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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2020

Effects of Different Types of Entrances on Natural Ventilation in a Subway Station

In this study, the natural ventilation of a horizontal entrance of a typical subway station is investigated based on numerical simulations and experiments. In addition, a renormalization group k-e model (RNG k-e model) is applied to compute both the internal and external airflow patterns. Computational fluid dynamics (CFD) simulations are validated based on the experimental results. Furthermore, a multiple variable regression model is employed to study how the different parameters affect the internal airflow rates of the subway station statistically, according to the experimental results. For this typical model, the parameter importance can be ranked as follows: (1) outdoor wind speed; (2) flow resistance of the subway station; (3) height of the wind catcher; and (4) length of the wind catcher. To understand the detailed pressure distribution of the horizontal entrance of the subway station with and without the wind catcher, 3D numerical simulations are conducted for different scenarios. We attempt to alter the size of the wind catcher (including the length and height) to study the characteristics of the pressure on the horizontal entrance of the subway station under outdoor wind-driven conditions. The pressure distributions for the entrance for different scenarios are compared and analyzed. Finally, the interactions between the internal and external flows are investigated by changing the resistance of the subway station. When the internal flow resistance is changed, the pressure coefficient (Cp) of the entrance is different as well. Hence, the Cp is not only affected by the outdoor environment, but is also influenced by the internal airflows.

CFD↗
DOE OSTI2024

Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO 2 and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite-based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite-based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite-based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high-quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite- and model-based AGB estimates. Furthermore, we suggest the carbon-modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Back-to-back high category atmospheric river landfalls occur more often on the west coast of the United States

Abstract The catastrophic December 2022-January 2023 nine atmospheric rivers in California underscore the urgent need to better understand such high-risk weather extremes. Here we applied a machine learning clustering tool to understand the activity of atmospheric river clusters. Reanalysis results show that clusters with high density, that is the time fraction under atmospheric river conditions within a cluster, exhibit more frequent high-category atmospheric rivers, alongside an increased likelihood for extreme precipitation and severe land surface responses. The key circulation patterns of atmospheric river clusters are primarily attributed to subseasonal variability. Furthermore, the occurrence and density of atmospheric river clusters are modulated by the daily variability of the geopotential height field. Climate model projections suggest that atmospheric river clusters with higher density and higher categories will be more frequent as warming level increases. Our findings emphasize the important role of atmospheric river clusters in the development of climate adaptation and resilience strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Dynamic response of nanosecond repetitively pulsed discharges to combustion dynamics: regime transitions driven by flame oscillations

Abstract When using nanosecond repetitively pulsed discharges to actuate on dynamic combustion instabilities, the environment the discharge is created in is unsteady and changing on the timescale of the combustion processes. As a result, individual discharge pulses are triggered in a background gas that evolves at the timescale of combustion dynamics, and pulse-to-pulse variations may be observed during the instability cycle. Prior work has studied nanosecond pulsed discharges in pin-to-ring configurations used to control instabilities in lean-operating swirl-stabilized combustors, and observed variable discharge behavior. The focus of this work is on characterizing how the pulse-to-pulse discharge morphology, energy deposition, and actuation authority, evolve during the combustion instability cycle. This has important implications for designing effective plasma-assisted combustion control schemes. The discharge is observed in two distinct modes, a streamer corona and a nanosecond spark, with the occurrence of each regime directly linked to the phase of the combustor instability. Variation of pulse repetition frequency affects the total fraction of pulses in each mode, while variation of voltage affects the onset of the nanosecond spark mode. The transitions are described in terms of ratios of the relevant combustion and plasma timescales and the implications of this coupled interaction on the design of an effective control scheme is discussed.

Physics↗
DOE OSTI2022

An experimental approach for crown to whole-canopy defoliation in forests

Canopy defoliation is an important source of disturbance in forest ecosystems that has rarely been represented in large-scale manipulation experiments. Scalable crown to canopy level experimental defoliation is needed to disentangle the effects of variable intensity, timing, and frequency on forest structure, function, and mortality. We present a novel pressure-washing-based defoliation method that can be implemented at the canopy-scale, throughout the canopy volume, targeted to individual leaves or trees, and completed within a timeframe of hours or days. Pressure washing proved successful at producing consistent leaf-level and whole-canopy defoliation, with 10%–20% reduction in leaf area index and consistent leaf surface area removal across branches and species. This method allows for stand-scale experimentation on defoliation disturbance in forested ecosystems and has the potential for broad application. Studies utilizing this standardized method could promote mechanistic understanding of defoliation effects on ecosystem structure and function and development of synthetic understanding across forest types, ecoregions, and defoliation sources.

