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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of New Reactor Core Configuration for Power Uprate - Fuel Reload & Heat Processing Analyses, Core Design, System Safety Assessments, and Fuel Performance Analyses

With the passage of the Infrastructure Investment and Jobs Act in 2021 and the Inflation Reduction Act (IRA) in 2022, the United States stands at a critical juncture for the future of nuclear power. These landmark policies provide significant support for clean energy initiatives, positioning nuclear power as a key component of the nation’s strategy to reduce carbon emissions and achieve energy security. This growing emphasis on nuclear energy is driven by the need for reliable, low-carbon power sources as the country transitions away from fossil fuels. Federal policy, along with increasing state-level support, is encouraging investment in nuclear technology advancements to meet these demands. Building new nuclear power plants (NPPs), however, presents significant challenges due to high costs and long construction timelines. As a result, increasing the power output of existing NPPs through power uprates has emerged as a more feasible and cost-effective strategy. One key area of advancement is the development of accident-tolerant fuel (ATF), such as chromium-coated zirconium alloy cladding, which offers enhanced material performance, enabling power uprates in light water reactors (LWRs). Given the growing demand for nuclear energy fueled by federal policies and state initiatives, it is essential to evaluate the feasibility and benefits of significant power uprates in existing pressurized water reactors (PWRs) using advanced fuel technologies. The introduction of ATF concepts opens new opportunities for safely and economically achieving these power increases. Assessing whether these innovations can support substantial power uprates while maintaining operational safety is crucial to maximizing the potential of the nation’s existing nuclear infrastructure. This project aims to explore how power uprates can be achieved by boosting reactor thermal power output and optimizing reactor core design, while ensuring the safety and economic viability of NPPs. Specifically, it will focus on demonstrating the technical and economic feasibility of power uprates in a PWR using low 5-10% enrichment uranium (LEU+) high burnup (HBU) fuel combined with ATF concepts. In fiscal year 2024 (FY24), the research and development focus on building foundational models and conducting multi-physics performance and safety analyses to support the power uprate. The findings of the study would be shared through LWRS Seasonal Meetings, conferences and workshops with utility companies and researchers. These also serve as a basis for further study of fuel reloading optimization with ATF claddings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

Parameter Design and Optimal Control of an Open Core Flywheel Energy Storage System

In low earth orbit (LEO) satellite applications spacecraft power is provided by photovoltaic cells and batteries. To overcome battery shortcomings the University of Maryland, working in cooperation with NASA/GSFC and NASA/LeRC, has developed a magnetically suspended flywheel for energy storage applications. The system is referred to as an Open Core Composite Flywheel (OCCF) energy storage system. Successful application of flywheel energy storage requires integration of several technologies, viz. bearings, rotor design, motor/generator, power conditioning, and system control. In this paper we present a parameter design method which has been developed for analyzing the linear SISO model of the magnetic bearing controller for the OCCF. The objective of this continued research is to principally analyze the magnetic bearing system for nonlinear effects in order to increase the region of stability, as determined by high speed and large air gap control. This is achieved by four tasks: (1) physical modeling, design, prototyping, and testing of an improved magnetically suspended flywheel energy storage system, (2) identification of problems that limit performance and their corresponding solutions, (3) development of a design methodology for magnetic bearings, and (4) design of an optimal controller for future high speed applications. Both nonlinear SISO and MIMO models of the magnetic system were built to study limit cycle oscillations and power amplifier saturation phenomenon observed in experiments. The nonlinear models include the inductance of EM coils, the power amplifier saturation, and the physical limitation of the flywheel movement as discussed earlier. The control program EASY5 is used to study the nonlinear SISO and MIMO models. Our results have shown that the characteristics and frequency responses of the magnetic bearing system obtained from modeling are comparable to those obtained experimentally. Although magnetic saturation is shown in the bearings, there are good correlations between the theoretical model and experimental data. Both simulation and experiment confirm large variations of the magnetic bearing characteristics due to air gap growth. Therefore, the gap growth effect should be considered in the magnetic bearing system design. Additionally, the magnetic bearing control system will be compared to other design methods using not only parameter design but H-infinity optimal control and mu synthesis.

