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DOE OSTI2022

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

Somnath, Suhas↗

DOE OSTI2024

Geothermal Uncertainty Representation in reV: the Renewable Energy Potential Model

We present a preliminary methodology for including geothermal resource uncertainty into the Renewable Energy Potential model, which estimates potential capacity and costs on a gridded surface at the national scale. The uncertainty outputs characterize the 10th, 50th and 90th percentile for geothermal resources using two energy capacity estimation equations. We then present a method and results that demonstrate how other geologic data layers, which may be indicative of permeability, can be used to inform the mean and standard deviation of the geothermal capacity. We demonstrate how the mean and standard deviation can be defined or partially informed by using collocated regression estimates and estimate errors, respectively . These regression results are from 36 observed geothermal power plants in the Great Basin region and are also used to benchmark the P10-P90 calculations.

exclusions↗

DOE OSTI2021

Valuing wind as a distributed energy resource: A literature review

As more distributed energy resources are deployed on electric grid systems across the world, it is important to identify, characterize, and quantify the value elements of different types of distributed energy resources so that policymakers, developers, and utilities can make informed energy deployment decisions. This paper focuses on the value of wind energy as a distributed energy resource (i.e., “distributed wind”). Because of a lack of distributed wind-specific valuation studies, in this review we document the current state of distributed energy resource valuation, analyze a wide array of distributed energy resource valuation metastudies, and identify several value elements for which we recommend developing more robust and standardized calculation methodologies for their potential inclusion in distributed wind valuation. These value elements are ancillary services and locational, resilience, reliability, and resource diversity benefits. Furthermore, this work lays the foundation for a future comprehensive framework for distributed wind valuation studies.

17 WIND ENERGY↗

NASA NTRS2016

Instrument for Analysis of Organic Compounds on Other Planets

The goal of this project is to develop the Instrument for Solvent Extraction and Analysis of Extraterrestrial Bodies using In Situ Resources (ISEE). Specifically, ISEE will extract and characterize organic compounds from regolith which is found on the surface of other planets or asteroids. The techniques this instrument will use are supercritical fluid extraction (SFE) and supercritical fluid chromatography (SFC). ISEE aligns with NASA's goal to expand the frontiers of knowledge, capability, and opportunities in space in addition to supporting NASA's aim to search for life elsewhere by characterizing organic compounds. The outcome of this project will be conceptual designs of 2 components of the ISEE instrument as well as the completion of proof-of-concept extraction experiments to demonstrate the capabilities of SFE. The first conceptual design is a pressure vessel to be used for the extraction of the organic compounds from the regolith. This includes a comparison of different materials, geometry's, and a proposition of how to insert the regolith into the vessel. The second conceptual design identifies commercially available fluid pumps based on the requirements needed to generate supercritical CO2. The proof-of-concept extraction results show the percent mass lost during standard solvent extractions of regolith with organic compounds. This data will be compared to SFE results to demonstrate the capabilities of ISEE's approach.

supercritical fluids↗

DOE OSTI2020

Materials Characterization Techniques Lecture Series: X-Ray Diffraction, A Summary of LANL's Materials Capabilities in MPA-11 [Slides]

This presentation provides an overview on X-Ray Diffraction (XRD) to cover background, fundamentals, limitations, best practices, applications, analysis, software, and resources. To summarize: XRD is a great tool for characterizing solid crystalline samples. X-Rays are E-Mag radiation and generate diffraction profiles based on the phase of the sample. Diffraction patterns are unique to the phase of the sample. Powder diffraction gives us better diffraction profiles. We can obtain both qualitative and quantitative data. Analysis requires us to know a little about our sample and a lot about our diffractometer.

