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At least 109 records · Page 6

Graphite Moderation in Fast Reactors

With the renewed interest in designing and building a fast test reactor in the U.S., several new reactor concepts have been emerging. Although the main mission of a fast test reactor would be to enable high fast flux irradiation capability, there could be added value for such a fast test reactor to also offer thermal neutron irradiation capabilities. As such, several of these concepts considered the use of a moderator material in a Sodium-cooled Fast Reactor (SFR), which is claimed to also offer benefits with respect of mass of fuel required. The work discussed in this paper focuses on exploring and assessing the benefits and challenges resulting from making use of thermalized neutrons to reduce the critical fuel mass. The analyses are performed for a graphite moderating material, using a simple core model to easily identify the phenomena observed. It is found that it is necessary to reduce the fuel enrichment near the moderated regions in order to avoid unacceptable power peaking. In the end, use of moderating materials outside a SFR core does not provide significant benefit in term of fuel volume reduction, but allows for a noticeable reduction of the mass of fissile material needed. However, it also implies a number of additional challenges which are highlighted in this paper.

core optimization↗

Preliminary Evaluation of Fuel Management Strategies for the Versatile Test Reactor (VTR)

Different fuel management approaches have been investigated for the Versatile Test Reactor (VTR). The main design variables were the number of batches, the number of (orifice) zones, and the loading pattern within the core. The optimization criteria are maximizing the fast flux at the centermost position, minimizing the peak assembly power, and reducing fuel consumption. Design constraints were mainly driven by material limits such as peak clad temperature, and maximum fuel burnup. The exploratory study determined that active fuel shuffling only brought very limited benefits. A three-orifice region was found to provide enough flexibility to ensure thermal criteria were met. Lastly, a flexible batch loading termed ‘5-6-8’ was identified as a promising management strategy from a resource utilization standpoint.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Comparison between Flownex and Corona thermal-hydraulic models for a single HTR prismatic fuel assembly - 18544

Computational tools and methodologies that can perform thermal-hydraulic analyses to reasonably predict the temperature distribution for the whole core of HTRs are useful for operational and safety analyses. In this paper, Flownex (a system code based on a one-dimensional thermal-fluid network methodology) and CORONA (Core Reliable Optimization and thermo-fluid Network Analysis) thermal-hydraulic models and results for a vertically stacked single fuel assembly will be compared. In Flownex, a basic unit cell containing part of the graphite and the associated fuel elements and coolant channels was developed. CORONA uses a basic unit cell concept for generating computational grids using several types of basic unit cells to model the heat transfer through the hexagonal blocks and a 1-D formulation to model the flow through the coolant channels. In CORONA, computational grids are generated using a combination of pre-generated mesh cells. The coolant channels and fuel rods are modelled explicitly. Flownex in contrast, models fuel and coolant channels implicitly by defining representative coolant channels, fuel rods and coated particle layers associated with each unit cell. Flownex can therefore model temperatures at coated particle level and also through each graphite block. The computational mesh employed by Flownex is much coarser than the mesh employed by CORONA. In both models, the helium gap between the fuel compact and the graphite block is modelled as stagnant. Flownex results were found to be of the same order of magnitude as those obtained using CORONA. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform

LWRS M3 milestone report due September 15, 2023. This report summarizes development and demonstration activities of PRLO optimization platform built in Risk Analysis and Virtual ENviroment (RAVEN), specifically: (1) Improvement of multi-objective non-dominated sorting genetic algorithm II (NSGA-II) to handle large size of objectives and constraints, (2) Demonstration of pressurized water reactor core design with NSGA-II multi-objective optimization platform, and (3) Single-objective optimized core design including system analysis and fuel performance feedback.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detection prospects of core-collapse supernovae with supernova-optimized third-generation gravitational-wave detectors

We discuss how to optimize the third-generation gravitational-wave detector to maximize the range to detect core-collapse supernovae. Based on three-dimensional simulations for core-collapse and the corresponding gravitational-wave waveform emitted, the corresponding detection range for these waveforms is limited to within our Galaxy even in the era of third-generation detectors. The corresponding event rate is two per century. We find from the waveforms that to detect core-collapse supernovae with an event rate of one per year, the gravitational-wave detectors need a strain sensitivity of 3 × 10 -27 Hz -1/2 in a frequency range from 100 to 1500 Hz. We also explore detector configurations technologically beyond the scope of third-generation detectors. We find with these improvements, the event rate for gravitational-wave observations from core-collapse supernovae is still low, but is improved to one in twenty years.

