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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Community-Informed Urban Flood Modeling for Impact Mitigation

The intensification of the hydrologic cycle due to climate change poses a threat to aging and under-designed water infrastructure systems which cannot adequately manage intense storm events. Developing a comprehensive plan for managing rain-driven flooding events is challenging due to uncertainties in the magnitude and frequency of future storm events and conflicting stakeholder objectives. In the City of Baltimore, Maryland, stormwater infrastructure is struggling to keep up with rainfall-driven (pluvial) flooding events, which regularly damage housing and disrupt transportation for residents. In this study, a hybrid of community engagement, numerical modeling, and artificial intelligence techniques are employed to explore prospective urban flooding adaptations. Community engagement drives the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed. The model integrates complex surface and subsurface stormwater infrastructure data from the City, high-resolution spatial data, insights from local public works experts, and the lived experiences of City residents. This co-developed model simulates adaptations of interest to stakeholders in the city, including green and grey infrastructure and operational management strategies. Stormwater management scenarios focused on inlet cleaning and spatially concentrated green infrastructure are found to be the most effective in reducing flood depths in community priority locations. Together, these adaptations can reduce the duration of intersection inundation by more than twenty minutes, allowing for quicker emergency response and restoration of typical transportation systems. Future work will combine this community engaged flooding model with the Deep Uncertainties Pathways framework to explore tradeoffs between adaptations and develop dynamic adaptations which align with community objectives, enhance climate resilience in Baltimore, and can be adjusted in response to changing future conditions.

Ava, Spangler [Pennsylvania State University]↗
NASA NTRS1979

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.

Martino, J. P.↗
NASA NTRS2013

Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-intrail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required

Operation↗
DOE OSTI2023

Quantitative, trait-based microbial ecology to accurately model the impacts of nitrogen deposition on soil carbon cycling in the Anthropocene (Final Technical Report)

Atmospheric nitrogen pollution has altered fundamental soil processes, challenging our understanding of the extent to which soils will continue to sequester carbon and slow the pace of future environmental change. While most evidence shows that increases in soil nitrogen have enhanced carbon storage in temperate forests, it remains unclear whether these effects will persist as nitrogen pollution continues to decline. Moreover, there remains uncertainty as to why some forests gain more carbon in response to nitrogen pollution than others. At the heart of this knowledge gap is a failure to link nitrogen–induced shifts in microbial biodiversity with gains or losses in their functional ability to decompose, assimilate, and ultimately stabilize soil carbon. Given that this uncertainty impedes the ability of predictive models to project future soil carbon stocks, there is a critical need to determine how key microbial traits drive soil carbon responses to nitrogen pollution. As such the goals of this project were to: (1) Quantify variation in taxon–specific and community–level microbial traits across gradients in microbial community composition, mycorrhizal symbioses, and nitrogen availability. (2) Integrate empirical data into a novel predictive framework that enhances our ability to project the regional soil carbon consequences of historical nitrogen pollution in temperate forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling the impact of high thermal conductivity paper on the performance and life of power transformers

Degradation of insulation paper is a key contributor to the failure of power transformers. Insulation degradation accelerates at elevated temperatures, which highlights the potential for better thermal management to prolong life. While several studies have analyzed the benefits of high thermal conductivity oil for reducing temperatures inside a transformer, this study is an initial assessment of the benefits of high thermal conductivity paper on transformer life. Blending particulates with cellulosic fibers offers a pathway for high thermal conductivity paper (with good dielectric properties), which can reduce internal temperatures. Presently, life extensions that can be achieved by the use of such thermally conducting papers were estimated, with the thermal conductivity of the paper being the key parameter under study. The analytical-numerical thermal model used in this study was validated against experimental measurements in a distribution transformer, adding confidence to the utility of the model. This model was then used to provide estimates of hot-spot temperature reduction resulting from the use of papers with higher thermal conductivity than baseline. Transformer life was predicted conventionally by tracking the degree of polymerization of paper over time, based on an Arrhenius model. Results indicate that increasing the thermal conductivity of paper from 0.2 W/mK (baseline) to 1W/mK reduces the hot spot temperature by 10°C. While degradation significantly depends on the moisture and oxygen content, the model shows that such a temperature reduction can increase life for all conditions, by as much as a factor of three.

