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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Comprehensive Assessment of Global Surface Net Radiation Products and Uncertainty Analysis

Abstract Earth surface net radiation ( R n ) characterizes the surface radiation budget and plays a critical role in ecological, biogeochemical, and hydrological processes. The R n products from remote sensing and reanalysis have not been validated comprehensively. In this study, four R n products (Clouds and the Earth's Radiant Energy System [CERES], ERA‐Interim, Modern‐Era Retrospective analysis for Research and Applications version 2, and Japanese 55‐year Reanalysis) were validated using global ground measurements on monthly (255 sites) and annual (172 sites) timescales. These products have similar accuracies, with average root‐mean‐square error (RMSE) ranges of 5.35 W m −2 (monthly) and 2.30 W m −2 (annually). However, varying accuracies and systemic biases exist across different climatic zones. The annual land R n intercomparison illustrates that large uncertainty exists over polar regions and deserts. A significantly negative annual anomaly in the CERES product for the 2001–2008 period is identified when examining annual R n anomalies over the global land surface. Detailed uncertainty analysis indicates that the global CERES R n anomaly is mainly due to different versions of input data such as aerosol optical thickness and atmospheric profiles (in 2006 and 2008) and cloud properties (in 2002). This work demonstrates that temporal analysis provides powerful quality control for global time series satellite products when the validation using ground measurements fails to capture potential issues.

Jia, Aolin↗
DOE OSTI2017

Does vapor pressure deficit drive the seasonality of δ 13 C of the net land-atmosphere CO 2 exchange across the United States?: The Influence of VPD on δ 13 C of NEE

The seasonal pattern of the carbon isotope content (δ 13 C) of atmospheric CO 2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO 2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δ source at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ 13 C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δ source at the forest sites (0.5‰variation). We did not find a consistent seasonal relationship between VPD and δ source across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δ sourc e (5‰) dominated by seasonal transitions in C 3 /C 4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ 13 C of land-atmosphere CO 2 exchange (δ source ) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C 3 /C 4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δs ource when background atmospheric observations are remote and/or prone to anthropogenic influence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multihead Attention U‐Net for Magnetic Particle Imaging–Computed Tomography Image Segmentation

Magnetic particle imaging (MPI) is an emerging noninvasive molecular imaging modality with high sensitivity and specificity, exceptional linear quantitative ability, and potential for successful applications in clinical settings. Computed tomography (CT) is typically combined with the MPI image to obtain more anatomical information. Herein, a deep learning‐based approach for MPI‐CT image segmentation is presented. The dataset utilized in training the proposed deep learning model is obtained from a transgenic mouse model of breast cancer following administration of indocyanine green (ICG)‐conjugated superparamagnetic iron oxide nanoworms (NWs‐ICG) as the tracer. The NWs‐ICG particles progressively accumulate in tumors due to the enhanced permeability and retention (EPR) effect. The proposed deep learning model exploits the advantages of the multihead attention mechanism and the U‐Net model to perform segmentation on the MPI‐CT images, showing superb results. In addition, the model is characterized with a different number of attention heads to explore the optimal number for our custom MPI‐CT dataset.

Juhong, Aniwat↗
DOE OSTI2018

Wrapping Nanocellulose Nets around Graphene Oxide Sheets

Constructing advanced functional nanomaterials with pre-designed organized morphologies from low-dimension synthetic and biological components is challenging. Herein, we report an efficient and universal amphiphilicity-driven assembly strategy to construct “hairy” flexible hybrid nanosheets with a 1D cellulose nanofibers (CNFs) net conformally wrapped around 2D graphene oxide (GO) monolayers. This interface-driven bio-synthetic assembly is facilitated by tailoring the surface chemistry of flexible GO sheets, resulting in individual sheets tightly surrounded by dense conformal nanocellulose network. The mechanical stability of the products far exceeds the compressive instability limits of both individual components. Finally, the CNF network significantly enhances the wetting ability of initial hydrophobic reduced GO nanosheets, allowing fast water transport combined with high filtration efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Catalytic Processes to Accelerate Decarbonization in a Net-Zero Carbon World

