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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

Building Foundations for International Collaboration Through Educational Outreach Initiatives

As human space exploration pursues journeying to the Moon and Mars, international and intercultural collaboration is key for the success of such ambitious goals. Since 2014, NASA's Johnson Space Center (JSC) Hispanic Employee Resource Group (HERG) has established relationships and participated in outreach events with emerging space organizations in Latin America with educational and public outreach as a common goal. Such efforts align with strategic goals to empower the next generation of innovators and explorers and to champion the development of space exploration capabilities. This paper discusses the partnerships developed to introduce Spanish speaking populations to science, space technology, aeronautics, research and development through television, webcasts and social media. The authors share accomplishments, challenges, and lessons learned to build foundations for international collaboration to ignite research and innovation and propel human space exploration. The methodology makes use of Space Act Agreements to leverage existing outreach materials and programs and translate the content into Spanish for the benefit of students, educational organizations and the public in general. The plan is to apply the same model in other regions and countries to create a Latin American network of language translation and diffusion of science and space technology content targeting emerging space sectors. This model could be used to reach out to other international communities to provide cultural and educational outreach for space exploration and research.

Fontanot, Carlos↗

Using NASA Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires can dramatically influence both abiotic and biotic components of a landscape, including soil stability and chemistry; vegetation health, density, and composition; and water flow and quality. In addition to the immediate hazards posed by wildfires, subsequent hazards such as flooding and debris flow can impact the area. In New Mexico’s Gila National Forest, wildfire events have occurred with increasing frequency and severity over recent years, notably including the Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), which burned over 290,000 acres and 138,698 acres, respectively, according to the Burned Area Emergency Response Team Executive Summary reports. Following a significant wildfire, land and resource management decisions are made, including when and where to focus vegetation and stream restoration efforts. This research is the result of a collaboration between the NASA DEVELOP National Program and the US Forest Service, which aimed to utilize NASA Earth observations to help inform those critical land management decisions. The project had two main objectives: 1) assess the efficacy of post-fire vegetation restoration efforts and 2) analyze the impact of burn events on the hydrology at the watershed-scale. To accomplish this first goal, data from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) were used to study the vegetation health over time of treated and non-treated burn areas. To accomplish the latter, various aspects of stream behavior were examined in relation to burn events, including the runoff coefficient and “flashiness” of streams based on USGS stream gauge data and Integrated Multi-satelllite Retrievals for GPM (IMERG) precipitation data. This will allow land managers to better understand the complex ecological relationship between the cascading effects after wildfire and the greater forest ecosystem.

Madeline Allen↗

Regional Response Assets, DOE’s Radiological Assistance Program – Believe it or not? INL isn’t the region’s most likely threat

The Department of Energy (DOE) National Nuclear Security Administration's (NNSA) Region 6 Radiological Assistance Program (RAP) personnel respond out of Idaho National Laboratory (INL) based in Idaho Falls, Idaho. An overview of the RAP is presented describing the capabilities and related radiological response capabilities. Several recent radiological responses will be discussed to illustrate the capabilities of this national resource.

99 GENERAL AND MISCELLANEOUS↗

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↗

Variable Renewable Energy Participation in U.S. Ancillary Services Markets: Economic Evaluation and Key Issues

Variable renewable energy (VRE) is not yet meaningfully participating in U.S. ancillary services (AS) markets. VRE participation in AS markets could provide a new source of revenues for VRE resource owners to offset declining energy and capacity values and a new tool for power system operators to address emerging system constraints. This paper uses a price-taker dispatch model and historical prices to estimate the economic value of standalone and hybrid (battery-paired) VRE participation in AS markets, from resource owner and electricity system perspectives, in each of the seven U.S. independent system operator and regional transmission organization (ISO/RTO) markets. Across ISO/RTO markets, average (2015-2019) simulated incremental revenues from regulation market participation were $\$$0.0-2.9/MWh (+0-15% of revenue without participation) for standalone VRE owners and $\$$1-33/MWh (+1-69%) for hybrid VRE owners. However, ISO/RTO reserve markets are relatively thin and have the potential to become saturated by energy storage projects that are currently in ISO/RTO interconnection queues. In most markets, standalone and hybrid VRE were able to provide regulation reserves during periods with high regulation prices, suggesting that VRE participation in AS markets could have high system value. The analysis highlights the value of separate upward and downward regulation products and suggests that ISOs/RTOs might consider initially focusing on enabling hybrid VRE provision of AS.

14 SOLAR ENERGY↗

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗

Economic evaluation of variable renewable energy participation in U.S. ancillary services markets

Variable renewable energy (VRE) is not yet meaningfully participating in U.S. ancillary services (AS) markets. VRE participation in AS markets could provide a new source of revenue for VRE resource owners to offset declining energy and capacity values and a new tool for power system operators to address emerging system constraints. This paper uses a price-taker dispatch model and historical prices to estimate the economic value of standalone and hybrid (battery-paired) VRE participation in AS markets, from the resource owner and electricity system perspectives, in each of the seven U.S. independent system operator and regional transmission organization (ISO/RTO) markets where ancillary service prices are set. Across ISO/RTO markets, average (2015–2019) simulated incremental revenues from power regulation market participation were 0.0–2.9 USD/MWh (+0–15% of revenue without participation) for standalone VRE owners and 1–33 USD/MWh (+1–69%) for hybrid VRE owners. However, ISO/RTO reserve markets are relatively thin and have the potential to become saturated by energy storage projects that are currently in ISO/RTO interconnection queues. In most markets, standalone and hybrid VRE could provide power regulation reserves during periods with high power regulation prices, suggesting that VRE participation in AS markets could have high system value. The analysis highlights the relevance of separate upward and downward power regulation products and indicates that ISOs/RTOs might consider initially focusing on enabling hybrid VRE provision of AS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multipleefforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of synthesized ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680 000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin G. [Fermilab]↗

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated - EDDI measures evaporative demand through potential evapotranspiration, and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks, and to implement the appropriate actions for preparation of drought onset.

