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DOE OSTI2022

Translator Plan: A Coordinated Vision for Fiscal Years 2023-2025

Translators serve a unique role in the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility, offering scientific input through various leadership and service roles. The Translators direct the creation of value-added products (VAPs) and analysis tools that make ARM measurements more accessible to the scientific community. Translators also serve as liaisons between users and the ARM infrastructure, collecting information about priorities and communicating ARM data and services. A key group focus is supporting the DOE Atmospheric System Research (ASR) program scientists and ASR’s efforts towards a process-level understanding of cloud-aerosol interactions, and in reducing uncertainty in global climate model projections. The ARM Translator Group (Table 1) consists of the five Translators, a representative of software development, and one from the Data Quality Office (DQO). Additionally, the ARM Engineering and Process Manager participates in this group and provides input and direction from ARM and its programmatic priorities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

DOE OSTI2022

Shifting Trade-offs: Finding the Sustainable Nexus of Hydropower and Environmental Flows in the San Joaquin River Watershed, California

Environmental flow management in watersheds with multi-objective reservoirs is often presented as an additional constraint to an already strained and over-allocated stream system. Nevertheless, environmental flow legislation and regulatory policies are increasingly being developed and implemented globally. In California, USA, recent legislative and regulatory policies place environmental flows at the forefront of the state’s water management objectives; however, the increased reliance on hydropower to support climate change mitigation goals may complicate efforts on both issues. This study modelled alternative environmental flow strategies in the major tributaries to the San Joaquin River in California. Strategies included detailed water management rules for hydropower production, flood control, and water deliveries, and three methodological approaches to environmental flow releases: minimum instream flows (“baseline”) year-round, 40% of full natural flow (FNF) during the spring runoff season and minimum releases the remainder of the year, and functional flows year-round. Results show that environmental flow strategies affect downstream flow releases in each of the San Joaquin’s four sub-basins differently depending on infrastructure capacity, water management objectives, and hydrologic year types. While hydropower production was comparable or declined in the Stanislaus, Tuolumne, and Merced basins, functional flow and 40% FNF strategies increased hydropower production in the Upper San Joaquin basin by 11%. Uncontrolled spill of high flow events decreased when high flow releases were based on hydrologic cues rather than exclusively on flood storage capacity. Water deliveries were reduced in all years regardless of environmental flow strategy. The 40% FNF and functional flow strategies both increased water released to the river relative to baseline, but in different ways. The functional flow strategy allocated water in a holistic approach that enhanced ecological functions in all years, but particularly in moderate and wet years. In contrast, the 40% FNF strategy provided increased flows relative to baseline and some ecological benefit in dry years, but less ecological benefit in other years. This study shows that alternative environmental flow strategies will have different and important trade-offs for integrated water management, and may mutually benefit seemingly conflicting objectives.

13 HYDRO ENERGY↗

DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

DOE OSTI2025

Advanced Fuels Campaign: Strategic Vision

The Advanced Fuels Campaign (AFC) is dedicated to propelling the United States to the forefront of nuclear fuel technology through a comprehensive strategic vision. The vision is structured around five key goals: driving U.S. leadership in nuclear fuel technology, expanding nuclear energy production from the existing fleet, completing the qualification basis for advanced reactor fuel technology, driving innovation in advanced nuclear fuel technology, and enabling a high-performing organization. By focusing on these goals, AFC aims to define and implement cutting-edge nuclear fuel technologies, support industry advancements, achieve critical fuel qualifications, foster innovative research, and ensure effective program management and stakeholder engagement. This strategic approach will solidify the United States’ position as a global leader in nuclear energy and fuel technology, while also preparing for the future of environmentally friendly and reliable nuclear power.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Advanced Fuels Campaign: Strategic Vision

