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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Performance Analysis and Limiting Parameters of Cross-flow Membrane-based Liquid-desiccant Air Dehumidifiers

We report that to dehumidify a humid air stream, existing air conditioning (AC) systems substantially overcool the outdoor humid air below its dew point, thereby significantly reducing energy efficiency. Directly capturing humidity, membrane-based liquid-desiccant dehumidification systems separate sensible and latent cooling (SSLC) loads and thus offer a promising pathway for a high-performance AC solution. Design of an energy-efficient SSLC-AC system, however, rests largely on detailed understating of the dehumidification process. While some studies have identified the dehumidification process mainly depends on membrane characteristics, other studies have argued that the process is limited by desiccant liquid or alternatively air thermo-hydraulic physics for typical humid climate conditions. The present study examines performance and physics of the membrane-based liquid-desiccant dehumidification process over a wide range of climate conditions through a novel 3D, two-phase, multi-species CFD model. Decoupling the thermodynamic and hydraulic effects, the study reveals that the dehumidification rate is a linear function of the water vapor pressure potential ($J=α ΔP$) summarizing the system's thermodynamic state. The slope of the curve (i.e., α) depends on hydraulic transport characteristics of the membrane pores, air stream, and desiccant solution. More importantly, it was found that the air dehumidification process is mainly limited by the air-side transport physics for thin liquid-desiccant films and commonly used porous superhydrophobic membranes. Additionally, results show that, depending on ambient/desiccant conditions and physical dehumidifier characteristics, energy effectiveness and dehumidification rate vary from 13 to 34% and from 0.13 to 1.4 g m -2 s -1 , respectively. Therefore, the present study allows to efficiently design future SSLC-based AC systems exhibiting high performance energy metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Cost of Fish Exclusion and Passage Technologies for Hydropower

Hydropower represents a reliable source of renewable energy and accounts for approximately 7% of the total electrical generation in the United States. Future expansion of hydropower is likely to be in the form of either smaller new stream development projects or powering existing non-powered dams. For these new projects to be successful, careful analysis of risks, costs, and uncertainty to offset reduced power production as well as ensuring the protection and safe passage of migratory fish to gain public support, will be required. Exclusion and passage are two common approaches to protect fish from entrainment and impingement at hydropower facilities. The thresholds for entrainment risk and requirements for exclusion and passage often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders. While the costs associated with environmental mitigations represent a large proportion of the total costs required for the licensing of hydropower facilities, little quantitative information is present within the literature regarding the specific costs of fish exclusion and passage. Working with FOA awardee Natel Energy, scientists at Oak Ridge National Laboratory were tasked with assessing the capital construction costs for downstream fish exclusion and passage infrastructure. This report used keyword searches of an existing environmental mitigation cost data set and manual extraction of additional cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening and passage from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 PM&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens, 142 pertaining to passage studies, and 26 pertaining to passage-related studies. PM&E measures associated with positive barrier screens represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with new stream development (NSD) projects. Results from these data indicate highly variable costs associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1 to 2 in.). Furthermore, estimated capital costs of passage infrastructure were positively related to the scale of the project based on installed capacity for some, but not all, types of passage. These data provide an initial baseline for estimating exclusion and passage costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects. More data may still be available within the FERC eLibrary, but significant effort will be required to manually identify and extract the data for future analyses.

13 HYDRO ENERGY↗
DOE OSTI2019

Global meta-analysis of published river bank erosion and migration rates

This dataset is a compilation of 993 measurements of riverbank erosion or migration rates from 336 rivers and streams compiled from 169 published English language studies. The dataset spans rivers across latitudes ranging from 46 deg south to 71 deg north. The rivers range in drainage area from 0.6 to 3 million square kilometers. If provided in a published study, recorded channel width, river drainage area, and sediment load and/or yield were summarized. In the absence of these ancillary data from the original source, this data was compiled from other published studies, global and regional datasets, or measured from Google Earth images. The dataset also provides information on whether the rates were measured at an individual river bend or represent reach-based averages, as well as, whether the river is single or multi-threaded.Revisions 2023 January updateAdded 72 new erosion measurements. Dropped 10 records that did not have mean erosion values.“DrainageArea(km^2)_rabpro” added“DrainageArea(km^2)” – updated to only include published drainage area and values obtained from sources other than the rabpro analysis.“River_slope_pub” added to provide river slope values provided in the published erosion study or other source listed in the “Slope Reference” field“RiverSlope_Lin” added“FLO1K_MonthlyMax_LT” and “FLO1K_MontlyMax_PoR” added“KG_Zone” added from Köppen-geiger climate classification based on Beck et al. 2018