42 ENGINEERING↗
NASA NTRSDate not supplied

Modeling and Impact of Solar Energetic Particles in the Heliosphere and Geospace

Understanding the radiation environment due to solar energetic particles in the heliosphere and the Earth’s magnetosphere is a challenging and practically important task. Exposure to energetic particles often leads to malfunctions and unexpected failures of electronics onboard spacecraft. The most vulnerable are exploratory missions when outside of the Earth’s magnetosphere. Geomagnetic field deflects Solar Energetic Particles (SEPs) moving through geospace though some of these particles propagate to LEO and have a high penetrating capability, thus producing significant radiation hazards for human spaceflight. Solar energetic particles also have an essential effect on the composition and dynamics of the Earth’s atmosphere. Precipitating SEPs enhance the atmospheric concentration of NOx and HOx, which play a crucial role in the ozone balance in the middle atmosphere by destroying odd oxygen through catalytic reactions. Numerical modeling of the radiation environment due to SEPs in the inner heliosphere and geospace is a multifold problem. That includes simulating 1) solar wind dynamics and the interplanetary magnetic field, 2) global modeling of the Earth’s magnetosphere, and 3) modeling transport and acceleration of SEPs in the inner heliosphere and geospace. The lecture will outline the key physical processes that control the behavior of SEPs in the heliosphere and geospace, along with the contemporary numerical methods used for their modeling. It will primarily focus on describing the SEP population in geospace across different altitudes, ranging from Low Earth Orbit (LEO) through Medium Earth Orbit (MEO) and Geostationary Orbit (GEO), up to the magnetopause, while considering the realistic geomagnetic field. Additionally, the lecture will cover how the SEP population in geospace varies in response to geomagnetic activity. This includes the temporal trapping of SEPs in geospace and the reduction of the rigidity cutoff during geomagnetic storms.

solar energetic particles↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP – Based Satellite Soil Moisture Retrievals into SWAT Hydrological Model: the Impact of Satellite Revisit Time and Product Spatial Resolution on Flood Simulations in Small Basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR obtained via S1 over ASCAT was small likely due to very challenging areas for S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the soil moisture pre-storm conditions.

Small basins↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP–based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via the Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR-SWI obtained via S1 over ASCAT was small, likely due to very challenging areas for the S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the pre-storm soil moisture conditions.

Shima Azimi↗
NASA NTRS2020

Gila Water Resources III - Modeling the Impacts of Post-fire Restoration Methods on Vegetation Recovery in the Gila National Forest

In recent years, wildfires in New Mexico’s Gila National Forest have become increasingly common and more severe. Wildfires can have powerful impacts on hydrology and soil stability, including erosion, flooding, and debris-flows that threaten lives and infrastructure downstream. Vegetation restoration treatments like seeding and mulching can mitigate these effects and facilitate ecosystem recovery. Understanding the effectiveness of various restoration methods is vital to planning a cost-effective and successful post-fire recovery strategy. The immediate response to a fire on US Forest Service land is coordinated by a Burned Area Emergency Response (BAER) team, a group responsible for mitigating immediate post-fire risks to human life, property, and critical natural and cultural resources. This study created a proof-of-concept methodology for a decision-support tool designed to help BAER teams identify the restoration treatments most likely to succeed in a given burned area. Leveraging random forest regression, Google Earth Engine, and Landsat 7 and 8 Earth observations, this study modeled vegetation recovery after the 2013 Silver Fire for seeded areas, seeded/mulched areas, and untreated areas. Treatment type and initial burn severity were the largest drivers of vegetation recovery across the landscape. Seeded/mulched areas showed higher recovery levels than untreated areas three months post-fire, but by four years post-fire, treated and untreated areas displayed similar recovery levels. To produce a robust predictive tool for the Gila National Forest, the model should be trained on many more fires and incorporate post-fire weather conditions into the process. Such a model will help partners ensure efficient resource use and plan effective post-fire restoration strategies.

