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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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FY21 highlights on historic preservation accomplishments, cultural resource accomplishment, and public outreach accomplishments. Future work and associated funding requests are presented.
The U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) proposes the removal of three primary resources and 24 accessory resources in Mercury on the Nevada National Security Site (NNSS) in Nye County, Nevada. The majority of the resources are concrete pads that have previously been recorded as either primary resources or accessory resources thereof within the Mercury Historic District (MHD). They represent the former locations of environmental support program buildings including a greenhouse (MHD Resource C312), warehouses (Resource C293), offices (Resource C314), dormitories (Resource C298), and two of unknown purpose (Resource C292). The other resources include a buried storage tank and sidewalks.
Summary of a project to install a solar array on roof upgrades at the historic Colonial Theatre in Bethlehem, New Hampshire.
Although spacecraft developers have been moving towards standardized product lines as the aerospace industry has matured, NASA's continual need to push the cutting edge of science to accomplish unique, challenging missions can still lead to spacecraft resource growth over time. This paper assesses historical mass, power, cost, and schedule growth for multiple NASA spacecraft from the last twenty years and compares to industry reserve guidelines to understand where the guidelines may fall short. Growth is assessed from project start to launch, from the time of the preliminary design review (PDR) to launch and from the time of the critical design review (CDR) to launch. Data is also assessed not just at the spacecraft bus level, but also at the subsystem level wherever possible, to help obtain further insight into possible drivers of growth. Potential recommendations to minimize spacecraft mass, power, cost, and schedule growth for future missions are also discussed.
Phytoplankton primary productivity in the Subarctic Atlantic Ocean sustains valuable fisheries and exports anthropogenic atmospheric carbon dioxide, but multiple Earth system models show that this productivity declines substantially in 21st century global warming scenarios. Prior studies have investigated the spatial and temporal dynamics of the seasonal cycle of the phytoplankton, which exhibit a prominent but spatially variable spring bloom that is caused by the closely related seasonal cycles in solar radiation and vertical mixing that modulate both phytoplankton growth and loss rates. However, recent work indicates that multi-decade declines in this spring bloom with global warming in multiple Earth system models are driven by reductions in circulation of nutrients from the subtropical and tropical thermocline, rather than local changes in vertical mixing or shortwave radiation in the Subarctic. It is unclear if current models of how phytoplankton productivity varies seasonally or over a century in global warming can be interpolated to explain the interannual to decadal variability. In this poster, I will quantify the interannual to decadal variability of phytoplankton chlorophyll using historical satellite ocean color observations and model simulations with the Community Earth System Model. I will then use the observations and model simulations to elucidate the mechanisms of interannual to decadal variability and how that variability is restructured in 21st century global warming scenarios.
Ground-motion simulations generated from physics-based wave propagation models are gaining increasing interest in the engineering community for their potential to inform the performance-based design and assessment of infrastructure residing in active seismic areas. A key prerequisite before the ground-motion simulations can be used with confidence for application in engineering domains is their comprehensive and rigorous investigation and validation. This article provides a four-step methodology and acceptance criteria to assess the reliability of simulated ground motions of not historical events, which includes (1) the selection of a population of real records consistent with the simulated scenarios, (2) the comparison of the distribution of Intensity Measures (IMs) from the simulated records, real records, and Ground-Motion Prediction Equations (GMPEs), (3) the comparison of the distribution of simple proxies for building response, and (4) the comparison of the distribution of Engineering Demand Parameters (EDPs) for a realistic model of a structure. Specific focus is laid on near-field ground motions (<10km) from large earthquakes (M w 7), for which the database of real records for potential use in engineering applications is severely limited. The methodology is demonstrated through comparison of (2490) near-field synthetic records with 5 Hz resolution generated from the Pitarka et al (2019) kinematic rupture model with a population of (38) pulse-like near-field real records from multiple events and, when applicable, with NGA-W2 GMPEs. Lastly, the proposed procedure provides an effective method for informing and advancing the science needed to generate realistic ground-motion simulations, and for building confidence in their use in engineering domains.
