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NASA’s Electric Propulsion Development Activities for Space Nuclear Propulsion Applications

Given increased worldwide support for advanced nuclear technology for terrestrial applications, there is a renewed interest in the possibility of nuclear-reactor-powered spacecraft. NASA continues investing in the technology areas necessary to support NASA’s future scientific and exploration goals. One of those technologies areas is electric propulsion, a highly efficient means for in-space propulsion that increases fuel economy by ionizing and accelerating an onboard propellant using spacecraft electrical power. The current NASA portfolio of electric propulsion investments in support of space nuclear applications focuses on a range of future applications with total system power levels of 50 kilowatts to multimegawatt. These investments support a fast-paced incremental rate for technology development advancement to support these applications. Systems at the 50-kilowatt power level can be accomplished today with existing technology and systems at the multimegawatt level will require further technology developments over the coming decade. Propulsion systems based an array of multiple Hall thrusters have been identified the most likely technology option for the near-term applications and systems utilizing lithium-fueled magneto-plasma-dynamic thrusters have been identified as the most promising alternative technology option for the far-term applications at very high-power levels.

Electric propulsion↗
DOE OSTI2021

The Role of Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology: Proceedings of a Workshop

Quantum concepts hold the potential to enable significant advances in sensing and imaging technologies that could be vital to the study of biological systems. The workshop Quantum Science Concepts in Enhancing Sensing and Imaging Technologies: Applications for Biology, held online March 8–10, 2021, was organized to examine the research and development needs to advance biological applications of quantum technology. Hosted by the National Academies of Sciences, Engineering, and Medicine, the event brought together experts working on state-of-the-art, quantum-enabled technologies and scientists who are interested in applying these technologies to biological systems. Through talks, panels, and discussions, the workshop facilitated a better understanding of the current and future biological applications of quantum-enabled technologies in fields such as microbiology, molecular biology, cell biology, plant science, mycology, and many others. The workshop was organized around three main themes. The first, quantum in biology, examined quantum concepts that are hypothesized to be important for life processes and that researchers are working to observe through biological imaging and sensing. The second, quantum for biology, addressed ways to use quantum concepts to enhance technologies for biological imaging and sensing. The third, biology for quantum, offered a wider discussion of how the frontiers of biological imaging and sensing could enable future study using quantum concepts, tools, or technologies. Throughout the workshop, participants identified a wide range of emerging approaches and opportunities at the intersection of quantum physics and biological sensing and imaging. During the workshop, there were some differences in how each speaker defined the term quantum. During one of the panels, Prem Kumar offered thoughts on what phenomena are classical versus quantum, explaining that techniques get progressively more quantum as you move from just having superposition to having superposition with measurement and entanglement. Another explanation from Clarice Aiello delineates the definition into several levels. This includes a base level of “quantum-ness,” which reflects that all matter is made of atoms, and when these particles are isolated they behave based on quantum mechanical principles. A second level is related to quantum coherence, where a single quantum object might be found in a coherent superposition state. A final level, which she described as the quantum-entangled level, involves multiple quantum systems which are entangled among themselves. Overall, the workshop touched on concepts such as superposition, entanglement, and squeezing and their potential implications for communication, computing, and simulation, in addition to the workshop’s main focal area, biological sensing and imaging. At the opening of the workshop, Thorsten Ritz of the University of California, Irvine, identified two questions at the heart of quantum biology: Is the machinery of life quantum mechanical, and can quantum mechanics be used to study the machinery of life in new ways? Participants highlighted systems in which researchers have explored these questions, from the vast array of molecular interactions involved in biological processes such as photosynthesis, to the mechanics involved in cellular functions such as differentiation and aggregation, to the role of oscillating magnetic fields in flight orientation among birds. Sensing and imaging technologies are crucial to biological research; these technologies could both enhance the study of quantum effects and be enhanced by quantum concepts. A critical challenge in biological research is to develop imaging and sensing tools that do not damage or interfere with the often fragile and fleeting systems being studied. Attendees discussed a variety of established and emerging technologies that could enhance noninvasive biological imaging, including single- and two-photon spectroscopy, single-molecule spectroscopy, quantum illumination, ghost imaging, and cryo-electron microscopy. One example came from Marlan Scully who gave a keynote address on the first day of the workshop. Scully emphasized the use of different laser technologies, which exhibit coherence and other quantum properties, in