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DOE OSTI2023

Polarized fusion and potential in situ tests of fuel polarization survival in a tokamak plasma

Abstract The use of spin-polarized fusion fuels would provide a significant boost towards the ignition of a burning plasma. The cross section for D + T → α + n, would be increased by 1.5 if the fuels were injected with parallel polarization. Furthermore, our simulations demonstrate additional non-linear power gains in large-scale machines such as ITER, due to increased alpha heating. Such benefits require the survival of spin polarizations for periods comparable to the particle confinement time. During the 1980s, calculations predicted that polarizations could survive a plasma environment, although concerns persisted regarding the cumulative impacts of wall recycling. In that era, technical challenges prevented direct tests and left the large scale fueling of a power reactor beyond reach. Over the last decades, this situation has changed dramatically. Detailed simulations of ITER have predicted negligible wall recycling in a high-power reactor, and recent advances in laser-driven sources project the capability of producing large quantities of ∼100% polarized D and T. The remaining crucial step is an in-situ demonstration of polarization survival in a plasma. For this, we outline a measurement strategy using the isospin-mirror reaction, D + 3 He → α + p. Polarized 3 He avoids the complexities of handling tritium, while encompassing the same spin-physics. We evaluate two methods of delivering deuterium, using dynamically polarized Lithium-Deuteride (with vector polarization P V D of 70%) or frozen-spin Hydrogen-Deuteride (with P V D of 40%), together with a method of injecting optically-pumped 3 He (with 65% polarization). Pellets of these materials all have long polarization decay times (∼6 min for LiD at 2 K, ∼2 months for HD at 2 K, and ∼3 d for 3 He at 77 K), all far greater than a plasma shot in a research tokamak such as DIII-D (∼20 s). Both species can be propelled from a single cryogenic injection gun. We review plasma requirements and strategies for detecting polarization survival. Polarization alters both fusion yields and the angular distribution of fusion products, and each of these provides a potential signal. In this paper we simulate a selection of shots with similar characteristics in a future high-T ion H plasma, and find ratios of yields from shots with fuel spins parallel and antiparallel reaching 1.3 (HD + 3 He) to 1.6 (LiD + 3 He) over a wide range of poloidal angles. (A companion paper finds sensitivity to fusion product angular distributions as reflected in the pitch angles of protons and alphas reaching the plasma facing wall.)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

A Study on the Microstructures and Properties of Selective Laser Melted Babbitt Metals

Babbitt metal cubes were prepared by means of selected laser melting (SLM) process using Sn—11% Sb—6% Cu alloy powders; their microstructures were studied using optical microscope (OM), SEM, EDS, XRD and DSC; and their mechanical properties were tested using Vickers hardness and tensile methods. The results show that fully dense Babbitt metal components can be prepared by using appropriate SLM process parameters and an interlayer staggered laser scanning strategy. Anisotropy characteristics appear in both the microstructure and mechanical properties of SLM-Babbitt cubic specimens. The average hardness was in the range of 32.5 HV0.05 to 35.3 HV0.05. Both tensile strength and elongation were somewhat higher in a direction parallel to the laser scanning speed (Y axis) than in a direction perpendicular to the laser scanning speed (X axis). The strengthening mechanism is suggested to include solid solution strengthening of oversaturated Sb in the Sn matrix, as well as dispersion strengthening of finely dispersed SnSb and Cu{sub 6}Sn{sub 5} particles. The overgrown acicular Cu{sub 6}Sn{sub 5} phases at low laser scanning speeds and void formation at higher laser scanning speeds seriously deteriorate the mechanical properties of the SLM-Babbitt specimens.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Computational general relativistic force-free electrodynamics: II. Characterization of numerical diffusivity