The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets creates uncertainty as well as new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. The proposed algorithm is approximately 100 times faster and uses orders of magnitude less data than a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.
Porphyrins are important molecules widely found in nature in the form of enzyme active sites and visible light absorption units. Recent interest in using these functional molecules as building blocks for the construction of metal–organic frameworks (MOFs) have rapidly increased due to the ease in which the locations of, and the distances between, the porphyrin units can be controlled in these porous crystalline materials. Porphyrin-based MOFs with atomically precise structures provide an ideal platform for the investigation of their structure–function relationships in the solid state without compromising accessibility to the inherent properties of the porphyrin building blocks. Here, this review will provide a historical overview of the development and applications of porphyrin-based MOFs from early studies focused on design and structures, to recent efforts on their utilization in biomimetic catalysis, photocatalysis, electrocatalysis, sensing, and biomedical applications.
Here, we present spectroscopic investigations of uranium in two historical glasses. A 1920's-1930's Art Deco (Bagley Carnival) green soda-lime-silica uranium glass bowl and a 1930's-1940's (Thomas Webb) yellow full lead crystal uranium glass vase were studied using optical absorption spectroscopy, XRF and SEM-EDX, X-band EPR and High- Energy Resolution Fluorescence-Detected (HERFD)-XANES. Uranium speciation may be different in the two glasses. Uranium occurs as uranyl groups (UO 2 2+ ) with minority reduced uranium species, mostly as U(V), more important in the Webb glass than in the Bagley glass. The differences between the two glasses arise from the fining procedure and result from the presence of other multivalent elements and differences in base glass composition. Electron Paramagnetic Resonance (EPR) spectra show the presence of an incipient signal close to g~2, partially annealed by heating to 550 °C, which we assign to a small concentration of radiation-induced defects caused by uranium decay. The presence of multivalent glass components in addition to U (As + Cu + Fe in the Bagley glass and Sb + Fe in the Webb glass) can trap the electron-hole pairs generated by the presence of uranium. This may explain the weakness of this signal in these glasses that anyway received a limited radiation dose since their fabrication. The low activity of these glasses, close to the background radiation, confirms that there is no danger to exhibiting them in museums.
Measurement of radioactive gas seepage from an underground nuclear explosion is one of the primary methods to confirm whether an event was nuclear in nature. Radioactive noble gas indicators that are commonly targeted by such measurements (e.g. 133Xe, 37Ar) have half-lives of 35 days or less. Argon-39, an activation product similar to 37Ar, is produced by the interaction between neutrons and potassium in the surrounding geology and has a half-life of 269 years. Measurements taken at three sites near three historic underground nuclear test locations at the Nevada National Security Site have all shown highly elevated levels of 39Ar in subsurface air decades after the test events. Elevated levels of 39Ar (30-50 times background) were also detected in atmospheric air collected roughly 30 cm above ground level near two of these sites, and outside the entrance of the one tunnel site. These measurements demonstrate that 39Ar has the potential to be a long-term signature of an underground nuclear event which can be reliably detected at the surface or in the shallow subsurface. This radionuclide detection of an underground nuclear event decades after the event takes place is in contrast to the commonly held assumption that detecting underground nuclear events via radionuclides at the surface needs to be done in a matter of months. Depending upon what further studies show about the robustness of this signature in a variety of geological settings, it may in fact be easy to detect underground nuclear events at the surface for a very long time post-detonation.
