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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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At least 127 records · Page 7

An Assessment of Energy Potential at Non-Powered Dams in the United States

The United States has produced clean, renewable electricity from hydropower for more than 100 years, but hydropower-producing facilities represent only a fraction of the infrastructure development that has taken place on the nation’s waterways. In contrast to the roughly 2,500 dams that provide 78 gigawatts (GW) 1 of conventional and 22 GW of pumped-storage hydropower, the United States has more than 80,000 non-powered dams (NPDs)—dams that do not produce electricity—providing a variety of services ranging from water supply to inland navigation. Importantly, many of the monetary costs and environmental impacts of dam construction have already been incurred at NPDs, so adding power to the existing dam structure can often be achieved at lower cost, with less risk, and in a shorter timeframe than development requiring new dam construction. The abundance, cost, and environmental favorability of NPDs, combined with the reliability and predictability of hydropower, make these dams a highly attractive source for expanding the nation’s renewable energy supply. To better characterize this unique national resource, the U.S. Department of Energy (DOE) Wind and Water Power Program has undertaken a national-scale analysis of U.S. dams to determine the ability of NPDs to provide hydroelectric power. DOE’s Oak Ridge National Laboratory (ORNL), with input from DOE’s Idaho National Laboratory, quantified the potential capacity and generation available from adding power production capability to U.S. NPDs. Of the more than 80,000 NPDs throughout the U.S., 54,391 dams were analyzed, with remaining dams eliminated from consideration due to erroneous geographic information, or erroneous flow or drainage area attributes that could not be resolved and corrected through independent investigation of maps and records. Anecdotal information suggests that these dams with missing or erroneous information are likely to be relatively small or have low potential to produce hydroelectric energy. Dams with a reported height of less than five feet were also excluded from analysis. A thorough quality control and review process ensured that the 54,391 remaining NPDs were analyzed and characterized as accurately as possible. Figure ES-1 demonstrates the spatial and capacity potential distribution of the nation’s NPDs. Electric generating capacities included in the report were calculated using the assumption that all water passing a facility would be available for conversion into electrical energy and that hydraulic head at the facility would remain constant. The analysis did not consider the economic feasibility of developing each unpowered facility. The assessment provides preliminary information for stakeholders (such as developers, municipal planners, and policymakers), who can further evaluate the potential to increase hydropower production at NPD sites. Developers could use the information provided in this assessment to focus on more detailed analysis of sites that demonstrate a reasonable potential for being developed. Adding power to U.S. NPDs has the potential to add up to 12 GW (12,000 megawatts or MW) of new renewable capacity—a potential equivalent to increasing the size of the existing conventional hydropower fleet by 15%. A majority of this potential is concentrated in just 100 NPDs, which could contribute approximately 8 GW of clean, reliable hydropower; the top 10 facilities alone could add up to 3 GW of new hydropower. Eighty-one of the 100 top NPDs are U.S. Army Corps of Engineers (USACE) facilities, many of which, including all of the top 10, are navigation locks on the Ohio River, Mississippi River, Alabama River, and Arkansas River, as well as their major tributaries. This study also shows that dams owned by the U.S. Bureau of Reclamation hold the potential to add approximately 260 MW of capacity; the Bureau has also engaged in an effort to conduct a more detailed evaluation of its own facilities.

13 HYDRO ENERGY↗

Advanced Numerical Model for Irradiated Concrete

In this report, we establish a numerical model for concrete exposed to irradiation to address these three critical points. The model accounts for creep in the cement paste and its coupling with damage, temperature and relative humidity. The shift in failure mode with the loading rate is also properly represented. The numerical model for creep has been validated and calibrated against different experiments in the literature [Wittmann, 1970, Le Roy, 1995]. Results from a simplified model are shown to showcase the ability of numerical homogenization to simulate irradiation effects in concrete. In future works, the complete model will be applied to the analysis of the irradiation experiments of Elleuch et al. [1972] and Kelly et al. [1969]. This requires a careful examination of the experimental environmental conditions as in both cases certain critical information are missing, including the relative humidity history. A sensitivity analysis will be conducted to provide lower and upper bounds of the concrete expansion under irradiation, and check if the scatter in the simulated results matches the one found in experiments. The numerical and experimental results will be compared in terms of expansion and loss of mechanical stiffness and strength. Both effects should be captured accordingly by the model to validate it. Once the model has been validated on these two experiments, it can be applied to simulate concrete from nuclear power plants. To do so, the materials used in these concrete must be as well characterized as possible. The main parameters required are the mechanical properties of each constituent in the concrete (aggregates, cement paste), namely the elastic modulus, the creep properties, the tensile and compressive strength, the thermal expansion coefficient, and the drying shrinkage. These can be either measured experimentally, estimated from the initial composition in the case of cement paste, or back-calculated from mechanical tests on concrete. If some are unknown, a sensitivity analysis must be carried out to provide lower and upper bounds of the material behaviour. Finally, the model can be used as a basis to formulate a macroscopic material model for concrete subject to irradiation, which later can be used in structural analyses to estimate the structural impact of irradiation on nuclear power plants.

