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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Scale‐Adaptive Urban Hydrologic Framework: Incorporating Network‐Level Storm Drainage Pipes Representation

Abstract Below‐ground urban stormwater networks (BUSNs) significantly influence urban flood dynamics, yet their representation at the watershed or larger scales remains challenging. We introduce a scalable urban hydrologic framework that centers on a novel network‐level BUSN representation, balancing the needs for physical basis, parameter parsimony, and computational efficiency. Our framework conceptualizes an urban watershed into four interacting zones: hillslopes (natural), storm‐sewersheds (urban), a sub‐network channel (tributaries), and a main channel. We develop an innovative Graph Theory‐based algorithm to derive network‐level BUSN parameters from publicly available datasets, enabling efficient, scalable parameterization. We demonstrate this framework's applicability at nine representative watersheds in the Houston metropolitan region, USA, with urban imperviousness ranging from 0% to 64% and drainage areas ranging from 24 to 302 . Our model achieves satisfying computational efficiency, completing hourly time step simulations for 18 years in less than 5 sec per watershed on a standard PC. Validation against observed daily streamflow confirms that the model can capture small‐to‐large flood peaks and seasonal and annual water balance over these watersheds. Comparisons with the National Water Model show better performance in predicting flood peaks and overall water balance, underscoring the promises of our new framework for urban hydrologic modeling at large scales. Furthermore, analysis reveals nonlinear relationships between BUSNs' designed capacities and flood reduction effects. Our approach bridges the gap between detailed hydraulic and large‐scale hydrologic models, providing a valuable tool for urban flood prediction and management across broader spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

17 WIND ENERGY↗
DOE OSTI2023

Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6

Abstract Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-corrected climate information, making it important to understand the uncertainties and potential biases of this approach. Here, we perform a variance decomposition to partition uncertainty in global climate projections and quantify the relative importance of downscaling and bias-correction. We analyze simple climate metrics such as annual temperature and precipitation averages, as well as several indices of climate extremes. We find that downscaling and bias-correction often contribute substantial uncertainty to local decision-relevant climate outcomes, though our results are strongly heterogeneous across space, time, and climate metrics. Our results can provide guidance to impact modelers and decision-makers regarding the uncertainties associated with downscaling and bias-correction when performing local-scale analyses, as neglecting to account for these uncertainties may risk overconfidence relative to the full range of possible climate futures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stability of hydrides in sub-Neptune exoplanets with thick hydrogen-rich atmospheres

Many sub-Neptune exoplanets have been believed to be composed of a thick hydrogen-dominated atmosphere and a high-temperature heavier-element-dominant core. From an assumption that there is no chemical reaction between hydrogen and silicates/metals at the atmosphere–interior boundary, the cores of sub-Neptunes have been modeled with molten silicates and metals (magma) in previous studies. In large sub-Neptunes, pressure at the atmosphere–magma boundary can reach tens of gigapascals where hydrogen is a dense liquid. A recent experiment showed that hydrogen can induce the reduction of Fe 2+ in (Mg,Fe)O to Fe 0 metal at the pressure–temperature conditions relevant to the atmosphere–interior boundary. However, it is unclear whether Mg, one of the abundant heavy elements in the planetary interiors, remains oxidized or can be reduced by H. Our experiments in the laser-heated diamond-anvil cell found that heating of MgO + Fe to 3,500 to 4,900 K (close to or above their melting temperatures) in an H medium leads to the formation of Mg 2 FeH 6 and H 2 O at 8 to 13 GPa. At 26 to 29 GPa, the behavior of the system changes, and Mg–H in an H fluid and H 2 O were detected with separate FeH x . The observations indicate the dissociation of the Mg–O bond by H and subsequent production of hydride and water. Therefore, the atmosphere–magma interaction can lead to a fundamentally different mineralogy for sub-Neptune exoplanets compared with rocky planets. The change in the chemical reaction at the higher pressures can also affect the size demographics (i.e., “radius cliff”) and the atmosphere chemistry of sub-Neptune exoplanets.

