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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Component-to-Optimization Workflow Demonstration

This report aims to demonstrate workflow-generating algorithms for optimizing dispatch across a broad range of Integrated Energy System applications using the Framework for Optimization of Resources and Economics (FORCE) tool suite. The optimization is performed at two different time scales. In the coarse time scale, the optimization focuses on a class of energy sources and consumers and aims to find the optimal combinations and flows of energy based on real-time price data information. In the fine time scale, the optimization focuses on a specific thermal energy delivery system and aims to find the optimal setpoints of components in order to meet the energy demands from coarse-time-scale optimizations. In this demonstration, the coarse-scale optimization is implemented using the newly developed Dispatch Optimization Variable Engine (DOVE), while the fine-scale optimization used Optimization of Real-Time Capacity Allocation (ORCA).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗
DOE OSTI2024

Structure and Dynamics of Aqueous Electrolytes at Quartz (001) and (101) Surfaces

Here, understanding and describing reactivity at mineral-water interfaces such as ion adsorption, the kinetics of dissolution, or surface charge development depends on our ability to improve the accuracy of electrical double layer (EDL) models. While molecular dynamics (MD) simulations are routinely used to investigate the structure and energetics of adsorbed ions comprising the EDL, less attention is paid to their self-diffusion dynamics, which can uniquely inform on coupling to interfacial reactions. Here we use MD to investigate both the organization and diffusion dynamics of water and electrolyte ions (NaCl, KCl, CaCl 2 ) at hydroxylated quartz (001) and (101) surfaces, a comparison which allowed us to assess surface structural effects of corrugation and silanol density. We found that inner- versus outer-sphere complex formation depends on cation size and charge but not necessarily hydration energies. Participation of surface silanols in the hydration spheres of Na + and K + generally indicated their preference for inner-sphere complexation, but this depends strongly on the orientation of the surface considered through its influence over the organization and dynamics of adsorbed water layers. In particular, surface orientation substantially affects the diffusive behavior of the near-surface water. Na + was found to decrease the mobility of water in the first layer, consistent with an increasing frequency of hydrolysis implied by faster quartz dissolution rates observed in experiments via the well known salt effect. Our results are also in good agreement with the observed dissolution rate of quartz vs. surface adsorption strength measure by Dove and Nix. This study sets the stage for a forthcoming paper examining how the dynamics at quartz/electrolyte interfaces are influenced by externally applied electric fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Passerine Bird Surveys for the Lawrence Livermore National Laboratory Site 200

Pursuant to Subcontract Number B644180 between ECORP Consulting, Inc. (ECORP) and Lawrence Livermore National Security, LLC. (LLNS) at Lawrence Livermore National Laboratory (LLNL), ECORP conducted passerine bird and waterfowl surveys at LLNL Livermore Site 200 (Site 200) during the spring and summer of 2021. While the point-count surveys were considered passerine and waterfowl surveys, other non-passerine species (e.g. raptors, doves, woodpeckers, hummingbirds) were surveyed for as well. LLNL conducts annual monitoring for nesting raptors at the Livermore Site 200. Because of this, raptors were not included as target species in this scope of work. The purpose of the surveys was to document the presence and abundance of all avian species in support of a Site-wide Environmental Impact Statement. Particular focus of the survey was on special status bird species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Avian Surveys Report for the Lawrence Livermore National Laboratory Arroyo Mocho Pumping Station

Pursuant to Subcontract Number B644180 between ECORP Consulting, Inc. and Lawrence Livermore National Security, LLC. at Lawrence Livermore National Laboratory (LLNL), ECORP conducted passerine bird and raptor surveys at the Arroyo Mocho pumping station site during the spring and summer of 2021. While the point-count survey was considered a passerine survey, other non-passerine species (e.g. doves, woodpeckers, hummingbirds) were surveyed for as well. The purpose of the surveys was to document the presence and abundance of all avian species within the survey area in support of a Site-wide Environmental Impact Statement. Particular focus of the survey was on special status bird species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Normalcy, Magic, Miracle and Error: Emergence along a Reversibility Spectrum