36 MATERIALS SCIENCE↗

NASA NTRS2023

Ch. 12. A Theoretical Approach to Management of Limited Attentional Resources to Support the m:N Operation in Advanced Air Mobility Ecosystem

Advanced air mobility (AAM) technologies incorporate increasingly autonomous systems that allow fully remote, independent, and intelligent operation of air vehicles to support the transportation of goods and passengers within and across urban and rural areas. With a myriad of automated technologies enabling the AAM ecosystem, the human operator’s role will likely be a passive supervisory monitor of the air vehicles, involving increasingly fewer humans (m) that manage many more autonomous systems (N), or m:N operations. Unfortunately, the human performance literature suggests that human operators will exhibit poor supervision of numerous autonomous agents due to the limits of attentional resources in the operators. In the general human information-processing model, a human operator exercises a limited pool of attentional resources to engage various information-processing stages including detecting, perceiving, comprehending, and predicting objects around them. Yamani and Horrey (2018) expanded the human information-processing model to characterize a tradeoff between information-processing demand and resource relief that automation brings in the context of automated driving. In their model, a driver interacting with an automated driving system is assumed to reallocate resources “freed” by automation to support other information-processing stages required for successful task performance. A future AAM ecosystem enabled by an orchestration of advanced automated systems, however, requires a single operator to interact with more than one air vehicle with varying levels and degrees of automated systems, making the traditional framework of human-automation interaction insufficient. To address this gap, we provide a review of the literature on situation assessment and trust, two constructs identified as critical for a fuller understanding of intimate and intricate interactions between a human operator and multiple air vehicles equipped with increasingly autonomous systems. Then, we propose an expansion of Yamani and Horrey’s (2018) model to motivate systematic research on the human operator’s role, identify factors that influence resource allocation and guide human-centered design of an interface supporting the m:N operation in the AAM environment.

Advanced Air Mobility↗

DOE OSTI2023

Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic

Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.

17 WIND ENERGY↗

DOE OSTI2024

Deploying a New AI Software Tool for Rapid Characterization & Quantification of Unconventional Sources of Critical Minerals

Poster for the 2024 NETL Resource Sustainability Meeting. The poster presents a new project award by the Office of Technology Transitions to accelerate application and commercial utilization of an NETL-developed technology to rapidly characterize critical mineral occurrences within secondary and/or unconventional feedstocks, such as coal refuse or waste impoundments.

Creason, Christopher↗

DOE OSTI2022

Calibrating the Classical Hardness of the Quantum Approximate Optimization Algorithm

The trading of fidelity for scale enables approximate classical simulators such as matrix product states (MPSs) to run quantum circuits beyond exact methods. A control parameter, the so-called bond dimension $\mathcal{χ}$ for MPSs, governs the allocated computational resources and the output fidelity. Here, we characterize the fidelity for the quantum approximate optimization algorithm by the expectation value of the cost function that it seeks to minimize and find that it follows a scaling law $\mathscr{F}$(ln $\mathcal{χ}$/N), where N is the number of qubits. With ln $\mathcal{χ}$ amounting to the entanglement that a MPS can encode, we show that the relevant variable for investigating the fidelity is the entanglement per qubit. Importantly, our results calibrate the classical computational power required to achieve the desired fidelity and benchmark the performance of quantum hardware in a realistic setup. For instance, we quantify the hardness of performing better classically than a noisy superconducting quantum processor by readily matching its output to the scaling function. Moreover, we relate the global fidelity to that of individual operations and establish its relationship with $\mathcal{χ}$ and N. We sharpen the requirements for noisy quantum computers to outperform classical techniques at running a quantum optimization algorithm in speed, size, and fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Community-Based Transactive Coordination Mechanism for Enabling Grid Edge Systems

The changing landscape of the electricity industry, characterized by a surge in distributed energy resources (DERs) and proactive customers, necessitates practical solutions for coordinated operations especially at the distribution-level. This paper introduces a community-based transactive coordination mechanism designed to incentivize customers for providing localized and system-level services reflected through real-time prices. The work presents a bidding approach for communities with DERs, such as solar photovoltaic (PV) and battery energy storage systems (BESS), to formulate their price-responsiveness for retail energy coordination, emphasizing a community-centric model. By sending bidding curves to a third-party, the mechanism enables customers with DER assets to actively participate in localized coordination with the load serving entity (LSE), thereby supplementing each other’s and even the utilities needs through a shared energy economy. The proposed transactive mechanism is implemented leveraging a co-simulation framework that integrates a distribution grid simulator and Python-based agents for performance evaluation. Collaboration with a local utility to access real distribution feeder models and consumption profiles yields simulation results demonstrating the potential to reduce costs by 12\% for communities with DERs like PV and BESS.

