SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
We leverage the Kellogg Biological Station Long Term Ecological Research Main Cropping System Experiment (KBS MCSE) field experiment to test trade-offs among high growth yield (Y), resource acquisition (A), and stress tolerance (S) traits using metagenomic data from plots with different land use, drought manipulation, and C addition.
Evaluating interventions through long-term human mobility data: initial methods and lessons learned. The tool generated a rich dataset for research and evaluation of behavior that would otherwise be unobserved. The data enabled robust energy estimation of the program. Practice revealed a need for further refinement to reduce participant data input burden.
How, where, and why carbon (C) moves into and out of an ecosystem through time are long-standing questions in biogeochemistry. Here, we bring together hundreds of thousands of C-cycle observations at the Harvard Forest in central Massachusetts, USA, a mid-latitude landscape dominated by 80–120-yr-old closed-canopy forests. These data answered four questions: (1) where and how much C is presently stored in dominant forest types; (2) what are current rates of C accrual and loss; (3) what biotic and abiotic factors contribute to variability in these rates; and (4) how has climate change affected the forest’s C cycle? Harvard Forest is an active C sink resulting from forest regrowth following land abandonment. Soil and tree biomass comprise nearly equal portions of existing C stocks. Net primary production (NPP) averaged 680–750 g C·m –2 ·yr –1 ; belowground NPP contributed 38–47% of the total, but with large uncertainty. Mineral soil C measured in the same inventory plots in 1992 and 2013 was too heterogeneous to detect change in soil-C pools; however, radiocarbon data suggest a small but persistent sink of 10–30 g C·m –2 ·yr –1 . Net ecosystem production (NEP) in hardwood stands averaged ~300 g C·m –2 ·yr –1 . NEP in hemlock-dominated forests averaged ~450 g C·m –2 ·yr –1 until infestation by the hemlock woolly adelgid turned these stands into a net C source. Since 2000, NPP has increased by 26%. For the period 1992–2015, NEP increased 93%. The increase in mean annual temperature and growing season length alone accounted for ~30% of the increase in productivity. Interannual variations in GPP and NEP were also correlated with increases in red oak biomass, forest leaf area, and canopy-scale light-use efficiency. Compared to long-term global change experiments at the Harvard Forest, the C sink in regrowing biomass equaled or exceeded C cycle modifications imposed by soil warming, N saturation, and hemlock removal. Furthermore, the results of this synthesis and comparison to simulation models suggest that forests across the region are likely to accrue C for decades to come but may be disrupted if the frequency or severity of biotic and abiotic disturbances increases.
Overview of the Jefferson Lab Long Term Schedule from 12 GeV to positrons and beyond
Bacterial species often undergo rampant recombination yet maintain cohesive genomic identity. Ecological differences can generate recombination barriers between species and sustain genomic clusters in the short term. But can these forces prevent genomic mixing during long-term coevolution? Cyanobacteria in Yellowstone hot springs comprise several diverse species that have coevolved for hundreds of thousands of years, providing a rare natural experiment. By analyzing more than 300 single-cell genomes, we show that despite each species forming a distinct genomic cluster, much of the diversity within species is the result of hybridization driven by selection, which has mixed their ancestral genotypes. This widespread mixing is contrary to the prevailing view that ecological barriers can maintain cohesive bacterial species and highlights the importance of hybridization as a source of genomic diversity.
ABSTRACT Ten soil cores were collected from the long-term heavy metal-contaminated Savannah River Site (SRS) and studied using shotgun metagenomics. In-line with our previous reports, Bradyrhizobium spp. dominated the SRS soils, and thus we recommend that SRS bioremediation studies target the Bradyrhizobium genus.
Here we propose a high dimensional Bayesian inference framework for learning heterogeneous dynamics of a COVID-19 model, with a specific application to the dynamics and severity of COVID-19 inside and outside long-term care (LTC) facilities. We develop a heterogeneous compartmental model that accounts for the heterogeneity of the time-varying spread and severity of COVID-19 inside and outside LTC facilities, which is characterized by time-dependent stochastic processes and time-independent parameters in ~ 1500 dimensions after discretization. To infer these parameters, we use reported data on the number of confirmed, hospitalized, and deceased cases with suitable post-processing in both a deterministic inversion approach with appropriate regularization as a first step, followed by Bayesian inversion with proper prior distributions. To address the curse of dimensionality and the ill-posedness of the high-dimensional inference problem, we propose use of a dimension-independent projected Stein variational gradient descent method, and demonstrate the intrinsic low-dimensionality of the inverse problem. We present inference results with quantified uncertainties for both New Jersey and Texas, which experienced different epidemic phases and patterns. Moreover, we also present forecasting and validation results based on the empirical posterior samples of our inference for the future trajectory of COVID-19.
