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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

SCIDAC Center for simulation of wave particle interactions CompX participation

Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. The next step toward the development of fusion as a practical energy source is the construction of ITER, a device capable of producing and controlling the high performance plasma required for self-sustaining fusion reactions, or “burning” plasma. The input power required to drive the ITER plasma into the burning regime will be supplied primarily with a combination of external power from radio frequency waves in the ion cyclotron range of frequencies and energetic ions from neutral beam injection sources, in addition to internally generated Ohmic heating from the induced plasma current that also serves to create the magnetic equilibrium for the discharge. The ITER project is a large multi-billion dollar international project in which the US participates. The success of the ITER project depends critically on the ability to create and maintain burning plasma conditions, it is absolutely necessary to have physics-based models that can accurately simulate the RF processes that affect the dynamical evolution of the ITER discharge. The Center for Simulation of WavePlasma Interactions (CSWPI), also known as RF-SciDAC, is a multi-institutional collaboration that has conducted ongoing research aimed at developing: (1) Coupled core-to-edge simulations that will lead to an increased understanding of parasitic losses of the applied RF power in the boundary plasma between the RF antenna and the core plasma; (2) Development of models for core interactions of RF waves with energetic electrons and ions (including fusion alpha particles and fast neutral beam ions) that include a more accurate representation of the particle dynamics in the combined equilibrium and wave fields; and (3) Development of improved algorithms that will take advantage of massively parallel computing platforms at the petascale level and beyond to achieve the needed physics, resolution, and/or statistics to address these issues. CompX provides computer codes and analysis for the calculation of the electron and ion distributions in velocity-space and plasma radius which are necessary for reliable calculations of power deposition and toroidal current drive due to combined radiofrequency and neutral beam at high injected powers. It has also contributed to ray tracing modeling of injected radiofrequency powers, and to coupling between full-wave radiofrequency wave models and the distribution function calculations. In the course of this research, the Fokker-Planck distribution function calculation was made substantially more realistic by inclusion of finite-width drift-orbit effects (FOW). FOW effects were also implemented in a calculation of the phase-space diffusion resulting from radiofrequency full-wave models. Average level of funding for CompX was approximately three man-months per year.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Engineering Precisely Controlled Negative and Zero Thermal Expansion Behaviors in Metal-Organic Frameworks

Positive thermal expansion can cause significant stress or even catastrophic device failure in applications where materials are placed in confined environments. At material interfaces such as coatings, thermal expansion effects can also lead to cracking and peeling behavior. The ability to impart controlled thermal expansion properties in an array of designs via additive manufacturing technologies would mitigate such problems and bring significant value to various materials science and engineering challenges. Negative thermal expansion materials are of interest for composite material applications whereby they can compensate for the behavior of a positive thermal expansion matrix. This Truman Fellowship LDRD research project presents complimentary experimental and molecular modeling results towards the fundamental understanding and development of metal-organic framework (MOF) materials with controlled thermal expansion properties. Design strategies for imparting precisely tailored negative, zero, and positive thermal expansion regimes in MOFs are studied and the implications of these design strategies for the use of MOFs as an emergent negative thermal expansion material class are examined. Challenges towards exploiting this nanoscale behavior at length scales relevant to composite material systems are introduced. ACKNOWLEDGEMENTS I will be forever grateful to the Truman Fellowship Selection Committee for providing me with the opportunity to pursue this research project. The unique opportunity to carry out this exciting scientific research with all of the resources and support that Sandia has to offer has been a truly rewarding experience. I would like to especially thank Yolanda Moreno for her endless assistance throughout my time as a Truman Fellow. It is hard to imagine a more supportive and stimulating scientific environment to carry out this research. I would also like to thank all of my colleagues and the individuals that have collaborated with me throughout this Fellowship, both internal and external to Sandia. Many of you appear as co-authors on the publications resulting from this LDRD, including especially fruitful collaborations with researchers at the Georgia Institute of Technology and the University of Amsterdam. I cannot express enough my gratitude for the significant role that you all played in shaping my educational experience and the success during my time at Sandia as a Truman Fellow.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A Call to Arms Control: Synergies between Nonproliferation Applications of Neutrino Detectors and Large-Scale Fundamental Neutrino Physics Experiments (A Snowmass White Paper)

