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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 1,135 records · Page 63

High-Fidelity CFD Modeling of Cryogenic Hydrogen Isotope Extrusion for Fusion Reactor Pellet Fueling

This study investigates the extrusion processes of deuterium and protium using ANSYS-Polyflow. The geometries and computational fluid dynamics (CFD) settings closely replicate the experimental setups and data acquired from the extruder experiments at Oak Ridge National Laboratory (ORNL) for validation purposes. We explore the impacts of (1) slip versus non-slip boundary conditions and (2) the use of constant, temperature-, and shear rate–dependent viscosities, concluding that the implementation of non-slip wall boundary conditions combined with shear rate–dependent viscosity produced more accurate predictions. The simulations achieved excellent agreement with the experimental data, with relative differences of only 5% for deuterium, and 3% to 6% for protium. This is the first time that experimental extrusion data at ORNL have been accurately predicted through high-fidelity CFD modeling. In conclusion, the advancements offer valuable insights and a foundational modeling tool for optimizing pellet injectors for ITER and other future reactor-scale devices.

ANSYS-Polyflow↗

J-TEXT achievements in turbulence and transport in support of future device/reactor

Following the reconstruction of the TEXT tokamak at Huazhong University of Science and Technology in China, renamed as J-TEXT, a plethora of experimental and theoretical investigations has been conducted to elucidate the intricacies of turbulent transport within the tokamak configuration. These endeavors encompass not only the J-TEXT device's experimental advancements but also delve into critical issues pertinent to the optimization of future fusion devices and reactors. Here, the research includes topics on the suppression of turbulence, flow drive and damping, density limit, non-local transport, intrinsic toroidal flow, turbulence and flow with magnetic islands, turbulent transport in the stochastic layer, and turbulence and zonal flow with energetic particles or helium ash. Several important achievements have been made in the last few years, which will be further elaborated upon in this comprehensive review.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Solving disorder in (3D) real space: a comparative study of the three-dimensional difference pair distribution function and atomic resolution holography reconstructions

The quantitative analysis of local ordering principles in disordered crystalline systems has gained much attention over the past few years, as it is often considered crucial for optimizing material functionality. This development has been driven by significant advancements in computational and experimental methods, which have led to the establishment and widespread use of various analytical techniques. In this study, we perform model calculations to compare the effectiveness of atomic resolution holography and three-dimensional difference pair distribution function analysis (3D-ΔPDF). Using Cu 3 Au as a model system, we demonstrate an approach to derive local order parameters quantitatively and show that both techniques are well suited to quantifying chemical short-range order correlations and local bond-distance variations. By evaluating the strengths and limitations of both techniques, we advocate for their combined use to solve complex short-range order problems accurately.

3D-ΔPDF↗

Real-Time Simulation of Modular Multilevel Converters

Modular multilevel converters (MMCs) are one of the most popular configurations of voltage-source converters (VSCs) used in applications like high-voltage direct current (HVdc) transmission systems and flexible alternate current transmission systems (FACTS). They have a large number of modules with thousands of capacitors and semiconductor devices, which make it hard to simulate in real-time. In this paper, a low-cost high-performance computing (HPC) configuration to simulate MMCs in real-time is proposed. The configuration uses a HPC digital signal processor (DSP) with 8 cores. An advanced MMC simulation algorithm is implemented using HPC techniques to optimize the real-time performance in the DSP. A comparison is performed with existing solutions to show the superiority of the proposed configuration and algorithms.