36 MATERIALS SCIENCE↗

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Gregg, W. W.↗

Persistent neural activity in head direction cells

Many neurons throughout the rat limbic system discharge in relation to the animal's directional heading with respect to its environment. These so-called head direction (HD) cells exhibit characteristics of persistent neural activity. This article summarizes where HD cells are found, their major properties, and some of the important experiments that have been conducted to elucidate how this signal is generated. The number of HD and angular head velocity cells was estimated for several brain areas involved in the generation of the HD signal, including the postsubiculum, anterior dorsal thalamus, lateral mammillary nuclei and dorsal tegmental nucleus. The HD cell signal has many features in common with what is known about how neural integration is accomplished in the oculomotor system. The nature of the HD cell signal makes it an attractive candidate for using neural network models to elucidate the signal's underlying mechanisms. The conditions that any network model must satisfy in order to accurately represent how the nervous system generates this signal are highlighted and areas where key information is missing are discussed.

Non-NASA Center↗

Explanation Capabilities for Behavior-Based Robot Control

A recent study that evaluated issues associated with remote interaction with an autonomous vehicle within the framework of grounding found that missing contextual information led to uncertainty in the interpretation of collected data, and so introduced errors into the command logic of the vehicle. As the vehicles became more autonomous through the activation of additional capabilities, more errors were made. This is an inefficient use of the platform, since the behavior of remotely located autonomous vehicles didn't coincide with the "mental models" of human operators. One of the conclusions of the study was that there should be a way for the autonomous vehicles to describe what action they choose and why. Robotic agents with enough self-awareness to dynamically adjust the information conveyed back to the Operations Center based on a detail level component analysis of requests could provide this description capability. One way to accomplish this is to map the behavior base of the robot into a formal mathematical framework called a cost-calculus. A cost-calculus uses composition operators to build up sequences of behaviors that can then be compared to what is observed using well-known inference mechanisms.

Huntsberger, Terrance L.↗

Using Random Hiveminds to Predict Solar Energetic Particles (SEPs)

The Problem: The use of conventional neural networks (CoNNs) to predict SEPs has become popular, but neural network models do not follow one-size-fits-all approaches and their chaotic natures can yield completely different results on identical data sets. Committees of neural networks identical in input features have been used to solve this problem by (Aminalragia et al., 2021), but they have the possibility of all agreeing together in lockstep and missing crucial information. The Solution: (O’Keefe et al., 2023) propose a solution consisting of neural network estimators in an ensemble, but with features randomly removed from them in a layout known as a random hivemind (RH). The decision weight, learning rate, and epoch count of each member in this ensemble are boosted in relation to how well its individual features perform in a chi-square test.

SMD↗

Evaluation of Water and Energy Cycles in Contemporary Atmospheric Reanalyses in US Basins

Global atmospheric reanalyses have become an important tool for climate studies, owing to the inclusion of observation driven model quantities that are not easily observed, if at all. This includes the study of regional water and energy budgets, despite the fact that the physical terms of the budgets do not balance, owing in large part to the influence of assimilated observations. Here, we focus on the regional water and energy budgets for key river basins in the US, related to the Humans and Hydroclimate in the US (H2US, a Global Energy and Watercycle EXchanges, GEWEX, regional hydroclimate project). Regional budgets and their residuals (related to the assimilated observations) from contemporary reanalyses will be evaluated and intercompared to assess the improvements over previous reanalyses and identify their strengths and weaknesses as contributions to H2US. When available, the observational analysis increments will be quantified directly, and as residuals when that information is missing. Early results show improvements over the Mississippi River basin water cycle closure, and reduced analysis increments. However, the energy analysis increments show non negligible seasonality. Results for the Colorado River basin and National Climate Assessment (NCA) regions will also be presented. The results will emphasize the need for reanalyses and models to produce complete budget equation terms.

