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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Particle Size Distributions Obtained Through Unfolding 2D Sections: Towards Accurate Distributions of Nebular Solids in the Allende Meteorite

Size distributions of nebular solids in chondrites suggest an efficient sorting of these early forming objects within the protoplanetary disk. The effect of this sorting has been documented by investigations of modal abundances of CAIs (e.g., [1-4]) and chondrules (e.g., [5-8]). Evidence for aerodynamic sorting in the disk is largely qualitative, and needs to be carefully assessed. It may be a way of concentrating these materials into planetesimal-mass clumps, perhaps 100 fs of ka after they formed. A key parameter is size/density distributions of particles (i.e., chondrules, CAIs, and metal grains), and in particular, whether the radius-density product (rxp) is a better metric for defining the distribution than r alone [9]. There is no consensus between r versus rxp based models. Here we report our initial tests and preliminary results, which when expanded will be used to test the accuracy of current dynamical disk models.

Christoffersen, P. A.↗
NASA NTRS2010

Studies of 21st-Century Precipitation Trends Over West Africa

West Africa includes a semi-arid zone between the Sahara Desert and the humid Gulf of Guinea coast, approximately between 10 N and 20 N, which is irrigated by summer monsoon rains. This article refers to the region as the Sahel. Rain-fed agriculture is the primary sustenance for Sahel populations, and severe droughts (in the 1970s and 1980s), therefore, have devastating negative societal impacts. The future frequency of Sahel droughts and the evolution of its hydrological balance are therefore of great interest. The article reviews 10 recent research studies that attempt to discover how climate changes will affect the hydrology of the Sahel throughout the 21st century. All 10 studies rely on atmosphere ocean global climate model (AOGCM) simulations based on a range of greenhouse gas emissions scenarios. Many of the simulations are contained in the Intergovernmental Panel on Climate Change archives for Assessment Reports #3 and #4. Two of the studies use AOGCM data to drive regional climate models. Seven studies make projections for the first half of the 21st century and eight studies make projections for the second half. Some studies make projections of wetter conditions and some predict more frequent droughts, and each describes the atmospheric processes associated with its prediction. Only one study projects more frequent droughts before 2050, and that is only for continent-wide degradation in vegetation cover. The challenge to correctly simulate Sahel rainfall decadal trends is particularly daunting because multiple physical mechanisms compete to drive the trend upwards or downwards. A variety of model deficiencies, regarding the simulation of one or more of these physical processes, taints models climate change projections. Consequently, no consensus emerges regarding the impact of anticipated greenhouse gas forcing on the hydrology of the Sahel in the second half of the 21st century.

Druyan, Leonard M.↗
NASA NTRSDate not supplied

Galactic Cosmic Ray Simulation at the NASA Space Radiation Laboratory – 2021 Update

For missions beyond low Earth orbit to the Moon or Mars, astronauts will encounter a complex space radiation field composed of various ion species with a broad range of energies. Such missions pose significant radiation protection challenges that need to be managed to minimize astronaut exposures and associated health risks. An innovative galactic cosmic ray simulator (GCRsim) was recently developed for the NASA Space Radiation Laboratory at Brookhaven National Laboratory. The GCRsim technology is intended to recapitulate major components of the space radiation environment in a ground-analog laboratory setting. It is used for experimental studies to improve the understanding of biological risks and act as a test bed for counter measure development and validation. Currently, the GCRsim consists of 33 energetic ion beams that collectively simulate the primary and secondary GCR field encountered by astronauts over the broad range of particle types, energies, and linear energy transfer (LET) of interest to human health effects. A virtual workshop was held in December 2020 to assess the status of NASA's GCRsim and attendees examined various aspects of simulator design, with an emphasis on beam selection strategies. Modeling approaches, experimental constraints, areas of consensus, and questions of concern were also discussed in detail. An overview of the workshop considerations and discussion for research strategies that are important for future advancements and applications in space radio biology are presented.