Debnath, Suman↗

WE-AB-BRA-07: Operating Room Quality Assurance (ORQA) for Spine Surgery Using Known-Component 3D-2D Image Registration

Purpose: Intraoperative x-ray radiography/fluoroscopy is commonly used to qualitatively assess delivery of surgical devices (e.g., spine pedicle screws) but can fail to reliably detect suboptimal placement (e.g., breach of adjacent critical structures). We present a method wherein prior knowledge of the patient and surgical components is leveraged to match preoperative CT and intraoperative radiographs for quantitative assessment of 3D pose. The method presents a new means of operating room quantitative quality assurance (ORQA) that could improve quality and safety, and reduce the frequency of revision surgeries. Methods: The algorithm (known-component registration, KC-Reg) uses patient-specific preoperative CT and parametrically defined surgical component models within a robust 3D-2D registration method to iteratively optimize gradient similarity using the covariance matrix adaptation evolution strategy. Advances from previous work address key challenges to clinical translation: i) absolving the need for offline geometric calibration of the C-arm; and ii) solving multiple component bodies simultaneously, thereby allowing QA in a single step (e.g., spinal construct with 4–20 screws), rather than sequential QA of each component. Performance was tested in a spine phantom with 10 pedicle screws, and first results from clinical studies are reported. Results: Phantom experiments demonstrated median target registration error (TRE) of (1.0±0.3) mm at the screw tip and (0.7°±0.4°) in angulation. The simultaneous multi-body registration approach improved TRE from the previous (sequential) method by 42%, reduced outliers, and fits into the natural workflow. Initial application of KC-Reg in clinical data shows TRE of (2.5±4.5) mm and (4.7°±0.5°). Conclusion: The KC-Reg algorithm offers a potentially valuable method for quantitative QA of the surgical product, using radiographic systems that are already within the surgical arsenal. For spine surgery, the method offers a near-real-time independent check on the quality of surgical product, facilitating immediate revision if necessary and potentially avoiding postoperative morbidity and/or revision surgery. Gerhard Kleinszig and Sebastian Vogt are employees of Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]

Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.

Sahu, Abhijeet↗

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗

Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

A Digital Twin built around Activated Sludge Model No. 1 was deployed at a full-scale water resource recovery facility. Its design included a waste rate recommender system based on automatic scenario analyses, where influent loads and waste rates are varied to determine their impact on nitrification. At the same frequency as these scenario analyses, scheduled auto-calibrations allow for nitrifier maximum specific growth rate (μmax-NITO) soft sensing, the only kinetic parameter shown to require adjustment if the objective is aeration tank effluent ammonia forecasting accuracy. By integrating temperature forecasting over the next three sludge ages, this Digital Twin approach creates opportunities for advancing waste rate decisions in anticipation of seasonal temperature changes, optimizing ammonia control authority under varying influent loads, and furnishing valuable insights for future capital projects requiring nitrifier kinetic understanding and modelling.

54 ENVIRONMENTAL SCIENCES↗

Final Report

The purpose of this project was to develop tools and techniques to improve the ability of computational scientists to investigate and correct problems (bugs) in their programs. Specifically, the University of Maryland component of this project focused on the problems associated with the finite number of bits available in a computer to represent numeric values. In large scale scientific computation, numbers are frequently added to and multiplied with each other billions of times. Thus even small errors due to the representation of numbers can accumulate into big errors. However, using too many bits to represent a number results in additional computation, memory, and energy costs. Thus it is critical to find the right size for numbers. This project focused on several aspects of this general problem. First, we developed a tool to look for cancelations, the catastrophic loss of precision in numbers due to the addition of two numbers whose actual values are close to each other, but whose representation in a computer is identical or nearly so. Second, we developed a suite of tools to allow programmers to identify exactly how much precision is required for each operation in their program. This tool allows programmers to both verify that enough precision is available, but more importantly find cases where extra precision could be eliminated to allow the program to use less memory, computer time, or energy. These tools use advanced binary modification techniques to allow the analysis of actual optimized code. The system, called Craft, has been applied to a number of benchmarks and real applications.