79 ASTRONOMY AND ASTROPHYSICS↗

3.5 kW/in3 Planar Coupled Inductor Design and Optimization for a 50 kW 3-level Four-Switch Buck-Boost (3L-FSBB) Converter

Planar magnetics design has been widely used in power electronics field because of the low profile, ease of manufacturability, and high power density. This paper first proposes a 3-level four-switch buck-boost (3L-FSBB) converter for the dc-dc applications where the zero common-mode (CM) voltage emissions, step-up and step-down are all required. With the consideration of power density, efficiency, and cost, a 15oz heavy copper coupled inductor for 3-level FSBB converter was designed and optimized with the low-cost commercial core and planar windings. According to the soft-switching quadrangle modulation for 3-L FSBB, the turns number and stacked core number are optimized first. And then, a two-board design is proposed to reduce the fringing effect and improve the thermal performance. Finally, a 75 kVA two-stage ac-dc-dc converter including a 3-level FSBB converter was built to verify the electrical design.

Cao, Yuliang↗

Implementation of fuel management multi-cycle optimization capabilities in RAVEN optimization framework

Optimization in nuclear fuel-management assists the core reload engineer with finding optimal out-of-core and in-core strategies. RAVEN is INL’s open source software that is equipped with fuel-management optimization capabilities including single-cycle, single- and multi-objective optimization of pressurized water reactors (PWRs) loading patterns (LP) of a fresh core using genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II). In practice, however, medium and long term planning of fuel-management needs a multi-cycle approach, where the history and availability of fuel assemblies is considered in the optimization process. In this paper, we present a description of an initial expansion of RAVEN fuel-management optimization capabilities for a multi-cycle optimization framework. N-th cycle optimization capabilities that account for the unique history of recycled fuel assembly in the core were added. The multi-cycle optimization approach taken is formulated as a cycle-wise optimization problem where out-of-core decisions are used to onset each cycle optimization. Out-of-core decisions are managed externally to the in-core optimization by a fuel inventory management module. A proof-of-concept optimization problem is also presented.

42 - ENGINEERING↗

Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. And, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

97 MATHEMATICS AND COMPUTING↗

Tuning the Core–Shell Structure of Au 144 @Fe 2 O 3 for Optimal Catalytic Activity for CO Oxidation

Core–shell heterostructures have been utilized as a catalyst that is thermally stable and exhibits a synergistic effect between core and shell, resulting in increased catalytic activity. We report on the synthetic procedure involving a Au 144 core with an iron oxide shell which can be varied in thickness. The Au 144 @Fe 2 O 3 particles with Au:Fe mass ratios of 1:2, 1:4, and 1:6 were synthesized and then deposited onto silica via colloidal deposition. Using CO oxidation, each Au 144 @Fe 2 O 3 /SiO 2 catalyst gave varying degrees of full CO conversion depending on the thickness of the iron oxide layer. The 1:4 Au 144 @Fe 2 O 3 /SiO 2 catalyst produced the best catalytic activity and was further investigated via thermal treatments, where calcination at 300 °C presented the best results, and the 1:4 ratio was still active at 100 °C after thermal treatments.