Nafisah Khan↗
NASA NTRS2018

Ozone Sensitivity to Varying Greenhouse Gases and Ozone-Depleting Substances in CCMI-1 Simulations

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

CCMI↗
NASA NTRS1972

Post-workshop models of Jupiter's radiation belts

Models for the charged particle populations of Jupiter's trapped radiation belts were derived at the Jupiter Radiation Belt Workshop on the basis of several assumptions which represented a consensus of opinion. It was possible to improve the models on the basis of work performed after the workshop concluded. These improvements affect the models in two ways. The effects of special relativity on the particle energy and flux dependences in the magnetosphere were included in a derivation based on L-shell diffusion with conservation of the magnetic moment. Quantitative conclusions are available for the limit which ion cyclotron instability places on the proton population. A set of models which incorporates these developments in a way consistent with the original workshop assumptions and conclusions is described.

Divine, N.↗
NASA NTRS1992

Consensus theoretic classification methods

Consensus theory is adopted as a means of classifying geographic data from multiple sources. The foundations and usefulness of different consensus theoretic methods are discussed in conjunction with pattern recognition. Weight selections for different data sources are considered and modeling of non-Gaussian data is investigated. The application of consensus theory in pattern recognition is tested on two data sets: 1) multisource remote sensing and geographic data and 2) very-high-dimensional remote sensing data. The results obtained using consensus theoretic methods are found to compare favorably with those obtained using well-known pattern recognition methods. The consensus theoretic methods can be applied in cases where the Gaussian maximum likelihood method cannot. Also, the consensus theoretic methods are computationally less demanding than the Gaussian maximum likelihood method and provide a means for weighting data sources differently.

Benediktsson, Jon A.↗
DOE OSTI2022

Chapter 9.12 - Weather, Climatic and Ecological Impacts of Onshore Wind Farms

Wind power is an environmentally sustainable technology that is likely to be part of the solution to the climate change, air pollution, and energy security problems. Despite many positive benefits, the rapid development of wind power has raised concerns about some potential adverse environmental impacts. While converting wind?s kinetic energy into electricity, wind turbines (WTs) modify properties of the atmospheric boundary layer (ABL) including the vertical profiles and surface-atmosphere exchanges of energy, momentum, mass, moisture, and trace gases. Given the current installed capacity and the projected installation worldwide, wind farms (WFs) are likely becoming a major driver of manmade land use change on Earth. Hence, understanding WT-atmosphere-surface interactions and assessing potential environmental impacts of WFs are of significant scientific, societal and economic importance. Here we review our progress in assessing potential impacts of onshore wind power on weather, climate and vegetation activity. A consensus is emerging based on observations and modeling studies that WFs cause a local to regional warming effect, particularly at nighttime, while the impacts on precipitation, wind patterns, crop yields and vegetation activity are uncertain. The warming effect results simply from vertical heat redistribution within the ABL due to turbine-enhanced vertical turbulent mixing in the wakes. At the global scale, with a substantial installation of WFs, mesoscale and climate models predicted large regional changes but small global impacts on temperature, while the impacts on precipitation, clouds, wind patterns and large-scale circulation have large uncertainties and are region specific and scale dependent. Despite increasing number of research efforts, our assessment of potential WF impacts is still very limited. Although the WF impacts are mostly local and limited to the near-surface ABL, this is the layer where we live and plants grow. Hence, more studies are needed to improve our understanding of WT-atmosphere-surface interactions and our capability to model and project the weather, climatic and ecological impacts of large WFs.

atmospheric boundary layer↗
NASA NTRS1988

An illustration of the complexity of continent formation

It was pointed out that a consensus may be emerging in crustal growth models, considering the clustering of most growth curves and their uncertainties. Curves most distant from this clustering represent models involving extensive recycling of continental material back into the mantle, but the author wondered if geochemical signatures for this would be recognizable considering the lack of evidence from seismic tomography for discrete mantle reservoirs, and the likelihood of core-mantle interaction based on recent high pressure experiments. Unreactivated Archean rocks represent only 2 percent of present continental area, and the author was uncomfortable about basing inferences on what the early Earth was like on such a small amount of information. He feels that the hypothesis of continental assembly that needs testing is that of banging together of island arcs, such as in Indonesia today. As an example of how complex this process can be, the author described the geology of the Caribbean arc system, which shows evidence for reversals of subduction polarity, numerous collisional events, and substantial strike-slip movements. It seemed unlikely to the author that Archean examples would have been less complicated.