97 MATHEMATICS AND COMPUTING↗

Abstract - Cooperative Research and Development Agreement between Penn State University and National Energy Technology Laboratory

This project will use bipolar membranes to produce efficient vapor-phase electrolysis cells for splitting CO 2 to CO and oxygen. CO is a valuable chemical feedstock that can be combined catalytically with hydrogen in the Fischer-Tropsch process to make liquid fuels. CO is arguably the best target for CO 2 reduction since, as a gaseous product, it is easily collected and is relatively immune to membrane crossover losses. The keys to success in this project are to design and synthesize hydrophilic, low resistance bipolar membranes and to create optimized electrode/catalyst/ electrolyte architectures based on these new membranes and advanced catalysts in order to achieve high current density at low overpotentials for CO 2 conversion. High current density is key to achieving industrially-relevant throughput for the process and low overpotentials maintain high overall efficiency for the process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence

Scientific Machine Learning (SciML) and Artificial Intelligence (AI) will have broad use and transformative effects across the Department of Energy. Accordingly, the January 2018 Basic Research Needs workshop identified six Priority Research Directions (PRDs). The first three PRDs describe foundational research themes that correspond to the need for domain-awareness (PRD #1), interpretability (PRD #2), and robustness (PRD #3). The other three PRDs describe capability research themes and correspond to the three major use cases for massive scientific data analysis (PRD #4), machine learning-enhanced modeling and simulation (PRD #5), and intelligent automation and decision-support for complex systems (PRD #6). The Priority Research Directions provide a sound basis for a coherent, long-term research and development strategy in SciML and AI. Over the last decade, DOE investments in applied mathematics have laid the groundwork for the type of basic research that will underpin key advances in the six PRDs. Such advances will build on the work from leading researchers in optimization, linear algebra, high-performance solvers and algorithms, multiscale modeling and simulation, complex systems research, uncertainty quantification, and the new basic research areas that will emerge from the pursuit of transformative technologies.

97 MATHEMATICS AND COMPUTING↗

Brochure on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence [Slides]

Scientific Machine Learning (SciML) and Artificial Intelligence (AI) will have broad use and transformative effects across the Department of Energy. Accordingly, the January 2018 Basic Research Needs workshop identified six Priority Research Directions (PRDs). The first three PRDs describe foundational research themes that correspond to the need for domain-awareness (PRD #1), interpretability (PRD #2), and robustness (PRD #3). The other three PRDs describe capability research themes and correspond to the three major use cases for massive scientific data analysis (PRD #4), machine learning-enhanced modeling and simulation (PRD #5), and intelligent automation and decision-support for complex systems (PRD #6). The Priority Research Directions provide a sound basis for a coherent, long-term research and development strategy in SciML and AI. Over the last decade, DOE investments in applied mathematics have laid the groundwork for the type of basic research that will underpin key advances in the six PRDs. Such advances will build on the work from leading researchers in optimization, linear algebra, high-performance solvers and algorithms, multiscale modeling and simulation, complex systems research, uncertainty quantification, and the new basic research areas that will emerge from the pursuit of transformative technologies.

97 MATHEMATICS AND COMPUTING↗

Handbook on the Material Properties of Yttrium Hydride for High Temperature Moderator Applications

Yttrium hydride is an optimal choice for a high-temperature moderator material in advanced thermal neutron spectrum reactors that require small core volumes. A complete database of the thermomechanical properties of yttrium hydride is not yet available, although it is much needed to understand and predict the moderator performance during service in reactors. This milestone report presents the properties of unirradiated bulk yttrium hydride as a function of hydrogen concentration—including density, crystal structure, specific heat capacity, thermal diffusivity, thermal conductivity, hardness, elastic/shear moduli, Poisson’s ratio, fracture strength, microstructure, and thermal stability. This information provides a baseline measurement for the subsequent neutron irradiation response study of yttrium hydride. The recommended empirical treatment of the data is suggested. In addition, other properties (i.e., hydrogen retention, thermal hydrogen migration, and irradiation response) requiring investigation are discussed. Also included are the Preliminary post-irradiation examination (PIE) data of yttrium hydride irradiated at 600 and 900°C to 0.1 dpa in the High Flux Isotope Reactor (HFIR). The thermophysical properties have insignificant change following this low dpa irradiation for both irradiation temperatures.