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Shirley et al. (2022) “Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed". [DOI].The dataset contains outputs from the global sensitivity analysis (GSA) of the “ecosys” model as reported in Shirley et al. (2022). The study showed that discontinuous permafrost environments are characterized by complex feedback loops and strong spatial heterogeneity which is created by variability in near-surface hydrology and soil properties. Additionally, the study demonstrated that missing representation of sub-grid heterogeneity in terrestrial ecosystem models can lead to biased estimates of the high-latitude carbon budget. Included in this dataset are the factor values for each run in the GSA and the model outputs used in this study. Included are two *.csv data files and one *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Sandia's Research in Support of COVID-19 Pandemic Response: Computing and Information Sciences

This report summarizes the goals and findings of eight research projects conducted under the Computing and Information Sciences (CIS) Research Foundation and related to the COVID- 19 pandemic. The projects were all formulated in response to Sandia's call for proposals for rapid-response research with the potential to have a positive impact on the global health emergency. Six of the projects in the CIS portfolio focused on modeling various facets of disease spread, resource requirements, testing programs, and economic impact. The two remaining projects examined the use of web-crawlers and text analytics to allow rapid identification of articles relevant to specific technical questions, and categorization of the reliability of content. The portfolio has collectively produced methods and findings that are being applied by a range of state, regional, and national entities to support enhanced understanding and prediction of the pandemic's spread and its impacts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Advanced architectures for high-performance quantum networking

As practical quantum networks prepare to serve an ever-expanding number of nodes, there has grown a need for advanced auxiliary classical systems that support the quantum protocols and maintain compatibility with the existing fiber-optic infrastructure. We propose and demonstrate a quantum local area network design that addresses current deployment limitations in timing and security in a scalable fashion using commercial off-the-shelf components. First, we employ White Rabbit switches to synchronize three remote nodes with ultra-low timing jitter, significantly increasing the fidelities of the distributed entangled states over previous work with Global Positioning System clocks. Second, using a parallel quantum key distribution channel, we secure the classical communications needed for instrument control and data management. Therefore, the conventional network that manages our entanglement network is secured using keys generated via an underlying quantum key distribution layer, preserving the integrity of the supporting systems and the relevant data in a future-proof fashion.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Polarity-Tolerant Chloride Binding in Foldamer Capsules by Programmed Solvent-Exclusion

Persistent anion binding in a wide range of solution environments is a key challenge that continues to motivate and demand new strategies in synthetic receptor design. Though strong binding in low-polarity solvents has become routine, our ability to maintain high affinities in high-polarity solvents has not yet reached the standard set by nature. Anions are bound and transported regularly in aqueous environments by proteins that use secondary and tertiary structure to isolate anion binding sites from water. Inspired by this principle of solvent exclusion, we created a sequence-defined foldameric capsule whose global minimum conformation displays a helical folded state and is preorganized for 1:1 anion complexation. The high stability of the folded geometry and its ability to exclude solvent were supported by solid-state and solution phase studies. This capsule then withstood a 4-fold increase in solvent dielectric constant (εr) from dichloromethane (9) to acetonitrile (36) while maintaining a high and solvent-independent affinity of 10 5 M –1 ; ΔG ~ 28 kJ mol –1 . This behavior is unusual. More typical of solvent-dependent behavior, Cl – affinities were seen to plummet in control compounds, such as aryl-triazole macrocycles and pentads, with their solvent-exposed binding cavities susceptible to dielectric screening. Finally, dimethyl sulfoxide denatures the foldamer by putative solvent binding, which then lowers the foldamer’s Cl – affinity to normal levels. Furthermore, the design of this capsule demonstrates a new prototype for the development of potent receptors that can operate in polar solvents and has the potential to help manage hydrophilic anions present in the hydrosphere and biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Constraining the Nucleon Size with Relativistic Nuclear Collisions