moving toward real-world biological applications, such as the detection of SARS-CoV-2. Both tools and theory will play an important role in advancing quantum biology research and applications. Several participants suggested theorists and experimentalists should work in tandem to understand and model biological processes. While physics often reduces systems to their simplest forms for fundamental insights, participants also noted the value of observing and understanding biological systems in all their “messiness,” capturing both the inner workings of biological systems and the complex interactions that occur within and between organisms. In discussions among participants, several attendees stressed the need to match emerging tools with the right scientific questions. Rather than developing quantum technologies as “a hammer looking for a nail,” participants emphasized a focus on exploring the problems these technologies are best suited to address. For example, it is important to consider the size of the phenomenon being studied, the timescales that are important in answering the scientific question, and other relevant considerations. Every tool along the spectrum from classical to quantum involves its own set of trade-offs. For example, Ted Laurence of the Lawrence Livermore National Laboratory said that quantum measurements, such as single photon counting, fluorescence transitions, and lasers, can take longer to produce the same results as classical measurements. These quantum measurements, however, do not require calibration and can enable new research questions to be answered. Prem Kumar, Northwestern University, noted that, despite their promise, quantum approaches should not be used simply for the sake of using quantum, especially in situations where classical approaches better meet the needs of the researcher. Understanding and applying quantum concepts could enable advances in a wide range of application areas including energy, synthetic biology, medicine, and sustainability. For example, Michelle O’Malley, University of California, Santa Barbara, described how improved noninvasive imaging approaches could help capture the complex interactions and functions involved in the breakdown of organic matter by microbial communities and lead to new technologies for capturing valuable products from plant waste. Several other participants discussed needs in tracking the movement of metabolites and molecules in microbial communities for insights into nutrient cycling in environments such as soil. Margaret Ahmad, Sorbonne University, discussed potential opportunities to leverage the magnetic properties of cryptochromes to advance new treatment approaches for diseases such as COVID-19 and cancer. Looking toward the future development of the field, participants discussed challenges to advancing quantum biology that arise from disciplinary disconnects between physicists and biologists. The siloing of academic research disciplines represents a significant barrier to progress. Disconnects in terminology, motivations and priorities, and structural barriers to collaborative work underscore the need for concerted efforts to bridge these divides. Attendees and speakers offered suggestions for resolving these divergences, establishing a shared language, moving the field forward, and fostering meaningful feedback between disciplines. Overall, participants stressed a need for balance, open communication, collaboration, unity, and clear dialogue on trade-offs between quantum and classical approaches. Keiko Torii, The University of Texas at Austin, said that the best collaborations happen when the project provides mutual advantages that can show off everyone’s talents, each team finds the work interesting, and partners develop a camaraderie to pursue new knowledge. To enable near- and long-term opportunities in this space, participants suggested that exploratory, high-risk funding could improve existing instrumentation to explore quantum enhancement collaboratively. They also emphasized the need for collaboration between quantum physicists and sensing/imaging scientists, which could be advanced through a dedicated quantum biology investigator program. People, even more than technology, will be crucial to the future of quantum biology. Participants explored training, education, and workforce needs to further develop this burgeoning field and cultivate the next generation of scientists. While many programs are still in their nascent stages, participants highlighted examples of approaches and programs being developed at various types of institutions to engage students and professional scientists in quantum biology research. Several participants stressed the need for an inclusive approach, spanning disciplines as well as communities to foster a diverse field fueled by the intellectual contributions of a wide range of people, including historically under-resourced schools and students. To increase awareness and excitement about quantum physics and related areas of biology, attendees suggested capitalizing on the “buzz” around quantum. Several participants emphasized the need to start early, introducing students to quantum concepts and their appealing “weirdness” in K–12 education. Engaging students early—before they become entrenched in traditional disciplinary siloes as typically happens in graduate school—could help to galvanize interest in the area and foster a generation of scientists with the interdisciplinary mindset and skills needed to advance this interdisciplinary field. While these efforts could be advanced at many levels and across multiple sectors, several participants suggested a national quantum biology center could be a valuable hub to coordinate and support quantum biology education and workforce development across academia, industry, and government.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Evaluating Application Characteristics for GPU Portability Layer Selection