Reducing carbon dioxide emissions is one of the critical challenges to mitigate global climate change, which is having detrimental impacts on society and the environment. Fossil fuel combustion in transportation, power generation, and industrial processes is the dominant contributor to carbon emissions. Over the past decades, sustainable solutions and strategies have been investigated and developed to enable decarbonization. Catalysis plays an essential role to address this global challenge by increasing energy efficiency, reducing carbon emissions, capturing carbon dioxide, and utilizing clean energy sources to displace fossil fuels. In this Review, the role of catalysis in reducing energy demand was discussed, enhancing process efficiency, displacing carbon-intensive feedstocks and products, and therefore, reducing carbon emissions. Here, recent advances in catalyst development were summarized, focusing on applications to enhance industrial processes efficiency and enable utilization of clean energy sources. Emerging approaches in catalysis were reviewed, including the manufacture of iron and steel, direct air capture of CO 2 , production of ethylene, ammonia, and sustainable aviation fuels, plastic recycling, and the synthesis of biobased plastics. The Review was concluded with suggested research directions to achieve a carbon net-zero world.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Ecohydrological controls on grass and shrub above‐ground net primary productivity in a seasonally dry climate

Abstract Seasonally dry, water‐limited regions are often co‐dominated by distinct herbaceous and woody plant communities with contrasting ecohydrological properties. We investigated the shape of the above‐ground net primary productivity (ANPP) response to annual precipitation ( P a ) for adjacent grassland and shrubland ecosystems in Southern California, with the goal of understanding the role of these ecohydrological properties on ecosystem function. Our synthesis of observations and modelling demonstrates grassland and shrubland exhibit distinct ANPP‐ P a responses that correspond with characteristics of the long‐term P a distribution and mean water balance fluxes. For annual grassland, no ANPP occurs below a ‘precipitation compensation point,’ where bare soil evaporation dominates the water balance, and ANPP saturates above the P a where deep percolation and runoff contribute to the modelled water balance. For shrubs, ANPP increases at a lower and relatively constant rate across the P a gradient, while deep percolation and runoff account for a smaller fraction of the modelled water balance. We identify precipitation seasonality, root depth, and water stress sensitivity as the main ecosystem properties controlling these responses. Observed ANPP‐ P a responses correspond to notably different patterns of rain‐use efficiency (RUE). Grass RUE exceeds shrub RUE over a wide range of typical P a values, whereas grasses and shrubs achieve a similar RUE in particularly dry or wet years. Inter‐annual precipitation variability, and the concomitant effect on ANPP, plays a critical role in maintaining the balance of grass and shrub cover and ecosystem‐scale productivity across this landscape. Copyright © 2015 John Wiley & Sons, Ltd.

Parolari, Anthony J.↗
DOE OSTI2020

Determination of Chemical Freeze-Out Parameters from Net-Kaon Fluctuations at RHIC

We calculate the mean-over-variance ratio of the net-kaon fluctuations in the Hadron Resonance Gas (HRG) Model for the five highest energies of the RHIC Beam Energy Scan (BES) for different particle data lists. We compare these results with the latest experimental data from the STAR collaboration in order to extract sets of chemical freeze-out parameters for each list. We focused on the PDG2012 and PDG2016+ particle lists, which differ largely in the number of resonant states. Furthermore, our analysis determines the effect of the amount of resonances included in the HRG on the freeze-out conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Peri-Net-Pro: the neural processes with quantified uncertainty for crack patterns

Abstract This paper develops a deep learning tool based on neural processes (NPs) called the Peri-Net-Pro, to predict the crack patterns in a moving disk and classifies them according to the classification modes with quantified uncertainties. In particular, image classification and regression studies are conducted by means of convolutional neural networks (CNNs) and NPs. First, the amount and quality of the data are enhanced by using peridynamics to theoretically compensate for the problems of the finite element method (FEM) in generating crack pattern images. Second, case studies are conducted with the prototype microelastic brittle (PMB), linear peridynamic solid (LPS), and viscoelastic solid (VES) models obtained by using the peridynamic theory. The case studies are performed to classify the images by using CNNs and determine the suitability of the PMB, LBS, and VES models. Finally, a regression analysis is performed on the crack pattern images with NPs to predict the crack patterns. The regression analysis results confirm that the variance decreases when the number of epochs increases by using the NPs. The training results gradually improve, and the variance ranges decrease to less than 0.035. The main finding of this study is that the NPs enable accurate predictions, even with missing or insufficient training data. The results demonstrate that if the context points are set to the 10th, 100th, 300th, and 784th, the training information is deliberately omitted for the context points of the 10th, 100th, and 300th, and the predictions are different when the context points are significantly lower. However, the comparison of the results of the 100th and 784th context points shows that the predicted results are similar because of the Gaussian processes in the NPs. Therefore, if the NPs are employed for training, the missing information of the training data can be supplemented to predict the results.

Mathematics↗
DOE OSTI2024

Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon

Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.