Community-based coordination, grid-edge systems, R↗

DOE OSTI2022

Response of Total (DNA) and Metabolically Active (RNA) Microbial Communities in Miscanthus × Giganteus Cultivated Soil to Different Nitrogen Fertilization Rates

Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Structural Characterization of Potential Carbon Dioxide Reservoirs and Adjacent Strata within the Llandovery Silurian to Middle Devonian Strata of Ohio

As part of the Midwest Regional Carbon Sequestration Partnership (MRCSP)’s regional characterization project, the Ohio Department of Natural Resources, Division of Geological Survey evaluated the structure of nine formations in the Appalachian Basin of Ohio to assess seal integrity and whether carbon dioxide (CO 2 ) migration pathways could pose a potential risk.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Princeton University (Abstract)

The National Energy Technology Laboratory (NETL) and Princeton University will collaborate in the development of microwave-plasma technology to convert methane into hydrogen and valuable solid carbon materials. The effort will combine NETL’s vast resources for microwave-enhanced process development, characterization, and design with Princeton University’s extensive expertise in the study of non-equilibrium plasmas employing supersonic nozzles. Lab-scale experiments will be conducted for different conditions to convert and compare their respective performance in hydrogen production. Computational modeling will be performed to verify results from experimental studies conducted in both labs.

08 HYDROGEN↗

NASA NTRS1978

The engineering analysis of solar radiation

A necessary precursor to construction of well-designed, efficient, and economically viable solar energy systems is the engineering analysis not only of the systems themselves but also of the solar radiation that will drive them. This paper presents the first steps in such an analysis to support the design of solar thermal power systems. A rationale for development of an integrated approach to this analysis is outlined, and elements of the approach are described. A dynamic computer simulation of a conceptual system was employed in an initial sensitivity analysis to explore how performance estimates might be affected by the precision and amount of detail in solar radiation data used as model input. A measurement program, including instrumentation, used to characterize precisely and in detail the solar resource at one location is described as is a probabilistic model derived from it, for predicting insolation as a function of time.

Reid, M. S.↗

NASA NTRS1995

Alternate assembly sequence databook for the Tier 2 Bus-1 option of the International Space Station

The JSC International Space Station program office requested that SSB prepare a databook to document the alternate space station assembly sequence known as Tier 2, which assumes that the Russian participation has been eliminated and that the functions that were supplied by the Russians (propulsion, resupply, initial attitude control, communications, etc.) are now supplied by the U.S. Tier 2 utilizes the Lockheed Bus-l to replace much of the missing Russian functionality. The space station at each stage of its buildup during the Tier 2 assembly sequence is characterized in terms of of properties, functionality, resource balances, operations, logistics, attitude control, microgravity environment and propellant usage. The assembly sequence as analyzed was defined by JSC as a first iteration, with subsequent iterations required to address some of the issues that the analysis in this databook identified. Several significant issues were identified, including: less than desirable orbit lifetimes, shortage of EVA, large flight attitudes, poor microgravity environments, and reboost propellant shortages. Many of these issues can be resolved but at the cost of possible baseline modifications and revisions in the proposed Tier 2 assembly sequence.

Brewer, L. M.↗

NASA NTRS2012

Development of Carbon Dioxide Removal Systems for Advanced Exploration Systems

"NASA's Advanced Exploration Systems (AES) program is pioneering new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit" (NASA 2012). These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must not only blast out of earth's gravity well as during the Apollo moon missions, but also launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by seeking more robust pelletized sorbents, evaluating structured sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach, which is then implemented in a full-scale integrated atmosphere revitalization test. This paper describes the carbon dioxide (CO2) removal hardware design and sorbent screening and characterization effort in support of the Atmosphere Resource Recovery and Environmental Monitoring (ARREM) project within the AES program. A companion paper discusses development of atmosphere revitalization models and simulations for this project.