Many regions worldwide have experienced increasing wildfire activity in recent years and climate changes are predicted to result in more frequent and severe fires. Reconstruction of past fire activity offers paleoenvironmental context for modern and future burning. Pyrogenic polycyclic aromatic hydrocarbons (PAHs) have been increasingly used as a molecular biomarker for fire occurrence in the paleorecord and offer opportunity for nuanced reconstructions of fire characteristics. A suite of PAHs are produced during combustion, and the emission amount and assemblage is influenced by many variables including fuel type, fire temperature, and oxygen availability. Despite recent advances in understanding the controls and taphonomy of these biomass burning markers, the spatial scale of this proxy is unknown. In this paper, measurements of PAH fluxes preserved in a lake sediment archive from the Sierra Nevada, California were compared with a historical geographic information system dataset of area burned up to 150 km distance from the lake to determine the spatial scales for which these biomarkers are reliable proxies of burning. Comparisons of PAH fluxes with charcoal accumulation rates in the same sediments suggest that pyrogenic particulate transport modulates low to mid-molecular weight PAHs via adsorption. Overall, the results indicate that PAH records integrate a combination of spatial signals of area burned and measurement of individual PAHs may enable cross-scale paleofire reconstructions.
The fire probabilistic risk assessment framework for nuclear power plants relies on experimental data to determine expected fire behavior or to validate models to predict fire conditions in the plant. To support reducing the uncertainty in this experimental data, a research effort was conducted to identify the most frequent and challenging fire scenarios using historic fire data from nuclear power plants in the United States. To support this effort, an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute was produced resulting in data on 2111 fire events, 540 events were labelled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. In conclusion, of these fire types, electrical and electronic equipment, transient combustibles, and liquid fires were the most frequent of the challenging fires. The fire scenario specifics were characterized for each of the eleven selected types and then related to existing fire experiments.
Simulated historical precipitation is evaluated for Coupled Model Intercomparison Project Phase 6 (CMIP6) models using precipitation indices defined by the Expert Team on Climate Change Detection and Indices. The model indices are evaluated against corresponding indices from the CPC unified gauge-based analyses of precipitation over seven geographical regions across the contiguous US (CONUS). The regions assessed match those in recent US National Climate Assessment Reports. To estimate observational uncertainty, precipitation indices for three other observational datasets (HadEx2, Livneh and PRISM) are evaluated against the CPC analyses. Both the moderate and extreme mean precipitation intensities are overestimated over the western CONUS and underestimated in the areas of the Central Great Plains (CGP) in most CMIP6 models tested. Most CMIP6 models overestimate the mean and variability of wet spell durations and underestimate the mean and variability of dry spell durations across the CONUS. Biases in interannual variability of most of the indices have similar patterns to those in corresponding mean biases. The median and interquartile model spreads in CMIP6 model biases are clearly smaller than those in CMIP5 model biases for wet spell durations. Multimodel medians of CMIP6 (CMIP6-MMM) and CMIP5 (CMIP5-MMM) have similar biases in climatology and variability but biases tend to be smaller in CMIP6-MMM. Depending on the index, extreme precipitation is slightly better in parts of the eastern half of the CONUS in CMIP6-MMM, otherwise, the biases in climatology and variability are similar to CMIP5-MMM. CMIP6-MMM performs better than individual models and even observational datasets in some cases. Differences between observational datasets for most indices are comparable to the CMIP6 interquartile model spread. The better-performing observational and model datasets are different in different parts of the CONUS.
The development of transistor architectures, evolving from 2D planar metal-oxide-semiconductor field-effect transistors (MOSFETs) to FinFETs and then to gate-all-around nanowire (GAANW) FETs, plays a crucial role in downscaling technology nodes in the semiconductor industry. This perspective reviews the concept of MOSFETs and summarizes this historical development with particular emphasis on GAANW transistors due to their importance in next-generation technology for nodes below 3 nm. Specifically, the concept of GAANW transistors and their advantages over planar and FinFET devices for further scaling are presented, along with a discussion of their transition from early conceptual ideas to laboratory demonstrations and, ultimately, industrial adoption. Furthermore, potential solutions, such as complementary FETs (CFETs) and 2D semiconductor-based FETs, and their associated challenges for the future generation, known as the Angstrom Era, are discussed in a technological roadmap. In conclusion, this perspective may inspire both industry and academia in future research directions for realizing the Angstrom Era.