Forestry↗
DOE OSTI2021

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗
DOE OSTI2023

Drought and Extreme Heat Impacts to Data Centers in Northern California

Commonly, data centers are designed and operated on the assumption of stationarity of the climate. Historical weather data informs the basis of their design and operations. However, as a result of climate change, this assumption is not valid and poses a great risk for data centers. In the coming decades, Northern California’s drought and extreme heat risk is projected to increase significantly. This report provides a drought and extreme heat impacts assessment of data centers in this region. Expert solicitation of data center experts enabled a tailored approach to this report. We identify the climate variables and analytics relevant for assessing data center-specific impacts from extreme heat and drought and demonstrate how to access and understand future climate projections from climate models. We emphasize the importance of including future climate projections into data center design and planning. This report is an important first step towards building an effective extreme heat and drought adaptation strategy for data centers in Northern California. While our geographical focus in this report is Northern California, many findings in this report are broadly applicable.

58 GEOSCIENCES↗
DOE OSTI2021

Prognostic Importance of MRI-Detected Extramural Venous Invasion in Rectal Cancer: A Literature Review and Systematic Meta-Analysis

Extramural venous invasion (EMVI) is recognized as a poor prognostic factor in rectal cancer. There are well-documented limitations associated with pathology detection of EMVI, including variable reporting and the inability to use it preoperatively to guide neoadjuvant treatment. Magnetic resonance imaging (MRI)-detected EMVI (mrEMVI) has been proposed as an imaging biomarker. This review assesses the prognostic significance of mrEMVI on survival outcomes and whether regression of mrEMVI after neoadjuvant therapy is associated with improvements in survival.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Spatiotemporal evolution of melt ponds on Arctic sea ice

Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 ± 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up one-to-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

What is Important? Morphological Asymmetries are Useful Predictors of Star Formation Rates of Star-forming Galaxies in SDSS Stripe 82

The morphology and structure of galaxies reflect their star formation and assembly histories. We use the framework of mutual information (MI) to quantify the interdependence among several structural variables and to rank them according to their relevance for predicting the specific star formation rate (SSFR) by comparing the MI of the predictor variables with the SSFR and penalizing variables that are redundant. We apply this framework to study ~3700 face-on star-forming galaxies (SFGs) with varying degrees of bulge dominance and central concentration and with stellar mass $M$ * ≈ 10 9 $M$ ⊙ at redshift $z$ = 0.02–0.12. We use the Sloan Digital Sky Survey (SDSS) Stripe 82 deep $i$-band imaging data, which improve measurements of asymmetry and bulge dominance indicators. We find that star-forming galaxies are a multiparameter family. In addition to $M$ * , asymmetry emerges as the most powerful predictor of SSFR residuals of SFGs, followed by bulge prominence/concentration. Star-forming galaxies with higher asymmetry and stronger bulges have higher SSFR at a given $M$ * . In conclusion, the asymmetry reflects both irregular spiral arms and lopsidedness in seemingly isolated SFGs and structural perturbations by galaxy interactions or mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Assessing the sensitivity and repeatability of permanganate oxidizable carbon as a soil health metric: An interlab comparison across soils

Soil organic matter is central to the soil health framework. Therefore, reliable indicators of Soil organic matter is central to the soil health framework. Therefore, reliable indicators of changes in soil organic matter are essential to inform land management decisions. Permanganate oxidizable carbon (PDXC), an emerging soil health indicator, has shown promise for being sensitive to soil management. However, strict standardization is required for widespread implementation in research and commercial contexts. Here, we used 36 soils-three from each of the 12 USDA soil orders-to determine the effects of sieve size and soil mass of analysis on PDXC results. Using replicated measurements across 12 labs in the US and the EU (n = 7951 samples), we quantified the relative importance of 1) variation between labs, 2) variation within labs, 3) effect soil mass, and 4) effect of soil sieve size on the repeatability of PDXC. We found a wide range of overall variability in PDXC values across labs (0.03 to 171.8%; mean = 13.4%), and much of this variability was attributable to within-lab variation (median = 6.5%) independently of soil mass or sieve size. Greater soil mass (2.5 g) decreased absolute PDXC values by a mean of 177 mg kg -1 soil and decreased analytical variability by 6.5%. For soils with organic carbon (SOC) >10%, greater soil mass (2.5 g) resulted in more frequent PDXC values above the limit of detection whereas the lower soil mass (0.75 g) resulted in PDXC values below the limit of detection for SOC contents <5%. A finer sieve size increased absolute values of PDXC by 124 mg kg -1 while decreasing the analytical variability by 1.8%. In general, soils with greater SOC contents had lower analytical variability. These results point to potential standardizations of the PDXC protocol that can decrease the variability of the metric. We recommend that the PDXC protocol be standardized to use 2.5 g for soils <10% SOC. Sieve size was a relatively small contributor to analytical variability and therefore we recommend that this decision be tailored to the study purpose. Tradeoffs associated with these standardizations can be mitigated, ultimately providing guidance on how to standardize PDXC for routine analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fabric controls on fracture surface roughness of an architected rock material

