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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Drivers of Atlantic Tropical Cyclogenesis: African Easterly Waves and the Environment

Abstract Tropical cyclone (TC) genesis requires favorable environmental conditions and an initial disturbance, which, in the North Atlantic, is often an African easterly wave (AEW). Although studies have examined how AEWs and the environment affect TC genesis, their relative importance is less understood. Here, we examine whether AEW strength or sea surface temperatures (SSTs) are the primary drivers of TC genesis. Regional model simulations were performed to address how increased AEW strength and SSTs affect the frequency of AEWs that develop into TCs in a year with below‐average TCs with AEW origins and SSTs. We found that environmental favorability plays a larger role than AEW strength in driving the frequency of TCs with AEW origins. Strengthening the AEWs did not affect the frequency of AEWs that develop into TCs due to low environmental favorability. Warmer SSTs led to increased environmental favorability and a statistically significant increase in TCs with AEW origins.

Bercos‐Hickey, Emily [Climate and Ecosystem Scienc↗
DOE OSTI2022

Reduced scale stripline platform to extend accessible pressures on the Z machine: Shockless compression of platinum to 650 GPa

Reaching astrophysically relevant high energy density (HED) material states in the laboratory is an ongoing effort at multiple experimental facilities. We have developed a new dynamic compression platform for the Z Pulsed Power Facility that allows for sample sizes 100s of [Formula: see text]m in thickness that accommodate multiple grains in order to fully capture bulk properties, such as material strength. A pair of experiments compressed platinum (Pt) to HED conditions and conventional inverse Lagrangian analysis as well as a recent Bayesian calibration technique were used to determine the principal isentrope to 650 GPa with density uncertainties of <2%. These low uncertainties are calculated for single sample experiments, presenting the possibility of even smaller experimental uncertainties with multiple samples the platform allows. Our new platform extends the accessible Pt ramp pressures achievable on the Z machine to over 80% of the pressure recently achieved using the National Ignition Facility planar Hohlraum platform. This new capability, the next generation evolution of the stripline platform, was made possible by advancements in both our understanding of the Z pulsed power driver and our overall magnetohydrodynamic modeling capabilities.

Porwitzky, Andrew↗
DOE OSTI2026

Did You Win the GPU Cloud Lottery? Benchmarking from TFLOPS to Tokens/$

Cloud GPUs are commonly assumed to deliver consistent performance for a given GPU model. This assumption does not always hold: cloud providers employ diverse system configurations and virtualization mechanisms, and GPUs themselves exhibit non-negligible manufacturing variability (the silicon lottery). In this work, we present a large-scale measurement study of GPU performance variability across 11 cloud providers, covering over 3,500 physical GPUs and 6,800 benchmark runs. Our hierarchical analysis shows that while execution-level variation stays below 9%, performance varies by up to 38% across devices and providers for the same GPU model. Regression analysis indicates that driver- and OS-related software factors contribute less than 1% of the variance; instead, silicon lottery effects dominate observed performance variation, and cloud providers further amplify them through persistent, systematic second-order effects.

Slynko, Platon [Silicon Data, New York, USA] (ORCI↗
DOE OSTI2021

Resource Occurrence and Productivity in Existing and Proposed Wind Energy Lease Areas on the Northeast US Shelf

