Conception multi-physique et multi-objectif des cœurs de RNR-Na hétérogènes : développement d’une méthode d’optimisation sous incertitudes

Since Phenix shutting down in 2010, CEA does not have Sodium Fast Reactor (SFR) in operating condition. According to global energetic challenge and fast reactor abilities, CEA launched a program of industrial demonstrator called ASTRID (Advanced Sodium Technological Reactor for Industrial Demonstration), a reactor with electric power capacity equal to 600MW. Objective of the prototype is, in first to be a response to environmental constraints, in second demonstrates the industrial viability of:•SFR reactor. The goal is to have a safety level at least equal to 3rd generation reactors. ASTRID design integrates Fukushima feedback;•Waste reprocessing (with minor actinide transmutation) and it linked industry.Installation safety is the priority. In all cases, no radionuclide should be released into environment. To achieve this objective, it is imperative to predict the impact of uncertainty sources on reactor behaviour. In this context, this thesis aims to develop new optimization methods for SFR cores. The goal is to improve the robustness and reliability of reactors in response to existing uncertainties. We will use ASTRID core as reference to estimate interest of new methods and tools developed.The impact of multi-Physics uncertainties in the calculation of the core performance and the use of optimization methods introduce new problems:•How to optimize “complex” cores (i.e. associated with design spaces of high dimensions with more than 20 variable parameters), taking into account the uncertainties?•What is uncertainties behaviour for optimization core compare to reference core?•Taking into account uncertainties, optimization core are they still competitive? Optimizations improvements are higher than uncertainty margins?The thesis helps to develop and implement methods necessary to take into account uncertainties in the new generation of simulation tools. Statistical methods to ensure consistency of complex multi-Physics simulation results are also detailed.By providing first images of innovative SFR core, this thesis presents methods and tools to reduce the uncertainties on some performance while optimizing them. These gains are achieved through the use of multi-Objective optimization algorithms. These methods provide all possible compromise between the different optimization criteria, such as the balance between economic performance and safety.Depuis la fermeture de Phénix en 2010 le CEA ne possède plus de réacteur au sodium. Vus les enjeux énergétiques et le potentiel de la filière, le CEA a lancé un programme de démonstrateur industriel appelé ASTRID (Advanced Sodium Technological Reactor for Industrial Demonstration), réacteur d’une puissance de 600MW électriques (1500 MW thermiques). L’objectif du prototype est double, être une réponse aux contraintes environnementales et démontrer la viabilité industrielle :•De la filière RNR-Na, avec un niveau de sureté au moins équivalent aux réacteurs de 3ème génération, du type de l’EPR. ASTRID intégrera dès la conception le retour d’expérience de Fukushima ;•Du retraitement des déchets (transmutation d’actinide mineur) et de la filière qui lui serait liée.La sûreté de l’installation est prioritaire, aucun radioélément ne doit être rejeté dans l’environnement, et ce dans toutes les situations. Pour atteindre cet objectif, il est impératif d’anticiper l’impact des nombreuses sources d’incertitudes sur le comportement du réacteur et ce dès la phase de conception. C’est dans ce contexte que s’inscrit cette thèse dont l’ambition est le développement de nouvelles méthodes d’optimisation des cœurs des RNR-Na. L’objectif est d’améliorer la robustesse et la fiabilité des réacteurs en réponse à des incertitudes existantes. Une illustration sera proposée à partir des incertitudes associées à certains régimes transitoires dimensionnant. Nous utiliserons le modèle ASTRID comme référence pour évaluer l’intérêt des nouvelles méthodes et outils développés.L’impact des incertitudes multi-Physiques sur le calcul des performances d’un cœur de RNR-Na et l’utilisation de méthodes d’optimisation introduisent de nouvelles problématiques :•Comment optimiser des cœurs « complexes » (i.e associés à des espaces de conception de dimensions élevée avec plus de 20 paramètres variables) en prenant en compte les incertitudes ?•Comment se comportent les incertitudes sur les cœurs optimisés par rapport au cœur de référence ?•En prenant en compte les incertitudes, les réacteurs sont-Ils toujours considérés comme performants ?•Les gains des optimisations obtenus à l’issue d’optimisations complexes sont-Ils supérieurs aux marges d’incertitudes (qui elles-Mêmes dépendent de l’espace paramétrique) ?La thèse contribue au développement et à la mise en place des méthodes nécessaires à la prise en compte des incertitudes dans les outils de simulation de nouvelle génération. Des méthodes statistiques pour garantir la cohérence des schémas de calculs multi-Physiques complexes sont également détaillées.En proposant de premières images de cœur de RNR-Na innovants, cette thèse présente des méthodes et des outils permettant de réduire les incertitudes sur certaines performances des réacteurs tout en les optimisant. Ces gains sont obtenus grâce à l’utilisation d’algorithmes d’optimisation multi-Objectifs. Ces méthodes permettent d’obtenir tous les compromis possibles entre les différents critères d’optimisations comme, par exemple, les compromis entre performance économique et sûreté