2-propanol conversion↗

Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. In addition, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

97 MATHEMATICS AND COMPUTING↗

Penalty-free method for multi-constrained optimization problems based on parallel simulated annealing

A method is presented for addressing constraints within the context of large-scale combinatorial optimization problems. The method, based on constraint annealing, eliminates the use of traditional constraint penalty factors by treating each constraint as separate and concurrently solved minimization problems within a global optimization search framework. Results are demonstrated for a core loading pattern optimization problem. (authors)

97 MATHEMATICS AND COMPUTING↗

Unusual Strain Effect of Pt-Based L10 Face-Centered Tetragonal Core in Core/Shell Nanoparticles for Oxygen Reduction Reaction

Here, nanoparticles with low-Pt content core and a few-layer Pt skin are attractive catalysts toward the oxygen reduction reaction (ORR) not only for its low cost, but also because its activity can be enhanced by judiciously choosing the core alloy. Achieving optimal ORR performance would require fine tuning of the core composition and structure. Previous work studying the enhancement effects has primarily focused on core alloys with a cubic structure, (i.e. disordered alloy or L12 ordered structure) which limits the tuning to composition alone. In this work, using ab initio calculations, we have systemically investigated a new class of Pt0.5M0.5 (M=V, Cr, Fe, Co, Ni and Cu) core alloy that has a face-centered tetragonal L10 intermetallic structure. We have calculated the adsorption energies of O, OH, and OOH on various Pt skins and the underlying tetragonal structured alloys, which allows us to not only predict the optimal number of pure Pt skin layers but also tune the activity of the catalysts toward the peak of the ORR volcano plot. More importantly, using adsorption energies on intermediate structures, we are able to decompose the enhancement factor into ligand, normal and shear strain effects, and reveal the significant contribution of the shear strain that is only possible with a tetragonal core but not a cubic one. Our results point to a new direction in designing tetragonal structured intermetallic core-shell nanoparticles for ORR applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Quantitative Proteomic Analysis of Optimal Cutting Temperature (OCT) Embedded Core-Needle Biopsy of Lung Cancer

With recent advances in understanding the genomic underpinnings and oncogenic drivers of pathogenesis in different subtypes, it is increasingly clear that proper pretreatment diagnostics are essential for the choice of appropriate treatment options for non-small cell lung cancer (NSCLC). Tumor tissue preservation in optimal cutting temperature (OCT) compound is commonly used in the surgical suite. However, proteins recovered from OCT-embedded specimens pose a challenge for LC-MS/MS experiments, due to the large amounts of polymers present in OCT. Here we present a simple workflow for whole proteome analysis of OCT-embedded NSCLC tissue samples, which involves a simple trichloroacetic acid precipitation step. Comparisons of protein recovery between frozen versus OCT-embedded tissue showed excellent consistency with more than 9200 proteins identified. Using an isobaric labeling strategy, we quantified more than 5400 proteins in tumor versus normal OCT-embedded core needle biopsy samples. Gene ontology analysis indicated that a number of proliferative as well as squamous cell carcinoma (SqCC) marker proteins were overexpressed in the tumor, consistent with the patient’s pathology based diagnosis of “poorly differentiated SqCC”. Among the most downregulated proteins in the tumor sample, we noted a number of proteins with potential immunomodulatory functions. Finally, interrogation of the aberrantly expressed proteins using a candidate approach and cross-referencing with publicly available databases led to the identification of potential druggable targets in DNA replication and DNA damage repair pathways. We conclude that our approach allows LC-MS/MS proteomic analyses on OCT-embedded lung cancer specimens, opening the way to bring powerful proteomics into the clinic. .