Scientific codes are an indispensable link between theory and experiment; in (astro-)plasma physics, such numerical tools are one window into the universe’s most extreme flows of energy. The discretization of Maxwell’s equations – needed to make highly magnetized (astro)physical plasma amenable to its numerical modeling – introduces numerical diffusion. It acts as a source of dissipation independent of the system’s physical constituents. Understanding the numerical diffusion of scientific codes is the key to classifying their reliability. It gives specific limits in which the results of numerical experiments are physical. We aim at quantifying and characterizing the numerical diffusion properties of our recently developed numerical tool for the simulation of general relativistic force-free electrodynamics by calibrating and comparing it with other strategies found in the literature. Our code correctly models smooth waves of highly magnetized plasma. We evaluate the limits of general relativistic force-free electrodynamics in the context of current sheets and tearing mode instabilities. We identify that the current parallel to the magnetic field (j ∥ ), in combination with the breakdown of general relativistic force-free electrodynamics across current sheets, impairs the physical modeling of resistive instabilities. We find that at least eight numerical cells per characteristic size of interest (e.g., the wavelength in plasma waves or the transverse width of a current sheet) are needed to find consistency between resistivity of numerical and of physical origins. High-order discretization of the force-free current allows us to provide almost ideal orders of convergence for (smooth) plasma wave dynamics. The physical modeling of resistive layers requires suitable current prescriptions or a sub-grid modeling for the evolution of j ∥ .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Design of a Multi-Chemistry Battery Pack System for Behind-the-Meter Storage Applications

Battery management systems (BMS) are essential for a battery pack's safe operation and longevity. This paper presents an active balancing method-based BMS for different cell chemistry structures to be used in behind-the-meter storage (BTMS) applications. The proposed system utilizes modular isolated dual active bridge (DAB) DC/DC converters to actively balance the battery pack through a low voltage (LV) bus. A supervisory controller monitors all the cell voltage, current, and state of charge (SOC) values. Based on the estimation of the SOCs, reference currents for the DAB converters are generated by the supervisory controller. Detailed modeling and the control approach of the modular DAB converters are presented in the paper. Moreover, the control strategy of the supervisory control is also analyzed. The proposed method and structure can be extended to any combination of the number of cells to design the battery pack. Simulation results are provided for a system consisting of three cells in parallel to form a cell block and three cell blocks in series to form the battery module. Experimental results are provided for three modular DAB converters operating with a LiFeMnPO4 prismatic cell with 3.2V, 20Ah rated values.

battery management systems↗

DOE OSTI2022

WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]

WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.

Harrison-Atlas, Dylan↗

DOE OSTI2018

Causes and Consequences of Spatial Within-Host Viral Spread

The spread of viral pathogens both between and within hosts is inherently a spatial process. While the spatial aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread within infected hosts are still understudied. Here, with a focus on influenza A viruses (IAVs), we first review experimental studies that have shed light on the mechanisms and spatial dynamics of viral spread within hosts. These studies provide strong empirical evidence for highly localized IAV spread within hosts. Since mathematical and computational within-host models have been increasingly used to gain a quantitative understanding of observed viral dynamic patterns, we then review the (relatively few) computational modeling studies that have shed light on possible factors that structure the dynamics of spatial within-host IAV spread. These factors include the dispersal distance of virions, the localization of the immune response, and heterogeneity in host cell phenotypes across the respiratory tract. While informative, we find in these studies a striking absence of theoretical expectations of how spatial dynamics may impact the dynamics of viral populations. To mitigate this, we turn to the extensive ecological and evolutionary literature on range expansions to provide informed theoretical expectations. We find that factors such as the type of density dependence, the frequency of long-distance dispersal, specific life history characteristics, and the extent of spatial heterogeneity are critical factors affecting the speed of population spread and the genetic composition of spatially expanding populations. For each factor that we identified in the theoretical literature, we draw parallels to its analog in viral populations. We end by discussing current knowledge gaps related to the spatial component of within-host IAV spread and the potential for within-host spatial considerations to inform the development of disease control strategies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus

The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ antiimmune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine, tumor necrosis factor alpha (TNFα), promote pathogenesis through a parallel feed-forward circuit that promotes inflammation. These results are consistent with previous studies showing the role of over-stimulation of the inflammatory response to SARS-CoV in pathogenesis. We conclude that the critical balance between immune response and inflammation can be manipulated to improve the outcome of the infection. Further, our study provides two potential therapeutic strategies for mitigating the effects of SARS-CoV infection, and may provide insight into treatment strategies for Middle East Respiratory Syndrome Coronavirus (MERS-CoV).