58 GEOSCIENCES↗
DOE OSTI2018

A Polywell Fusion Reactor Designed for Net Power Generation

A brief history of Polywell progress is recounted. The present PIC simulation explains why the most recent Polywell fusion reactor failed to produce fusion energy. Synchronized variations of multiple parameters would require DC power supplies, not available in historic model testing. Even with DC power, the simulation showed that the trapping of cold electrons would ruin plasma stability during start-up. A theoretical solution to this trapping problem was found in Russian literature describing diocotron-pumping of electrons out of a plasma trap at Kharkov Institute. In Polywell, diocotron-pumping required matching the depth of the potential-well to the electron-beam current falling on a special aperture installed in one of the electromagnets. With diocotron-pumping the reactor was simulated to reach steady-state, maximum-power operation in a few milliseconds of simulated time. These improvements, validated in simulating small-scale DD reactors, were scaled up by a factor of 30 to simulate a large, net-power reactor burning p + {sup 11}B fuel. Power-balance was estimated from a textbook formula for fusion power density by numerically integrating the power density. Unity power-balance required the size of the p + {sup 11}B reactor to be somewhat larger than ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Full and Elementary Nets over the Quotient Field of a Principal Ideal Ring

Let K be the quotient field of a principal ideal ring R, and let σ = (σ{sub ij}) be a full (respectively, elementary) net of order n ≥ 2 (respectively, n ≥ 3) over K such that the additive subgroups σ{sub ij} are nonzero R-modules. It is proved that, up to conjugation by a diagonal matrix, all σ{sub ij} are ideals of a fixed intermediate subring P, R ⊆ P ⊆ K.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Vibrations of a Fluid Containing a Wide Spaced Net with Floats Under Its Free Surface

We consider the problem of low-frequency vibrations of a heavy viscous incompressible fluid occupying a vessel. Under the free surface of the fluid, there is a wide spaced net with floats forming a nonperiodic structure. On the walls of the vessel and the surface of the floats the adhesion condition (zero Dirichlet condition) is imposed. For this problem, which is formulated in terms of a quadratic operator pencil, we construct a limit (homogenized) pencil and establish a homogenization theorem in the case of a “fairly small” number of floats. It is shown that asymptotically, this structure does not affect free vibrations of the fluid.

42 ENGINEERING↗
DOE OSTI2016

Bulk combinatorial synthesis and high throughput characterization for rapid assessment of magnetic materials: Application of laser engineered net shaping (LENS)

A bulk combinatorial approach for synthesizing alloy libraries using laser engineered net shaping (LENS; i.e., 3D printing) was utilized to rapidly assess material systems for magnetic applications. The LENS system feeds powders in different ratios into a melt pool created by a laser to synthesize samples with bulk (millimeters) dimensions. By analyzing these libraries with autosampler differential scanning calorimeter/thermal gravimetric analysis and vibrating sample magnetometry, we are able to rapidly characterize the thermodynamic and magnetic properties of the libraries. Furthermore, the Fe-Co binary alloy was used as a model system and the results were compared with data in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China

The ecological structure in the arid and semi-arid region of Northwest China with forest, grassland, agriculture, Gobi, and desert, is complex, vulnerable, and unstable. It is a challenging and sustaining job to keep the ecological structure and improve its ecological function. Net primary productivity (NPP) modeling can help to improve the understanding of the ecosystem, and therefore, improve ecological efficiency. The boreal ecosystem productivity simulator (BEPS) model provides the possibility of NPP modeling in terrestrial ecosystem, but it has some limitations for application in arid and semi-arid regions. In this paper we improve the BEPS model, in terms of its water cycle by adding the processes of infiltration and surface runoff, to be applicable in arid and semi-arid regions. We model the NPP of forest, grass, and crop in Gansu Province as an experimental area in Northwest China in 2003 using the improved BEPS model, parameterized with moderate resolution remote sensing imageries and meteorological data. The modeled NPP using improved BEPS agrees better with the ground measurements in Qilian Mountain than that with original BEPS, with a higher R2 of 0.746 and lower root mean square error (RMSE) of 46.53 gC/m2 compared to R2 of 0.662 and RMSE of 60.19 gC/m2 from original BEPS. The modeled NPP of three vegetation types using improved BEPS show evident differences compared to that using original BEPS, with the highest difference ratio of 9.21% in forest and the lowest value of 4.29% in crop. The difference ratios between different vegetation types lie on the dependence on natural water sources. The modeled NPP in five geographic zones using improved BEPS are higher than those with original BEPS, with higher difference ratio in dry zones and lower value in wet zones.