Michael Bosilovich↗

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in reference two. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized* data are perfect; 2. Normality: The prior and posterior PDF are normal; and 3. Linearity: The model is linear. In this work we outline how the framework in 1 could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in 1 to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implement- ing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS, and the stochastic method, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Radiation-Induced Fate of Fission Product Iodine in Molten Salts

Understand and Predict Radiation-Induced Iodine Speciation, Chemistry, and Transport in High-Temperature Molten Salts Award Number: DE-AC07-05ID1451 Gregory P. Holmbeck (Gregory.Holmbeck@inl.gov), Center for Radiation Chemistry Research, Idaho National Laboratory, 1955 N. Fremont Avenue Idaho Falls, ID, 83415, USA. Project Scope The goal of this Chemical and Materials Sciences to Advance Clean Energy Technologies and Low-Carbon Manufacturing project is to understand and predict the radiation-induced speciation, chemistry, and transport of fission product iodine in the triumvirate extremes of high-temperature, ionizing radiation, and corrosive molten salts. This missing fundamental information is critical for the accelerated development and deployment of safe, clean nuclear energy based on molten salt reactor (MSR) and pyrochemical reprocessing technologies. The central hypothesis driving this research is, the radiation-induced conversion of iodide will yield an extensive suite of transient and steady-state iodine radiolysis products that will alter the bulk chemical and physical properties of the irradiated molten salt system—the speciation, distribution, and chemical transport of which will be dictated by the composition and the availability of multivalent metal cations and metal alloy interfaces. To test this hypothesis, this project initiated three synergistic Research Objectives: (1) determine how the inclusion of iodine/iodide influences the chemical and physical properties of complex molten salt mixtures; (2) elucidate the speciation and fundamental chemical behavior of transient and steady-state iodine/iodide species formed by the irradiation of molten and solid salt mixtures; and (3) understand the influence of interfacial processes on determining the final disposition of iodine in high temperature molten salts, notably the structure and chemical speciation of iodine at metal-salt interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data about data – when, why and how metadata can support the digital plant

A structured approach for recording data quality and contextual information about how and why a signal exists – i.e. metadata – is central to interpret and use sensor data correctly. This is becoming increasingly important with the global trend with data-driven applications such as digital twins and AI-models. But a structured metadata collection and organization of sensor data is not routine in most plants, which can result in lost information and missed opportunities to make use of the investments made in the data collection. Therefore, the IWA task group on Metadata Collection and Organization in wastewater resource recovery systems (MetaCO) was initiated in 2020 and recently delivered the IWA scientific and technical report number 31. The report gives and in-depth description about metadata in water resources recovery facilities (WRRFs) and is available as open access at IWA publishing. The report is the outcome of the collaboration between more than 80 water professionals with the intention to serve WRRF data users with a guide on how to structure and make use of metadata throughout the data pipeline in order to maximize the value of sensor data.

Alferes, Janelcy [VITO, Belgium]↗

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.

Nguyen, Tri [Northwestern U. (main); SkAI, Chicago↗

Particle Physics Division Lifting Fixtures Database Restructure

In this project, a thorough investigation is conducted to determine the current placements of all lifting fixtures within the Particle Physics Division (PPD) buildings - as well as whether which ones are still operable. Briefly, the reasoning as to why these lifting fixtures must be found and the database must be updated is covered in the beginning sections of the report. Many tools and fixtures get moved around and forgotten about, and Fermilab’s systems have been updated more than a few times throughout the years, so data can get lost and forgotten about. Considering that many of these lifting fixtures have not been used in years or there is missing, impertinent information that is required by Fermilab’s modern standards and safety regulations. Lifting fixtures found at each site are measured, photographed, and logged; later analyzed to determine if they are under PPD’s purview or another department so that the respective authorities can be notified. Once maximum information is found for all the fixtures they are formatted to 2025 Fermilab standards in an easily accessible digital list for PPD employees.

Creedon, Carroll [Unlisted, US, IL]↗

Observations of Dust Using the NASA Geoscience Laser Altimeter System (GLAS): New New Measurements of Aerosol Vertical Distribution From Space

On January 12, 2003 NASA launched the first satellite-based lidar, the Geoscience Laser -Altimeter System (GLAS), onboard the ICESat spacecraft. The GLAS atmospheric measurements introduce a fundamentally new and important tool for understanding the atmosphere and climate. In the past, aerosols have only been studied from space using images gathered by passive sensors. Analysis of this passive data has lead to an improved understanding of aerosol properties, spatial distribution, and their effect on the earth's climate. However, these images do not show the aerosol's vertical distribution. As a result, a key piece of information has been missing. The measurements now obtained by GLAS will provide information on the vertical distribution of aerosols and clouds, and improve our ability to study their transport processes and aerosol-cloud interactions. Here we show an overview of GLAS, provide an update of its current status, and present initial observations of dust profiles. In particular, a strategy of characterizing the height profile of dust plumes over source regions will be presented.