Pang, D.↗
DOE OSTI2022

Dependence of the boundary heat flux width on core and edge profiles in Alcator C-Mod

This work presents new evidence that the heat flux width, λ q , in the Alcator C-Mod tokamak scales with the edge electron pressure, as observed in the ASDEX Upgrade (AUG) tokamak, but the scaling with volume-averaged pressure, $\bar{p}$, from the plasma stored energy, is a better predictor of λ q in Alcator C-Mod than the edge electron pressure. These previous studies, which find that λ q decreases with increasing plasma pressure, imply that a high performance core at high pressure will lead to challenging heat and particle exhaust due to very small λ q . This concern has led to our significant enlargement of the C-Mod database with the electron density, temperature, and pressure profile data from the Thomson scattering and electron cyclotron emission diagnostics. Using the C-Mod database augmented with new profile data, we find that λ q decreases with increasing edge electron pressure as ${\lambda }_{q}\propto {p}_{\mathrm{e},95}^{-0.26}$, similar to results from AUG, and showing the strength of cross-machine comparisons. We also find that ${\lambda }_{q}\propto {p}_{\mathrm{e},\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e}}^{-0.56}$, consistent with the original finding from C-Mod that the heat flux width scales as ${\bar{p}}^{-0.48}$. The scalings of λ q with separatrix pressure and gradient scale length are found to match the AUG results qualitatively. The C-Mod scalings with edge plasma quantities have more scatter than the $\bar{p}$ scaling, and, importantly, show different trends for H-modes relative to L- and I-mode. Furthermore, investigating the source of this discrepancy presents an opportunity for further study that may improve our ability to predict the heat flux width in different confinement scenarios in the pursuit of optimizing core-edge performance in future reactors.

Alcator C-Mod↗
DOE OSTI2022

Optimization of COMPASS-U Support Structure

The global support structure for Compass Upgrade (COMPASS-U) employs many bolted and pinned components to improve the manufacturability of the whole structures. This is a departure from other designs used for highly loaded tokamaks, like Alcator C-Mod which used large forgings. Modeling of the numerous connections and interfaces was a challenge. This article will describe how to optimize the C-frame support structure with the goal to eliminate differential displacements at those interfaces and, importantly, minimize toroidal mutual displacement at the sliding joint of the toroidal field (TF) coils. The global support structure consists of 16 C-frames, and it can be simplified as a 1/8th cyclic symmetry model due to the eight vertical rods mounting that connect bottom CS and PF1-3 assemblies to the C-frames. Structure variants with different connection webs between two neighboring C-frames have been analyzed. The preloading of bolts can be split into several preload substeps to simulate the real assembly process of the COMPASS-U support structure. Additionally, the TF crown and the wedge plate can be further improved to become a solid part to better hold the TF coils.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Studies of the outer-off-midplane lower hybrid wave launch scenario for plasma start-up on the TST-2 spherical tokamak

Abstract Establishment of an efficient central solenoid (CS) free tokamak plasma start-up method may lead to an economical fusion reactor. CS-free start-up using lower hybrid (LH) waves has been studied on the TST-2 spherical tokamak. Plasma current of about a quarter of CS-driven discharges has been obtained fully non-inductively using the outer-midplane and top LH launchers. Recently, an outer-off-midplane LH launcher was developed to achieve higher plasma current by optimizing for core absorption and minimal fast electron losses. Using the (outer-)off-midplane launcher, fully non-inductive plasma current start-up up to about 8 kA was achieved. Coupled ray-tracing and Fokker–Planck simulation was performed on equilibria reconstructed with an extended MHD model. It was found that the experimentally observed plasma current was in reasonable agreement with the numerical simulation. The simulation predicted appreciable orbit losses for the off-midplane launcher driven discharge at the present parameters, which was consistent with the experimentally observed x-ray radiation characteristics. The simulation showed that the current density was saturated for the present off-midplane launcher discharges and higher density and higher LH power was necessary to achieve higher plasma current.