Improvement of code behaviour in a design of experiments by metamodeling

It is now common practice in nuclear engineering to base extensive studies on numerical computer models. These studies require to run computer codes in potentially thousands of numerical configurations and without expert individual controls on the computational and physical aspects of each simulations.In this paper, we compare different statistical metamodeling techniques and show how metamodels can help to improve the global behaviour of codes in these extensive studies. We consider the metamodeling of the Germinal thermalmechanical code by Kriging, kernel regression and neural networks. Kriging provides the most accurate predictions while neural networks yield the fastest metamodel functions. All three metamodels can conveniently detect strong computation failures. It is however significantly more challenging to detect code instabilities, that is groups of computations that are all valid, but numerically inconsistent with one another. For code instability detection, we find that Kriging provides the most useful tools

Nature of the inheritance of gluten strength and carotenoid pigment content in winter by spring and durum wheat crosses (Triticum turgidum L. Var. durum)

Durum wheat cultivars for North-Eastern Oregon have to be competitive in terms of their yield potential with soft white winter wheat cultivars and meet strict quality requirements of the milling industry. Combining the high yield potential of fall planted durum wheat cultivars which have an acceptable level of winter hardiness with the good quality characteristics of the spring types through winter by spring crosses is believed to be an appropriate strategy. However, to be efficient, quality traits of the breeding lines and the nature of their inheritance must be evaluated early in the breeding process. The primary objective of this study was to investigate the nature of genetic variability involving two main quality traits, namely gluten strength and carotenoid pigment content. These traits are measured by the SDS sedimentation test and by spectrophotometric analysis of pigment extracts, respectively. Total genetic variability involving grain yield, kernel weight and protein content was also studied. Combining ability analysis of a 4x4 diallel cross using two winter and two spring parents was performed according to Griffing's (1956) Model 1, method 1. Both additive and non additive type gene action controlled all traits studied. Non additive type gene action was particularly important for grain yield and kernel weight suggesting that selection for these traits should be delayed until later generations (F5 or F6). Protein and pigment content were controlled primarily by genes functioning in an additive manner although they are also influenced by significant non additive type gene action. Reciprocal effects were significant for pigment content suggesting that some maternal effect might be involved. The predominance of additive type gene action for sedimentation volume suggests that this trait can be used to screen early generation material (F2, F3) for gluten strength. F2 populations generated from the diallel cross were compared in terms of their genetic variances, potential transgressive segregation and were used to investigate the possible associations between the traits measured. Winter by spring crosses were usually characterized by an enhanced genetic variability for yield and gluten strength. Transgressive segregation for sedimentation volume was present in these crosses. Protein content was negatively associated with grain yield. No relationship between gluten strength and grain yield was observed. Gluten strength did not appear to be associated with total protein content of the grain. Sedimentation volume varied greatly, even in populations with low variability in protein content. Consequently, selection on the basis of sedimentation volume per se would not be result in selecting inadvertently agronomically unsuitable types

FASTTRACK RECOMMENDER SYSTEM

Network operators are overloaded with numerous recommendations coming from vendors, some of which come from automated recommender systems. Such automated recommendations may or may not apply to a customer’s specific environment, often lack an assessment of priority within the context of the other recommendations, and may or may not apply to an individual customer’s scenario. To address these challenges, techniques are presented herein that provide a novel approach to generating and ranking recommendations coming from a dynamic recommender system where rankings are based on enriched context from, for example, live data on real networks, activities performed by real customers, etc. Such techniques enhance the operational features of existing networks by recommending popular items to new customers, identifying critical items that can be proactively addressed in order to provide additional services, and reducing Technical Assistance Center (TAC) cases when patches exist for common issues

Agronomic performance of durum wheat landraces and modern cultivars and its association with genotypic variation in vernalization response (Vrn-1) and photoperiod sensitivity (Ppd-1) genes