58 GEOSCIENCES↗
DOE OSTI2025

A tale of two planets: Disparate evolutionary models for Mars inferred from radiogenic isotope compositions of Martian meteorites

The radiogenic isotopic compositions of basaltic Martian meteorites (shergottites) and clinopyroxene/olivine cumulate meteorites (nakhlite/chassignites) are used to define the global evolution of Mars. However, the two main groups of meteorites demonstrate that their sources underwent divergent styles of magmatic evolution. The shergottites portray a planet that differentiated ~4.52 billion years ago via solidification of a magma ocean, producing incompatible element-depleted and -enriched reservoirs that remained isolated until melt production. In contrast, the reservoir from which the nakhlite/chassignites derive may have formed earlier, produced melts that fractionated Sm/Nd and Hf/W differently, was compositionally less variable, and experienced a significantly more complex history following primordial differentiation than the shergottite sources. The disparate histories recorded by these two groups of meteorites elucidate important questions that could be addressed by acquiring additional samples. Obtaining samples that shared the isotopic systematics of the shergottites would provide confidence that extrapolating the primordial differentiation history of Mars from shergottite radiogenic isotope systematics is reasonable. Returned samples from Mars will also constrain the physical locations of the meteorite source regions, providing insights into the general structure of the Martian mantle. In addition, they will help constrain the phases present in the martian mantle during melting and the conditions under which they are stable. Finally, identifying an evolved lithology that satisfies the geochemical and isotopic constraints placed on the incompatible element-enriched endmember observed in the shergottites would define the nature of magmatic evolution on Mars and whether it is more akin to processes on the Earth or the Moon.

Mars↗
DOE OSTI2025

Increased frequency of planetary wave resonance events over the past half-century

We demonstrate a tripling in the frequency of planetary wave resonance events over the past halfcentury, coinciding with the rise in persistent boreal summer weather extremes. This increase aligns with changes in the underlying climate conditions favoring these events, including amplified Arctic warming and land-sea thermal contrast. We also observe increased prevalence of resonant amplification events following the mature phase of strong El Niño events, suggesting that such events may precondition the mean state conditions in ways that favor large-scale quasi-stationary wave patterns and quasi-resonant wave amplification. Since the impact of anthropogenic warming on quasi-resonant amplification is not well captured by current-generation climate models, it is likely that models are underpredicting the potential increase, indicating even greater risk of persistent extreme summer weather events with ongoing warming.

Arctic amplification↗
DOE OSTI2025

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗
DOE OSTI2022

Performance Analysis of Speculative Parallel Adaptive Local Timestepping for Conservation Laws

Stable simulation of conservation laws, such as those used to model fluid dynamics and plasma physics applications, requires the satisfaction of the so-called Courant-Friedrichs-Lewy condition. By allowing regions of the mesh to advance with different timesteps that locally satisfy this stability constraint, significant work reduction can be attained when compared to a time integration scheme using a single timestep size. However, parallelizing this algorithm presents considerable difficulty. Since the stability condition depends on the state of the system, dependencies become dynamic and potentially non-local. In this article, we present an adaptive local timestepping algorithm using an optimistic (Timewarp-based) parallel discrete event simulation. We introduce waiting heuristics to limit misspeculation and a semi-static load balancing scheme to eliminate load imbalance as parts of the mesh require finer or coarser timesteps. Last, we outline an interface for separating the physics of the specific conservation law from the temporal integration allowing for productive adoption of our proposed algorithm. We present a misspeculation study for three conservation laws, demonstrating both the productivity of the local timestepping API, for which 74% of the lines of code are reused across different conservation laws, and the robustness of the waiting heuristics—at most 1.5% of element updates are rolled back. Our performance studies demonstrate up to a 2.8× speedup versus a baseline unoptimized local timestepping approach, a 4x improvement in per-node throughput compared to an MPI parallelization of synchronous timestepping, and scalability up to 3,072 cores on NERSC’s Cori Haswell partition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Comparison of Machine Learning Methods to Forecast Tropospheric Ozone Levels in Delhi

