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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 235 records · Page 13

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗

An Introduction to Flight Software Development: FSW Today, FSW 2010

Experience and knowledge gained from ongoing maintenance of Space Shuttle Flight Software and new development projects including Cockpit Avionics Upgrade are applied to projected needs of the National Space Exploration Vision through Spiral 2. Lessons learned from these current activities are applied to create a sustainable, reliable model for development of critical software to support Project Constellation. This presentation introduces the technologies, methodologies, and infrastructure needed to produce and sustain high quality software. It will propose what is needed to support a Vision for Space Exploration that places demands on the innovation and productivity needed to support future space exploration. The technologies in use today within FSW development include tools that provide requirements tracking, integrated change management, modeling and simulation software. Specific challenges that have been met include the introduction and integration of Commercial Off the Shelf (COTS) Real Time Operating System for critical functions. Though technology prediction has proved to be imprecise, Project Constellation requirements will need continued integration of new technology with evolving methodologies and changing project infrastructure. Targets for continued technology investment are integrated health monitoring and management, self healing software, standard payload interfaces, autonomous operation, and improvements in training. Emulation of the target hardware will also allow significant streamlining of development and testing. The methodologies in use today for FSW development are object oriented UML design, iterative development using independent components, as well as rapid prototyping . In addition, Lean Six Sigma and CMMI play a critical role in the quality and efficiency of the workforce processes. Over the next six years, we expect these methodologies to merge with other improvements into a consolidated office culture with all processes being guided by automated office assistants. The infrastructure in use today includes strict software development and configuration management procedures, including strong control of resource management and critical skills coverage. This will evolve to a fully integrated staff organization with efficient and effective communication throughout all levels guided by a Mission-Systems Architecture framework with focus on risk management and attention toward inevitable product obsolescence. This infrastructure of computing equipment, software and processes will itself be subject to technological change and need for management of change and improvement,

Gouvela, John↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

A Generic Primary-Control Model for Grid-Forming Inverters: Towards Interoperable Operation & Control

This paper outlines an architectural vision centered around the notion of interoperability to integrate grid-forming inverter-based resources in large-scale grids. With the underlying principle of interoperability guiding developments, we focus on modeling the characteristics of droop, virtual synchronous machine, and virtual oscillator controls. Emphasis is placed on these three controllers since they are leading grid-forming control candidates and are likely to be commonplace as primary-control schemes in future systems. We show that these controllers can each be considered as instantiations of a more generic model and that all these controllers exhibit similar droop-like relations between pertinent terminal variables in steady state. This commonality between controllers gives interoperability among them such that automatic synchronization, power sharing, and voltage regulation can be achieved. Simulation results validate the models and demonstrate how the steady-state droop characteristics of these control methods can be aligned with the aid of the developed modeling paradigm.

control↗

Energy Intensity Baselining & Tracking Summary Guide: Better Buildings, Better Plants

The Department of Energy (DOE) Better Plants (BP) program is a voluntary energy efficiency leadership initiative for U.S. manufacturers that encourages companies to reduce their energy intensity, typically by 25% within a ten-year period. BP partners are required to report their progress to the DOE annually by establishing an energy intensity baseline and tracking their energy consumption. BP partners receive access to a Technical Account Manager (TAM), DOE resources including software tools and trainings, and recognition when they achieve their goal. This summary guide provides the basics of baselining and tracking your energy intensity. For a more information and special considerations, please see the Energy Intensity Baselining and Tracking Guidance 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Strengthening Resilience: Florida Resident Voices on Resource Needs During Power Outages

Extreme weather events related to climate change, and an aging electricity infrastructure are disrupting reliable electricity services to a greater degree. Further, previous research has found that more socially vulnerable populations are more likely to live in areas with a higher probability of power outages. Here, this study examines the issues that people face during power outages and the resources that help individuals maintain resilience during power outages caused by extreme weather events in socially vulnerable communities. Using qualitative data from focus groups with 56 individuals in Central and North Florida, the research highlights lived experiences during outages and difficulties using and accessing resources during these conditions. Based on a qualitative review of the focus group discussions, this paper explores the solutions and support systems residents believe would improve their ability to cope. The findings offer insights to guide policy and strategic planning, with the goal of strengthening personal preparedness and response by focusing on the resources people consider most helpful for enduring frequent and severe outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Engineering an Escherichia coli strain for production of long single-stranded DNA