Burke, Kevin↗
DOE OSTI2022

A level-of-details framework for representing occupant behavior in agent-based models

We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.

42 ENGINEERING↗
DOE OSTI2023

Multi-Model Future Typical Meteorological (fTMY) Weather Files for nearly every US County

Exploring climate-induced impacts on building energy consumption can provide valuable insights for sustainable energy planning and environmental management in the face of a changing climate. By utilizing future weather data statistically downscaled from the Intergovernmental Panel on Climate Change (IPCC) General Circulation Models (GCMs) from 2020-2100, this paper presents a broadening industry-consensus approach for generating future Typical Meteorological Year (fTMY) weather files through a combination of statistical downscaling and high-performance computing that generalizes across decades, multiple locations for a region, and varying climate models. Furthermore, these fTMY files have been generated for 3,128 US counties for capturing potential weather on a 20-year basis.

Building↗
NASA NTRS2014

Comparison of Climatological Planetary Boundary Layer Depth Estimates Using the GEOS-5 AGCM

Planetary boundary layer (PBL) processes, including those influencing the PBL depth, control many aspects of weather and climate and accurate models of these processes are important for forecasting changes in the future. However, evaluation of model estimates of PBL depth are difficult because no consensus on PBL depth definition currently exists and various methods for estimating this parameter can give results that differ by hundreds of meters or more. In order to facilitate comparisons between the Goddard Earth Observation System (GEOS-5) and other modeling and observational systems, seven PBL depth estimation methods are used to produce PBL depth climatologies and are evaluated and compared here. All seven methods evaluate the same atmosphere so all differences are related solely to the definition chosen. These methods depend on the scalar diffusivity, bulk and local Richardson numbers, and the diagnosed horizontal turbulent kinetic energy (TKE). Results are aggregated by climate class in order to allow broad generalizations. The various PBL depth estimations give similar midday results with some exceptions. One method based on horizontal turbulent kinetic energy produces deeper PBL depths in the winter associated with winter storms. In warm, moist conditions, the method based on a bulk Richardson number gives results that are shallower than those given by the methods based on the scalar diffusivity. The impact of turbulence driven by radiative cooling at cloud top is most significant during the evening transition and along several regions across the oceans and methods sensitive to this cooling produce deeper PBL depths where it is most active. Additionally, Richardson number-based methods collapse better at night than methods that depend on the scalar diffusivity. This feature potentially affects tracer transport.

Planetary Boundary Layer Depth↗
DOE OSTI2025

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗
DOE OSTI2025

SWARM: Reimagining scientific workflow management systems in a distributed world

Modern scientific workflows process massive amounts of data from diverse instruments and sensors, leveraging geographically distributed, heterogeneous compute and storage resources—from leadership-class systems to edge devices—connected by high-performance networks. The diversity of resources introduces challenges in harnessing their full potential, with resilience issues arising across applications, system software, networks, storage, and hardware. Today, workflow management systems (WMS) coordinate the execution of computation and data management tasks across target resources. However, WMS’s centralized nature makes them vulnerable to faults and scalability issues that may result in failures of entire computational campaigns. In conclusion, this paper introduces a novel agentic framework for workflow management, fully distributing and decentralizing the WMS functions and modeling them as swarm intelligence agents infused with advanced artificial intelligence solutions and traditional distributed computing algorithms that can make coordinated decisions in the presence of failures of the underlying cyberinfrastructure.