The function and lifetime of an atmospheric particle are greatly dependent upon its phase state. Studying particle phase states from specific ambient source types is often challenging due to uncontrolled environmental conditions and multiple source contributions. However, a historic Pacific Northwest wildfire event occurred in September 2020, providing a rare opportunity to study a pseudo-single particle type ambient sample (i.e., wildfire) over time. Sampling was performed in Richland, Washington, capturing aged particles from shifting wildfire sources. In addition to source variability, temporal variation in wildfire particle phase state was observed from single particle analyses. Despite this, single particle elemental compositions were homogenous over time (=87% carbonaceous) with no significant temporal variation in organic functional group abundances within individual particles either (e.g., 4% relative standard deviation in alkene contributions). While particle composition is indeed known to affect phase state, water uptake appeared to be the most significant contributor to phase state variability amongst single particles here, as particle aspect ratios (related to phase state) linearly correlated with ambient relative humidity during sampling (R2 = 0.65). Therefore, while limited to a case study, meteorological considerations are found to convey greater comparative importance than particle composition for aged particle phase state predictions.
Abstract Reconstructed historical streamflow time series can supplement limited streamflow gauge observations. However, there are common challenges of typical modeling approaches: process‐based hydrologic models can be data/computation‐intensive, and statistics‐based models can be region/stream‐specific. Here we present a nationally scalable modeling framework integrating the simulated runoff from the Variable Infiltration Capacity (VIC) model with the Routing Application for Parallel computatIon of Discharge (RAPID) routing model leveraging high‐performance computing. We demonstrate an efficient method of assimilating streamflow at US Geological Survey (USGS) streamflow monitoring sites using a simple hierarchical approach in the VIC‐RAPID framework. The result is a reconstructed 36‐year (1980–2015) daily and monthly streamflow dataset (Dayflow) at ∼2.7 million NHDPlusV2 stream reaches in the conterminous US (CONUS). We perform a comprehensive evaluation at 7,526 USGS sites and characterize their error statistics. The results demonstrate that 49% of the USGS sites demonstrate Kling–Gupta Efficiency (KGE) > 0.5 and 58% of the sites show percentage bias within ±20% for the daily naturalized streamflow. Streamflow data assimilation across CONUS shows an overall improvement over naturalized streamflow, notably in the western semiarid‐to‐arid regions. Comparison to other national and global streamflow reanalysis datasets such as the National Water Model and Global Reach‐scale A priori Discharge Estimates for SWOT demonstrates improved KGE, reduced bias, and directions for Dayflow improvements. Investigations of error statistics with key hydrologic, hydroclimatic, and geomorphologic basin characteristics reveal region‐specific patterns which may help improve future framework applications. Overall, Dayflow may enable a better understanding of hydrologic conditions in a changing environment, especially in locations currently not represented by streamflow monitoring networks.
Abstract Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.
Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate the water resource impacts of forest management scenarios targeting partial or full restoration of the pre-colonial disturbance return interval in the central Sierra Nevada mountains. In a fully restored disturbance regime that includes fire, thinning, and insect mortality, reservoir inflow increases by 4%–9% total and 8%–14% in dry years. At sub-watershed scales (10–100 km2), thinning dense forests can increase streamflow by >20% in dry years. In a thinner forest, increased understory transpiration compensates for decreased overstory transpiration. Consequentially, 73% of streamflow gains are attributable to decreased overstory rain and snow interception loss. Thinner forests can increase headwater peak flows, but reservoir-scale peak flows are almost exclusively influenced by climate. Uncertainty in future precipitation causes high uncertainty in future water yield, but the additional water yield attributable to forest disturbance is about five times less sensitive to annual precipitation uncertainty. This partial decoupling of the streamflow disturbance response from annual precipitation makes disturbance especially valuable for water supply during dry years. Our study can increase confidence in the water resource benefits of restoring historic forest disturbance frequencies in the central Sierra Nevada mountains, and our modeling framework is widely applicable to other forested mountain landscapes.