Knox, James C.↗

NASA NTRS2011

Comparing the Earth Impact Flux from Comets and Near-Earth Asteroids

Long-period comets (LPC), defined here as those active comets with orbital periods greater than 200 years, are the most difficult objects to mitigate should one be found on an Earth threatening trajectory. The arrival of these objects from the distant Oort cloud cannot be predicted and the impact warning time would be measured in a few months - not years. At the distance of Jupiter, an inactive cometary nucleus with a diameter of one kilometer and a geometric albedo equal to 0.04 would have an apparent magnitude fainter than 25 near opposition and, hence would be well outside the detection capability of current NEO search telescopes. In general LPCs do not become active, and hence discoverable, until inside the orbit of Jupiter and it takes but nine months for a LPC to travel the distance from Jupiter's orbit to that of the Earth.Estimating the impact energy for long-period comets is particularly difficult because the sizes and masses of these objects are not well known. Their solid nuclei are hidden from ground-based telescopes by their gas and dust atmospheres and even when nearby spacecraft observations can determine a size and shape for a cometary nucleus, there are no direct determinations of any cometary mass or bulk density to date. However, a variety of indirect bulk density determinations consistently provide values below one gram per cubic centimeter, the value for water. From measurements made by the Deep Impact spacecraft during its encounter with comet Tempel 1 in July 2005, the bulk density was estimated to be 0.6 grams per cubic centimeter. The mean impact velocity of a LPC is about 51 km/s, three times the 17 km/s value for a typical near-Earth asteroid (NEA) so the impact energy for an LPC would be 9 times that of a NEA of similar mass. However, the bulk density of a comet (approx. 0.6 g/cu cm) is several times less than the density of a stony NEA (approx. 2.6 g/ cu cm) so for a LPC and a stony NEA of the same size, the LPC's impact energy would be about twice that of the NEA.To properly allocate the limited resources available for NEO surveys and physical characterization, it is important to understand the relative threat from long-period comets versus the threat posed by near-Earth asteroids.

near Earth objects↗

NASA NTRS2017

Documenting Surface and Sub-surface Volatiles While Drilling in Frozen Lunar Simulant

NASA's Resource Prospector (RP) mission is intended to characterize the three-dimensional nature of volatiles in lunar polar regions and permanently shadowed regions. RP is slated to carry two instruments for prospecting purposes. These include the Neutron Spectrometer System (NSS) and Near-Infrared Volatile Spectrometer System (NIRVSS). A Honybee Robotics drill (HRD) is intended to sample to depths of 1 m, and deliver a sample to a crucible that is processed by the Oxygen Volatile Extraction Node (OVEN) where the soil is heated and evolved gas is delivered to the gas chromatograph / mass spectrometer of the Lunar Advanced Volatile Analysis system (LAVA). For several years, tests of various sub-systems have been undertaken in a large cryo-vacuum chamber facility (VF-13) located at Glenn Research Center. In these tests a large tube (1.2 m high x 25.4 cm diameter) is filled with lunar simulant, NU-LHT-3M, prepared with known abundances of water. There are thermo-couples embedded at different depths, and also across the surface of the soil tube. The soil tube is placed in the chamber and cooled with LN2 as the pressure is reduced to approx.5-6x10(exp -6) Torr. Here we discuss May 2016 tests where two soil tubes were prepared and placed in the chamber. Also located in the chamber were 5 crucibles, an Inficon mass spectrometer, and a trolly permitting x-y translation, where the HRD and NIRVSS, were mounted. The shroud surrounding the soil tube was held at different temperatures for each tube to simulate a warm and cold lunar environment.

Oxygen Volatile Extraction Node↗