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimization strategies for sustainable fuel cycle of the BR2 Reactor

The objective of the present study is to achieve a sustainable fuel cycle in a long term of reactor operation applying advanced in-core loading strategies. The optimization criteria concern mainly enhancement of nuclear safety by means of reactivity margins and minimization of the operational fuel cycle cost at a given (constant) power level and same or longer cycle length. An important goal is also to maintain the same or to improve the experimental performances. Current developments are focused on optimization of control rods localization; optimization of fresh and burnt fuel assemblies in-core distribution; optimization of azimuth and axial fuel burn up strategies, including fuel assembly rotating and flipping upside down. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Novel Method for Controlling Crud Deposition in Nuclear Reactors Using Optimization Algorithms and Deep Neural Network Based Surrogate Models

This work presents the use of a high-fidelity neural network surrogate model within a Modular Optimization Framework for treatment of crud deposition as a constraint within light-water reactor core loading pattern optimization. The neural network was utilized for the treatment of crud constraints within the context of an advanced genetic algorithm applied to the core design problem. This proof-of-concept study shows that loading pattern optimization aided by a neural network surrogate model can optimize the manner in which crud distributes within a nuclear reactor without impacting operational parameters such as enrichment or cycle length. Several analysis methods were investigated. Analysis found that the surrogate model and genetic algorithm successfully minimized the deviation from a uniform crud distribution against a population of solutions from a reference optimization in which the crud distribution was not optimized. Strong evidence is presented that shows boron deposition in crud can be optimized through the loading pattern. This proof-of-concept study shows that the methods employed provide a powerful tool for mitigating the effects of crud deposition in nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimization of a heterogeneous fast breeder reactor core with improved behavior during unprotected transients

Innovative Sodium-cooled Fast Reactors (SFRs) are currently being investigated by CEA, AREVA and EDF in the framework of a joint French collaboration, and the construction of a GEN IV prototype, ASTRID (Advanced Sodium Technical Reactor for Industrial Demonstration), is scheduled in the years 2020. Significant improvements are expected so as to improve the reactor safety: the goal is to achieve a robust safety demonstration of the mastering of the consequences of a Core Disruptive Accident (CDA), whether by means of prevention or mitigation features. In this framework, an innovative design was proposed by CEA in 2010. It aims at strongly reducing the sodium void effect, thereby improving the core behavior during unprotected loss of coolant transients. This design is strongly heterogeneous and includes, amongst others, a fertile plate, a sodium plenum associated with a B{sub 4}C upper blanket and a stepwise modulation of the fissile height of the core (onwards referred to as the 'diabolo shape'). In this paper, studies which were entirely carried out at EDF are presented: the full potential of this heterogeneous concept is thoroughly investigated using the SDDS methodology. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗

Design and full core fuel performance assessment of high burnup cores for 4-loop PWRs

Increasing the fuel discharge burnup of current light water reactors (LWRs) promises reductions in fuel cycle and/or operations costs. By assuming a constant core power density, the economic gain is enabled by better fuel utilization and/or an increased capacity factor. In this effort to investigate greater than 62 MWd/kgU maximum rod average burnup for 110+ kW/l core power density, two core designs have been developed for a standard 17x17, 193 fuel assemblies pressurized water reactor (PWR). The levelized unit cost methodology is employed to evaluate fuel cycle, operation and maintenance, and capital cost impacts and to examine the economic viability of both core design pathways. Core design and optimization are performed using the commercial STUDSVIK code package. Fuel performance analysis is realized in full core configuration via auditing FRAPCON4.1, FAST1.2, and the high-fidelity code BISON. To provide a realistic assessment, the core design process takes into consideration best practices in current PWR core design. It features acceptable performance in terms of various core design constraints on maximum allowable peaking and boron concentration. Gadolinia (Gd2O3) is used as a burnable poison with a maximum of 9 wt% concentration while feeding 89 or 77 fuel assemblies in a 3-batch refueling scheme. Full core fuel performance simulation, which allows for characterization of relevant fuel temperatures, plenum pressures, stresses, and strains, is performed with respect to two bounding burnup levels. Such performance is potentially licensable for the 18-month high burnup core (<68 MWd/kgU peak pin), while it is more challenging for the 24-month high burnup core design pathway (<75 MWd/kgU peak pin). Maximum rod plenum pressure is identified as the most limiting fuel performance parameter. Here, while the scope of the present study focuses on the steady-state plus overpower conditions, the acceptability of the new discharge burnup has to be further assessed by considering uncertainties and impacts under accident scenarios in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