DEVELOP Project Summary↗
DOE OSTI2026

Differences in Lightning—Storm Microphysical Relationships in Subtropical South America Versus the Continental U.S. and Their Impact on Model Lightning Parameterizations

Satellite studies have shown that some of the deepest convection with high lightning flash rates occurs downstream of the Andes in subtropical South America (SSA). Using high resolution ground‐based observations in SSA, we explore the relationship between lightning and radar‐inferred storm microphysics. Results show these storms have significantly larger 35‐dBZ volumes and more graupel per lightning flash compared to storms in the U.S. We then test microphysics‐based lightning parameterizations for storms in SSA on a 1‐km convection‐permitting simulation of a mesoscale convective system. Results from the simulation match well with observed flash rates. If parameterizations based on U.S. storms had been applied, flash rates would have been overestimated by a factor of eight. These results suggest that storms in SSA are fundamentally different compared to storms in the U.S., and caution should be exercised when applying microphysics‐based lightning parameterizations in different regions of the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dark Energy Survey Year 3 results: magnification modelling and impact on cosmological constraints from galaxy clustering and galaxy–galaxy lensing

We study the effect of magnification in the Dark Energy Survey Year 3 analysis of galaxy clustering and galaxy–galaxy lensing, using two different lens samples: a sample of luminous red galaxies, redMaGiC, and a sample with a redshift-dependent magnitude limit, MagLim. We account for the effect of magnification on both the flux and size selection of galaxies, accounting for systematic effects using the Balrog image simulations. We estimate the impact of magnification on the galaxy clustering and galaxy–galaxy lensing cosmology analysis, finding it to be a significant systematic for the MagLim sample. We show cosmological constraints from the galaxy clustering autocorrelation and galaxy–galaxy lensing signal with different magnifications priors, finding broad consistency in cosmological parameters in ΛCDM and wCDM. However, when magnification bias amplitude is allowed to be free, we find the two-point correlation functions prefer a different amplitude to the fiducial input derived from the image simulations. We validate the magnification analysis by comparing the cross-clustering between lens bins with the prediction from the baseline analysis, which uses only the autocorrelation of the lens bins, indicating that systematics other than magnification may be the cause of the discrepancy. We show that adding the cross-clustering between lens redshift bins to the fit significantly improves the constraints on lens magnification parameters and allows uninformative priors to be used on magnification coefficients, without any loss of constraining power or prior volume concerns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Development of Saturated Zone Three-Dimensional Initial Condition Plumes for the Composite Analysis and Cumulative Impacts Evaluation Modeling

The purpose of this environmental calculation file (ECF) is to document and present the methodology, input data, and results of extending two-dimensional (2-D) plume depictions documented in DOE/RL- 2017-66, Hanford Site Groundwater Monitoring for 2017, into three dimensions (3-D) for select contaminants of interest (COIs) in the 200-BP-5, 200-UP-1, 200-ZP-1, and 200-PO-1 Groundwater Operable Units at the Hanford Site. Plumes with sufficient available vertical profile data were interpolated in 3-D using the Leapfrog Geo®1 geologic modeling platform, which includes an interpolation engine for analyzing and visualizing 3-D data. Results of these interpolations are intended for use in developing inputs for transport modeling to support forecasts of Central Plateau contaminant plume fate and transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Modeling the Impact of Flexible CHP on the Future Electric Grid In California

Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States. Typically fueled with natural gas, a CHP system combines a prime mover (such as a reciprocating engine) with a generator and heat recovery equipment, allowing operation at very high efficiencies (65–85%). Traditionally, CHP systems have been configured to serve local electrical and thermal loads at the sites where they are deployed. Units are sized to ensure a high capacity factor for the equipment, and the electricity generated tends to be used on site. CHP units in the United States already generate over 12% of the nation’s electricity. However, CHP’s potential benefits could be much greater if power generated could be used beyond the site, because the analysis was performed under the assumption that sites could use all the thermal output. Analysis of a few key sectors confirmed that this assumption is valid (for more information, see Appendix E). Those benefits could include improved grid reliability and resilience, as well as lower-cost options for providing energy and other grid services. The potential benefits also align well with grid modernization objectives, as shown in Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States., and greater electrification of loads, driven by carbon reduction priorities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