Riparian and instream restorations are commonly implemented to improve ecosystem condition. However, very few restoration activities are monitored for multiple years to assess long-term effectiveness. At the Department of Defense’s Fort Benning Military Installation (FBMI) in west-central Georgia, two experimental restoration projects (ephemeral drainage revitalization and instream habitat augmentation [i.e., coarse woody debris (CWD) additions]) were implemented ~14 years ago with the goal of reducing environmental impacts of military training activities. A SERDP project found that instream restoration improved some aspects of ecosystem function and community structure but not others. The objective of the current study was to re-evaluate the effect of these restoration practices on stream ecosystem processes ~14 years after implementation.
This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.
Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.
The authors designed and executed the integrated assessment modeling for the United States long-term strategy. They bring diverse expertise to the modeling and analysis of United States decarbonization. Russell Horowitz, Matthew Binsted, and Haewon McJeon are scientists at the Joint Global Change Research Institute, a partnership between Pacific Northwest National Laboratory and the University of Maryland. Allen Fawcett, James McFarland, and Morgan Browning are economists at the Environmental Protection Agency’s Climate Economics Branch. Claire Henly is White House Fellow at the Office of the US Special Presidential Envoy for Climate. Nathan Hultman is the Director of the Center for Global Sustainability at the University of Maryland.
Triassic rift basins of the eastern United States present a potential option for long–term carbon dioxide (CO 2 ) sequestration. Exposed and buried basins are located near large point CO 2 sources. Because of their similar origins, comparable fill successions indicate a level of reproducibility that can be conveyed between basins. The thick rock successions of the exposed Culpeper and Gettysburg basins served as proxies for understanding of the basin sequences. Their study allowed recognition of five mappable assemblages of rock types, herein termed lithofacies associations. These lithofacies associations were formed by alluvial fan, braided and meandering streams and marginal and distal lake depositional processes.Stratigraphic architecture of the lithofacies associations within exposed basins suggests a vertical succession that consists of an initial coarse-grained fluvial succession that is progressively replaced upward and basinward by finer grained lacustrine deposits. Along the faulted margins of the basins alluvial fans transitioning to fluvial delta deposits reflect lateral progradation and contemporaneous lateral components of the basin filling.To test the model devised in exposed basins, facies associations were developed for the buried Taylorsville Basin. This basin preserves over 8,000 feet of Triassic rocks that are concealed beneath more than 2,000 feet of Cretaceous and Tertiary Coastal Plain sediments. Composition and stratigraphic architecture of these rocks are similar to those observed in exposed basins. Infilling of the basin was the result of vertical aggradation and lateral progradation of coarse-grained to fine-grained facies. Based upon study of outcrops in the Culpeper and Gettysburg basins, groups of recurring lithologic facies were identified as the fundamental constructs of the basin’s sediment infilling. These groups of facies, termed lithofacies associations, represent an amalgamation of lithologic components from broadly similar depositional systems. These lithologic associations were then extrapolated into the exposed and buried portions of the Taylorsville basins. This effort determined that Triassic rift basins provide several avenues for potential study of geologic sequestration of carbon. The characteristic rift basin succession in the basins presents possible reservoir targets within the marginal fluvial deposits. Furthermore, intrusive and extrusive mafic bodies present a potential source of fracture porosity that could serve as CO 2 reservoirs. Porosity values from thin section analysis of exposed basin samples are higher in alluvial fan and braided fluvial lithofacies. Porosity is highest in samples that show less compaction, due to a lack of ductile lithic fragments and/or higher stratigraphic position. Log data from the Taylorsville Basin indicates that porosity and permeability values in basin marginal fluvial strata are elevated. Near the center of the basin, porosity and permeability values are greatly reduced, primarily owing to the fine-grained character of the lacustrine deposits. Some Triassic basins also contain thick intervals of concordant extrusive and intrusive mafic igneous rocks. These igneous bodies are potential CO 2 reservoirs for several reasons. Firstly, extrusive lava flows provide potential storage in the layers of primary porosity that occur in the vesicules formed at the top of lava flows. Secondly, both lava flows and subsurface igneous sills exhibit extensive fracture porosity produced by the rapid cooling of the flows and intrusions. Thirdly, these igneous rocks are mafic in composition, and studies have shown that iron- and magnesium-rich mafic rocks provide sequestration opportunities through carbonate remineralization. Lastly, extrusive and intrusive igneous rocks are invariably preserved within fine-grained lake deposits. These lacustrine sediments can serve as a fine-grained confining layer that encases the igneous rocks both above and below.