GPUs have become the dominant source of computing power for high performance computing and are increasingly being used across the High Energy Physics computing landscape for a wide variety of tasks. Though NVIDIA is currently the main provider of GPUs, AMD and Intel are rapidly increasing their market share. As a result, programming using a vendor-specific language such as CUDA can significantly reduce deployment choices. There are a number of portability layers such as Kokkos, Alpaka, SYCL, OpenMP and std::par that permit execution on a broad range of GPU and CPU architectures, significantly increasing the flexibility of application programmers. However, each of these portability layers has its own characteristics, performing better at some tasks and worse at others, or placing limitations on aspects of the application. In this presentation, we report on a study of application and kernel characteristics that can influence the choice of a portability layer and show how each layer handles these characteristics. We have analyzed representative heterogeneous applications from CMS (patatrack and p2r), DUNE (Wire-Cell Toolkit), and ATLAS (FastCaloSim) to identify key application characteristics that have different behaviors for the various portability technologies. Using these results, developers can make more informed decisions on which GPU portability technology is best suited to their application.

Atif, Mohammad [Brookhaven]↗
DOE OSTI2024

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗
DOE OSTI2023

A Fine-grained Asynchronous Bulk Synchronous parallelism model for PGAS applications

The Partitioned Global Address Space (PGAS) model is well suited for executing irregular applications on cluster-based systems, due to its efficient support for short, one-sided messages. Separately, the actor model has been gaining popularity as a productive asynchronous message-passing approach for distributed objects in enterprise and cloud computing platforms, typically implemented in languages such as Erlang, Scala or Rust. To the best of our knowledge, there has been no past work on using the actor model to deliver both productivity and scalability to irregular PGAS applications with large number of small messages. In this paper, we introduce a new programming system for PGAS applications, in which point-to-point remote operations can be expressed as fine-grained asynchronous actor messages. In our approach, the programmer does not need to worry about programming complexities related to message aggregation and termination detection. Our approach can be viewed as extending the classical Bulk Synchronous Parallelism model with fine-grained asynchronous communications within a phase or superstep. Here, we believe that our approach offers a desirable point in the productivity-performance space for PGAS applications, with more scalable performance and higher productivity relative to past approaches. Specifically, for seven irregular mini-applications from the Bale Kernels and three graph kernels executed using 2048 cores in the NERSC Cori system, our approach shows geometric mean performance improvements of ≥ 20X relative to standard PGAS versions (UPC and OpenSHMEM) while maintaining comparable productivity to those versions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Medium grain niobium SRF cavity production technology for science frontiers and accelerator applications

Herein we present the cost-effective production of superconducting radio frequency (SRF) cavities made of medium grain (MG) niobium (Nb) discs directly sliced from forged and annealed billet. This production method provides clean surface conditions and reliable mechanical characteristics with sub-millimeter average grain size resulting in stable SRF cavity production. We propose to apply this material to particle accelerator in the science and industrial applications. The science applications require high field gradients(≥ 30 MV/m) particularly in pulsed mode. The industrial applications require high $Q_0$ values with moderate gradients (~ 20 MV/m) in CW mode operation. This paper describes the MG Nb disc production recently demonstrated and discusses future prospects for application in advanced particle accelerators in the science and industrial applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Graphitic Carbon Nitride Quantum Dots (g‐C 3 N 4 QDs): From Chemistry to Applications

Since their emergence in 2014, graphitic carbon nitride quantum dots (g-C 3 N 4 QDs) have attracted much interest from the scientific community due to their distinctive physicochemical features, including structural, morphological, electrochemical, and optoelectronic properties. Owing to their desirable characteristics, such as non-zero band gap, ability to be chemically functionalized or doped, possessing tunable properties, outstanding dispersibility in different media, and biocompatibility, g-C 3 N 4 QDs have shown promise for photocatalysis, energy devices, sensing, bioimaging, solar cells, optoelectronics, among other applications. As these fields are rapidly evolving, it is very strenuous to pinpoint the emerging challenges of the g-C 3 N 4 QDs development and application during the last decade, mainly due to the lack of critical reviews of the innovations in the g-C 3 N 4 QDs synthesis pathways and domains of application. Herein, an extensive survey is conducted on the g-C 3 N 4 QDs synthesis, characterization, and applications. Scenarios for the future development of g-C 3 N 4 QDs and their potential applications are highlighted and discussed in detail. In conclusion, the provided critical section suggests a myriad of opportunities for g-C 3 N 4 QDs, especially for their synthesis and functionalization, where a combination of eco-friendly/single step synthesis and chemical modification may be used to prepare g-C 3 N 4 QDs with, for example, enhanced photoluminescence and production yields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An overview of visualization and visual analytics applications in water resources management

