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DOE OSTI2019

The Potential Role of Concentrating Solar Power within the Context of DOE's 2030 Solar Cost Targets

For solar electricity generating technologies to be cost competitive at a large scale with conventionally generated electricity, cost reductions are needed for both concentrating solar power (CSP) and solar photovoltaic (PV) systems. In 2011, the U.S. Department of Energy (DOE) established solar cost targets that corresponded to reducing CSP and PV prices by approximately 75% in order to achieve a levelized cost of electricity (LCOE) of $0.06 per kilowatt-hour (kWh) for both utility-scale PV and high-capacity factor CSP-TES systems in 2020. Utility-scale PV achieved its 2020 cost target in 2017, and recent estimates for the LCOE of CSP-TES with a molten-salt power tower system are approximately $0.10/kWh for projects that are expected to come online in 2020, which represents a substantial reduction since 2010 - when the LCOE for CSP-TES was around $0.21/kWh. To continue the momentum for cost reductions in solar technologies, DOE recently established cost targets for 2030 that would make solar one of the lowest-cost sources of new electricity in the United States. For CSP-based systems, the new targets correspond to an LCOE in 2030 of $0.05/kWh for a dispatchable, high-capacity factor CSP-TES plant configuration. This aggressive target would have been unimaginable a decade ago. However, building on the previously described reduction in CSP-TES costs over the past decade, recent announcements suggest the next phase of projects will continue this downward trend through lower installation costs, attractive financing, longer-duration PPAs, and the ability to capitalize on the value that the flexibility of storage brings CSP. This presentation summarizes a recent report that evaluates the potential impacts of simultaneously achieving the 2030 cost targets for PV and CSP-TES, and it includes a detailed evaluation of the role that CSP-TES could play in realizing those impacts. The scenarios in this analysis are designed to isolate and assess the potential impacts of achieving DOE's 2030 cost targets for CSP-TES and PV, and they do not reflect the potential benefits or system impacts associated with success in other DOE research programs. The low-cost solar scenarios include DOE's 2030 solar cost targets--which are represented via a roughly 50% reduction in LCOE by 2030 (from current levels) with additional cost reductions thereafter representing technology learning and/or improvements that could result from innovation - coupled with a variety of market, technology, and demand assumptions. With these assumptions, the evolution of the contiguous U.S. electricity system is evaluated with NREL's Renewable Energy Deployment System (ReEDS) model, which was specifically designed to represent the temporal and locational value of renewable generation technologies in the U.S. power system. ReEDS relies on system-wide least-cost optimization to estimate the type and location of future generation and transmission capacity. In addition, it accounts for the locational and temporal variations in variable renewable technologies, including the need for new transmission, curtailment, dynamic capacity value, and the need to hold operating reserves to account for the uncertainty and variability of these technologies. This presentation summarizes the key findings that arise from a detailed evaluation of the impacts of achieving DOE's 2030 cost targets for CSP-TES and PV systems, noting again the inherent challenges associated with modeling future scenarios of the large, complex system electricity system in the contiguous United States within the context of various market features.

14 SOLAR ENERGY↗
DOE OSTI2021

Integrating Cambium Marginal Costs into Electric Sector Decisions: Opportunities to Integrate Cambium Marginal Cost Data into Berkeley Lab Analysis and Technical Assistance

NREL’s Cambium tool generates forward-looking simulations of marginal wholesale electricity costs associated with NREL’s Standard Scenarios. The scenarios include growing shares of variable renewable energy (VRE, i.e. wind and solar), among other power sector assumptions, between 2018 and 2050. The tool’s primary output—hourly costs at more than 130 balancing areas—could serve as public and transparent data source that supports electric-sector decision-making processes across the U.S. Berkeley Lab conducts a large range of analyses that use historical and forward-looking wholesale electricity prices to inform electric-sector decisions. In this report, Berkeley Lab uses its expertise to evaluate the Cambium cost data. We compare Cambium data with historical wholesale prices for the year 2018 and other modeled prices for the year 2030. We then present eight case studies in which Berkeley Lab researchers use Cambium data to replicate previous analyses based on other price datasets. We describe where primary findings and underlying key price dynamics align or differ, and highlight possible novel insights from the Cambium data. Finally, we qualitatively evaluate the suitability of Cambium costs in ten additional Berkeley Lab studies, though a direct comparison with alternative price data was not feasible at this time. The goal is to inform how electric-sector decision-makers and DOE program offices may be able to use this cohesive dataset, and to highlight what improvements to Cambium may make it even more useful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Development of a Computational Framework for Multiphysics Multiphase Species Tracking using NEAMS Tools

This report implements a high-fidelity multiphysics modeling framework using the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program tools to track isotopic species in Molten Salt Reactors (MSRs), with a specific focus on the 91-depletion chain within the Molten Salt Reactor Experiment (MSRE). The model integrates neutronics, thermal-hydraulics, depletion, and thermochemistry to simulate the production, transport, and phase transitions of isotopes under steady-state and transient conditions. The main findings reveal that isotopes such as bromine-91 largely remain in the liquid phase, while others, including krypton-91and yttrium-91, transition to the gas phase, significantly influencing the reactor’s radiological source term. The study also shows that during transients, like a reactivity insertion transient, rapid void formation and the expansion of the liquid-gas interface led to substantial transfers of dissolved isotopes into the gas phase, altering isotope distribution and largely increasing the source term in the off-gas system. Additionally, the research highlights that short-lived isotopes dominate the initial off-gas response during transients, while longer-lived isotopes determine the equilibrium state, underscoring the necessity of dynamic simulations for accurate species tracking and reactor safety analysis. The developed methodology will be applied in the future to the tracking of a larger number of species and introduce other species tracking mechanisms, such as deposition and plating.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US

Technology learning rates can be dynamic quantities as a technology moves from early development to piloting and from low volume manufacturing to high volume manufacturing. This work describes a generalizable technology analysis approach for disaggregating observed technology cost reductions and presents results of this approach for one specific case study (micro-combined heat and power fuel cell systems in Japan). We build upon earlier reports that combine discussion of fuel cell experience curves and qualitative discussion of cost components by providing greater detail on the contributing mechanisms to observed cost reductions, which were not quantified in earlier reports. Greater standardization is added to the analysis approach, which can be applied to other technologies. This paper thus provides a key linkage that has been missing from earlier literature on energy-related technologies by integrating the output of earlier manufacturing cost studies with observed learning rates to quantitatively estimate the different components of cost reduction including economies of scale and cost reductions due to product performance and product design improvements. This work also provides updated fuel cell technology price versus volume trends from the California Self-Generation Incentive Program, including extensive data for solid-oxide fuel cells (SOFC) reported here for the first time. The Japanese micro-CHP market is found to have a learning rate of 18% from 2005 to 2015, while larger SOFC fuel cell systems (200 kW and above) in the California market are found to have a flat (near-zero) learning rate, and these are attributed to a combination of exogenous, market, and policy factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Preface and Summary

Primary Physics with Secondary Beams of K L 's Not all of physics can be explored by primary beams of electrons and protons, however much these have taught us over the past 60 years. Electron-positron colliders give access to restricted sets of quantum numbers. From proton-proton collisions we have long learned about all manner of high energy reactions. However, access to excited mesons and baryons has been most universally achieved with pion and kaon secondary beams, and latterly pho-ton beams both virtual and real. Nowadays the wealth of information on polarized photon beams on polarized targets has totally revolutionized baryon spectroscopy, especially in the lightest flavor sector. The measurement of polarization asymmetries has constrained partial wave analyses far beyond anything conceivable with pion beams. Nevertheless, these only give access to the product of photocouplings of each excited baryon and its coupling to the hadron final state, such as πN , ππN , ηN , etc. Contemporaneously, in the meson sector, the COMPASS experiment with pion beams on protons at 190 GeV/c, together with heavy flavor decays in e + e - annihilation, have given access to multi-meson final states, like 2π, 3π, with greater precision than ever before. This has given hints and suggestions of new resonances, like the a 1 (1420). To understand the constituent structure of hadrons requires information on the relationship of each meson and baryon to those with different flavors, but the same J P quantum numbers. At its simplest, this is to understand the quark model multiplet structure, where this is appropriate. What is more, so ubiquitous are ππ, πK, KK, ηπ, ηK, ... final states as the decay products of almost every hadron, that knowledge of the properties of these is critical to every analysis. Unitarity colors and shapes the universality of such final state interactions in each set of quantum numbers. This means that however precise our measurements of γN → πη () N , with GlueX for instance, we cannot really determine the fine resonant structure of such a process without some information on πη and πη scattering too. Nor can we determine any flavor partners without information on the corresponding Kη () channels. For that secondary kaon beams are essential. While J-PARC has a whole program of charged strange particle and hypernuclear reactions, photon beams allow unique access to other channels. It was realized long ago that intense photon beams like that about to be delivered to Hall D at JLab, could produce secondary beams. The charged particles can readily be bent away, leaving a neutral particle beam dominated by K L : long lived kaons being produced far more copiously than neutrons above 3–4 GeV momentum. Such a facility provides access to a whole range of physics that is the subject of this meeting. The reactions that can be studied cover the meson spectrum and dynamics, the baryon spectrum and dynamics, and final state interactions that link mesons and baryons together. This includes particularly the channels Kπ, Kη, Kη in the meson sector. These explore the very limitations of chiral dynamics: the strange quark's current mass is 30-50 times that of the

42 ENGINEERING↗
DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The Dynamics and Thermodynamics of Gaseous Molecule-Ions. Final report

The overall objectives of this research effort were to expand the capabilities of spectroscopic and ion chemistry tools for the structural characterization of polyatomic ions of relevance to the broad mission of the Department of Energy. Mass spectrometry currently plays an important role in virtually all of the molecular sciences by virtue of the value of the accurate measurement of mass and the structural information that can be derived from various structural probes based on, for example, ion chemistry, ion mobility, and ion spectroscopy. Mass spectrometry has long played important roles in supporting the missions of the Department of Energy and its predecessor agencies, particularly in the area of isotopic analysis of nuclides. Molecular mass spectrometry has played increasingly important roles is many aspects of the production and use of energy as the nation has diversified its energy portfolio. There is an ongoing need for the expansion of the measurement capabilities associated with molecular mass spectrometry that involves both technological developments as well as improved understanding of the chemical and physical processes that take place upon ionization and ion analysis in a mass spectrometer. Advances in mass spectrometry have impacted science broadly and further advances will be required to meet the needs of current energy and environmental research. This program has historically focused on the structural characterization of polyatomic ions, usually within the context of a tandem mass spectrometry experiment. A wide variety of physical and chemical processes can take place within a mass spectrometer and advantage can be taken of such processes to enhance the quality and quantity of information that can be derived for a given chemical system of interest. For example, ions can undergo interactions with neutral molecules/atoms, light, surfaces, electrons, or oppositely charged ions. The outcomes of all such interactions can be sensitive to the structures of the ions and are therefore candidates for probes of ion structure. This program has historically focused on the chemistry and physics associated with ion/neutral interactions at both low and high translational energies, and ion/ion reactions. The former area has involved the study of ion/molecule reactions at thermal energies and the extensive study of collisional activation under a wide variety of conditions. A major area of emphasis has been collisional activation in electrodynamic ion traps. The study of gas-phase ion/ion reactions within the context of tandem mass spectrometry was initiated in this program and has grown to be a major research area in this group. Most of the focus in ion/ion chemistry has been on proton transfer and electron transfer reactions and some of the work in the previous budget period was directed, in particular, to fundamental aspects of electron transfer. Recently, the discovery of selective covalent ion/ion reactions has opened up new vistas for research that will expand significantly the capabilities of tandem mass spectrometry for the structural characterization of polyatomic ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting

Many popular vetting tools for Android applications use static code analysis techniques. In particular, Interprocedural Data-Flow Graph (IDFG) construction is the computation at the core of Android static data-flow analysis and consumes most of the analysis time. Many analysis tools use a worklist algorithm, an iterative fixed-point approach, to construct the IDFG. In this paper, we observe that a straightforward GPU parallelization of the worklist algorithm leads to significant underutilization of the GPU resources. We identify four performance bottlenecks, namely, frequent dynamic memory allocations, high branch divergence, workload imbalance, and irregular memory access patterns. Accordingly, we propose GDroid, a GPU-based worklist algorithm implementation with multiple fine-grained optimizations tailored to common characteristics of Android applications. The optimizations considered are: matrix-based data structure, memory access-based node grouping, and worklist merging. Our experimental evaluation, performed on 1000 Android applications, shows that the proposed optimizations are beneficial to performance, and GDroid can achieve up to 128X speedups against a plain GPU implementation.

Android security↗
DOE OSTI2024

New systems in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) serves as a common library of classes between applications developed for advanced reactor analysis, fusion device engineering, spent fuel cask analysis, geochemistry studies, among other fields. These applications drive the development of the framework to meet their needs. Systems in MOOSE group capabilities that share a common purpose and generally common code. They can be leveraged by all downstream applications, providing extensive code re-use and shared maintenance. They facilitate the discovery by new users of the classes meeting at least partially their needs, and offer the same opportunities for customization as other systems. The addition of a new system to MOOSE opens new ways of solving or discretizing nonlinear problems, of performing distributed postprocessing, and a plethora of other needs. While new systems can be introduced in downstream applications rather than at the framework level, the framework team monitors common needs across the community and often triggers their addition. Documentation, training material, development needs can be centralized, limiting duplicated work across the community. The last three years have seen a large expansion in the capabilities of MOOSE. The supporting role of the framework in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has created numerous feature requests to support neutronics, thermal hydraulics, computational fluid dynamics and thermo-mechanics simulations in the Griffin, SAM, Pronghorn and Bison applications respectively. Similarly, laboratory-directed research and development (LDRD) projects in additive manufacturing, high-Reynolds flow simulations, structure optimization also necessitate an expansion of the framework capabilities. This summary reports on the new systems created in MOOSE, their design, their capabilities and some of the relevant interfaces.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Economic Optimal Control for Minimizing Fuel Consumption of Heavy-Duty Trucks in a Highway Environment

This paper provides a comparative assessment of three economic optimal control strategies, aimed at minimizing the fuel consumption of heavy-duty trucks in a highway environment, under a representative lead vehicle model informed by traffic data. These strategies fuse a global, offline dynamic programming (DP) optimization with online model predictive control (MPC). We then show how two of the three strategies can be adapted to accommodate the presence of traffic and optimally navigate signalized intersections using infrastructure-to-vehicular (I2V) communication. The MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. The three candidate economic MPC formulations that are evaluated include: a nonlinear time-based formulation that directly penalizes predicted fuel consumption, a nonlinear time-based formulation that penalizes braking effort as a surrogate for fuel consumption, and a linear distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity profile obtained from DP. Using a medium-fidelity Simulink model, based on a Volvo truck's longitudinal and engine dynamics, we analyze the optimization's performance on four highway routes under various traffic scenarios. Results demonstrate 3.7-8.3% fuel economy improvement on highway routes without traffic and 6.5-10% on the same routes with traffic included. Furthermore, we present a detailed analysis of energy usage by "type" (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Implementation and Verification of Cable Bending Stiffness in MoorDyn: Preprint

Cable bending stiffness capabilities have been added to MoorDyn to enable modeling of dynamic power cables. The relatively large motions experienced by floating wind turbines and wave energy converters pose a challenge for power cables, whose internal components provide significant bending resistance and are sensitive to deformation. The behavior and associated design considerations of power cables in these highly dynamic applications make coupled analysis relevant for design. MoorDyn is a lumped-mass mooring dynamics model that is used for floating wind energy simulation (often coupled with OpenFAST) and floating wave energy converter simulation (often coupled with WEC-Sim). Its existing line elasticity formulation considers axial stiffness only. To properly capture the dynamics of power cables, a cable bending stiffness model has been added that approximates cable curvature based on the difference in tangent vectors of adjacent line elements. The resulting bending moment is realized by applying forces on adjacent nodes, leaving the underlying lumped-mass formulation unchanged. The bending stiffness implementation is verified in static conditions against analytical solutions and then in a dynamic power cable scenario in comparison with OrcaFlex. The dynamic scenario uses prescribed motions and includes wave loadings on the cable. Results indicate correct implementation of bending stiffness and show close agreement with OrcaFlex.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2014

Mechanical Modeling of a WIPP Drum Under Pressure

Mechanical modeling was undertaken to support the Waste Isolation Pilot Plant (WIPP) technical assessment team (TAT) investigating the February 14th 2014 event where there was a radiological release at the WIPP. The initial goal of the modeling was to examine if a mechanical model could inform the team about the event. The intention was to have a model that could test scenarios with respect to the rate of pressurization. It was expected that the deformation and failure (inability of the drum to contain any pressure) would vary according to the pressurization rate. As the work progressed there was also interest in using the mechanical analysis of the drum to investigate what would happen if a drum pressurized when it was located under a standard waste package. Specifically, would the deformation be detectable from camera views within the room. A finite element model of a WIPP 55-gallon drum was developed that used all hex elements. Analyses were conducted using the explicit transient dynamics module of Sierra/SM to explore potential pressurization scenarios of the drum. Theses analysis show similar deformation patterns to documented pressurization tests of drums in the literature. The calculated failure pressures from previous tests documented in the literature vary from as little as 16 psi to 320 psi. In addition, previous testing documented in the literature shows drums bulging but not failing at pressures ranging from 69 to 138 psi. The analyses performed for this study found the drums failing at pressures ranging from 35 psi to 75 psi. When the drums are pressurized quickly (in 0.01 seconds) there is significant deformation to the lid. At lower pressurization rates the deformation of the lid is considerably less, yet the lids will still open from the pressure. The analyses demonstrate the influence of pressurization rate on deformation and opening pressure of the drums. Analyses conducted with a substantial mass on top of the closed drum demonstrate that the drums will still open provided the pressure is high enough. Investigation teams should look for displaced drum lids when searching for drums that have pressurized and failed. The mechanical modeling study for this program is summarized in the following memo. Following a brief introduction, there is a summary of a brief literature review of previous pressure testing of drums, an explanation of the model, presentation of the key results, some discussion, and concluding with a summary and key points.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Measurement of polarization observables in vector meson photoproduction using a transversely-polarized frozen-spin target and polarized photons at CLAS, Jefferson Lab

The study of baryon resonances provides a deeper understanding of the strong interaction because the dynamics and relevant degrees of freedom hidden within them are re ected by the properties of the excited states of baryons. Higher-lying excited states at and above 1.7 GeV/c 2 are generally predicted to have strong couplings to final states involving a heavier meson, e. g. one of the vector mesons, ρ, ω φ, as compared to a lighter pseudoscalar meson, e. g. π and η. Decays to the ππΝ final states via πΔ also become more important through the population of intermediate resonances. We observe that nature invests in mass rather than momentum. The excited states of the nucleon are usually found as broadly overlapping resonances which may decay into a multitude of final states involving mesons and baryons. Polarization observables make it possible to isolate single resonance contributions from other interference terms. The CLAS g9 (FROST) experiment, as part of the N* spectroscopy program at Jefferson Laboratory, accumulated photoproduction data using circularly- & linearly-polarized photons incident on a transversely-polarized butanol target (g9b experiment) in the photon energy range 0:3-2:4 GeV & 0:7-2:1 GeV, respectively. In this work, the analysis of reactions and polarization observables which involve two charged pions, either in the fully exclusive reaction γρ -> ρπ+π- or in the semi-exclusive reaction with a missing neutral pion, γρ -> ρπ + π - (π 0 ) will be presented. For the reaction ρπ + π - , eight polarization observables (I s , I c , P x , P y , $P^s_{x;y}$, $P^c_{x; y}$) have been extracted. The high statistics data rendered it possible to extract these observables in three dimensions. All of them are first-time measurements. The fairly good agreement of Is, Ic obtained from this analysis with the experimental results from a previous CLAS experiment provides support for the first-time measurements. For the reaction γρ -> ρω -> ρπ + π(π 0 , five polarization observables (T, Σ, F, H, P) have been extracted, four of which are first-time measurements at all energies. This analysis thus represents a comprehensive program on vector-meson photoproduction: The ω is observed and studied directly from the data and the polarization observables for the (broad) ω can be extracted from the double-pion reaction in a partial-wave analysis. The 13 polarization observables extracted in this analysis substantially augment the world database of polarization observables for these reactions and are expected to play a crucial role in identifying the contributing baryon resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Developments and Challenges in the Design of the ITER DRGA

We report the ITER Diagnostic Residual Gas Analyzer (DRGA) will measure the distribution of gas species, i.e., deuterium (D), tritium (T), and impurities, in the divertor exhaust stream and in the plasma periphery, with time resolution relevant to fusion plasma–wall particle dynamics. The uniqueness of the DRGA, over previous implementations of plasma dynamics residual gas analysis, is an integrated approach, combining mass and low-temperature plasma-activated optical spectroscopy, in a differentially pumped analysis station. A further unique feature of the ITER divertor-specific DRGA is an ~8-m separation of the analysis station from the sampled pumping duct, while still maintaining a ~1-s response time for hydrogen isotopic concentrations. ITER DRGA final design activities are strongly benefiting from testing of prototypical DRGA components and methods on present fusion devices, most currently on JET and W7-X. DRGA systems are implemented on both these devices and include sensors (and pumping methods) that are directly relevant to the ITER DRGA design. The recent JET-DTE2 campaign has provided the first experience on operating the combined ITER DRGA sensors with D-T plasmas. While enhancing system design for ITER, this experience on operating devices has also revealed additional engineering challenges, which further guide the continuing final design project. Meanwhile, the recent determination that the ITER DRGA, with slight optimization, will resolve the helium isotopes well enough to support an ITER pre-DT, He-3-based heating scheme, has greatly increased ITER Research Program interest in the DRGA and its implementation well ahead of the DT phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Kraken2 Metagenomic Virus Database

The Database: Kraken2 [1] database built from a classification tree containing over 700k metagenomic viruses from JGI IMG/VR [2]. (1) Wood, D. E., Lu, J., and Langmead, B. (2019). Improved metagenomic analysis with Kraken 2. Genome Biol., 20(1), 1–13. doi: 10.1186/s13059-019-1891-0 (2) Paez-Espino D, Chen I-MA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses. Nucleic Acids Res. 2017;45:D457-65. For Paper: Title: A k-mer based approach for virus classification in metatranscriptomic and metagenomic samples identifies viral associations in the Populus phytobiome and autism brains Abstract Background Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an important role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which further limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus' genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples. Methods To identify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses. We then integrated the viral classification tree with the NCBI taxonomy for use with ParaKraken, a metagenomic/transcriptomic classifier. Results To illustrate the breadth of our utility for classifying viruses with ParaKraken, we analyzed data from a plant metagenome study identifying the differences between two Populus genotypes in three different compartments and on a human metatranscriptome study identifying the differences between Autism Spectrum Disorder patients and controls in post mortem brain biopsies. In the Populus study, we identified genotype and compartment specific viral signatures, while in the Autism study we identified a significant increased abundance of eight viral sequences in Autism brain biopsies. Conclusion Viruses represent an important aspect of the microbiome. The ability to classify viruses represents the first step in being able to better understand their role in the microbiome. The viral classification method presented here allows for more complete identification of viral sequences for use in identifying associations between viruses and the host and viruses and other microbiome members. Acknowledgements and Funding This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This research was also supported by the Plant-Microbe Interfaces Scientific Focus Area in the Genomic Science Program, the Office of Biological and Environmental Research (BER) in the U.S. Department of Energy Office of Science, and by the Department of Energy, Laboratory Directed Research and Development funding (ProjectID 8321), at the Oak Ridge National Laboratory. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US DOE under contract DE-AC05-00OR22725. This research used resources of the Compute and Data Environment for Science (CADES).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Semi-Annual Report for Horizontal Compact High Temperature Gas Reactor (HC-HTGR) Development during Performance Period April 2023 – September 2023

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This fourth semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY23. As a part of the RCCS design task, recent efforts have been made to complete a conceptual design of the RCCS for the HC-HTGR, including the design update of the water panel and system configuration favorable in point of view of fabrication and system operation. Design calculations were conducted under various heat load conditions to validate the system design. Transient simulations using RELAP5-3D were conducted to investigate system dynamics under transients of interest and to evaluate the system performance in the design condition. The results demonstrated the overall system feasibility that the RCCS design maintains structures temperatures lower than maximum allowable temperature with sufficient system inventory without any active heat sink. In the primary system thermal hydraulics task, the preliminary analysis was performed for a long term pressurized conduction cooldown (PCC) transient. This analysis used a combination of a fully resolved and coarse homogenized mesh to predict the temperature distribution for the steady-state initial condition and the PCC transient. The steady-state initial condition was determined using a fully resolved full core model with 3D solid to 1D fluid coupling. The fully resolved mesh was also used to model the first 20 seconds of the PCC. The temperature difference between fuel pins and the graphite matrix becomes minimal and the dominant heat transfer shifts to a larger scale radially towards the RCCS. After 20 seconds, a homogenized coarse mesh is used, greatly reducing the computational costs of the model. These results demonstrate that the core is designed to passively remove enough decay heat in a protected loss of primary coolant flow to prevent an unsafe rise of core temperatures.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Upgrade of Gamma Spectrometry Systems for ORNL TRISO Fuel PIE

Gamma spectrometry is a key element in much of the post-irradiation examination (PIE) work performed under the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program (Demkowicz et al. 2015; Stempien et al. 2021). Gamma spectrometers are integrated into three major capabilities used at the Oak Ridge National Laboratory (ORNL) Irradiated Fuels Examination Laboratory (IFEL) for PIE of tristructural-isotropic (TRISO) coated particles and fuel compacts: the Core Conduction Cooldown Test Facility (CCCTF), the Vertical Counting System (VCS), and the Irradiated Microsphere Gamma Analyzer (IMGA). The CCCTF includes liquid-nitrogen-cooled traps to extract 85 Kr out of the He sweep gas that passes through the furnace in which the fuel compacts are heated during safety testing. Analysis of the 85 Kr activity in the traps is the primary indicator for TRISO failure during safety testing. The VCS is a system used to accurately measure gamma emission from components placed in a lead-shielded chamber. It is used to count the CCCTF deposition cups after removal from furnace. Each cup resides in the CCCTF furnace for typically 12–24 h and is periodically replaced with a fresh cup throughout the safety test. Metallic fission products collect on the water-cooled cups and several gamma-emitting isotopes ( 110 mAg, 134 Cs, 137 Cs, 154 Eu, and 155 Eu) are often measured and provide indication of the retention performance of the TRISO coatings. The VCS is also used to measure the presence of these isotopes on the CCCTF tantalum liner and sweep gas inlet tube for the determination of cup collection efficiency, as well as support other gamma spectrometry needs related to calibration of the 85 Kr fission gas traps and various other special PIE tasks. The IMGA uses gamma spectrometry to measure the inventory of gamma-emitting isotopes in individual TRISO particles. An automated particle handling system within the IMGA hot cell removes each particle from a source vial and positions it in front of a gamma detector, and output from the gamma spectrometer is used by the IMGA software to determine a destination vial such that particles are sorted according to their inventory and retention characteristics. At the conclusion of the AGR-1 and AGR-2 PIE campaigns, the gamma spectrometer systems used at ORNL to support that PIE had reached the end of its life cycle due to gradual obsolescence of the hardware and software. Upgrade of the Canberra Genie 2000 software used by these systems to a Windows 10 version was not a viable option, because the newest Windows 10 version offered by Mirion (the new owner of the Canberra technology) did not include the dynamic-link libraries (DLLs) needed for integration with the custom PIE software used with the CCCTF and IMGA, and Mirion had no current plans for development and release of Windows 10 versions of these DLLs with the Model S560 Genie 2000 Programming Library. Ultimately a switch was made to ORTEC gamma spectrometry systems, which appeared to be a more sustainable solution due to more proactive vendor support. The ORTEC conversion involved replacing the aging detector preamplifier and multichannel analyzer (MCA) hardware, upgrading the obsolete Windows 7 computers to Windows 10 compatible models, adopting ORTEC GammaVision software, and extensive modification of the ORNL-developed Visual Basic .NET (VB.NET) programs that provide the CCCTF and IMGA user interfaces.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advancing the Understanding of Cloud Microphysical Processes and Aerosol Indirect Effects in High-Latitude Mixed-Phase Clouds by Linking ARM Measurements with Climate Model Simulations (Final Report)

The key objectives of this project were to advance our understanding of cloud microphysical characteristics and aerosol indirect effects on mixed-phase clouds in high latitudes. To improve the representation of ice and mixed-phase clouds in Earth System Models (ESMs), we propose an integrated observation and modeling study of cloud macro- and microphysical properties, including spatial heterogeneities, mass partitioning between ice crystals and supercooled liquid water, effects of ice nucleating particles (INPs), and efficiency of secondary ice production (SIP), etc. Specifically, we took four main approaches in this project: (1) examining macro- and microphysical properties of ice and mixed-phase clouds based on in-situ and ground-based observations from multiple field campaigns funded by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program, including the Mixed-Phase Arctic Cloud Experiment (M-PACE), Indirect and Semi-Direct Aerosol Campaign (ISDAC), Ice Nucleating Particle Sources at Oliktok Point (INPOP), ARM West Antarctic Radiation Experiment (AWARE), Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS), and Macquarie Island Cloud and Radiation Experiment (MICRE); (2) evaluating the DOE Energy Exascale Earth System Model (E3SM) simulations based on observations, particularly for ice and mixed-phase cloud microphysical properties; (3) examining the impacts of INPs on ice and mixed-phase clouds. Specifically, a series of comparisons were conducted using observations over the Arctic, Southern Ocean, and Antarctica, including comparisons between the lower and higher southern latitudes as well as comparisons between the northern and southern hemispheres. In addition, aerosol indirect effects from distinct sources of dust particles were examined; and (4) investigating the impacts of SIP. Ultimately, these results helped to improve cloud microphysics and aerosol-cloud interaction parameterizations in the E3SM model. Overall, the project provided improved understanding regarding various factors, including thermodynamic, dynamic, and aerosol conditions, on the micro- and macrophysical properties of ice and mixed-phase clouds in the high latitudes. Resulting analysis helped to provide an improved physical basis for refining the current cloud microphysics parameterizations related to ice and mixed-phase clouds in E3SM.

54 ENVIRONMENTAL SCIENCES↗