Long single-stranded DNA (ssDNA) is a versatile molecular reagent with applications including RNA-guided genome engineering and DNA nanotechnology, yet its production is typically resource-intensive. We introduce a novel method utilizing an engineered Escherichia coli ‘helper’ strain and phagemid system that simplifies long ssDNA generation to a straightforward transformation and purification procedure. Our method obviates the need for helper plasmids and their associated contamination by integrating M13mp18 genes directly into the E. coli chromosome. We achieved ssDNA lengths ranging from 504 to 20 724 nt with titers up to 250 μg/l following alkaline lysis purification. The efficacy of our system was confirmed through its application in primary T-cell genome modifications and DNA origami folding. The reliability, scalability and ease of our approach promise to unlock new experimental applications requiring large quantities of long ssDNA.

59 BASIC BIOLOGICAL SCIENCES↗

Rockets: Physical science teacher's guide with activities

This guide begins with background information sections on the history of rocketry, scientific principles, and practical rocketry. The sections on scientific principles and practical rocketry are based on Isaac Newton's three laws of motion. These laws explain why rockets work and how to make them more efficient. The background sections are followed with a series of physical science activities that demonstrate the basic science of rocketry. Each activity is designed to be simple and take advantage of inexpensive materials. Construction diagrams, materials and tools lists, and instructions are included. A brief discussion elaborates on the concepts covered in the activities and is followed with teaching notes and discussion questions. The guide concludes with a glossary of terms, suggested reading list, NASA educational resources, and an evaluation questionnaire with a mailer.

Vogt, Gregory L.↗

Overview of NASA's Space Solar Power Technology Advanced Research and Development Program

Large solar power satellite (SPS) systems that might provide base load power into terrestrial markets were examined extensively in the 1970s by the US Department of Energy (DOE) and the National Aeronautics and Space Administration (NASA). Following a hiatus of about 15 years, the subject of space solar power (SSP) was reexamined by NASA from 1995-1997 in the 'fresh look' study, and during 1998 in an SSP 'concept definition study', and during 1999-2000 in the SSP Exploratory Research and Technology (SERT) program. As a result of these efforts, during 2001, NASA has initiated the SSP Technology Advanced Research and Development (STAR-Dev) program based on informed decisions. The goal of the STAR-Dev program is to conduct preliminary strategic technology research and development to enable large, multi-megawatt to gigawatt-class space solar power (SSP) systems and wireless power transmission (WPT) for government missions and commercial markets (in-space and terrestrial). Specific objectives include: (1) Release a NASA Research Announcement (NRA) for SSP Projects; (2) Conduct systems studies; (3) Develop Component Technologies; (4) Develop Ground and Flight demonstration systems; and (5) Assess and/or Initiate Partnerships. Accomplishing these objectives will allow informed future decisions regarding further SSP and related research and development investments by both NASA management and prospective external partners. In particular, accomplishing these objectives will also guide further definition of SSP and related technology roadmaps including performance objectives, resources and schedules; including 'multi-purpose' applications (commercial, science, and other government).

Howell, Joe↗

Impact-Identified Medical Capabilities with Largest Effect on Medical Risk for an Extended Duration Artemis Mission

Historically, identifying resources to include in a medical system has been based on heuristically guided clinical subject matter expert assessment. Probabilistic risk assessment (PRA) and tradespace analysis have the power to simplify and increase the fidelity of this traditional approach by providing initial risk estimates and system design solutions that fit within the specified constraints. This will be especially important as the increased mission complexity, distance from Earth, and duration of LDEMs is likely to drive an increase in mission medical risk. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) is designed to do just that. IMPACT uses an evidence based medical database of conditions likely to affect LDEM outcomes and a PRA computational engine to estimate how medical conditions and included medical capabilities affect mission outcomes. We identified the 10 medical conditions with the largest effect on medical risks and determined what medical system capabilities affected risk reduction the greatest.