The notion of the "size" of nucleons and their constituents plays a pivotal role in the current paradigm of the formation and the fluctuations of the quark-gluon plasma produced in high-energy nuclear collision experiments. Here, we report on state-of-the-art hydrodynamic results showing that the correlation between anisotropic flow, $v^{2}_{n}$, and the mean transverse momentum of hadrons, [$p_t$], possesses a unique sensitivity to the nucleon size in off-central heavy-ion collisions. We argue that existing experimental measurements of this observable support a picture where the relevant length scale characterizing the colliding nucleons is of order 0.5 fm or smaller, and we discuss the broad implications of this finding for future global Bayesian analyses aimed at extracting initial state and medium properties from nucleus-nucleus collision data, including $v^{2}_{n}$-[$p_t$] correlations. Determinations of the nucleon size in heavy-ion collisions will provide a solid independent constraint on the initial state of small system collisions, and will establish a deep connection between collective flow data in nucleus-nucleus experiments and data on deep inelastic scattering on protons and nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Randomized algorithms for accelerating linear algebraic computations

The project supported the development of new methodologies for performing matrix computations that form key building blocks in modern scientific computing, such as low rank approximation of matrices, and efficient representations of global operators that arise in simulations of physical phenomena.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

3D Printing of Cement-Based Materials Using Seawater for Simulated Marine Environments

Global demand for adaptable and rapidly deployable construction solutions in offshore, coastal, and fluvial environments continues to rise, driven by pressing needs to develop energy platforms, improve coastal resilience, and support emergency response in the face of natural disasters. Increased investment in human-made coastal infrastructure, such as piers, support structures for power lines, offshore wind farms, and seawall protection systems, further underscores this trend. This study investigates the development of printable concrete mixtures for underwater environments using seawater as a replacement for freshwater, using a 3D printing syringe-based extrusion system. The effect of seawater addition and the printing medium (in air vs. underwater) was assessed via rheological and mechanical performance characterization. The results indicate rheological properties are favorable for seawater adoption by producing mixtures with higher yield stress and viscosity with the same levels of admixtures used for freshwater. Seawater-based mixtures demonstrated superior dimensional stability compared to freshwater counterparts, maintaining cross-sectional geometry, while compressive strength results showed no statistical differences between in-air and underwater samples. However, flexural strength was significantly influenced by geometry and printing medium. These findings establish critical rheological parameters for printable underwater mixtures and highlight the need for optimized curing strategies and layer bonding techniques to improve interfacial strength in underwater 3D printing applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Transforming Buildings Around the World

Buildings are where we live, work, go to school, gather as a community, and so much more. Globally, buildings are responsible for 30% of energy consumption and 26% of energy-related emissions. The National Renewable Energy Laboratory (NREL) is committed to adapting tools and capabilities to support emerging economies and improve the energy efficiency and flexibility of their buildings.

building technology innovation↗

DOE OSTI2023

SPRUCE Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog: Supporting data

This data set contains measurements of anaerobic oxidation of methane (AOM), net methane (CH4) production, carbon dioxide (CO2) production, and gross CH4 production measurements from the SPRUCE experiment (Hanson et al. 2017). CH4 is greenhouse gas with 45 times the sustained global warming potential of CO2 over 100 years, which may have significant implications on global climate change. The process of AOM plays a large role in the extent of CH4 emissions from wetland environments like those at the SPRUCE experiment site. This study conducted two on different dates. In experiment 1, net CH4 and CO2 production were measured with a gas chromatograph through the peat profile at in situ temperatures of the SPRUCE plots four times from May to October, 2016 (2016-05 to 2016-10). Two treatments were examined, a Porewater Treatment that was a 1:1 volumetric peat:porewater slurry and a No Porewater Treatment that was field-moist peat with no porewater added. Additionally, net CH4 production were measured at frequent intervals (from 4 hr to 9 d) in peat from selected SPRUCE plots from soil collected on October 16, 2016 (2016-10-16). Samples were collected from the SPRUCE plots, immediately made anaerobic, and transported to the University of Oregon for rate measurements within several days of collection. In experiment 2, AOM, net CH4 production, CO2 production, and gross CH4 production were measured through the peat profile at in situ field temperatures once from samples collected in July, 2021 (2021-07). The same two porewater treatments were examined. AOM was measured with a 13CH4 tracer method using a Picarro G2201-i analyzer for isotopic CO2/CH4 quantification with a small stable isotope module attached. This data set contains three data files in comma separate (*.csv) format. This data set is associated with the following publication: Barney, M, AM Hopple, LL Gregory, JK Keller, and SD Bridgham. 2024. Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog. Soil Biology and Biochemistry, 190, 109316. https://doi.org/10.1016/j.soilbio.2024.109316.

