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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Segmenting water and shadow regions within WorldView imagery using local binary patterns

Many shadow detection algorithms pertaining to remotely sensed imagery exist. Several of these algorithms exploit the spectral characteristics of shadows within imagery to identify shaded regions. However, these algorithms can have problems when water is also present within the imagery because water shares similar spectral characteristics with shadows. Many of these algorithms are applied to small image subsets instead of the image as a whole and frequently are applied to urban environments that require additional use of the normalized difference water index or other features to affect the removal of water from the shadow mask. This diversity of the image scene content coupled with the complexity and wide variety of environmental conditions that satellite imagery can acquire makes reliably separating shadow and water within larger images a complex problem. Thresholding various spectral indices to produce segmentation maps can be challenging when large, complex, and often imbalanced scenes are captured, which may require manual adjustment of algorithmic parameters for different image areas. Here, we present a methodology that makes use of the near-infrared channel using a watershed segmentation algorithm, local binary pattern measurements, and a support vector machine to classify shadow and water within a full WorldView scene. Results are promising with initial accuracies above 97% for both shadow and water.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Adaptive continuity-preserving simplification of street networks

While street network data are nearly universally available, their representation is usually transportation-based. However, for many types of analyses, e.g., urban morphology or network science, unprocessed transportation-based street network data is unsuitable, making a cumbersome manual simplification process necessary. To address this challenge, in this paper we propose an algorithm for simplification of street networks, based on the detection of network portions that need to be simplified, and continuity-preserving heuristics that generate new geometries. The algorithm, released in the open-source Python package neatnet, facilitates the generation of morphological networks and generalises to various geographical contexts without a need to alter the parameters, while offering better performance than other available solutions.

Fleischmann, Martin [Charles University, Prague, C↗
NASA NTRS2018

Ground and Satellite Based Observation Datasets for the Lower Mekong River Basin

In ‘Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability’ [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work. Moreover, land cover land use raster data that contains 18 classes that cover agriculture, urban, range and forests land cover land use classes for the basin is offered. In addition, a soil data that contains physical and chemical characteristics needed by physically based hydrological models to simulate the cycling of water and air is also provided.

Streamflow↗
DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗
NASA NTRS2017

The Net Decay Time of Anomalies in Concentrations of Atmospheric Pollutants

This paper introduces a new parameter to characterize the random component in temporal variability of atmospheric pollutants and proposes a simple statistical technique for its evaluation. That parameter is the net decay time (or the time scale) of the local anomalies in concentrations of atmospheric pollutants, rather than the traditionally used chemical lifetimes of total amounts of the species. Using widely available data of hourly multi-year surface trace gas pollutant concentrations we demonstrate a simplified way to estimate the net decay time with an exponential approximation of lag-correlation functions. We assessed the decay times of fluctuations in observations of eight atmospheric pollutants (SO2, NO, NO2, NOy, O3, CO, NH3, and HNO3) at two urban sites and one cleaner rural site in the Eastern US. The time scales of temporal fluctuations (net decay times) vary from about one hour to slightly more than one day. These scales are generally much shorter in urban environments than in remote regions. We also compared day- and night-time observations in warm and cold seasons. At night in the cold season, time scales of fluctuations in atmospheric pollutants are usually the longest. Such estimates should be useful to air quality prediction, public health, and satellite remote sensing research communities.

air quality prediction↗
NASA NTRS2020

Urban Air Mobility (UAM) Working Groups

The NASA Aeronautics Research Mission Directorate (ARMD) is bringing together public, private, and academic organizations to collaborate with NASA in Urban Air Mobility (UAM) working groups. The primary purpose of the working groups is to accelerate the development of safe, high-volume UAM flight operations in the existing and anticipated future national airspace system. In coordination with the Grand Challenge series, industry developments and other ARMD efforts, these working groups will contribute to the enablement of UAM markets. Working group activities will seek to align the community on concepts to enable UAM, including communicating industry demonstrations and R&D priorities. The collaborative efforts will facilitate the identification of critical parameters and standards necessary to develop the framework and approach for safety, certification, airspace, aircraft concepts, technologies, and architectures. The realization of the UAM vision will be possible only though the efforts and contributions of multiple stakeholders, each possessing the necessary authority, expertise, and/or resources to fulfill a critical role in UAM's development, approval, and implementation. The applicable participants will become integral to the UAM working groups and will provide a platform for those stakeholders to collaborate and impact the overall ecosystem.