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Factors controlling seasonal groundwater and solute flux from snow‐dominated basins

Abstract Critical zone influences on hydrologic partitioning, subsurface flow paths and reactions along these flow paths dictate the timing and magnitude of groundwater and solute flux to streams. To isolate first‐order controls on seasonal streamflow generation within highly heterogeneous, snow‐dominated basins of the Colorado River, we employ a multivariate statistical approach of end‐member mixing analysis using a suite of daily chemical and isotopic observations. Mixing models are developed across 11 nested basins (0.4 to 85 km 2 ) spanning a gradient of climatological, physical, and geological characteristics. Hydrograph separation using rain, snow, and groundwater as end‐members indicates that seasonal contributions of groundwater to streams is significant. Mean annual groundwater flux ranges from 12% to 33% whereas maximum groundwater contributions of 17% to 50% occur during baseflow. The direct relationship between snow water equivalent and groundwater flux to streams is scale dependent with a trend toward self‐similarity when basins exceed 5.5 km 2 . We find groundwater recharge increases in basins of high relief and within the upper subalpine where maximum snow accumulation is coincident with reduced conifer cover and lower canopy densities. The mixing model developed for the furthest downstream site did not transfer to upstream basins. The resulting error in predicted stream concentrations points toward weathering reactions as a function of source rock and seasonal shifts in flow path. Additionally, the potential for microbial sulfate reduction in floodplain sediments along a low‐gradient, meandering portion of the river is sufficient to modify hillslope contributions and alter mixing ratios in the analysis. Soil flushing in response to snowmelt is not included as an end‐member but is identified as an important mechanism for release of solutes from these mountainous watersheds. End‐member mixing analysis used in combination with high‐frequency observations reveals important aspects of catchment hydrodynamics across scale.

Carroll, Rosemary W. H.↗
DOE OSTI2020

Evaluation of near-ambient algal biomass fractionation conditions for bioproduct development

This contribution describes an algal fractionation scheme based on cell lysing and carbohydrate hydrolysis under acidic conditions, coupled with solvent extraction, that produces algal lipids, carbohydrates, and proteinaceous solid from partially dewatered algal biomass. Here, a design of experiments analysis was employed to identify the effect of fractionation conditions on the yields of the three product streams. By selection of appropriate conditions, the process can be steered from simple lipid extraction to near complete fractionation of the biomass. Lipid purification and upgrading were respectively achieved with a low-cost adsorbent and an inexpensive Ni-based catalyst that deoxygenated the lipids via decarboxylation/decarbonylation, an approach offering several advantages over the hydrodeoxygenation-based processes typically employed to convert lipids to hydrocarbons. The proteinaceous solids obtained were found to have much lower ash content as well as higher protein content relative to the untreated algae, enhancing the suitability of this material as a feedstock for the production of bioplastics.

09 BIOMASS FUELS↗
DOE OSTI2025

Ion Clusters Reveal the Sources, Impacts, and Drivers of Freshwater Salinization

Population growth, land use change, climate change, and natural resource extraction are driving the salinization of freshwater resources worldwide. Reversing these trends will require data-centric approaches that identify salt sources, environmental drivers, and ecosystem responses. In this study, we applied principal component analysis and hierarchical clustering to identify ion covariance patterns, or “ion clusters,” in Broad Run, an urban stream in the Mid-Atlantic United States. These clusters correspond to distinct hydrologic regimes and reveal specific salinization risks: (1) phosphorus pollution mobilized during summer storms (Cluster 1); (2) elevated concentrations of sulfate and bicarbonate during baseflow (Cluster 2), likely reflecting groundwater discharge; and (3) elevated specific conductance and sodium, chloride, and potassium ion concentrations during snowmelt and rain-on-snow events (Cluster 3), driven by deicer and anti-icer wash-off. These ion fingerprints offer a transferable framework for diagnosing salt sources, assessing ecological risk, and identifying management targets. Our findings underscore the need for next-generation stormwater infrastructure and smart growth policies to protect aquatic life in rapidly urbanizing watersheds.