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R2 values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R 2 of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Agreements/subagreements Applicable to Wallops, 12 Nov. 1991

The status of space science agreements are noted. A general overview of the Wallops Flight Facility (WFF) is given. The geography, history, and mission of the facility are briefly surveyed. Brief accounts are given of NASA earth science activities at the WFF, including atmospheric dynamics, atmospheric optics, ocean physics, microwave altimetry, ocean color research, wind-wave-current interaction, flight support activities, the Sounding Rocket Program, and the NASA Balloon Program. Also discussed are the WFF launch range, the research airport, aircraft airborne science, telemetry, data systems, communications, and command and control.

Source record↗
NASA NTRS1993

Spacelab program's scientific benefits to mankind

The paper describes the important scientific discoveries and accomplishments achieved by the Spacelab program during the ten years of its operation starting with the first flight in 1983, with emphasis on the discoveries and accomplishments in the fields of astronomy and astrophysics, atmospheric science, life sciences, microgravity science, plasma physics, and earth observations. The Spacelab systems performance and operations are discussed with particular attention given to the operations applicable to the Space Station era.

Graft, Harry G., Jr.↗
NASA NTRS2000

Compact Hyperspectral Mapper for Environmental Remote Sensing Applications (CHyMERA) End-of-phase Data Review Package

CHYMERA is an Instrument Incubator concept to design, build, and test an instrument that will reduce size, mass, and cost and increase science potential and flexibility for future atmospheric remote sensing missions within the focus of NASA's Earth Science Enterprise (ESE). The primary effort of the development plan will be on high spatial resolution ozone, N02, S02, aerosol, and cloud measurements, but it is hoped that the techniques developed will prove useful for other measurements as well. The core design will involve a high performance, wide field-of-view (FOV) front end telescope which will illuminate a filter/focal plane array (FFPA) package. The use of a non-dispersive optical configuration will reduce size, mass and complexity. The wide FOV optics will permit short duration global coverage (1-2 days) without the need for a scanner.

Janz, Scott J.↗
NASA NTRS2003

The Orbiting Carbon Observatory (OCO) Mission

This viewgraph presentation gives a general overview of The Orbiting Carbon Observatory (OCO) Mission. The contents include: 1) The Orbiting Carbon Observatory (OCO); 2) Why Measure CO2?; 3) An Uncertain Future; 4) Monitoring CO2 from Space; 5) Validation Program Ensures Accuracy and Minimizes Spatially Coherent Biases; 6) The OCO Instrument; 7) The OCO Spacecraft; 8) Mission Operations and Data Downlink; 9) OCO Data Products; 10) OCO Data Product Summary; 11) OCO in the A-Train; 12) Summary; and 13) Simulated Performance.

Pathfinder Program↗
NASA NTRS2012

Atmospheric Research 2011 Technical Highlights

The 2011 Technical Highlights describes the efforts of all members of Atmospheric Research. Their dedication to advancing Earth Science through conducting research, developing and running models, designing instruments, managing projects, running field campaigns, and numerous other activities, is highlighted in this report.

Source record↗
NASA NTRS1975

Interim Report of the Astronomy Spacelab Payloads Study: Ultraviolet and Optical Astronomy - Volume 2