The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications in cooperative nonproliferation contexts. Since approximately 2010, US nonproliferation researchers, supported by the National Nuclear Security Administration (NNSA), have been studying a range of possible applications of relatively large (100 ton) to very large (hundreds of kiloton) water and scintillator neutrino detectors. In parallel, the fundamental physics community has been developing detectors at similar scales and with similar design features for a range of high-priority physics topics, primarily in fundamental neutrino physics. These topics include neutrino oscillation studies at beams and reactors, solar, and geological neutrino measurements, supernova studies, and others. Examples of ongoing synergistic work at U.S. national laboratories and universities include prototype gadolinium-doped water and water-based and opaque scintillator test-beds and demonstrators, extensive testing and industry partnerships related to large area fast position-sensitive photomultiplier tubes, and the development of concepts for a possible underground kiloton-scale water-based detector for reactor monitoring and technology demonstrations. Some opportunities for engagement between the two communities include bi-annual Applied Antineutrino Physics conferences, collaboration with U.S. National Laboratories engaging in this research, and occasional NNSA funding opportunities supporting a blend of nonproliferation and basic science R&D, directed at the U.S. academic community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Understanding Part to Part Variability During Directed Energy Deposition Processes Using In Situ and Ex Situ Process Characterization

The overall goal of this technical collaboration is the use of in situ and ex situ characterization techniques to understand part to part variability in Ti-6Al-4V parts fabricated using directed energy deposition (DED) process, and subsequently qualify parts fabricated using AM. The primary goal of the Phase-1 of this CRADA was to demonstrate the feasibility of capturing the above changes using a combination of high speed stereo imaging and in situ monitoring using two wavelength pyrometers. The in situ monitoring was then correlated using ex situ characterization performed using optical microscopy. The results from phase-1 clearly show that changes to the process and shielding gases have a significant impact on the geometric conformity of the build and the build layer height. The results from phase-1 show that in addition to using IR thermography as a tool to measure the temperature and gradients, we could use it to monitor the build topography and the layer height and use the information to develop closed loop control systems. The phase-1 results show that there is a narrow zone under which the process must operate in order to be “passively stable” or autocorrect for over building. In addition, the results demonstrate that when operated within this range the build autocorrects and there is a drastic reduction in the interlayer lack of fusion defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗
DOE OSTI2026

OC6 Project Phase IV: Validation of Numerical Models for Novel Floating Offshore Wind Support Structures

The fourth phase of the Offshore Code Comparison, Collaboration, Continued, with Correlation and unCertainty (OC6) aims to assess the ability of the tools to model a novel floating wind design. The design that was selected for this project is the TetraSpar designed by Stiesdal Offshore Technologies. The platform is a unique design that features a spar like stability with a very low center of gravity, but does not require deep-water ports. This combination is achieved with a system made of two separate steel structures, a hull at the water’s surface that supports the wind turbine tower, and a keel that is suspended below the main body. This lower keel has a very high density and drives the total platform’s low center of gravity. Scaled model tests of the TetraSpar design were performed in 2018-2019 by the University of Maine. The tests were performed with 1:43 Froude scaling. The data collected in the model tests provide a detailed description of the response of the platform in various controlled and relatively well understood conditions. Comparison with these data provides a good opportunity for validation of numerical models. The OC6 Phase IV work will focus on the specific parameters used in these scaled model tests. The load cases (LC) considered in this project are as follows: LC 1.X - Equilibrium and Static Offset Tests LC 2.X - Platform Free Decays LC 3.X - Turbine Thrust (Wind Only) LC 4.X - Regular and Irregular Waves (Wave only) LC 5.X - Combined Wind and Wave Loading

17 WIND ENERGY↗
DOE OSTI2020

Twenty Years of Collaborative Materials Exercises by the Nuclear Forensics International Technical Working Group