Kopardekar, Parimal H.↗
DOE OSTI2024

Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification

Abstract Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge of recovering fine-scale information from coarse data. This limits their compatibility with many global climate model outputs, often available between ∼50- and 100-km resolution, to scales of interest such as cloud resolving or urban scales. This study systematically examines the capability of a type of superresolving convolutional neural network (SR-CNNs) to downscale surface wind speed data over land from different coarse resolutions (25-, 48-, and 100-km resolution) to 3 km. For each downscaling factor, we consider three convolutional neural network (CNN) configurations that generate superresolved predictions of fine-scale wind speed, which take between one and three input fields: coarse wind speed, fine-scale topography, and diurnal cycle. In addition to fine-scale wind speeds, probability density function parameters are generated through which sample wind speeds can be generated, accounting for the intrinsic stochasticity of wind speed. For assessing generalization to new data, CNN models are tested on regions with different topography and climate that are unseen during training. The evaluation of superresolved predictions focuses on subgrid-scale variability and the recovery of extremes. Models with coarse wind and fine topography as inputs exhibit the best performance when compared with other model configurations, operating across the same downscaling factor. Our diurnal cycle encoding results in lower out-of-sample generalizability when compared with other input configurations.

17 WIND ENERGY↗
NASA NTRS2016

Remote Sensing and Modeling for Improving Operational Aquatic Plant Management

The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Agriculture↗
NASA NTRS2016

Adaptive Management Methods to Protect the California Sacramento-San Joaquin Delta Water Resource

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Agriculture↗
NASA NTRSDate not supplied

Evaluation of Response Surface Experiment Designs for Distributed Propulsion Aircraft Aero-Propulsive Modeling

Modern distributed hybrid and electric propulsion aircraft, including vertical, short, and conventional takeoff and landing configurations, exhibit significant aero-propulsive complexity and a large number of interacting test factors. This paper presents the development and evaluation of experiment designs for aero-propulsive characterization of distributed propulsion aircraft. Five different foundational response surface designs are evaluated to inform the development of two sequential design approaches tailored to complex aircraft aerodynamic characterization experiments. The first approach, which builds on sequential face-centered central composite designs, has been used previously to develop aero-propulsive models for complex aircraft using wind tunnel testing. The second approach is a new design strategy leveraging a regular I-optimal and nested I-optimal design that was developed for this study. The two sequential design strategies are compared for experiments with a large number of test factors using pre-experiment design evaluation metrics, as well as modeling results obtained from simulated wind tunnel data for the NASA LA-8 aircraft. The design evaluation metrics show that the sequential I-optimal base design has higher statistical power, lower correlation among candidate regressors, lower prediction variance, and more precise parameter estimates. The simulated wind tunnel experiments conducted using each design reveal that the sequential I-optimal base design has better predictive capability with fewer test points. The experiment design and evaluation procedures are described in detail to inform future aerodynamic characterization experiments for complex aircraft.

design of experiments↗
DOE OSTI2025

Opportunities in multiscale modeling of mosquito-borne flaviviruses

Mosquito-borne flaviviruses, such as Zika, dengue, West Nile, and yellow fever virus, represent a growing public health concern due to their widespread distribution and the severe diseases they cause. These viruses are difficult to control as climate change and urbanization help mosquitoes expand into new areas, increasing the risk of outbreaks. Mathematical models play a key role in understanding their spread, providing insights at every level—from how the virus multiplies inside cells to how it circulates through entire populations. This review examines various approaches used in modeling arboviruses, including microscale models that focus on cellular and molecular dynamics, mesoscale models that address within-host processes, and macroscale models that capture population-level transmission. We briefly summarize the methodology used for models at each scale, which primarily consists of sets of differential equations with parameters that represent physical rates of change for different subprocesses. We particularly highlight how temperature affects virus transmission, which is key to understanding the impact of climate change. We also show how multiscale models can connect viral replication, immune response, and the spread of infection at a larger scale. This is essential for developing better vaccines and treatments, evaluating disease control measures, predicting the impact of climate change, and improving public health responses to outbreaks.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2001

A Strategy to Assess Aerosol Direct Radiative Forcing of Climate Using Satellite Radiation Measurements