Welton, Ellsworth↗

Smart Grid Information Clearinghouse (SGIC)

Since the Energy Independence and Security Act of 2007 was enacted, there has been a large number of websites that discusses smart grid and relevant information, including those from government, academia, industry, private sector and regulatory. These websites collect information independently. Therefore, smart grid information was quite scattered and dispersed. The objective of this work was to develop, populate, manage and maintain the public Smart Grid Information Clearinghouse (SGIC) web portal. The information in the SGIC website is comprehensive that includes smart grid information, research & development, demonstration projects, technical standards, costs & benefit analyses, business cases, legislation, policy & regulation, and other information on lesson learned and best practices. The content in the SGIC website is logically grouped to allow easily browse, search and sort. In addition to providing the browse and search feature, the SGIC web portal also allow users to share their smart grid information with others though our online content submission platform. The Clearinghouse web portal, therefore, serves as the first stop shop for smart grid information that collects smart grid information in a non-bias, non-promotional manner and can provide a missing link from information sources to end users and better serve users’ needs. The web portal is available at www.sgiclearinghouse.org. This report summarizes the work performed during the course of the project (September 2009 – August 2014). Section 2.0 lists SGIC Advisory Committee and User Group members. Section 3.0 discusses SGIC information architecture and web-based database application functionalities. Section 4.0 summarizes SGIC features and functionalities, including its search, browse and sort capabilities, web portal social networking, online content submission platform and security measures implemented. Section 5.0 discusses SGIC web portal contents, including smart grid 101, smart grid projects, deployment experience (i.e., use cases, lessons learned, cost-benefit analyses and business cases), in-depth information (i.e., standards, technology, cyber security, legislation, education and training and demand response), as well as international information. Section 6.0 summarizes SGIC statistics from the launch of the portal on July 07, 2010 to August 31, 2014. Section 7.0 summarizes publicly available information as a result of this work.

Rahman, Saifur↗

MISIP: a data standard for the reuse and reproducibility of any stable isotope probing-derived nucleic acid sequence and experiment

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, process rates, and population dynamics, offering valuable insights for a wide range of research questions. Data reuse maximizes the information derived from the labor and resource-intensive SIP approaches. Yet, a review of publicly available SIP sequencing metadata showed that critical information necessary for reproducibility and reuse was often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) framework and include examples of MISIP reporting for common SIP experiments. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires 5 metadata fields—isotope, isotopolog, isotopolog label, labeling approach, and gradient position—and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data (e.g., gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension (e.g., soil). The adoption of the proposed data standard will improve the reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.

Simpson, Abigayle↗

The genome of jojoba ( Simmondsia chinensis ): A taxonomically isolated species that directs wax ester accumulation in its seeds

Seeds of the desert shrub, jojoba ( Simmondsia chinensis ), are an abundant, renewable source of liquid wax esters, which are valued additives in cosmetic products and industrial lubricants. Jojoba is relegated to its own taxonomic family, and there is little genetic information available to elucidate its phylogeny. Here, we report the high-quality, 887-Mb genome of jojoba assembled into 26 chromosomes with 23,490 protein-coding genes. The jojoba genome has only the whole-genome triplication (γ) shared among eudicots and no recent duplications. These genomic resources coupled with extensive transcriptome, proteome, and lipidome data helped to define heterogeneous pathways and machinery for lipid synthesis and storage, provided missing evolutionary history information for this taxonomically segregated dioecious plant species, and will support efforts to improve the agronomic properties of jojoba.

Sturtevant, Drew↗

Covariance Realism Is Not Enough

A great deal of effort has been put into improving the practice of space situational awareness such that covariance data associated with predicted close approaches is more “realistic.” However, “realistic” usually has meant “larger” and this presents a problem. In many cases, there exist multiple sources for predictive ephemerides, which may be fused to produce predictive states with smaller associated covariances. Ancillary to the fusion computation is the capability to assess consistency of the estimates. If actionable covariance information becomes available, interval estimates for the miss distance provide a more informative alternative to collision probability for risk assessment.

Carpenter, J. Russell↗