States in the Northeast United States have the ambitious goal of producing more than 22 GW of offshore wind energy in the coming decades. The infrastructure associated with offshore wind energy development is expected to modify marine habitats and potentially alter the ecosystem services. Species distribution models were constructed for a group of fish and macroinvertebrate taxa resident in the Northeast US Continental Shelf marine ecosystem. These models were analyzed to provide baseline context for impact assessment of lease areas in the Middle Atlantic Bight designated for renewable wind energy installations. Using random forest machine learning, models based on occurrence and biomass were constructed for 93 species providing seasonal depictions of their habitat distributions. We developed a scoring index to characterize lease area habitat use for each species. Subsequently, groups of species were identified that reflect varying levels of lease area habitat use ranging across high, moderate, low, and no reliance on the lease area habitats. Among the species with high to moderate reliance were black sea bass ( Centropristis striata ), summer flounder ( Paralichthys dentatus ), and Atlantic menhaden ( Brevoortia tyrannus ), which are important fisheries species in the region. Potential for impact was characterized by the number of species with habitat dependencies associated with lease areas and these varied with a number of continuous gradients. Habitats that support high biomass were distributed more to the northeast, while high occupancy habitats appeared to be further from the coast. There was no obvious effect of the size of the lease area on the importance of associated habitats. Model results indicated that physical drivers and lower trophic level indicators might strongly control the habitat distribution of ecologically and commercially important species in the wind lease areas. Therefore, physical and biological oceanography on the continental shelf proximate to wind energy infrastructure development should be monitored for changes in water column structure and the productivity of phytoplankton and zooplankton and the effects of these changes on the trophic system.

17 WIND ENERGY↗
NASA NTRS2011

Climate Forcing Reconstructions for Use in PMIP Simulations of the Last Millennium (v1.0)

Simulations of climate over the Last Millennium (850-1850 CE) have been incorporated into the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3). The drivers of climate over this period are chiefly orbital, solar, volcanic, changes in land use/land cover and some variation in greenhouse gas levels. While some of these effects can be easily defined, the reconstructions of solar, volcanic and land use-related forcing are more uncertain. We describe here the approach taken in defining the scenarios used in PMIP3, document the forcing reconstructions and discuss likely implications.

volcanoes↗
NASA NTRS2014

Nano-Launcher Technologies, Approaches, and Life Cycle Assessment

Assist in understanding NASA technology and investment approaches, and other driving factors, necessary for enabling dedicated nano-launchers by industry at a cost and flight rate that (1) could support and be supported by an emerging nano-satellite market and (2) would benefit NASAs needs. Develop life-cycle cost, performance and other NASA analysis tools or models required to understand issues, drivers and challenges.

launch costs↗
NASA NTRS2017

Incorporating Planetary-Scale Waves Into the VTGCM: Understanding the Waves Impact on the Upper Atmosphere of Venus.

Venus has proven to have a very dynamic upper atmosphere. The upper atmosphere of Venus has been observed for many decades by multiple means of observation (e.g. ground-based, orbiters, probes, fly-by missions going to other planets). As of late, the European Space Agency Venus Express (VEX) orbiter has been a main observer of the Venusian atmosphere. Specifically, observations of Venus' O2 IR nightglow emission have been presented to show its variability. Nightglow emission is directly connected to Venus' circulation and is utilized as a tracer for the atmospheric global wind system. More recent observations are adding and augmenting temperature and density (e.g. CO, CO2, SO2) datasets. These additional datasets provide a means to begin analyzing the variability and study the potential drivers of the variability. A commonly discussed driver of variability is wave deposition. Evidence of waves has been observed, but these waves have not been completely analyzed to understand how and where they are important. A way to interpret the observations and test potential drivers is by utilizing numerical models.

Venus↗
NASA NTRS2004

Advances in Scientific Balloon Thermal Modeling

The National Aeronautics and Space Administration's Balloon Program office has long acknowledged that the accurate modeling of balloon performance and flight prediction is dependant on how well the balloon is thermally modeled. This ongoing effort is focused on developing accurate balloon thermal models that can be used to quickly predict balloon temperatures and balloon performance. The ability to model parametric changes is also a driver for this effort. This paper will present the most recent advances made in this area. This research effort continues to utilize the "Thrmal Desktop" addition to AUTO CAD for the modeling. Recent advances have been made by using this analytical tool. A number of analyses have been completed to test the applicability of this tool to the problem with very positive results. Progressively detailed models have been developed to explore the capabilities of the tool as well as to provide guidance in model formulation. A number of parametric studies have been completed. These studies have varied the shape of the structure, material properties, environmental inputs, and model geometry. These studies have concentrated on spherical "proxy models" for the initial development stages and then to transition to the natural shaped zero pressure and super pressure balloons. An assessment of required model resolution has also been determined. Model solutions have been cross checked with known solutions via hand calculations. The comparison of these cases will also be presented. One goal is to develop analysis guidelines and an approach for modeling balloons for both simple first order estimates and detailed full models. This papa presents the step by step advances made as part of this effort, capabilities, limitations, and the lessons learned. Also presented are the plans for further thermal modeling work.