Atmospheric aerosols have a complex internal chemical composition and optical properties. Therefore it is difficult to model their impact on redistribution and absorption of solar radiation, and the consequent impact on atmospheric dynamics and climate. The use in climate models of isolated aerosol parameters retrieved from satellite data (e.g. optical thickness) may result in inconsistent calculations, if the model assumptions differ from these of the satellite retrieval schemes. Here we suggest a strategy to assess the direct impact of aerosol on the radiation budget at the top and bottom of the atmosphere using satellite and ground based measurements of the spectral solar radiation scattered by the aerosol. This method ensures consistent use of the satellite data and increases its accuracy. For Kaufman and Tanre: Strategy for aerosol direct forcing anthropogenic aerosol in the fine mode (e.g. biomass burning smoke and urban pollution) consistent use of satellite derived optical thickness can yield the aerosol impact on the spectral solar flux with accuracy an order of magnitude better than the optical thickness itself. For example, a simulated monthly average smoke optical thickness of 0.5 at 0.55 microns (forcing of 40-50 W/sq m) derived with an error of 20%, while the forcing can be measured directly with an error of only 0-2 W/sq m. Another example, the effect of large dust particles on reflection of solar flux can be derived three times better than retrievals of optical thickness. Since aerosol impacts not only the top of the atmosphere but also the surface irradiation, a combination of satellite and ground based measurements of the spectral flux, can be the most direct mechanism to evaluate the aerosol effect on climate and assimilate it in climate models. The strategy is applied to measurements from SCAR-B and the Tarfox experiments. In SCAR-B aircraft spectral data are used to derive the 24 hour radiative forcing of smoke at the top of the atmosphere of (Delta)F(sub 24hr)/(Delta)tau = - 25 +/- 5 W/sq m. Ground based data give forcing at the surface of (Delta)F(sub 24hr)/(Delta)taur = -80 +/- 5 W/sq m. In TARFOX a mixture of maritime and regional pollution aerosol resulted in a varied forcing at the top of the atmosphere, (Delta)F(sub 24hr)/(Delta)tau, between -26 W/sq 2 and -50 W/sq m depending on mixture of coarse and accumulation modes, for Angstrom exponents of 1.0 and 0.2 respectively.

Kaufman, Yoram J.↗
NASA NTRS2020

A Quiet Helicopter for Air Taxi Operations

NASA is exploring rotorcraft designs for VTOL air taxi operations, also known as urban air mobility (UAM) or on-demand mobility (ODM) applications. Several concept vehicles have been developed, intended to focus and guide NASA research activities in support of aircraft development for this emerging market. This paper examines a single main-rotor helicopter designed specifically for low-noise air taxi operations. Based on demonstrated technology, the aircraft uses a turboshaft engine with a sound-absorbing installation, and the NOTAR anti-torque system to eliminate tail-rotor noise, consequently the noise and annoyance of the aircraft are dominated by the main rotor. Several design parameters are explored to reduce the noise, including rotor tip speed, blade geometry, and higher-harmonic control. Commensurate with the level of design detail, the noise is calculated for compact loading and thickness sources on the rotating blades. The metric is the reduction of the noise for the helicopter certification conditions (takeoff, flyover, and approach), relative a baseline aircraft with typical (high) tip speed, conventional blade planform, and no higher-harmonic control.

Johnson, Wayne↗
NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) GUI implementation via MATLAB Application Designer

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor wake interacting with the rotor blades. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of Blade-Vortex Interaction (BVI) noise. RABBIT enables engineers to quickly locate and understand designs or configurations that cause significant BVI noise. Furthermore, RABBIT can identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict only BVI noise. To date, RABBIT has been validated against CAMRAD II and ANOPP2/AARON for three NASA Revolutionary Vertical Lift Technology (RVLT) concept vehicles: the Quiet Single Main Rotor (QSMR), Side-by-Side, and Quadrotor. RABBIT has been shown to be a useful BVI prediction tool capable of visualizing BVI as a function of various parameters. Impulse factor and time rate of change of loading allows for a unique BVI prediction technique that provides information on impulse strength, location, and frequency. This presentation will highlight how MATLAB’s App Designer was utilized to enable users to navigate RABBIT easily and efficiently without prior experience with MATLAB or rotorcraft acoustics. RABBIT users can build and view rotors in real time with options to control blade chord, radius, phasing, and airfoil geometry. Furthermore, multiple rotors can be combined to create state-of-the-art multi-rotor vehicles or fleets. Editable tables, sliding bars, and push buttons were implemented within MATLAB’s App Designer for RABBIT’s GUI to allow engineers and designers to predict low order acoustic impact of BVI occurrences.