Formation of a butterfly from a pupa, extraction of a live dove from a magician’s empty hat, generation of new particles from high-energy particle collisions and spawning a new dream world from mind in sleep are all examples of a common, fuzzy notion called ‘emergence’. Emergence is intuitively defined in a subjective manner in various contexts, yet it eludes a universally acceptable objective definition. In this paper1 I pin the concept of emergence to the element of surprise in a phenomenon. I then propose a characterisation of emergence by first defining surprise in terms of an objective dimension called reversibility. Using this definition, I categorise the various notions of emergence into three main classes: (1) weak emergence in which the evolution from pre-emergence to post-emergence states is fully reversible and hence evokes the least amount of surprise, (2) quasi emergence in which the evolution from pre-emergence to post-emergence states holds surprise in the form of gaps in reversibility, but the gaps can be overcome via placeholders such as deterministic pseudo-randomness, and (3) strong emergence in which it is impossible to find any reversible description of evolution from pre-emergence states to post-emergence states, thereby making the element of surprise fundamental and impossible to redress. In fact, in the strong emergence case, the pre- and post-emergence states continue to co-exist despite an apparent transformation of the pre-emergence state to post-emergence state. These definitions are used to explain instances of emergence, organised along a continuous spectrum as normality, magic, miracle and error.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Metastable solubility and local structure of amorphous calcium carbonate (ACC)

The properties of amorphous calcium carbonate provide the foundation for understanding mineralization of calcified skeletons but inconsistencies between studies suggest the physical picture is incomplete. This study quantifies the metastable solubility and structure of ACC produced under a series of chemical conditions. Using complementary in situ methods that quantify ACC structure (in situ PDF analysis) in parallel with chemical composition (TGA, ICP-OES), we find two short-range structures are produced that also show distinct morphological differences. Conditions with high carbonate ion concentrations stabilize a Ca-rich ACC with short-range order that is independent of Mg content. In contrast, low carbonate solutions favor Mg-rich ACC with mixed Ca- and Mg-short range order. Measurements of solubility product determined from supersaturated and undersaturated conditions find the distinctive structures are related to solution carbonate activity while solubility is primarily determined by the magnesium content of the solid. Bulk solubility is a composite that concurs with established values. The findings demonstrate the type of ACC that forms is tuned by Mg2+ and CO3-2- concentration and suggest ACC structure, not bulk composition, is a reliable indicator of intermediate phase. This chemical framework also provides a basis for interpreting apparent differences between observations of ACC in synthetic and natural systems that reconciles previous structural studies.

Mergelsberg, Sebastian T.↗
DOE OSTI2021

Axion Dark Matter Experiment: Detailed design and operations

Axion dark matter experiment ultra-low noise haloscope technology has enabled the successful completion of two science runs (1A and 1B) that looked for dark matter axions in the 2.66–3.1 μeV mass range with Dine–Fischler–Srednicki–Zhitnisky sensitivity. Therefore, it is the most sensitive axion search experiment to date in this mass range. Here, we discuss the technological advances made in the last several years to achieve this sensitivity, which includes the implementation of components, such as the state-of-the-art quantum-noise-limited amplifiers and a dilution refrigerator. Furthermore, we demonstrate the use of a frequency tunable microstrip superconducting quantum interference device amplifier in run 1A, and a Josephson parametric amplifier in run 1B, along with novel analysis tools that characterize the system noise temperature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Axion dark matter experiment: Run 1B analysis details

Searching for axion dark matter, the ADMX Collaboration acquired data from January to October 2018, over the mass range 2.81–3.31 μeV, corresponding to the frequency range 680–790 MHz. Using an axion haloscope consisting of a microwave cavity in a strong magnetic field, the ADMX experiment excluded Dine-Fischler-Srednicki-Zhitnisky (DFSZ) axions at 90% confidence level and 100% dark matter density over this entire frequency range, except for a few gaps due to mode crossings. This paper explains the full ADMX analysis for run 1B, motivating analysis choices informed by details specific to this run.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