Bohaboj, T.↗
NASA NTRS2018

Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing

We present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from ten climate models, we show how modeled global mean precipitation increases by 2-3% per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature-driven (slow) ocean HS of 3-5%/K, while the slow land HS is only 0-2%/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. We identify a particular need for model investigations and observational constraints on convective precipitation in the Arctic, and large-scale precipitation around the Equator.

Samset, B. H.↗
NASA NTRS2012

Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

Cook, Bruce D.↗
DOE OSTI2026

Accelerated Carbon and Water Cycles in the Amazon and Congo Basins Revealed From TRENDY Models and Remote Sensing Products

Tropical forests play a vital role in the global carbon cycle and land–atmosphere interactions. Estimating tropical forest carbon–water dynamics is challenging due to observational and modeling uncertainties. This study leverages the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project models and satellite observations to assess changes (2003–2021) in vegetation carbon, gross primary production (GPP), evapotranspiration (ET), and net biosphere production (NBP) in the Amazon and Congo. Atmospheric CO 2 , climate variability, and land use and land cover changes constrain these variables between 1700 and 2021 with the overall increasing trends of carbon stock and fluxes. The models overestimate vegetation carbon and GPP, while ET and NBP are consistent with observations. Fire-activated models predict lower values for vegetation carbon and GPP, ET, and NBP, aligning more closely with observations. The higher ET from fire-activated models may result from enhanced soil evaporation due to increased canopy openings. Fire-inactivated models could well estimate the magnitudes of NBP. The high vegetation carbon in nitrogen-enabled models points to simulation uncertainties and imbalance in model numbers regarding the nitrogen cycle. Although the nitrogen cycle enhances water use efficiency in both the Amazon and Congo, the models show a higher sensitivity to the nitrogen cycle in the Congo. This study highlights the challenges in accurately representing tropical biogeochemical cycles and the values of satellite products in model evaluations, underscoring the need for standard modeling protocols that address biogeochemical components (e.g., nutrient cycles) to better resolve process-based representations.

Shi, Mingjie [Pacific Northwest National Laborator↗
NASA NTRS2004

Modeling of Turbulence Effects on Liquid Jet Atomization and Breakup

Recent experimental investigations and physical modeling studies have indicated that turbulence behaviors within a liquid jet have considerable effects on the atomization process. For certain flow regimes, it has been observed that the liquid jet surface is highly turbulent. This turbulence characteristic plays a key role on the breakup of the liquid jet near to the injector exit. Other experiments also showed that the breakup length of the liquid core is sharply shortened as the liquid jet is changed from the laminar to the turbulent flow conditions. In the numerical and physical modeling arena, most of commonly used atomization models do not include the turbulence effect. Limited attempts have been made in modeling the turbulence phenomena on the liquid jet disintegration. The subject correlation and models treat the turbulence either as an only source or a primary driver in the breakup process. This study aims to model the turbulence effect in the atomization process of a cylindrical liquid jet. In the course of this study, two widely used models, Reitz's primary atomization (blob) and Taylor-Analogy-Break (TAB) secondary droplet breakup by O Rourke et al. are examined. Additional terms are derived and implemented appropriately into these two models to account for the turbulence effect on the atomization process. Since this enhancement effort is based on a framework of the two existing atomization models, it is appropriate to denote the two present models as T-blob and T-TAB for the primary and secondary atomization predictions, respectively. In the primary breakup model, the level of the turbulence effect on the liquid breakup depends on the characteristic time scales and the initial flow conditions. This treatment offers a balance of contributions of individual physical phenomena on the liquid breakup process. For the secondary breakup, an addition turbulence force acted on parent drops is modeled and integrated into the TAB governing equation. The drop size formed from this breakup regime is estimated based on the energy balance before and after the breakup occurrence. The turbulence energy is also considered in this process.