Fluid flow through fractures is intimately linked to the fracture surfaces that define the void geometry through which fluids flow. Thus, an understanding of what controls fracture surface roughness is essential to the development of models for predicting fluid transport through fractured rock. The difficulty in predicting surface roughness arises from the complexity of rock which is inherently heterogeneous and nonuniform in composition, fabric, and structural components, even when samples are acquired from the same rock mass. Here, a benchmarked-simulation approach motivated from geo-architected 3D printed synthetic gypsum rocks is used to provide insight into the competing contributions from fabric and layering on fracture roughness formation. Simulation results from a discrete element model (Particle Flow Code, Itasca Consulting Group, Inc.) clearly indicate that the relative orientation between mineral layers and in-layer mineral fabric, and the variability in mineral bonding strengths determine whether anisotropic corrugated surfaces or isotropic surfaces are formed. Weak mineral layers oriented perpendicular to the applied load resulted in strong roughness anisotropy. Peak failure loads were found to vary up to 30% depending on the strength of the mineral fabric at the location of fracture initiation, which provides insight into the observed high variability in strength values of natural rock. The uniqueness of induced fracture roughness and peak failure load is intimately linked to layering, mineral fabric, and their distribution in the rock. These findings have important implications for any architected material fabricated through serial printing of layers with local compositional heterogeneity.

3D printed rock↗
DOE OSTI2020

El Niño–Southern Oscillation Evolution Modulated by Atlantic Forcing

The El Niño–Southern Oscillation (ENSO) exerts a strong influence on tropical Atlantic variability, but it is also affected by Atlantic forcing. Previous research has proposed three Atlantic precursors for ENSO: the North tropical Atlantic, the equatorial Atlantic, and the entire tropical Atlantic. However, the relative importance of these Atlantic precursors for ENSO remains unclear. Here, we present evidence from a set of multimodel partial ocean assimilation experiments that equatorial Atlantic cooling is the main contributor for weakening equatorial zonal winds in the Indo-Pacific sector and subsequent ocean warming in the tropical Pacific. Opposite tendencies occur for a warmer equatorial Atlantic. The equatorial Atlantic affects the interbasin climate seesaw between the Atlantic and Pacific through an atmospheric zonal Wavenumber 1 pattern. However, model mean state biases and systematic errors prevent a precise assessment of the response times for the equatorial Pacific trade winds to Atlantic forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific

Variations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. Here we suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Controlling the spacing of the linked graphene oxide system with dithiol linkers under confinement

2D nanoscale confined systems exhibit behavior that is markedly different from that observed at the macroscale. Confinement can be tuned by controlling the interlayer spacing between confining layers using organic dithiol linkers. Adjusting spacing and selective intercalation have important impacts for catalysis, superconductivity, spin engineering, sodium ion batteries, 2D magnets, optoelectronics, and many other applications. In this study, we report how reaction conditions and organic linkers can be used to create variable, reproducible spacings between graphene oxide to provide confinement systems. We determined the conditions under which the spacing can be variably adjusted by the type of linker used, the concentration of the linker, and the reaction conditions. Employing dithiol linkers of different lengths, such as three (TPDT) and four (QPDT) aromatic rings, we can adjust the spacing between graphene oxide layers under varied reaction conditions. Here, we show that by varying dithiol linker length and using different reaction conditions, we can reproducibly control the spacing between graphene oxide layers from 0.37 nm to over 0.50 nm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Simultaneous observations of the blazar PKS 2155-304 from ultra-violet to TeV energies

Here we report the results of the first ever contemporaneous multi-wavelength observation campaign on the BL Lac object PKS 2155−304 involving Swift , NuSTAR , Fermi -LAT, and H.E.S.S. The use of these instruments allows us to cover a broad energy range, which is important for disentangling the different radiative mechanisms. The source, observed from June 2013 to October 2013, was found in a low flux state with respect to previous observations but exhibited highly significant flux variability in the X-rays. The high-energy end of the synchrotron spectrum can be traced up to 40 keV without significant contamination by high-energy emission. A one-zone synchrotron self-Compton model was used to reproduce the broadband flux of the source for all the observations presented here but failed for previous observations made in April 2013. A lepto-hadronic solution was then explored to explain these earlier observational results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Testing GFM and GFL Inverters Operating With Synchronous Condensers

Inverter-based resources (IBRs) are quickly evolving into a source of reliability services to the electric grid. Penetration levels of variable generation are rapidly increasing, ranging from 60% -70% in some systems. To go further, a fundamental shift is required to address challenges associated with grid stability. Synchronous condensers (SCs) are considered an important complementary technology in such transitions. This paper provides one-of-a-kind insights into real experimental results from operating a real MW-scale system consisting of a 2.2-MVA grid-forming (GFM) and grid-following (GFL) battery energy storage system, 2.5-MVA SCs, and a 3-MVA load bank operating as a small, islanded grid. Challenges that are expected in larger systems were mimicked in this small but real system to demonstrate seamless transitions from one mode to another as well as stable operation with different combinations of GFM and GFM resources, including a "loss of last synchronous generator" case. The experimental results presented in this paper are a valuable resource to everyone involved in developing and validating models or developing controls of power systems consisting of inverters and synchronous condensers.

grid-following converter↗