Recent advances in information, communication, and environmental monitoring technologies have increased the availability, spatiotemporal resolution, and quality of water-related data, thereby leading to the emergence of many innovative big data applications. Among these applications, visualization and visual analytics, also known as the visual computing techniques, empower the synergy of computational methods (e.g., machine learning and statistical models) with human reasoning to improve the understanding and solution toward complex science and engineering problems. These approaches are frequently integrated with geographic information systems and cyberinfrastructure to provide new opportunities and methods for enhancing water resources management. Here, we present a comprehensive review of recent hydroinformatics applications that employ visual computing techniques to (1) support complex data-driven research problems, and (2) support the communication and decision-makings in the water resources management sector. Then, we conduct a technical review of the state-of-the-art web-based visualization technologies and libraries to share our experiences on developing shareable, adaptive, and interactive visualizations and visual interfaces for water resources management applications. We close with a vision that applies the emerging visual computing technologies and paradigms to develop the next generation of hydroinformatics applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Nanoengineering of 2D MBenes for energy storage applications: A review

2D transition metal borides (MBenes), a flourishing member of the 2D nanomaterial family, show great potential in a number of study areas. MBenes have received increasing attention thanks to their excellent electrical conductivity, structural and mechanical properties, and chemical stability, which have captivated researchers and sparked further exploration. Extensive theoretical and experimental investigations have unveiled its remarkable potential as electrode materials for electrochemical storage applications, making MBenes a subject of great interest. Despite the growing interest and numerous studies conducted, there is a lack of a comprehensive and systematic appraisal of MBenes' applications in electrochemical energy storage systems. Here, in light of this, firstly, we provide an overview of the current progress in the fabrication and characterization of MAB phases and MBenes. For the synthesis of MBenes, the following fabrication techniques were discussed; liquid-phase exfoliation, solid-state mechanical exfoliation, chemical vapor deposition, high-pressure chemical vapor deposition, microwave-assisted chemical etching, and ultrasound-assisted chemical etching methods. Then, we delve into the captivating potential of MBenes, specifically in the realm of energy storage applications and their role in enhancing electrochemical storage capabilities. The discussion encompasses their application in lithium-ion, lithium-sulfur, and lithium-selenide batteries, supercapacitors and other energy storage systems, providing a comprehensive perspective on their contributions to the energy landscape. Finally, a brief but significant summary of the challenges and opportunities of MBenes in practical applications was summarized. The present review provides a guide and scientific motivation for creating and developing advanced MBene-based nanomaterials, addressing the growing demand for cutting-edge energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Study of interconnect errors, network congestion, and applications characteristics for throttle prediction on a large scale HPC system

Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Codes and standards for ceramic composite core materials for High Temperature Reactor applications

Fiber-reinforced ceramic matrix composites are attractive for high-temperature nuclear applications due to excellent thermal and mechanical properties as well as reasonable-to-outstanding radiation resistance. Over the past 20 years, the use of ceramic matrix composite applications expanded to many commercial non-nuclear industries as fabrication and application of the technologies mature. The ASME Boiler Pressure Vessel Code, under Section III Division 5, provides the design and construction rules for High Temperature Reactor components. It published the first rules for ceramic matrix composites to be used for reactor core components. The rules lay out the quality requirements together with the design and materials criteria for the use and application of silicon carbide- and carbon-based matrix material technologies. As with the established graphite rules, the ceramic composite material rules are structured in Subsection HH (from Section III), that addresses the criteria for class SN nonmetallic core components. The code rules rely heavily on the development and publication of standards for composite specification, classification, and testing of mechanical, thermal, and other properties. These test methods are developed in ASTM Committee C28 on Advanced Ceramics, with a current focus on ceramic composite tubes. This article describes the detail of the composites code, the design methodology and similarities to the graphite code, the guidance for the development of specifications for ceramic composites (for nuclear applications) including recent standard developments, and it mentions the next steps to support licensing aspects by validating the code with benchmarking data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Impact of recent ENDF nuclear data update, high initial enrichment and high burnup fuel on critical experiments applicability determination via the integral index c k for burnup credit validation