Anderson A↗

ESS-DIVE Reporting Format for Location Metadata

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

54 ENVIRONMENTAL SCIENCES↗

A phased workflow to define permit‐ready locations for large volume CO 2 injection and storage

Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

58 GEOSCIENCES↗

Symmetry dilemmas in quantum computing for chemistry: A comprehensive analysis

Symmetry adaptation, universality, and gate efficiency are central but often competing requirements in quantum algorithms for electronic structure and many-body physics. For example, fully symmetry-adapted universal operator pools typically generate long and deep quantum circuits; gate-efficient universal operator pools generally break symmetries; and gate-efficient, fully symmetry-adapted operator pools may not be universal. In this work, we analyze such symmetry dilemmas both theoretically and numerically. On the theory side, we prove that the popular, gate-efficient operator pool consisting of singlet spin-adapted singles and perfect-pairing doubles is not universal when spatial symmetry is enforced. To demonstrate the strengths and weaknesses of the three types of pools, we perform numerical simulations using an adaptive algorithm paired with operator pools that are (i) fully symmetry-adapted and universal, (ii) fully symmetry-adapted and non-universal, and (iii) breaking a single symmetry and universal. Our numerical simulations encompass three physically relevant scenarios in which the target state is (i) the global ground state, (ii) the ground state crossed by a state differing in multiple symmetry properties, and (iii) the ground state crossed by a state differing in a single symmetry property. Our results show when symmetry-breaking but universal pools can be used safely, when enforcing at least one distinguishing symmetry suffices, and when a particular symmetry must be rigorously preserved to avoid variational collapse. Together, the formal and numerical analyses provide a practical guide for designing and benchmarking symmetry-adapted operator pools that balance universality, resource requirements, and robust state targeting in quantum simulations for chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BioGeoChemistry of Actinides (LLNL SFA OBER - SBR FY20 Program Management and Performance Report)

The focus of the BioGeoChemistry of Actinides SFA is to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach includes: (1) Field Studies (Research Thrust 1) that capture actinide behavior on the timescale of decades and (2) Fundamental Laboratory Studies (Research Thrust 2) that isolate specific biogeochemical processes observed in the field. These research thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory (LLNL), allowing the BioGeoChemistry of Actinides SFA to advance our understanding of actinide migration behavior in the environment, and serve as an international resource for environmental radiochemistry research (Figure 1). Research Thrusts 1 and 2 are guided by broad central hypotheses: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limit their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides, providing DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites and, more broadly, increasing our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. Although our focus is on actinide biogeochemistry, the increased focus on biogeochemistry at unique Test Bed locations associated with this SFA is providing fundamental information on redox processes and associated microbiological processes that control the cycling of redox sensitive metals under dynamic and transient biogeochemical conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The project is motivated by the challenges, risks, and costs associated with geothermal exploration and production. Many processes and parameters impacting geothermal conditions are poorly understood. Diverse datasets are available to help characterize subsurface geothermal conditions (public and proprietary; satellite, airborne surveys, vegetation/water sampling, geological, geophysical, etc.). Yet, it is not clear how to properly leverage these datasets for geothermal exploration due to an incomplete understanding of how physical processes impacting subsurface geothermal conditions are represented in these observations. Recent advancements in machine learning (ML) provide great promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. Our goals and work under Phases 1 and 2 (as proposed) of this project address all these needs.

15 GEOTHERMAL ENERGY↗

Sustainable Water Management: Understanding the Socioeconomic and Cultural Dimensions

With the pressing challenges of water scarcity and pollution, achieving sustainable water management is imperative for promoting long-term development. Therefore, this paper aims to examine the socio-economic and cultural factors that shape the sustainability of water management strategies in Brazil and Portugal. This study highlights various factors that influence water management, including robust legal frameworks, socio-economic disparities, cultural practices, agricultural water usage, knowledge sharing, public participation, climate change resilience, water scarcity risks, industrial water consumption, and urbanization. By conducting a SWOT analysis of water management strategies, this research synthesizes information through an extensive literature review, encompassing the legal frameworks, policies, and implemented strategies in both countries. Additionally, it investigates comparative studies among Brazil, Portugal, and other European nations to facilitate the exchange of knowledge and experiences in water management practices. The findings of this study offer valuable insights into the strengths, weaknesses, opportunities, and threats associated with water management strategies in Brazil and Portugal, thereby guiding the development of tailored policies and strategies that foster sustainability in water resource management. Additionally, the research highlights the role of digital transformation in optimizing water management practices. By integrating socio-economic, cultural, and digital factors, this study contributes to effective and sustainable water management in Brazil and Portugal, ensuring responsible utilization and preservation of water resources.

Santos, Eleonora↗

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

The Small Satellite Reliability Initiative (SSRI)Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. NASA’s Small Spacecraft Systems Virtual Institute (S3VI) funds the SSRI Knowledge Base. The S3VIis jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