The Collaborative Materials Exercise (CMX) series are a critical mechanism used to advance the ITWG's mission of identifying, developing and promoting the best practices of nuclear forensics. These exercises are not designed to test laboratory performance, but as learning experiences that provide opportunities for participants to test and demonstrate state-of-the-practice to the global scientific and law enforcement communities. They are run as mock nuclear forensic investigations under realistic scenarios, with timelines and conditions designed to mimic actual operations. These situations provide the relatively unique opportunity for the appropriate governmental agencies to exercise their collective response to a nuclear security incident. Utilizing well-characterized materials of a known history and origin that are taken from specific process locations within the nuclear fuel cycle, these 'real world' materials are used to fully consider the potential significance of process-derived heterogeneities and characteristics that might be used by investigators to derive useful information such as intended use, point of loss of control, process history or origin. While individual laboratory results are kept confidential, a summary of the major outcomes of each exercise is published in the open literature. The ITWG has carried out six CMXs since 1999. The sixth (CMX-6) and largest (21 participants) was completed in June 2019. Each CMX has contributed demonstrably to advancements in the state of practice and the emergence of novel techniques in nuclear forensic science.

Schwantes, Jon M.↗
DOE OSTI2021

Effects of Hybridization on Selective Catalytic Reduction (SCR) Thermal Management of a Medium Heavy-Duty Hybrid Work Truck

The increased market penetration of hybrid electric powertrains in medium heavy-duty (MHD) applications has provided a novel platform for vehicle research. One example of such a platform is the MHD parallel hybrid truck developed by Odyne Systems, LLC. In collaboration with Odyne Systems, LLC and the Department of Energy (DOE), Oak Ridge National Laboratory (ORNL) developed a validated vehicle plant model for this truck and tested the Odyne powertrain in a hardware-in-the-loop (HIL) environment. While testing in the HIL environment, the effects of reduced engine load, and thus catalyst heating, on the selective catalytic reduction (SCR) catalyst produced diminished hybrid improvement as the level of energy storage usage increased. This article will discuss these results and the potentially unforeseen interactions with modern aftertreatment systems when hybridizing conventional powertrains.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗
DOE OSTI2020

RAMSeS: Rapid Analysis of Mission Software Systems

Over the past few decades, software has become ubiquitous as it has been integrated into nearly every aspect of society, including household appliances, consumer electronics, industrial control systems, public utilities, government operations, and military systems. Consequently, many critical national security questions can no longer be answered convincingly without understanding software, including its purpose, its capabilities, its flaws, its communication, or how it processes and stores data. As software continues to become larger, more complex, and more widespread, our ability to answer important mission questions and reason about software in a timely way is falling behind. Today, to achieve such understanding of third-party software, we rely predominantly on the ability of reverse engineering experts to manually answer each particular mission question for every software system of interest. This approach often requires heroic human effort that nevertheless fails to meet current mission needs and will never scale to meet future needs. The result is an emerging crisis: a massive and expanding gap between the national security need to answer mission questions about software and our ability to do so. Sandia National Laboratories has established the Rapid Analysis of Mission Software Systems (RAMSeS) effort, a collaborative long-term effort aimed at dramatically improving our nation’s ability to answer mission questions about third-party software by growing an ecosystem of tools that augment the human reverse engineer through automation, interoperability, and reuse. Focusing on static analysis of binary programs, we are attempting to identify reusable software analysis components that advance our ability to reason about software, to automate useful aspects of the software analysis process, and to integrate new methodologies and capabilities into a working ecosystem of tools and experts. We aim to integrate existing tools where possible, adapt tools when modest modifications will enable them to interoperate, and implement missing capability when necessary. Although we do hope to automate a growing set of analysis tasks, we will approach this goal incrementally by assisting the human in an ever-widening range of tasks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

DECOVALEX-2019 (Task G Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task G which was proposed by the Swedish Radiation Safety Authority (SSM) and coordinated by geomecon GmbH, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task G in DECOVALEX-2019 is primarily concerned with the evolution of transmissivity throughout the lifetime of a repository for radioactive waste, and in particular of spent nuclear fuel, in sparsely fractured and competent crystalline rock masses, and the representation of these processes via numerical simulation. The numerical simulations were to be evaluated for their suitability, and to be validated. Over the course of the work presented here, not only were transmissivity changes and the best approaches to simulate those change examined, but also strategies were to be developed on how to monitor transmissivity change. Guidelines on what a control program and a monitoring system for a repository should include and be able to measure, and how this can be done in practice, was a key objective of the research project.