The Space Shuttle will comprise NASA's primary transportation system into near-earth orbit during the 1980s. The Shuttle will provide the astronomical community with a major new capability to send a wide variety of instrumentation into orbit, to utilize it there under manned or automatic control for periods from seven to thirty days, and to return it to the ground. To this end the European Space Research Organization (ESRO) is developing Spacelab, an array of interchangeable components -pressurized manned modules, unpressurized pallets and related support systems - to be mounted in the Shuttle payload bay. Spacelab will offer important opportunities to carry out astronomical research with instruments optimized for specific objectives. With a high flight frequency and with the ability to modify or interchange telescopes and instruments between flights, one will not need to make rigid long-term commitments to specific and compromised telescope/instrument/ detector combinations as is the case for automated satellites. Observational techniques demanding the physical return of data and equipment - in particular the use of photographic film, instruments requiring tight calibration controls, cryogens, high-risk detectors and degradeable optical coatings -will open research areas not readily addressed by automated satellites. Although Shuttle flight duration will be limited to periods from seven to thirty days, substantial data can be obtained with a single instrument on short missions, if targets are carefully selected and prioritized, and a large number of instruments can be accommodated on a single flight. Important astronomical data are regularly obtained on sounding rocket flights of five minutes duration. Spacelab will provide far longer observing periods for large and small telescopes, with resources greatly exceeding those of sounding rockets, while retaining much of the sounding rocket philosophy in terms of instrument flexibility, simplicity, reliability assurance and development costs. The Ultraviolet and Optical Astronomy Program on Spacelab is being planned to provide optical astronomers with relatively simple and regular access to the extended wavelength coverage, the superior image quality and the darkness of the night sky available above the earth's atmosphere. In a rapidly evolving science one cannot predict what problems will be timely in the 1980s. Extrapolating from the current epoch, however, one can envision a continuing interest in such areas as the structure, composition and phenomenology of planetary surfaces and atmospheres; the composition and physical nature of the interstellar medium; the composition, structure and life history of stars, especially those in advanced stages of evolution; the stellar population of other galaxies; such enigmatic phenomena as X-ray binary black holes, pulsars, active galactic nuclei and quasars; large scale interactions between galaxies and the nature of the intergalactic medium; precise calibration of the Hubble law for the expansion of the universe; the average density of the universe; and the existence of extraterrestrial life.

Source record↗
NASA NTRSDate not supplied

GEWEX SRB Release 4: Public Release

The NASA/GEWEX Surface Radiation Budget (SRB) project produces 3-hourly shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-nearpresent time period. Here we announce the public availability of the new Release 4 Integrated data product (R4-IP). R4-IP uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Release 3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters constituting an “Integrated Product” for energy and water cycle studies. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated shortwave (SW or solar wavelengths) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both SW and LW (longwave or thermal infrared) also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC). Both LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added.Here we analyze the new SW SRB datasets, comparing them to the previous Release 3, BSRN and PMEL surface measurements. Validation results show improved agreement compared to Release 3. Comparisons to ERBE and CERES TOA and surface satellite datasets before and after overlap periods show the long-term agreement with radiometric uncertainty. Monthly anomalies at global and zonal regions show very good correlation with the shorter ERBE and CERES flux anomalies linking those to the longer term. The uncertainties are discussed and periods of potential issues in inputs and/or algorithms are identified.

Earth energy budget↗
NASA NTRS2024

Observational Constraint on A Feedback From Supercooled Clouds Reduces Projected Warming Uncertainty

The increase of carbon-dioxide-doubling-induced warming (climate sensitivity) in the latest climate models is primarily attributed to a larger extratropical cloud feedback. This is thought to be partly driven by a greater ratio of supercooled liquid-phase clouds to all clouds, termed liquid phase ratio. We use an instrument simulator approach to show that this ratio has increased in the latest climate models and is overestimated rather than underestimated as previously thought. In our analysis of multiple models, a greater ratio corresponds to stronger negative cloud feedback, in contradiction with single-model-based studies. We trace this unexpected result to a cloud feedback involving a shift from supercooled to warm clouds as climate warms, which corresponds to greater cloud amount and optical depth and weakens the extratropical cloud feedback. Better constraining this ratio in climate models – and thus this supercooled cloud feedback – impacts their climate sensitivities by up to 1 ˚C and reduces inter-model spread.

Climate and Earth system modelling↗