Physics↗
DOE OSTI2013

YAPPA: a Compiler-Based Parallelization Framework for Irregular Applications on MPSoCs

Modern embedded systems include hundreds of cores. Because of the difficulty in providing a fast, coherent memory architecture, these systems usually rely on non-coherent, non-uniform memory architectures with private memories for each core. However, programming these systems poses significant challenges. The developer must extract large amounts of parallelism, while orchestrating communication among cores to optimize application performance. These issues become even more significant with irregular applications, which present data sets difficult to partition, unpredictable memory accesses, unbalanced control flow and fine grained communication. Hand-optimizing every single aspect is hard and time-consuming, and it often does not lead to the expected performance. There is a growing gap between such complex and highly-parallel architectures and the high level languages used to describe the specification, which were designed for simpler systems and do not consider these new issues. In this paper we introduce YAPPA (Yet Another Parallel Programming Approach), a compilation framework for the automatic parallelization of irregular applications on modern MPSoCs based on LLVM. We start by considering an efficient parallel programming approach for irregular applications on distributed memory systems. We then propose a set of transformations that can reduce the development and optimization effort. The results of our initial prototype confirm the correctness of the proposed approach.

Irregular applications↗
DOE OSTI2024

Real-time High-resolution X-Ray Computed Tomography

Computed Tomography (CT) serves as a key imaging technology that relies on computationally intensive filtering and back-projection algorithms for 3D image reconstruction. While conventional high-resolution image reconstruction (> 2K3) solutions provide quick results, they typically treat reconstruction as an offline workload to be performed remotely on large-scale HPC systems. The growing demand for post-construction AI-driven analytics and the need for real-time adjustments call for high-resolution reconstruction solutions that are feasible on local computing resources, i.e. a multi-GPU server at most. In this paper, we propose a novel approach that utilizes Tensor Cores to optimize image reconstruction without sacrificing precision. We also introduce a framework designed to enable real-time execution of end-to-end distributed image reconstruction in a multi-GPU environment. Evaluations conducted on a single Nvidia A100 and H100 GPU show performance improvements of 1.91 × and 2.15 × compared to highly optimized production libraries. Furthermore, our framework, when deployed on 8-card Nvidia A100 GPU system, demonstrates the ability to reconstruct real-world datasets into 20483 volumes (32 GB) in slightly more than one minute and 40963 volumes (256 GB) in 7 minutes.

Wu, Du↗
DOE OSTI2016

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

09 BIOMASS FUELS↗
DOE OSTI2011

Coated Particle and Deep Burn Fuels Monthly Highlights December 2010

During FY 2011 the CP & DB Program will report Highlights on a monthly basis, but will no longer produce Quarterly Progress Reports. Technical details that were previously included in the quarterly reports will be included in the appropriate Milestone Reports that are submitted to FCRD Program Management. These reports will also be uploaded to the Deep Burn website. The Monthly Highlights report for November 2010, ORNL/TM-2010/323, was distributed to program participants on December 9, 2010. The final Quarterly for FY 2010, Deep Burn Program Quarterly Report for July - September 2010, ORNL/TM-2010/301, was announced to program participants and posted to the website on December 28, 2010. This report discusses the following: (1) Thermochemical Data and Model Development - (a) Thermochemical Modeling, (b) Core Design Optimization in the HTR (high temperature helium-cooled reactor) Pebble Bed Design (INL), (c) Radiation Damage and Properties; (2) TRISO (tri-structural isotropic) Development - (a) TRU (transuranic elements) Kernel Development, (b) Coating Development; (3) LWR Fully Ceramic Fuel - (a) FCM Fabrication Development, (b) FCM Irradiation Testing (ORNL); (4) Fuel Performance and Analytical Analysis - Fuel Performance Modeling (ORNL).

Snead, Lance Lewis↗
DOE OSTI2021

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

Program Models Propagation Of Failures

FIRM is software tool for identification of failure and management of risk based on directed-graph ("digraph") approach. Three core algorithms optimized for processing singletons and doubletons and also handle tripletons. FIRM identifies loops in digraphs and displays direct failure paths between any two nodes. Solves for reachability for given node without computing reachability for entire digraph. Represents hybrid between schematic-diagram and fault-tree approaches. Written in C.

Hackler, Donald B.↗
NASA NTRS2001

Efficient Translation of LTL Formulae into Buchi Automata

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

Giannakopoulou, Dimitra↗
DOE OSTI2019

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↗
DOE OSTI2019

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↗
DOE OSTI2016

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↗
DOE OSTI2023

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↗