Wang, Peijuan↗
DOE OSTI2026

Accelerating laser ray tracing in high fidelity physics simulations of laser melting using squeeze U-net

Laser melting is a core component of the ongoing industrial revolution, dubbed Industry 4.0, as lasers facilitate fast and precise melting and fusion in advanced manufacturing. There is a strong need to optimize the laser process using simulations. However, this has proven challenging as high fidelity simulations are needed for predictive modeling and this is currently prohibitively expensive even when run on hundreds of processors on high performance computers. The challenge is capturing complex physics of laser material interaction, fluid dynamics, thermal physics and material phase transformations at various length and time scales. To close this technological gap, we modified a squeeze U-net to accelerate the laser ray tracing component of such high fidelity models by ~4x–40x while preserving the core physics principle of conservation of energy with 97% accuracy. This approach enables the accurate modeling of global laser energy absorption as a function of local surface temperatures and complex surface topologies, which govern the reflection directions and energy losses of laser rays upon interacting with the material surface.

Computer science↗
DOE OSTI2020

Hydrometeorological sensitivities of net ecosystem carbon dioxide and methane exchange of an Amazonian palm swamp peatland

Here, we report ecosystem-scale CO 2 and CH 4 flux observations for an Amazonian palm swamp peatland over a two-year period in relation to hydrometeorological forcings. Seasonal and short-term variations in hydrometeorological forcing had a strong effect on carbon dioxide and methane fluxes. High air temperature and vapor pressure deficit exerted an important limitation on photosynthesis during the dry season, while latent heat flux appeared to be insensitive to these climate drivers. Evidence from light-response analyses and flux partitioning support that photosynthetic activity was downregulated during dry conditions, while ecosystem respiration was either inhibited or enhanced depending on water table position. The cumulative net ecosystem carbon dioxide exchange indicated that the peatland was a significant carbon dioxide sink ranging from –465 (–279 to –651) g C m -2 y -1 in 2018 to –462 (–277 to –647) g C m -2 y -1 in 2019. The forest was a methane source of 22 (20 to 24) g C m -2 y -1 , similar in magnitude to other tropical peatlands and larger than boreal and arctic peatlands. Furthermore, the annual carbon budget of this Amazonian palm swamp peatland appears to be a major carbon sink under current hydrometeorological conditions, but evidence indicates that the sink strength is vulnerable to future climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Into the net zero emissions and climate change control: From solid carbon waste to effective solar convertors

Here, in this work, we demonstrate the potential for solar-to-heat conversion of carbon byproducts and their outstanding effects to reduce anthropogenic emissions. Those carbon byproducts are soots (biomass, evaporated carbon, etc.) as well as morphed graphenes. Our results cover optical characterization to demonstrate their suitability as heat capacitors and solar-to-heat convertors. Our raw materials are sustainable and currently considered environmental pollutants that require true attention to minimize global warming effects. Fortunately, they are ideal candidates to reduce the carbon footprints and can contribute towards a true net-zero environmental transition. We explore and demonstrate that soots are among the most competitive materials to transform solar energy into heat due to their absorption capacity, and durability. These materials are more competitive than commercial products and other known solar convertors demonstrating the superior thermosolar benefits. The best candidate is biomass with solar absorptivity, light emission, and cost reduction of 96, 85% and 15-fold, respectively, when compare to commercial products. Biomass and soot have comparable or better solar conversion characteristics, and sustainability than pristine carbon nanostructures and they are up to 3 orders of magnitude cheaper.

14 SOLAR ENERGY↗
DOE OSTI2024

The role of the iron and steel sector in achieving net zero U.S. CO 2 emissions by 2050

The U.S. steel sector is a hard-to-abate sector because of its heavy dependence on fossil fuels and its high capital requirements. In 2015, the sector was one of the major carbon emitters, contributing 10 % of the U.S. industrial CO 2 emissions. The ability to decarbonize the U.S. iron and steel sector directly affects the ability of the U.S. to achieve economy-wide net zero CO 2 by 2050. In this paper, we use the Global Change Analysis Model (GCAM) to analyze different U.S. steel sector decarbonization pathways under varying technology, policy, and demand futures. These pathways provide insights on how various low-carbon steelmaking technologies such as those using carbon capture and storage (CCS), hydrogen, or scrap could help reduce U.S. steel emissions by mid-century. In our primary decarbonization pathway, we find that nearly all of the conventional fossil-based steelmaking capacity is fully integrated with CCS by 2050. However, without CCS availability, almost all of the conventional fossil-based steelmaking is phased-out by 2050 and is replaced by hydrogen-based production. Scrap-based production continues to remain vital across both of these decarbonization pathways. Furthermore, we find that demand reduction could help reduce the required levels of CCS and hydrogen-based production in the decarbonization pathways. Implementation of advanced energy efficiency measures could help substantially reduce the sector's energy usage. Finally, we observe that addressing the embodied carbon transfer associated with steel imports will be crucial for fully decarbonizing the U.S. steel sector.

54 ENVIRONMENTAL SCIENCES↗