In 2012, NUREG/CR-7109 reported on the validation of burnup credit calculations involving major and minor actinides and major fission products which was investigated for pressurized and boiling water reactor (PWR and BWR) fuel enrichments up to 5 wt% 235 U and assembly-average burnups up to 60 GWd/MTU. Recently, there has been interest in increasing the maximum enrichment used in PWR fuel as high as 8 wt% 235 U and correspondingly increasing the maximum assembly-average burnups to approximately 75 GWd/MTU. These proposed increases in enrichment and burnup necessitate reinvestigation of the validation basis for k eff calculations for this expanded application space. Additionally, the 2012 study was performed by using the Evaluated Nuclear Data File (ENDF)/B-VII.0 nuclear data with the SCALE 6 covariance library, and the effects of using the newly released ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data and covariance libraries should be evaluated. In this work, published in NUREG/CR-7309 in 2025, the validation assessment was performed consistently with NUREG/CR-7109: modeling irradiated fuel assemblies in the Generic Burnup Credit (GBC)-32 cask defined in NUREG/CR-6747. The TSUNAMI-3D sequence was used to generate sensitivity data for the application model, and the data were compared with sensitivity data from select benchmark models. The integral parameter c k is the metric of similarity used in this study and is consistent with NUREG/CR-7109, where a c k value in excess of 0.8 indicates sufficient similarity for use in validation. A new set of benchmark experiments with sensitivity data has been assembled for this effort. The number of experiments with available sensitivity data is now 2,104, compared to 474 in NUREG/CR-7109. This increase was facilitated by the efforts of the Nuclear Energy Agency to generate sensitivity data for a majority of the experiments in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook to supplement the data available in the Oak Ridge National Laboratory (ORNL) Verified, Archived Library of Inputs and Data (VALID). The complete set of benchmarks considered here includes experiments for low-enriched uranium (LEU), intermediate enriched uranium (IEU), and a mixture of uranium and plutonium (MIX) from the ICSBEP Handbook and VALID, as well as ORNL models of the Haut Taux de Combustion (HTC) experiments and other potentially relevant models not included in VALID. The updated similarity study shows that none of the extended burnup and higher enrichment combinations considered show a significant decrease in the number of potentially applicable experiments, meaning sufficient critical experiments exist for the validation of BUC criticality safety calculations, with initial enrichments up to 8 wt% 235 U and burnups up to 80 GWd/MTU. Additionally, both the ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries can be used for validation since the number of critical experiments applicable for validation increases for most cases with the most recent nuclear data compared to the previous one. As in previous BUC validation studies, the French HTC experiments are the most similar in a majority of the application cases studied, especially from representative discharge burnups ranging from 40 to 80 GWd/MTU. In conclusion, these results match the conclusions presented in NUREG/CR-7109 regarding validation of the primary actinides in BUC analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Cooperative lane control application for fully connected and automated vehicles at multilane freeways

Advances in communications technology have made the development of connected and automated vehicle (CAV) applications that may potentially replace traditional, gantry operated lane control signals (LCSs) possible. Here, we develop the concept of a prototype CAV-enabled LCS application and provides a preliminary assessment of the potential improvement it offers over traditional LCS. Real-world data obtained from an LCS on I-66 in Northern Virginia was used to calibrate and validate a baseline simulation model. Further, the current lane control scenarios utilized in the Northern Virginia LCS were identified and relevant data resulting from implementation of those scenarios were collected to model the LCS in a simulation environment. The performance of real-world LCS was then compared to a prototype CAV-enabled LCS application developed in this research. The CAV-enabled LCS application consistently outperformed the traditional LCS with increased throughput and speeds. On average, an increase of 18.4%, 9.6% and 12.8% in throughput was observed for three selected scenarios under the best case of a 1 sec headway. Furthermore, the CAV-enabled LCS application was also found to reduce volatility, represented by variation in acceleration and deceleration regimes, by an average of 25.6% and 49.6%. The reduction in turbulence in the traffic stream may indicate potential improved safety with the CAV system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Covalent Triazine Framework-Derived Membranes: Engineered Sol–Gel Construction and Gas Separation Application