This presentation describes an approach to include grid enhancing technologies (GETs) in long-term transmission planning, demonstrating benefits beyond use in operations.
In the past 20 years, it has become clear that the long-term exposure of chromia-forming austenitic stainless steels to air containing ~ 10 vol% water vapor at 650–800 °C significantly increases the Cr consumption rate compared to laboratory air. However, a similar acceleration does not occur in 100% steam because O 2 is not available to form volatile CrO 2 (OH) 2 . As the research has shown, this accelerated Cr loss is particularly important for thin-walled components like gas turbine recuperators. Typically, conventional austenitic stainless steels exhibit accelerated attack (i.e., rapid formation of Fe-rich oxide nodules), while higher alloyed steels resist this type of degradation until the alloy surface becomes Cr depleted. The development of strategies and solutions for this issue are reviewed. Model Fe–Cr–Ni alloys have been used to study composition effects on this behavior. For example, increasing the Mn content up to ~ 4 wt% was not beneficial, but increasing the Ni content improved oxidation resistance in this environment. However, at 650–700 °C even highly alloyed steels showed surface Cr depletion at alloy grain boundaries resulting in Fe-rich oxide nodule formation. The path forward for this issue will require more refined mechanistic understanding and increased used of modeling to develop better application-specific lifetime models to identify the most cost-effective alloy solutions.
This report highlights best practices for enhanced load modeling and forecasting for long-term power sector planning. The best practices touch on stakeholder engagement, data acquisition and management, modeling and validation, and scenario development. Case studies are provided to highlight crosscutting lessons that could inform enhanced load modeling and forecasting across different country settings. Though this work presents best practices resulting from support to the PDOE, the list is by no means exhaustive—nor is it meant to be prescriptive.
A long-term culture of a selected freshwater microalgal assemblage on power plant flue gas was realized using a pilot-scale photobioreactor. Different culture conditions of light cycle, harvesting amount, pH stabilization, and sulfur addition were tested during a 12-month continuous operation at a natural gas fired power plant. The results concluded that the daily harvesting amount of 60% with no light-cycle and NH 4 NO 3 as the nitrogen source and pH stabilization agent, resulted in optimal cultivation performance. Biomass concentration and biomass productivity reached 1.07 ± 0.23 g L -1 and 0.43 ± 0.14 g L -1 d -1 , respectively. During the year-long cultivation period, the algal assemblage was relatively stable with average abundances of 88 ± 4% and 12 ± 4% for algae and bacteria, respectively, and no significant differences between individual case scenarios. The stable culture fostered a stable biomass composition. Protein, carbohydrate, and lipid contents of the algal biomass were 58.60 ± 2.41%, 19.5 ± 2.44%, and 9.70 ± 1.68%, respectively.
The lack of long-term observations and satellite retrievals of health-damaging fine particulate matter in China has demanded the estimates of historical PM 2.5 (particulate matter less than 2.5 µm in diameter) concentrations. This study constructs a gridded near-surface PM 2.5 concentration dataset across China covering 1980–2019 using the space-time random forest model with atmospheric visibility observations and other auxiliary data. The modeled daily PM2.5 concentrations are in excellent agreement with ground measurements during 2015–2019, with a coefficient of determination of 0.95 and mean relative error of 12%. Besides the atmospheric visibility which explains 30% of total importance of variables in the model, both emissions and meteorological conditions are also essential factors affecting PM2.5 predictions. From 1980 to 2014, the model-predicted PM2.5 concentrations increased constantly with the maximum growth rate of 5–10 µg/m3/decade over eastern China. Due to the clean air actions, PM 2.5 concentrations have decreased effectively at a rate over 50 µg/m 3 /decade in the North China Plain and 20–50 µg/m 3 /decade over eastern China during 2014–2019. The newly generated dataset of 1-degree gridded PM 2.5 concentrations for the past 40 years across China provides a useful means for investigating interannual and decadal environmental and climate impacts related to aerosols.
A report that investigates the long-term reliability and aging characteristics of chip-on-board LEDs over the operating lifetime.