network inference↗

NASA NTRS1991

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗

NASA NTRS2008

Europa Explorer Operational Scenarios Development

In 2007, NASA conducted four advanced mission concept studies for outer planets targets: Europa, Ganymede, Titan and Enceladus. The studies were conducted in close cooperation with the planetary science community. Of the four, the Europa Explorer Concept Study focused on refining mission options, science trades and implementation details for a potential flagship mission to Europa in the 2015 timeframe. A science definition team (SDT) was appointed by NASA to guide the study. A JPL-led engineering team worked closely with the science team to address 3 major focus areas: 1) credible cost estimates, 2) rationale and logical discussion of radiation risk and mitigation approaches, and 3) better definition and exploration of science operational scenario trade space. This paper will address the methods and results of the collaborative process used to develop Europa Explorer operations scenarios. Working in concert with the SDT, and in parallel with the SDT's development of a science value matrix, key mission capabilities and constraints were challenged by the science and engineering members of the team. Science goals were advanced and options were considered for observation scenarios. Data collection and return strategies were tested via simulation, and mission performance was estimated and balanced with flight and ground system resources and science priorities. The key to this successful collaboration was a concurrent development environment in which all stakeholders could rapidly assess the feasibility of strategies for their success in the full system context. Issues of science and instrument compatibility, system constraints, and mission opportunities were treated analytically and objectively leading to complementary strategies for observation and data return. Current plans are that this approach, as part of the system engineering process, will continue as the Europa Explorer Concept Study moves toward becoming a development project.

Lock, Robert E.↗

DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗

DOE OSTI2022

Developing an ELM Ecosystem Dynamics Model on GPU with OpenACC

Porting a complex scientific code, such as the E3SM land model (ELM), onto a new computing architecture is challenging. The paper presents design strategies and technical approaches to develop an ELM ecosystem dynamics model with compiler directives (OpenACC) on NVIDIA GPUs. The code has been refactored with advanced OpenACC features (such as deepcopy and routine directives) to reduce memory consumption and to increase the levels of parallelism through parallel loop reconstruction and new data structures. As a result, the optimized parallel implementation achieved more than a 140-time speedup (50 ms vs 7600 ms), compared to a naive implementation that uses OpenACC routine directive and parallelizes the code across existing loops on a single NVIDIA V100. On a fully loaded computing node with 44 CPUs and 6 GPUs, the code achieved over a 3.0-times speedup, compared to the original code on the CPU. Furthermore, the memory footprint of the optimized parallel implementation is 300 MB, which is around 15% of the 2.15 GB of memory consumed by a naive implementation. This study is the first effort to develop the ELM component on GPUs efficiently to support ultra-high-resolution land simulations at continental scales.

Schwartz, Peter↗

DOE OSTI2018

A modular synthetic approach for band-gap engineering of armchair graphene nanoribbons

Despite the great promise of armchair graphene nanoribbons (aGNRs) as high-performance semiconductors, practical band-gap engineering of aGNRs remains an unmet challenge. Given that width and edge structures are the two key factors for modulating band-gaps of aGNRs, a reliable synthetic method that allows control of both factors would be highly desirable. We report a simple modular strategy for efficient preparation of N = 6 aGNR, the narrowest member in the N = 3p (p: natural number) aGNR family, and two unsymmetrically edge-functionalized GNRs that contain benzothiadiazole and benzotriazole moieties. The trend of band-gap transitions among these GNRs parallels those in donor-acceptor alternating conjugated polymers. In addition, post-functionalization of the unsymmetrical heterocyclic edge via C-H borylation permits further band-gap tuning. Therefore, this method opens the door for convenient band-gap engineering of aGNRs through modifying the heteroarenes on the edge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

OsCAldOMT1 is a bifunctional O-methyltransferase involved in the biosynthesis of tricin-lignins in rice cell walls

Abstract Lignin is a phenylpropanoid polymer produced in the secondary cell walls of vascular plants. Although most eudicot and gymnosperm species generate lignins solely via polymerization of p -hydroxycinnamyl alcohols (monolignols), grasses additionally use a flavone, tricin, as a natural lignin monomer to generate tricin-incorporated lignin polymers in cell walls. We previously found that disruption of a rice 5-HYDROXYCONIFERALDEHYDE O -METHYLTRANSFERASE ( OsCAldOMT1 ) reduced extractable tricin-type metabolites in rice vegetative tissues. This same enzyme has also been implicated in the biosynthesis of sinapyl alcohol, a monolignol that constitutes syringyl lignin polymer units. Here, we further demonstrate through in-depth cell wall structural analyses that OsCAldOMT1 -deficient rice plants produce altered lignins largely depleted in both syringyl and tricin units. We also show that recombinant OsCAldOMT1 displayed comparable substrate specificities towards both 5-hydroxyconiferaldehyde and selgin intermediates in the monolignol and tricin biosynthetic pathways, respectively. These data establish OsCAldOMT1 as a bifunctional O -methyltransferase predominantly involved in the two parallel metabolic pathways both dedicated to the biosynthesis of tricin-lignins in rice cell walls. Given that cell wall digestibility was greatly enhanced in the OsCAldOMT1 -deficient rice plants, genetic manipulation of CAldOMT s conserved in grasses may serve as a potent strategy to improve biorefinery applications of grass biomass.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Multiphysics analysis system for heat pipe cooled micro-reactors employing PRAGMA-OpenFOAM-ANLHTP