58 GEOSCIENCES↗
DOE OSTI2024

ROADRUNNER MiniFuel Experiment: Irradiation Target Design and Sample Characterization

High-density uranium nitride (UN) is a fuel candidate for several advanced nuclear reactor designs currently under development. Because there are limited UN performance data relative to fuel fabrication impurity and density variation, an irradiation campaign has been developed as part of a collaborative effort among the University of Texas at San Antonio (UTSA), Westinghouse Electric Company, Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL) under the Nuclear Science User Facilities program. This project, entitled ROADRUNNER, or Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments, aimsto support UN fuel qualification for advanced reactors by investigating the impact of density and impurity variations on UN performance as a function of irradiation temperature and burnup. The MiniFuel experiment vehicle developed by ORNL, which leverages the High Flux Isotope Reactor, was selected to perform this accelerated separate-effects irradiation testing. The experiment test matrix consists of six MiniFuel targets containing miniature UN fuel disks, and targets three distinct burnup levels (37.5, 60, and 75 MWd/kg U) and three distinct temperatures (600, 900, and 1200°C). Neutronics and thermal analyses were performed to determine the experimental parameters needed to meet the desired irradiation conditions and to predict the experiment components temperatures. UN pellets were fabricated at LANL with tightly controlled parameters to produce specimens with three distinct densities and three levels of carbon content. The pellets were then thinned down by UTSA to the experiment-required thickness. The pre-characterization of the specimens includes density measurements, carbon and oxygen contents, microstructure analysis, and x-ray computed tomography. The selected specimens will be assembled into the MiniFuel experiment, and the first ROADRUNNER MiniFuel targets are intended for HFIR insertion during the Fall of 2024. After irradiation, the targets will be shipped to ORNL’s hot cell facility for disassembly. The post-irradiation examination on the fuel specimens includes fission gas release measurements, visual inspection, fuel swelling measurements, gamma spectroscopy, and microstructure analysis. The data collected post-irradiation will be used to develop fuel performance models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Renewal: Coherent control of spin states in organic electronics – discovery and investigation of complex room-temperature magnetic quantum excitations

In the course of four funding cycles of this project, its research focused on the exploration and understanding of spin-dependent electronic processes in organic semiconductors. It aimed to investigate the potential of harnessing the spin degree of freedom in organic materials for various applications such as spin electronics, quantum information, sensors, and as well as quantum coherent spin phenomena of charge carrier states in organic semiconductors, with the aim to develop room-temperature-based quantum applications. Specifically, the project aimed to: Apply new diagnostic tools, i.e. spin spectroscopy techniques, for paramagnetic charge carrier states in organic semiconductors, based on coherent control with pulsed electron spin resonance to understand spin relaxation and spin mixing mechanisms in organic semiconductor materials and devices such as OLEDs. Explore the nature of charge carrier spin-coupling and pathways for its manipulation to control the physical behaviors of these materials. This involves investigating spin interactions through materials structure, composition, morphological dependencies, isotopic effects, and externally applied electric and magnetic fields, with the goal to manipulate electrical and optical material properties by adjusting spin-orbit, spin-dipolar, spin-exchange, as well as spin-hyperfine interactions to open up this materials class for new applications. Study spin-dependent charge carrier transport and recombination and how these observables are governed by spin-propagation, especially coherent spin propagation as well as collective spin-effects such as the spin-Dicke effect and resonant multi-photon magnetic dipole transitions. The project utilized pulsed electrically detected magnetic resonance (pEDMR) and pulsed optically detected magnetic resonance (pODMR) techniques over a wide frequency range. These techniques enabled the observation and quantification of various spin-spin coupling types, including spin-exchange, spin-dipolar, hyperfine, and spin-orbit interactions. The project will leverage low- to mid-frequency pEDMR/pODMR facilities and collaboration with the National High Magnetic Field Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Grimsel Test Site - A Successful International Underground Research Laboratory for Many Decades - 20429