Swarm intelligence↗
NASA NTRS1991

The study of PDF turbulence models in combustion

The accurate prediction of turbulent combustion is still beyond reach for today's computation techniques. It is the consensus of the combustion profession that the predictions of chemically reacting flow were poor if conventional turbulence models were used. The main difficulty lies in the fact that the reaction rate is highly nonlinear, and the use of averaged temperature, pressure, and density produces excessively large errors. The probability density function (PDF) method is the only alternative at the present time that uses local instant values of the temperature, density, etc. in predicting chemical reaction rate, and thus it is the only viable approach for turbulent combustion calculations.

Hsu, Andrew T.↗
DOE OSTI2023

Towards understanding the robust strengthening of ENSO and more frequent extreme El Niño events in CMIP6 global warming simulations

The El Niño Southern Oscillation (ENSO) has profound impacts on weather patterns across the globe, yet there is no consensus on its response to global warming. Several modelling studies find a stronger ENSO in global warming scenarios, while other studies suggest ENSO weakening. Using a broad range of models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and four types of warming experiments, here we show that the majority of the models predict a stronger ENSO by century-end in Shared Social Pathway (SSP) experiments, and in idealized 1pctCO 2 and abrupt 4xCO 2 experiments. Several models, however, do predict no change or ENSO weakening, especially in the idealized experiments. Critically, the strongest forcing (abrupt-4xCO 2 ) does not induce the strongest ENSO response, while differences between the models are much greater than those between warming scenarios. For the long-term response (over 1000 years) the models disagree even on the sign of change. Furthermore, changes in ENSO sea surface temperature (SST) variability are only modestly correlated with the tropical Pacific mean state change. The highest correlation for ENSO SST amplitude is found with the mean zonal SST gradient in the SSP5-8.5 experiment (R = –0.58). In contrast, changes in ENSO rainfall variability correlate well with changes in the mean state, as well as with changes in ENSO SST variability. When evaluating the Bjerknes Stability Index for a subset of models, we find that it is not a reliable predictor of ENSO strengthening, as this index tends to predict greater stability with warming. We argue that the enhanced ENSO stability is offset by increases in atmospheric noise or/and potential nonlinear effects. However, a robust inter-model mechanism that can explain a stronger ENSO simulated with global warming is still lacking. Therefore, caution should be exercised when considering ENSO changes based on a single model or warming scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Watching a signaling protein function: What has been learned over four decades of time-resolved studies of photoactive yellow protein

Photoactive yellow protein (PYP) is a signaling protein whose internal p-coumaric acid chromophore undergoes reversible, light-induced trans-to-cis isomerization, which triggers a sequence of structural changes that ultimately lead to a signaling state. Since its discovery nearly 40 years ago, PYP has attracted much interest and has become one of the most extensively studied proteins found in nature. The method of time-resolved crystallography, pioneered by Keith Moffat, has successfully characterized intermediates in the PYP photocycle at near atomic resolution over 12 decades of time down to the sub-picosecond time scale, allowing one to stitch together a movie and literally watch a protein as it functions. But how close to reality is this movie? To address this question, results from numerous complementary time-resolved techniques including x-ray crystallography, x-ray scattering, and spectroscopy are discussed. Emerging from spectroscopic studies is a general consensus that three time constants are required to model the excited state relaxation, with a highly strained ground-state cis intermediate formed in less than 2.4 ps. Persistent strain drives the sequence of structural transitions that ultimately produce the signaling state. Crystal packing forces produce a restoring force that slows somewhat the rates of interconversion between the intermediates. Moreover, the solvent composition surrounding PYP can influence the number and structures of intermediates as well as the rates at which they interconvert. When chloride is present, the PYP photocycle in a crystal closely tracks that in solution, which suggests the epic movie of the PYP photocycle is indeed based in reality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Software reliability through fault-avoidance and fault-tolerance

Accomplishments in the following research areas are summarized: structure based testing, reliability growth, and design testability with risk evaluation; reliability growth models and software risk management; and evaluation of consensus voting, consensus recovery block, and acceptance voting. Four papers generated during the reporting period are included as appendices.

Vouk, Mladen A.↗
NASA NTRS2013

Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.

Remotely sensed soil moisture validation↗