A multiphysics analysis system for neutronics/thermo-mechanical/heat-pipe analysis of heat pipe cooled micro-reactors was developed using the PRAGMA code as the neutronics engine. PRAGMA, which used to be a GPU-based continuous-energy MC code for power reactor applications, now has an extended geometry package to handle geometries with unstructured meshes generated by the ANSYS Design-Modeler and Meshing. The NVIDIA ray tracing engine OptiX was exploited for efficient neutron transport on unstructured geometry. On the multiphysics side, the open-source CFD tool OpenFOAM and one-dimensional heat pipe analysis code ANLHTP were adopted. The manager-worker system based on the MPI dynamic process management (DPM) model enables efficient coupling of codes employing different parallelization schemes. With all the features, the multiphysics analysis of the one-sixth symmetrical MegaPower 2D core was performed and it demonstrated the benefit of the tight integration of the three-way coupling system and one-to-one geometry coupling strategy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Integrating Marine Hydrokinetic and Offshore Wind Energy: A Review of Technologies, Deployment, and Challenges

Together, offshore wind (OSW) and marine hydrokinetic (MHK) technologies have vast potential to expand the world’s access to abundant energy resource. With more than 60 GW of offshore wind energy capacity and 527 MW of ocean energy deployed globally by 2023, there is a significant amount of available resources; however, technical and non-technical challenges prevent the combined large-scale deployment of these technologies. There is still a lack of research that provides a parallel review of both MHK and OSW technologies in order to better understand their synergistic working principles. This paper aimed to address that research gap by presenting a comprehensive side-by-side review of the worldwide technological landscape, global deployment trends, integration strategies, and modeling approaches for MHK and OSW. A particular focus has been given on analyzing existing modeling and simulation techniques, assessing integration and control strategies, and comparing technologies based on water depth. Furthermore, this study provides important insights into the readiness levels of both technologies by highlighting ongoing international projects. By addressing these issues, this review will give researchers and industry stakeholders an outline for assessing the maturity of OSW and MHK systems and facilitating their transition to large-scale, sustainable deployment.

16 - TIDAL AND WAVE POWER↗

DOE OSTI2012

A modern solver framework to manage solution algorithms in the Community Earth System Model

Global Earth-system models (ESM) can now produce simulations that resolve ~50 km features and include finer-scale, interacting physical processes. In order to achieve these scale-length solutions, ESMs require smaller time steps, which limits parallel performance. Solution methods that overcome these bottlenecks can be quite intricate, and there is no single set of algorithms that perform well across the range of problems of interest. This creates significant implementation challenges, which is further compounded by complexity of ESMs. Therefore, prototyping and evaluating new algorithms in these models requires a software framework that is flexible, extensible, and easily introduced into the existing software. We describe our efforts to create a parallel solver framework that links the Trilinos library of solvers to Glimmer-CISM, a continental ice sheet model used in the Community Earth System Model (CESM). We demonstrate this framework within both current and developmental versions of Glimmer-CISM and provide strategies for its integration into the rest of the CESM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving net- works spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with promi- nent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a “Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named “Relative Selectivity" that is used to se- lect between different query processing strategies. Our experiments performed on real online news, network traffic stream and a syn- thetic social network benchmark demonstrate 10-100x speedups over selectivity agnostic approaches.

graphs, cybersecurity↗

NASA NTRS1987

Spacecraft on-board SAR processing technology

This paper provides an assessment of the on-board SAR processing technology for Eos-type missions. The proposed Eos SAR sensor and flight data system are introduced, and the SAR processing requirements are described. The SAR on-board SAR processor architecture selection is discussed, and a baseline processor architecture using a frequency-domain processor for range correlation and a modular fault-tolerant VLSI time-domain parallel array for azimuth correlation are described. The mass storage and VLSI technologies needed for implementing the proposed SAR processing are assessed. It is shown that acceptable processor power and mass characteristics should be feasible for Eos-type applications. A proposed development strategy for the on-board SAR processor is presented.

Liu, K. Y.↗