SPRUCE Experiment, Marcell Experimental Forest, Me↗

DOE OSTI2021

Global Ethanol-Blended-Fuel Vehicle Compatibility Study

The objective of this study is to understand the impact of ethanol-blended fuel at various blending levels (10%, 15%, and 20% vol.) on "in-operation" vehicles built to differing emissions and manufacturing standards around the world. The study focuses on vehicles used in Canada, China, India, Indonesia, Japan, South Korea, and Mexico. Historical experience in the United States and Brazil informs the analysis. The primary study question is: Are vehicles in targeted countries physically and operationally compatible with ethanol blended fuel? For a fuel to be compatible with a vehicle, the fuel must perform its function as part of the integrated fuel-vehicle system, meaning: the car should start easily and drive normally, the fuel should not cause catastrophic fuel system leaks, the fuel should not cause corrosion or degradation of any engine or fuel system components (including emissions control components). The history of E10 use in the United States, beginning in 1978, was evaluated and shows no reliability or operability issues for cars dating back to pre-emissions-control times -- and likely included many cars manufactured in the 1960s. This strongly supports the contention that fuel chemistry and property differences between E0 and E10 are so small that any car made to international standards in the last 50 years will have a very high probability of being fully compatible with E10. This conclusion is supported by the experience in Brazil in the 1970s, where E10 was also introduced, and ethanol blending for conventional cars rapidly ramped up to even higher blend levels. A limited number of fuel system and component manufacturers supply the global market, including Bosch, Continental, Denso, Delphi, and Visteon. To reduce complexity, ethanol-compatible materials began to be integrated in fuel system designs globally. Fuel systems evolved over the following decades to incorporate ethanol-compatible materials with core subsystem families, such as in-tank fuel pumps used across several global vehicle original equipment manufacturers (OEMs). A similarly compelling case can be made that all cars at the Tier 1 (or equivalent) emissions-control technology level or higher are fully compatible with E15 blends, based on the data evaluated by the U.S. Environmental Protection Agency (EPA) and Ricardo in 2010. For cars at this technology level, the minor differences in fuel chemistry and properties between E10 and E15 are not significant. For E20, studies are not as extensive but are still highly significant. A long-term durability study conducted on mileage accumulation dynamometers presents convincing evidence that Tier 2 technology level cars have materials of construction and engine control authority for compatibility with E20, although this conclusion is not as strong as those drawn for E10 and E15, which are also partly based on real-world experience.

09 BIOMASS FUELS↗

DOE OSTI2024

A Refined Method to Translate Solar Data Quality Assessment Flags to Estimated Measurement Uncertainty

Integrating solar resource uncertainties due to radiometer measurement performance and operational data quality assessment can provide improved estimates of economic bankability, system design performance, and compliance of solar energy conversion systems. Estimating radiometer measurement uncertainty is an established procedure consistent with recognized best practices and international guidelines. SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the fourth of six for the Data Quality and Uncertainty Integration Project, presents a refined algorithm description for software to translate solar resource data quality assessment results into estimated uncertainty values in a Solar Resource Operational Uncertainty Integrator (SROUI) application. This algorithm requires three-component solar irradiance measurements - global horizontal irradiance, direct normal irradiance, and diffuse horizontal irradiance - collected at 1- to 60-minute intervals, as described in the previous deliverables. The development of this report as Deliverable 6.4 was an iterative process that included reviews and feedback from the project team on initial drafts designed to refine how the new software could best support determining solar resource data uncertainty. The results of this effort will contribute to the final software system development by National Renewable Energy Laboratory staff.

14 SOLAR ENERGY↗

DOE OSTI2024

Scientists’ call to action: Microbes, planetary health, and the Sustainable Development Goals

Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.

59 BASIC BIOLOGICAL SCIENCES↗