For more than 35 years, Nagra and its partners from around the world have been conducting underground research projects at the Grimsel Test Site (GTS, www.grimsel.com) to contribute to the development and confirmation of safe geological disposal concepts and for the characterization of suitable host rock formations. Over the years, the results of this internationally recognized research program have been, and continue to be, incorporated directly into exploration programs, modelling, safety, and engineering feasibility studies on options for deep geological repositories. Each project of the GTS program involves field-testing, laboratory studies, design and modelling tasks, and integrates all scientific and technical aspects. Each project phase is planned with a duration of three to five years to facilitate practical and administrative aspects and allow flexibility for updating the overall project plans with the latest findings. Scientific and engineering interaction among the different projects is ensured via an international steering committee meeting. Hosting an IAEA level C radiation- controlled zone, which allows use of radionuclides, including actinides such as thorium, uranium, neptunium, plutonium and americium, in in-situ experiments is one of the reasons why GTS also developed as a center of excellence for work with radioactive tracers under realistic in-situ boundary conditions. Last year, a new five-year program (2019 to 2023) started which includes projects with a planning horizon of decades. The new five-year program includes a new phase of in-situ experiments using radionuclides such as migration experiments in the Colloid Formation and Migration project (CFM), the Long-Term Diffusion experiment (LTD) and the newly established C-14 and I-129 Migration in cement project (CIM). The 'High Temperature effects on Bentonite' (HotBENT) project is starting in the current phase and is studying the effects of elevated temperatures (>175 deg. C) on bentonite materials. As a generic underground research laboratory (URL) it is expected that the GTS will provide in the coming years a platform for international collaboration, knowledge development and knowledge transfer for the next generation of scientists and engineers in the area of radioactive waste disposal and geosciences. A key role regarding knowledge transfer and training is provided by the well-established Grimsel Training Center (GTC), which (beside many URL related issues) also covers many general aspects of radioactive waste management. In this paper we provide an overview of the current program at the GTS, focusing on the experiments that study the migration of radionuclides through engineered barrier materials and the geosphere. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Identification of Adaptive Fungal Pathogen Resistance Loci in Switchgrass (Final Report)

Switchgrass (Panicum virgatum) has great potential as a sustainable bioenergy and bioproducts feedstock. However, there are a number of challenges that must be overcome to achieve this goal. One of the most significant challenges to switchgrass productivity are fungal pathogens, especially rusts and smuts. The primary goals of our project were to characterize the distribution of fungal pathogens on switchgrass across central North America and to identify genetic loci that control resistance to those pathogens. The research was primarily conducted with large common garden plantings of a switchgrass, distributed along a latitudinal gradient from South Texas to South Dakota. By conducting this research simultaneously at 10 field locations, we were able establish the relative contributions of genes and the environment to pathogen resistance. Through this research, we identified multiple genomic regions (loci) that contribute to rust resistance and found that the effects of these loci on resistance were highly influenced by field site location. Our research revealed that most of the rust damage to switchgrass from Texas to the northern United States is caused by a single fungal species, Puccinia novopanici. Therefore, genetic variation within this species and/or local environmental conditions are responsible for the inconsistent efficacy of pathogen resistance loci. We are currently investigating these two non-mutually exclusive hypotheses. In addition to our studies of rust pathogens, we were able to identify resistance loci for the head smut fungal pathogen Tilletia maclaganii. The funding from this grant facilitated a collaboration with the DOE Joint Genome Institute to develop a reference genome for T. maclaganii. A reference genome will make population genetic studies of this smut fungus possible, which in turn will facilitate the development of strategies to mitigate its impact. Overall, the funded research has greatly advanced our understanding of the genetic basis of fungal pathogen resistance switchgrass. This knowledge will help facilitate the breeding of more resistant cultivars and thus, increase the productivity of swichgrass generally.

09 BIOMASS FUELS↗