Covalent triazine frameworks (CTFs) represent one of the most extensively studied organic networks characterized by graphitic π-conjugated structures linked by aza-fused rings, possessing unique features such as compositions of light elements (e.g., C, H, and N), porous architectures abundant heteroatom involvement, and extensively conjugated structures. In addition, the textural and chemical structures of CTFs could be engineered via synthesis control to accommodate diverse applications. CTF materials with notable characteristics, including plentiful (ultra-)micropores, high surface areas, and the presence of CO 2 -philic functional groups involving nitrogen (N), oxygen (O), and fluorine (F), hold great promise as potential candidates for anthropogenic CO 2 capture and sequestration (CCS) applications. However, the conventional high-temperature involved ionothermal procedures and the solution-based coupling pathway only afforded CTF materials in powder form, which is difficult to be processed toward membrane formation. Successful fabrication of CTF-derived membranes will rely on the development of alternative polymerization approaches as well as structural engineering to afford membrane architectures with controllable porosity distribution and active interaction sites with CO 2 benefiting the CO 2 separation procedure. In this Account, a demonstration of the latest progress in the development of CTF-derived membranes was provided. The CTF membranes were mainly synthesized via a superacid (e.g., CF 3 SO 3 H)-promoted sol–gel approach involving the polymerization of aromatic nitrile monomers. The formation of the triazine unit through the trimerization of cyano groups served as the cross-linkers, resulting in the creation of π-conjugated networks alongside the arenes present in the starting materials. The aromatic nitrile monomers with rigid and sterically hindered structures were required to afford CTF membranes with nanoporous architectures. The acidity of the superacid and reactivity of the aromatic monomers played critical roles in the polymerization efficiency. The monomer diversity and synthesis tunability endowed the introduction of CO 2 -philic functionalities (e.g., pyrazole and fluorine) within the CTF skeletons, and integration of ionic moieties was achieved by adopting FSO 3 H with stronger acidity as the catalyst and aromatic nitrile monomers with pyrazine structures. To ensure the successful construction of fluorinated CTF membranes, it is important to avoid any fluorines on the ortho-position of the cyano groups on the benzene ring. Through control over the monomers and reaction conditions, flexible, transparent, and insoluble CTF membranes could be fabricated. The sol–gel method could be further expanded to membrane fabrication through acetyl-to-benzene transformation through synthesis control. The mild oxidation-exfoliation-filtration method was also demonstrated to fabricate substrate-supported CTF membranes. The as-afforded membranes are well characterized to determine the structural features and provide information to study the structure-performance relationship. Here, the application of CTF membranes in CO 2 separation was summarized, focusing on the approaches being developed to enhance CO 2 uptake and separation performance. In addition to utilizing the pristine CTF membranes for gas separation, functionalized carbon molecular sieve membranes could be obtained from the pyrolysis of thermally stable CTF membrane precursors toward efficient CO 2 separation, benefiting from the abundant ultramicropores being created during the pyrolysis/decomposition procedure and involvement of CO 2 -philic functionalities such as fluorine and nitrogen-containing moieties. Based on these achievements, unsolved issues in CTF membrane-related fabrication and applications, including the potential solution approaches, have been proposed to advance the application of CTF membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Critical Review of Heat Pipe Experiments in Nuclear Energy Applications

This critical review provides heat pipe (HP) experimental data sets that contain pertinent information regarding nuclear technology that may be beneficial to researchers. Heat pipes have been shown to have a tremendously positive impact on nuclear technologies and will continue to become a more prevalent technology as more nuclear reactor concepts embrace this robust technology. Most previous reviews may focus on only a specific HP design or application, and some are backdated. Herein, this critical review extends previous efforts; integrates and summarizes previously reported HP experimental efforts; and provides updates with recently reported results in the literature for HPs in all nuclear-related applications, including space power (thermal radiators, core cooling, and electricity production), microreactors (emergency core cooling, hybrid control rods, and reactor core cooling), and HP involvement in other nuclear-related technologies (spent fuel pool cooling). The two main objectives of this critical review are (1) to facilitate the development of HP codes by outlining some of the existing experimental data sets to validate their codes and directing developers to these efforts and (2) to provide comprehensive information regarding the vast applicability of HPs used in the nuclear industry, including the theory of operation and limitations to supplement researchers in the development of new ideas for potential applications in nuclear-related technologies. The review clearly shows extensive and diverse experimental data sets for HPs developed under diverse testing conditions depending on the available nuclear application for validation purposes. Thus, this critical review is oriented to providing attention to the existing efforts rather than determining gaps in HP research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