Adelaide Schmid↗

Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland

Spatial relationships between clinical data for pediatric asthmatics (hospital and emergency department utilization rates), and socioeconomic and urban characteristics in Baltimore City were analyzed with the aim of identifying factors that contribute to increased asthma rates. Socioeconomic variables and urban characteristics derived from satellite data explained 95% of the spatial variation in hospital rates. The proportion of families headed by a single female was the most important variable accounting for 89% of the spatial variation. Evidence suggests that the high rates of hospital admissions and emergency department (ED) visits may partially be due to the difficulty of single parents with limited resources managing their child's asthma condition properly. This knowledge can be used for education towards mitigating ED and hospital events in Baltimore City.

Emergency Service, Hospital/utilization↗

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin [Fermilab] (ORCID:0000000157000288↗

Earth-Independent Medical Operations (EIMO) Concept of Operations

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

Earth-Independent Medical Operations (EIMO) Concept of Operations (ConOps)

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

Material Design Strategies for Recovery of Critical Resources from Water

Population growth, urbanization, and decarbonization efforts are collectively straining the supply of limited resources that are necessary to produce batteries, electronics, chemicals, fertilizers, and other important products. Securing the supply chains of these critical resources via the development of separation technologies for their recovery represents a major global challenge to ensure stability and security. Surface water, groundwater, and wastewater are emerging as potential new sources to bolster these supply chains. Recently, a variety of material-based technologies have been developed and employed for separations and resource recovery in water. Judicious selection and design of these materials to tune their properties for targeting specific solutes is central to realizing the potential of water as a source for critical resources. Here, the materials that are developed for membranes, sorbents, catalysts, electrodes, and interfacial solar steam generators that demonstrate promise for applications in critical resource recovery are reviewed. In addition, a critical perspective is offered on the grand challenges and key research directions that need to be addressed to improve their practical viability.

36 MATERIALS SCIENCE↗

Zinc batteries for grid-scale energy storage: Challenges, opportunities, and future directions

The global electricity sector is undergoing rapid transformation, increasing demand for reliable stationary energy storage and intensifying the need for safe, cost-effective, and scalable technologies for grid-scale applications. While lithium-ion batteries currently dominate the market, concerns over cost, safety, and resource availability motivate the exploration of alternative chemistries. Zinc-based batteries have emerged as a promising option due to the abundance, low cost, and wide geographic distribution of zinc, combined with the inherent safety of aqueous electrolytes. This perspective examines the potential of zinc batteries for stationary energy storage, with particular focus on rechargeable zinc-air systems. We discuss the evolution of zinc battery technologies and compare zinc-air, zinc-bromine, nickel-zinc, and aqueous zinc-ion chemistries, highlighting their advantages for grid applications. Key challenges limiting rechargeable zinc battery performance are analyzed, including dendrite formation and corrosion at the zinc anode, electrolyte degradation from carbonation and evaporation, and sluggish oxygen electrocatalysis at the air cathode. Emerging strategies to address these limitations are reviewed, including advanced electrode architectures, electrolyte engineering, catalyst development, and system-level design improvements. Lastly, we outline future research directions and opportunities for developing durable, efficient, and economically viable zinc-based energy storage systems for grid-scale applications.

Aqueous electrolytes↗

Miktoarm Star Polymers: Synthesis and Applications

Polymers with precisely controlled structure and function are in high demand across a diverse array of applications spanning the life sciences and nanotechnology. One prototypical example is a class of branched block copolymers known as miktoarm stars (μ-stars), which contain two or more arm compositions connected at a common junction. Miktoarm stars have attracted considerable attention since their physical properties can be different from conventional linear block copolymers. This perspective highlights the latest developments and historical context in the field of miktoarm star polymers, including design strategies, synthetic techniques, and advanced characterization tools used to avoid common preparation pitfalls and tailor properties for emerging applications. Furthermore, our contemporary perspective on μ-star polymers is a resource for inspiring future research into this exciting class of materials at the intersection of chemistry, physics, and advanced technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of water recovery and solid waste processing for aerospace and domestic applications. Volume 2: Final report

The manner in which current and advanced technology can be applied to develop practical solutions to existing and emerging water supply and waste disposal problems is evaluated. An overview of water resource factors as they affect new community planning, and requirements imposed on residential waste treatment systems are presented. The results of equipment surveys contain information describing: commercially available devices and appliances designed to conserve water; devices and techniques for monitoring water quality and controlling back contamination; and advanced water and waste processing equipment. System concepts are developed and compared on the basis of current and projected costs. Economic evaluations are based on community populations of from 2,000 to 250,000. The most promising system concept is defined in sufficient depth to initiate detailed design.

Guarneri, C. A.↗