This study analyzed the relationship between important agronomic traits and major genes regulating flowering time in a panel of 151 Mediterranean durum wheat landraces and 20 modern cultivars. Field experiments were conducted under rainfed conditions during six crop seasons in northeastern Spain. Multivariate analysis of agronomic traits and genotypic data allowed the modern cultivars to be differentiated from the landraces and germplasm pools to be identified within the landraces associated with their geographic origin. The high frequency of the Vrn-A1c allele and the photoperiod insensitive alleles GS105 and GS100 at Ppd-A1 reduced time to anthesis and enlarged the grain filling period of the modern cultivars compared with the landraces. Ancient durums collected close to the domestication area of wheat showed a high frequency of the winter allele vrn-B1 and the photoperiod sensitivity allele Ppd-B1b. None of the allele variants or allelic combinations accounted significantly for variations in any agronomic trait of modern cultivars. Vernalization and photoperiod genes acted additively in explaining the genotypic variance for the agronomic traits of the landraces. Vrn-A1 alleles and Vrn-A1+Vrn-B1 allelic combinations significantly affected the number of grains per spike (NGS), thousand kernel weight (TKW) and grain filling rate (R), accounting for 9%–12% of the genotypic variance for these traits. Ppd-1 accounted for 6%–21% of the genotypic variance for R, grain filling duration (GFD), plant height (PH), biomass at anthesis (CDW) and harvest index (HI). Vrn-1+Ppd-1 allelic combinations accounted for 21%–26% of the genotypic variance for these traits. Except for NGS, the effect of vernalization and photoperiod genes on the agronomic traits was linked to their effect on anthesis time. The three-day delay in anthesis time caused by the allele Vrn-A1d irrespective of the allele Vrn-A1c resulted in increases of 10 % in R and 7% in TKW. The eight-day delay in anthesis time caused by the allele Ppd-A1(DelCD) compared with Ppd-A1(GS105) increased R by 19 % and PH by 28 %, but reduced GFD and HI by 10 %. None of the allele variants or allelic combinations at the Vrn-1 or Ppd-1 genes accounted significantly for variations in yield or number of spikes m−2 (NSm2).info:eu-repo/semantics/publishedVersio

Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars

A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (HT) was 0.40 with a genetic differentiation (GST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log10p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.info:eu-repo/semantics/publishedVersio

Agronomic, Physiological and Genetic Changes Associated With Evolution, Migration and Modern Breeding in Durum Wheat

A panel of 172 Mediterranean durum wheat landraces and 200 modern cultivars was phenotyped during three years for 21 agronomic and physiological traits and genotyped with 46,161 DArTseq markers. Modern cultivars showed greater yield, number of grains per spike (NGS) and harvest index (HI), but similar number of spikes per unit area (NS) and grain weight than the landraces. Modern cultivars had earlier heading but longer heading-anthesis and grain-filling periods than the landraces. They had greater RUE (Radiation Use Efficiency) up to anthesis and lower canopy temperature at anthesis than the landraces, but the opposite was true during the grain-filling period. Landraces produced more biomass at both anthesis and maturity. The 120 genotypes with a membership coefficient q > 0.8 to the five genetic subpopulations (SP) that structured the panel were related with the geographic distribution and evolutionary history of durum wheat. SP1 included landraces from eastern countries, the domestication region of the “Fertile Crescent.” SP2 and SP3 consisted of landraces from the north and the south Mediterranean shores, where durum wheat spread during its migration westward. Decreases in NS, grain-filling duration and HI, but increases in early soil coverage, days to heading, biomass at anthesis, grain-filling rate, plant height and peduncle length occurred during this migration. SP4 grouped modern cultivars gathering the CIMMYT/ICARDA genetic background, and SP5 contained modern north-American cultivars. SP4 was agronomically distant from the landraces, but SP5 was genetically and agronomically close to SP1. GWAS identified 2,046 marker-trait associations (MTA) and 144 QTL hotspots integrating 1,927 MTAs. Thirty-nine haplotype blocks (HB) with allelic differences among SPs and associated with 16 agronomic traits were identified within 13 QTL hotspots. Alleles in chromosomes 5A and 7A detected in landraces were associated with decreased yield. The late heading and short grain-filling period of SP2 and SP3 were associated with a hotspot on chromosome 7B. The heavy grains of SP3 were associated with hotspots on chromosomes 2A and 7A. The greater NGS and HI of modern cultivars were associated with allelic variants on chromosome 7A. A hotspot on chromosome 3A was associated with the high NGS, earliness and short stature of SP4.info:eu-repo/semantics/publishedVersio

Exact and efficient solutions of the LMC Multitask Gaussian Process model

The Linear Model of Co-regionalization (LMC) is a very general model of multitask gaussian process for regression or classification. While its expressivity and conceptual simplicity are appealing, naive implementations have cubic complexity in the number of datapoints and number of tasks, making approximations mandatory for most applications. However, recent work has shown that under some conditions the latent processes of the model can be decoupled, leading to a complexity that is only linear in the number of said processes. We here extend these results, showing from the most general assumptions that the only condition necessary to an efficient exact computation of the LMC is a mild hypothesis on the noise model. We introduce a full parametrization of the resulting \emph{projected LMC} model, and an expression of the marginal likelihood enabling efficient optimization. We perform a parametric study on synthetic data to show the excellent performance of our approach, compared to an unrestricted exact LMC and approximations of the latter. Overall, the projected LMC appears as a credible and simpler alternative to state-of-the art models, which greatly facilitates some computations such as leave-one-out cross-validation and fantasization.Comment: 21 pages, 5 figures, submitted to AISTAT