desorption,convection, purification, neutron activation, radioactive decrease.The V1.1 version of the OSCAR package is qualified for fission products (Xe, Kr, I, Sr),actinides (U, Np, Pu, Am, Cm) and corrosion products (Ni, Fe, Co, Cr).This paper presents the different release modes (defective fuel rod release, fissile materialdissemination, material corrosion and release), then the processes which govern contaminationtransfer, and finally, we give examples of the comparison of the OSCAR package results withmeasurements in French PWR primary circuit obtained for representative radioisotopes : $^{133}$Xe,$^{90}$Sr, $^{58}$Co, $^{60}$Co. In particular, we focus on the main upgrades in the OSCAR simulations compared to thePROFIP and PACTOLE codes : adaptation of the MARGARET module to assess fission productrelease out of fuel pellets in a defective rod, adsorption/desorption model development forstrontium behaviour, multi-criteria calibration of input data which are not well known forcorrosion product simulation

Achievements of recent research on severe accidents at CEA/IRESNE in support of future nuclear fission technology

International audienceIn the current context of nuclear revival under the constraint of global warming and an ever-increasing world demand for energy, it is essential to take all precautions in the event of a serious accident during the design phase and to review the severe accident mitigation features of existing plants. The current nuclear revival is accompanied by the development of prototypes based on alternative concepts to light water reactors, such as the Sodium-cooled Fast Reactor (SFR), High Temperature Reactor (HTR), Molten Salt Reactor (MSR), which are also under consideration as reactors of reduced power output, or Small Modular Reactors (SMR). This paper summarizes the main outcomes and achievements of the last five years of experimental and numerical research conducted at CEA/IRESNE into prospective severe accidents within Pressurized Water Reactors (PWR) and SFRs

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries