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DOE OSTI2021

Trailhead for quantum simulation of SU(3) Yang-Mills lattice gauge theory in the local multiplet basis

Maintaining local interactions in the quantum simulation of gauge field theories relegates most states in the Hilbert space to be unphysical—theoretically benign, but experimentally difficult to avoid. Reformulations of the gauge fields can modify the ratio of physical to gauge-variant states often through classically preprocessing the Hilbert space and modifying the representation of the field on qubit degrees of freedom. This paper considers the implications of representing SU(3) Yang-Mills gauge theory on a lattice of irreducible representations in both a global basis of projected global quantum numbers and a local basis in which controlled-plaquette operators support efficient time evolution. Classically integrating over the internal gauge space at each vertex (e.g., color isospin and color hypercharge) significantly reduces both the qubit requirements and the dimensionality of the unphysical Hilbert space. Initiating tuning procedures that may inform future calculations at scale, the time evolution of one and two plaquettes are implemented on one of IBM’s superconducting quantum devices, and early benchmark quantities are identified. The potential advantages of qudit environments, with either constrained two-dimensional hexagonal or one dimensional nearest-neighbor internal state connectivity, are discussed for future large-scale calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

The ongoing need for high-resolution regional climate models: Process understanding and stakeholder information

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. High resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding regional climate variability and change, and are critical for supporting societal responses to changing climate.

Gutowski, William↗

DOE OSTI2024

Carbon storage cost modeling for the offshore Gulf of Mexico

Groundbreaking for geologic carbon storage (GCS) projects in the offshore Gulf of Mexico is imminent, and there is great interest in utilizing this region for GCS projects. Offshore saline reservoirs provide a significant and accessible resource for GCS. However, conducting GCS in the offshore environment will pose distinct challenges pertaining to site selection, operations, infrastructure use, and monitoring compared to operating onshore that ultimately affect technoeconomic assessment of offshore GCS projects. Carbon storage and transport costs are critical to project developers looking to deploy carbon storage in the offshore environment. We present CO2_S_COM_Offshore, a model developed by the National Energy Technology Laboratory (NETL) as a screening-level offshore saline GCS cost modeling tool. Based on NETL’s widely used CO2_S_COM cost model for onshore saline CS, CO2_S_COM_Offshore enables technoeconomic analysis of GCS in offshore areas. This model comprehensively incorporates multiple facets of offshore GCS projects, from regional evaluation and site selection to permitting, transport, operations, monitoring, site closure, and decommissioning. In general, the model can explore the cost implications for potential offshore GCS project(s) by enabling the user to change several project operational and financial attribute configurations. Key inputs include offshore storage formation options, CO2 injection rate and duration, infrastructure types, monitoring intensity, project financing, and post-injection site care duration. Supporting cost algorithms within CO2_S_COM_Offshore were compiled utilizing S&P Global’ s QUE$TORTM cost estimation software alongside a variety of open-source scientific literature. In addition to reviewing key model components, we discuss several sensitivity analyses, input variabilities, and results on analysis of break-even CO2 price required by a project based on different regulation/policy and operational scenarios for the offshore Gulf of Mexico. These results indicate the value of modeling offshore GCS specifically, and the potential of offshore GCS within a decarbonization value chain. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Mark-Moser, Mackenzie K.↗

DOE OSTI2024

University of Louisiana at Lafayette

A partnership with the University of Louisiana and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect solar data to support future solar power generation in the United States. The measurement station monitors global, direct, and diffuse irradiance to define the amount of solar energy that hits this particular location. The solar measurement instrumentation is also accompanied by meteorological monitoring equipment to provide scientists with a complete picture of the solar power possibilities.

14 SOLAR ENERGY↗

DOE OSTI2024

University of Florida

A partnership with the University of Florida and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect solar data to support future solar power generation in the United States. The measurement station monitors global, direct, and diffuse irradiance to define the amount of solar energy that hits this particular location. The solar measurement instrumentation is also accompanied by meteorological monitoring equipment to provide scientists with a complete picture of the solar power possibilities.

14 SOLAR ENERGY↗

DOE OSTI2021

Register-Like Block RAM: Implementation, Testing in FPGA and Applications for High Energy Physics Trigger Systems

In high energy physics experiment trigger systems, block memories are utilized for various purposes, especially in indexed searching algorithms. It is often demanded to globally reset all memory locations between different events which is a feature not supported in regular block memories. Another common demand is to be able to update the contents in any memory location in a single clock cycle. These two demands can be fulfilled with registers but the cost of using registers for large memory is unaffordable. In this paper, a register-like block memory design scheme is described, which allows updating memory locations in single clock cycle and effectively refreshing entire memory within a single clock. The implementation and test results are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

A New Process for Small-Batch Purification of the Medical Isotope Molybdenum-99: Non-Technical Overview

The U.S. medical community depends on a reliable supply of the radioisotope molybdenum-99 (Mo-99) for nuclear medical diagnostic procedures. Mo-99's decay product, technetium-99m (Tc-99m), is used in over 40,000 medical procedures in the United States each day to diagnose heart disease and cancer, to study organ structure and function, and to perform other important medical applications. For example, patients undergoing a common procedure—the cardiac “stress test”—likely have benefited from Tc-99m. Historically, Mo-99 was primarily produced through the fission of uranium-235, in the form of highly enriched uranium (HEU) targets irradiated in research and test reactors. HEU is a proliferation-sensitive material that, if diverted or stolen, could be used as a component of a nuclear weapon. NNSA’s Office of Material Management and Minimization (M3) manages the Molybdenum-99 (Mo-99) Program as part of its mission to minimize the use of HEU in civilian applications. The Mo-99 Program assists global Mo-99 production facilities in converting to non-HEU processes and supports the establishment of domestic supplies of Mo-99 without the use of proliferation-sensitive HEU. As part of this program, M3 funds U.S. national laboratories to provide non-proprietary technical support to U.S. companies working to establish non-HEU-based Mo-99 production capabilities. The results of this research are published on OSTI.gov for the benefit of the Mo-99 community and the public. However, it can be difficult for readers without a scientific background to understand and interpret these publications. In order to increase public understanding of the work being done in M3’s Mo-99 Program, this paper aims to provide an overview of a key, recent national laboratory technical publication in terms that can be understood by readers without a technical background. To accomplish this, the paper first explains key scientific concepts—primarily related to chemistry—that provide a foundation for understanding research in this area. This includes chromatography, absorption vs. adsorption, dissolution and precipitation, and liquid-liquid extraction. Drawing on these concepts, the paper then provides an explanation for non-technical audiences of the Argonne National Laboratory publication entitled Recovery of High Specific Activity Molybdenum-99 from Accelerator-Induced Fission on Low-Enriched Uranium for Technetium-99m Generators (Brown, M.A. et al., 2021) and related article Separation and Purification of Mo-99 Produced from Natural U3O8 Targets via Photo-Fission (Brown, M.A. et al., 2021).

Stamler, Bradley↗

DOE OSTI2025

NREL Is Strengthening the Future of Hydropower, A Cornerstone of America's Energy System

The National Renewable Energy Laboratory (NREL) is a leader in advancing hydropower technologies, positioning hydropower as a pillar of an affordable, reliable, and secure energy future. Through its hydropower program, NREL is conducting innovative research that reduces energy costs, drives efficiency, and supports systems integration - unlocking economic opportunities, rebuilding supply chains, and fueling America's global competitiveness.

13 HYDRO ENERGY↗

DOE OSTI2022

A Statistical Interpolation Code for Ocean Analysis and Forecasting

Abstract We present a data assimilation package for use with ocean circulation models in analysis, forecasting, and system evaluation applications. The basic functionality of the package is centered on a multivariate linear statistical estimation for a given predicted/background ocean state, observations, and error statistics. Novel features of the package include support for multiple covariance models, and the solution of the least squares normal equations either using the covariance matrix or its inverse—the information matrix. The main focus of this paper, however, is on the solution of the analysis equations using the information matrix, which offers several advantages for solving large problems efficiently. Details of the parameterization of the inverse covariance using Markov random fields are provided and its relationship to finite-difference discretizations of diffusion equations are pointed out. The package can assimilate a variety of observation types from both remote sensing and in situ platforms. The performance of the data assimilation methodology implemented in the package is demonstrated with a yearlong global ocean hindcast with a 1/4° ocean model. The code is implemented in modern Fortran, supports distributed memory, shared memory, multicore architectures, and uses climate and forecasts compliant Network Common Data Form for input/output. The package is freely available with an open source license from www.tendral.com/tsis/ .

Srinivasan, Ashwanth↗

DOE OSTI2021

Comparing Global Spray Combustion Characteristics and Local Shot-to-Shot Variations in a Reacting n -Heptane Spray

In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.

42 ENGINEERING↗

DOE OSTI2025

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Cyclotron Road Partnership (CRADA Final Report)

The Cyclotron Road program was launched in 2015 by LBNL, with support from the DOE Advanced Manufacturing Office (AMO), to accelerate technical innovation in the energy sector. The program brought scientist-entrepreneurs to LBNL to access unique research assets and expertise. In 2016, LBNL partnered with Activate Global, Inc., a 501(c)(3) non-profit, to expand the program and provide enhanced access to capital and business support services. Under this Cooperative Research and Development Agreement (CRADA), LBNL provided technical support and expertise, while Activate engaged with private sector, philanthropic, and government partners to support innovators and research-phase small businesses, aiming to translate high-impact materials and manufacturing technologies from lab to market. The program received funding from various sponsors, including the DOE, DARPA, and the California Energy Commission, and was managed through a collaborative framework that maintained accountability by the participant organization and Berkeley Lab regarding roles and tasks relevant to this collaboration.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

The Need for a System Science Approach to Global Magnetospheric Models

This perspective advocates for the need of a combined system science approach to global magnetospheric models and to spacecraft magnetospheric data to answer the question “Do simulations behave in the same manner as the magnetosphere does?” (instead of the standard validation question “How well do simulations reproduce spacecraft data?”). This approach will 1) validate global magnetospheric models statistically, without the need for a direct comparison against spacecraft data, 2) expose the deficiencies of the models, and 3) provide physics support to the system analysis performed on the magnetospheric system.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Spring 2023 Solar Industry Update [Slides]

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗

DOE OSTI2026

National Solar Thermal Test Facility: Operations & Maintenance Report

The NSTTF O&M Project continues the operation and maintenance activities of the existing critical capabilities and infrastructure at the NSTTF. This project is to support and assure the success of Solar Heat for Industrial Process in the United States and the larger global community by ensuring the NSTTF is a safe and operational facility. The primary goal of this project will be to maintain the solar tower and heliostat field while also allowing NSTTF staff to improve processes for operations and maintenance. This includes expanding our preventative maintenance program, inventory systems, and our data sharing capabilities. Additionally, this will support an outreach program with regular seminars, sharing of data, and the release of open-source software to support heliostat metrology

14 SOLAR ENERGY↗

DOE OSTI2024

Needle bacterial community structure across the species range of limber pine

Abstract Bacteria on and inside leaves can influence forest tree health and resilience. The distribution and limits of a tree species’ range can be influenced by various factors, with biological interactions among the most significant. We investigated the processes shaping the bacterial needle community across the species distribution of limber pine, a widespread Western conifer inhabiting a range of extreme habitats. We tested four hypotheses: (i) Needle community structure varies across sites, with site-specific factors more important to microbial assembly than host species selection; (ii) dispersal limitation structures foliar communities across the range of limber pine; (iii) the relative significance of dispersal and selection differs across sites in the tree species range; and (iv) needle age structures bacterial communities. We characterized needle communities from the needle surface and tissue of limber pine and co-occurring conifers across 16 sites in the limber pine distribution. Our findings confirmed that site characteristics shape the assembly of bacterial communities across the host species range and showed that these patterns are not driven by dispersal limitation. Furthermore, the strength of selection by the host varied by site, possibly due to differences in available microbes. Our study, by focusing on trees in their natural setting, reveals real needle bacterial dynamics in forests, which is key to understanding the balance between stochastic and deterministic processes in shaping forest tree-microbe interactions. Such understanding will be necessary to predict or manipulate these interactions to support forest ecosystem productivity or assist plant migration and adaptation in the face of global change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Forecasting Marine Sediment Properties with Geospatial Machine Learning

Using a combination of geospatial machine learning prediction and sediment thermodynamic/physical modeling, we have developed a novel software workflow to create probabilistic maps of geoacoustic and geomechanical sediment properties of the global seabed. This new technique for producing reliable estimates of seafloor properties can better support Naval operations relying on sonar performance and seabed strength, can constrain models of shallow tomographic structure important for nuclear treaty compliance monitoring/detection, and can provide constraints on the distribution and inventory of shallow methane gas and gas hydrate accumulations on the continental shelves.

58 GEOSCIENCES↗

DOE OSTI2025

Sextupole reduction via chaos suppression at NSLS-II

We revisit the nonlinear lattice design approach for the National Synchrotron Light Source II (NSLS-II) storage ring. By suppressing chaos, we identify alternative sextupole configurations to the original design, which relied on the conventional approach of simultaneously minimizing Resonance Driving Terms (RDTs) and Amplitude-Dependent Detuning (ADD). These alternatives achieve comparable performance while requiring fewer sextupoles. A detailed comparison of two representative solutions is presented and supported by experimental validation. Our results indicate that dynamic aperture correlates more strongly with global chaos than with individual RDTs, and that the importance of minimizing ADD may have been overstated in earlier design approach.

43 PARTICLE ACCELERATORS↗