The Role of Chemistry in Fracture Pattern Development and Opportunities to Advance Interpretations of Geological Materials

Abstract Fracture pattern development has been a challenging area of research in the Earth sciences for more than 100 years. Much has been learned about the spatial and temporal complexity inherent to these systems, but severe challenges remain. Future advances will require new approaches. Chemical processes play a larger role in opening‐mode fracture pattern development than has hitherto been appreciated. This review examines relationships between mechanical and geochemical processes that influence the fracture patterns recorded in natural settings. For fractures formed in diagenetic settings (~50 to 200 °C), we review evidence of chemical reactions in fractures and show how a chemical perspective helps solve problems in fracture analysis. We also outline impediments to subsurface pattern measurement and interpretation, assess implications of discoveries in fracture history reconstruction for process‐based models, review models of fracture cementation and chemically assisted fracture growth, and discuss promising paths for future work. To accurately predict the mechanical and fluid flow properties of fracture systems, a processes‐based approach is needed. Progress is possible using observational, experimental, and modeling approaches that view fracture patterns and properties as the result of coupled mechanical and chemical processes. A critical area is reconstructing patterns through time. Such data sets are essential for developing and testing predictive models. Other topics that need work include models of crystal growth and dissolution rates under geological conditions, cement mechanical effects, and subcritical crack propagation. Advances in machine learning and 3‐D imaging present opportunities for a mechanistic understanding of fracture formation and development, enabling prediction of spatial and temporal complexity over geologic timescales. Geophysical research with a chemical perspective is needed to correctly identify and interpret fractures from geophysical measurements during site characterization and monitoring of subsurface engineering activities.

58 GEOSCIENCES↗
DOE OSTI2022

Climatic controls on soil and saprock nitrogen distribution and persistence in the Sierra Nevada

Nitrogen (N) is an essential nutrient in soil that regulates plant growth, terrestrial sequestration of atmospheric carbon dioxide, and persistence of organic compounds. However, major knowledge gaps remain about how climate change may impact N accumulation and persistence, especially in deep soil and saprock (friable weakly weathered bedrock). Our objective was to understand how climate impacts the accumulation of N in soil and saprock and how climate impacts soil N distribution, persistence, and mechanisms of N persistence. We investigated N concentration in bulk soil and density fractions. We estimated N persistence along a bio-climatic sequence—sites range from a low-elevation oak savannah, mid-elevation pine-oak/mixed-conifer forest, to a high-elevation subalpine forest—in the southern Sierra Nevada in California. A combination of radiocarbon and elemental composition measurements along with a first-order kinetic model was used. The N concentration in the bulk soil and density fractions declined with depth, and there was a relatively greater mineral-associated heavy fraction (HF) N in deeper samples. The cooler/wetter mixed conifer site held 37% of profile N in saprock, which was greater than that of the entire soil profile at the drier/hotter oak savannah. The majority of N in soil, which was in the HF, was not influenced by climate proxies tested. However, both unprotected and occluded fractions of N were strongly influenced by climate. Soil N mean residence time (MRT) showed that drier/hotter climates have a shorter MRT, compared to mid-elevation sites with cooler/wetter climates. The effect of climate on deep saprock N storage might be indirect, primarily through climatic influence on the thickness of saprock. Overall, our findings suggest the mineral-associated HF N pool will not be vulnerable to changes in climate and will continue to contribute to the persistent soil N pool. The amount of topsoil and subsoil unprotected and occluded N can be explained by gross primary productivity and mean annual precipitation indicating that changes in climate can influence N partitioning. N stored in deep soil and saprock may be less vulnerable to climate than N stored in drier/hotter climates with less deeply stored N. It is critical to dig deeper to understand terrestrial ecosystems’ response to climate.

58 GEOSCIENCES↗