Natasha Lydia Schatzman↗
NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) Reimagined: Algorithm Improvement and User-Friendly Interface Implementation

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor blades interacting with the rotor wake. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of BVI noise. RABBIT enables engineers to quickly design and simulate UAM configurations and understand BVI occurrences for a desired flight condition. Furthermore, RABBIT can also identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict BVI aerodynamics. RABBIT algorithm has been further developed including reduction of computational time, accounting for BVI source time arrival, improved vortex strength modeling, and BVI impulse factor. A user-friendly app is presented with the intent of bringing RABBIT to the masses to allow engineers from various educational backgrounds to design and begin to understand BVI. Furthermore, RABBIT capabilities are highlighted by a parameter study highlighting key parameters that impact BVIalong with highlighting RABBIT’s ability to identify BVI occurrences from other rotors.

RApid↗
DOE OSTI2026

Urban wash-off of tire wear particles

Tire wear particles (TWPs) are an important class of microplastics due to their toxicity and abundance. Because most TWPs are generated on impervious road surfaces, urban wash-off is the critical first phase of waterborne transport from their zone of production to stormwater drainage. However, little is known about the driving factors behind their mobilization. In this study, we use a rainfall simulator to investigate how surface roughness, rainfall intensity, and surface slope affect wash-off behaviors of TWPs. We also analyze how the size and shape of mobilized TWPs change over the course of simulated storm events. We found that low surface roughness, high rainfall intensity (most significant factor), and low slope result in the most rapid conveyance of TWP load. On average, large particles (>1000 µm) travelled faster than small particles (<125 µm). Particle shape explained a very small amount of variance in TWP wash-off velocity but was found to be more important under higher surface roughness conditions. In addition to wash-off velocity, we found similar conditions controlled the percent mobilization of TWPs. Low surface roughness and high rainfall intensity resulting in higher TWP wash-off rates is consistent with mineral sediment wash-off behavior. Conversely, low surface slope and large particle size leading to faster conveyance is directly opposed to mineral sediment wash-off. Our findings suggest drag-dominated flow and that sufficient runoff depth is the most important parameter governing TWP wash-off. These findings are important first steps to understanding wash-off behaviors of TWPs and informing future modeling efforts and mitigation strategies.

13 HYDRO ENERGY↗
DOE OSTI2024

Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania

Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regionsprovide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantageand shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantagediffers between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within theUS context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site ofWaynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a goodrepresentation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected fromstudents, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty andstudents group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personalcharacteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commutersvalue personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to moveback and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show ahigher propensity for using shared shuttles. Furthermore, the findings from this study could be helpful for agencies in improving rural mobility andconsidering such shared mobility services for rural communities

42 ENGINEERING↗
DOE OSTI2023

Interseismic Strain Accumulation between the Colorado Plateau and the Eastern California Shear Zone: Implications for the Seismic Hazard near Las Vegas, Nevada

ABSTRACT Crustal deformation in the central Basin and Range between the Colorado plateau and the Eastern California Shear Zone is active but slow, making it a challenge to assess how strain is distributed and crustal motion transferred. However, knowledge of strain rates is very important, particularly for addressing the seismic hazard for both the Las Vegas urban area and the site of the proposed Yucca Mountain nuclear waste repository, in southern Nevada. Global Positioning System (GPS) data provide important constraints, particularly now that the GPS network in the area has substantially expanded in recent years. However, because deformation is slow, it is important to mitigate any transient tectonic and nontectonic signals to obtain the most accurate long-term interseismic motion and robust estimation of strain rates. We use data from all GPS stations in the region including both long-running continuous and semicontinuous stations. We model and remove postseismic displacements at these stations using source parameters for 41 events, dating back to the 1700 Cascadia megathrust earthquake, which contribute significantly to the deformation field within the central Basin and Range. We also remove correlated noise from the time series with the common-mode component imaging technique. We find that removal of both the postseismic transients and common-mode noise substantially reduces the uncertainties and spatial variation in the velocities. We find east–west extension across the Las Vegas Valley of 0.5–0.6 mm/yr. The interseismic strain rate field, calculated with the final velocities, reveals higher strain rates through southern Nevada than in previous studies, with rates within Las Vegas Valley of 8.5±2.4×10−9 yr−1. Our results also confirm shear along the Pahranagat shear zone, but the estimated amplitude is strongly affected by postseismic relaxation.

Geochemistry & Geophysics↗