36 MATERIALS SCIENCE↗

Hydrothermal Liquefaction: Path to Sustainable Aviation Fuel

A variety of technologies are currently under development for producing sustainable aviation fuel (SAF), and one of the most promising technologies is the hydrothermal liquefaction (HTL) of low-cost waste feedstocks. Organizations across the globe are conducting research and development on HTL technology at scales varying from the laboratory to demonstrations focused on various aspects of technology development. The identification of more advanced and sustainable solutions to maximize the fuel yield while optimizing fuel properties and achieving cost parity with conventional fuels is the major focus in developing HTL technology. This workshop on the application of HTL to produce SAF, coordinated by the U.S. Department of Energy Bioenergy Technologies Office, Commercial Aviation Alternative Fuels Initiative, and Pacific Northwest National Laboratory (PNNL), was held virtually on November 17–19, 2020. A broad spectrum of experts from industry, academia, national laboratories, and government from across the globe participated in the workshop, contributing their ideas, insights, and perspectives. A series of keynote presentations, plenary presentations, and breakout sessions provided an interdisciplinary framework for sharing information and building collaboration. This document provides an overview of the content discussed in the presentations as well as the breakout session discussion. Diverse stakeholder perspectives were gathered, and this wealth of information collectively provides an update on the current state of the field and identifies the key research opportunities.

09 BIOMASS FUELS↗

PRO-X Parallelization Study

The proliferation resistance optimization (PRO-X) program is actively supporting the design of nuclear systems by developing a framework to both optimize the fuel cycle infrastructure for nuclear reactor (including both advanced reactors (ARs) and research reactors (RRs)) and minimize the potential for production of weapons-usable nuclear material (Figure 1). One area of interest is in the impact a modular approach to bulk handling fuel cycle facilities could have on meeting safeguards requirements to identify future areas of growth within the proliferation resistance space. This study evaluates how changing the number of streams within a fuel cycle facility could impact a facilities ability to meet both domestic and international safeguards requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Delivery of LiH Shell for DANCE

Material for a new LiH shell for neutron shielding has been obtained for the Detector for Advanced Neutron Capture Experiments. This is a critical component for optimizing sensitivity of neutron capture experiments performed in support of Office of Experimental Sciences mission, particularly in the case of small, rare samples.

42 ENGINEERING↗

Community-Centric Microgrid Feasibility Analysis Framework to Accelerate Resilience of Island Communities

Marine energy offers a reliable energy solution for island and coastal communities, which often lack traditional local generation, to support their transition to energy independence and reduce reliance on externally imported fuels. Successful deployment of new technologies in these isolated locations requires community acceptance and approval from the outset, as these communities typically lack the financial and technical resources to operate and maintain new systems. This report presents a community-centric microgrid planning framework for remote coastal and island communities. Community engagement is integrated as the first step in the planning process, incorporating community profiles and visions into energy development scenarios. A case study was conducted in St. George, Pribilof Islands, Alaska, which relies entirely on diesel yet has significant wind and wave energy potential. Community engagement revealed a unique history and current economic status, with an interest in adopting advanced energy technologies despite past failures. Various microgrid configurations were optimized, considering different technologies to meet current and future energy needs while balancing cost and energy resilience. Wave energy converters (WECs) were a key component, integrated with other energy sources using the Xendee optimization tool. The Marine Energy Microgrid Toolkit, developed as part of this work, uses commercial power system analysis tools to optimize and analyze microgrid scenarios. The developed framework and toolkit can be applied to island and coastal communities to enhance resilience and support microgrid deployments. Future enhancements will include incorporating new marine resources, developing dynamic models, and automating the integration of Xendee and PowerFactory simulations.

02 PETROLEUM↗

Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems

To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