Trinh, Huu↗
DOE OSTI2026

Improving coastal water level estimation by merging nadir-only satellite altimetry data into a hydrodynamic model

Providing robust real time flood warnings is of paramount importance to coastal communities. Although state-of-the-art hydrodynamic models are capable of robustly predicting Coastal Water Levels (CWL), unresolved drivers affecting level fluctuations are often not represented by the model governing equations. This work evaluates a novel method to improve the performance of the ADvanced CIRCulation (ADCIRC) hydrodynamic model by assimilating observations from four nadir-only satellite altimetry missions against a set of National Oceanic and Atmospheric Administration (NOAA) gauge stations located across the entire U.S. East Coast. Two different types of simulations were performed – Open Loop (OL) and Data Assimilation (DA). Five different simulations were performed where four different satellite altimetry observations were assimilated individually and combined with two different scenarios – with and without considering the data quality flags. Results indicate that, despite their limited spatial coverage, merging nadir-only observations into ADCIRC from the newly launched Surface Water and Ocean Topography (SWOT)’s nadir altimeter can improve the model performance at 76% of the gauge locations, whereas Sentinel-6 improves 73% of the total locations, Jason-3 74%, and SARAL 21%. Furthermore, combining observations from SWOT-nadir, Jason-3, and Sentinel-6 can improve the ADCIRC performance at more than 80% of the gauge locations for 107-day simulation. Nadir-only satellite altimetry observations can be useful for improving the model performance even if flagged as “poor quality” near the coast. When the flagged data are disregarded, SWOT can improve ADCIRC at 78%, Sentinel-6 at 73%, Jason-3 at 53%, and SARAL at 21% of the gauge locations. The ability to improve the model simulations largely depends on the availability of a satellite overpass nearby. Therefore, model performance can be further enhanced if satellite observations are available during a storm surge event, stressing the importance of frequent satellite overpasses.

Aafnan Bhuiyan, Soelem↗
DOE OSTI2021

The Highly Integrated Vehicle Ecosystem (HIVE): A Platform for Managing the Operations of On-Demand Vehicle Fleets

This paper introduces the Highly Integrated Vehicle Ecosystem (HIVE), a transportation modeling tool developed by within the Center for Integrated Mobility Sciences (CIMS) group at the National Renewable Energy Laboratory (NREL). HIVE is an agent-based supply/demand model for Mobility on Demand (MoD) which mixes agent-based modeling and centralized dispatch for automated and human-driven fleets and ride hail passengers. Research questions using HIVE span multiple categories, including intelligent fleet planning (assessing fleet, battery, and infrastructure investment decisions), intelligent fleet control (charge management, vehicle dispatching) and strategic business model decision-making (depot-based full-time drivers versus gig-based drivers, human-driven versus automated). The components of the HIVE model are explained and then HIVE is demonstrated in a case study using demand data from the New York City Taxi & Limousine Commission data set.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Ice Sheet and Ice Shelf Freshwater Forcing of the NASA GISS ModelE GCM

Recent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS-E2.1-G (a CMIP6 model) simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. In this ensemble there are detectable differences in zonal-mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Southern Ocean surface temperature and Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all-forcing historical simulations in future coupled model intercomparisons.

Ice sheet↗
DOE OSTI2022

Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads

Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and extreme changes in wind direction are also considered for the 5 MW model. Perhaps surprisingly, veer is identified as an important driver of main-bearing load fluctuations. Upscaling results indicate that similar behaviour holds as turbines become larger, but with mean loads and load fluctuation levels increasing at least cubically with the turbine rotor radius. Strong links between turbine control and main-bearing load response are also observed.

17 WIND ENERGY↗
DOE OSTI2023

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