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

Examination of Global Midlatitude Atmospheric River Lifecycles Using an Object-Oriented Methodology

Tracking atmospheric rivers (ARs) across their lifecycles is a field of recent interest with a multitude of emerging methodologies. The CONNected-objECT (CONNECT) algorithm is adapted for the tracking of global midlatitude AR lifecycles and associated precipitation by implementing a seeded region growing segmentation algorithm, creating the AR-CONNECT algorithm. To facilitate the permissiveness of the methodology, AR-CONNECT is without hard-coded geometric criteria yet is still shown to extract synoptic-scale elongated objects >99.99% of the time. One of the consequences of the methodology is the ability to occasionally track atmospheric water vapor anomalies before evolving into AR geometries, effectively tracking AR genesis further back than other studies. With the aid of subdaily satellite-derived rain data, we investigate the climatology, trends, and patterns of AR lifecycles from 1983–2016 and compare with other AR tracking studies. We find that AR frequency, genesis, and terminus locations are in generally good agreement with other AR tracking methodologies, though with key differences, and that AR frequencies in each hemisphere are determined by the number of AR hotspots. Furthermore, we uncover evidence that certain AR characteristics, such as frequency, areal extent, and duration, show evidence of increasing trends. Midlatitude precipitation uncovered by AR-CONNECT shows contributions up to 50% over land and 65% over the ocean. Trend analysis of AR precipitation shows an increase in precipitation associated with ARs propagated by the Southern Jet Stream and ARs that traverse over the Sahara Desert, among others, but is determined not to be a driver of changes in global precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Theory of critical balance in plasma turbulence

Critical balance, a statement of the approximate equality of a timescale of motion parallel to the magnetic field with a timescale of turbulent motion perpendicular to the field, is analyzed from a statistical description of the relative motion of two particles consistent with two-point correlation in a nonlinear gyrokinetic system with collisions. Critical balance is understood from a premise that the fastest time to any spatial scale that encounters decorrelated motions sets an overall correlation time for both perpendicular and parallel scales. For a regime of weak collisionality, this leads to the approximate equality of the parallel streaming time and the perpendicular turbulent correlation time, which is a standard statement of critical balance. These two timescales are only approximately equal because of effects in parallel streaming dynamics and collisions, the former producing deviations tied to variations of perpendicular and parallel wavenumbers. Finally, analysis of a collisional regime shows that critical balance also applies in that limit with a modified relation between parallel and perpendicular spatial scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Measurement of Kinetic-Scale Current Filamentation Dynamics and Associated Magnetic Fields in Interpenetrating Plasmas

Here, we present the first local, quantitative measurements of ion current filamentation and magnetic field amplification in interpenetrating plasmas, characterizing the dynamics of the ion Weibel instability. The interaction of a pair of laser-generated, counterpropagating, collisionless, supersonic plasma flows is probed using optical Thomson scattering (TS). Analysis of the TS ion-feature revealed anticorrelated modulations in the density of the two ion streams at the spatial scale of the ion skin depth c/ω pi = 120 μm, and a correlated modulation in the plasma current. The inferred current profile implies a magnetic field amplitude ~30 ± 6 T , corresponding to ~1% of the flow kinetic energy, indicating that magnetic trapping is the dominant saturation mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Heat transfer distribution on a discontinuously convective cooled surface

An active cooling scheme in which discrete cooling passages are used was investigated. In this scheme, the coolant passages are placed perpendicular to the main stream direction. Streamwise temperature oscillations result from the highly cooled regions, near the coolant channels, being next to regions not directly cooled between the channels. The accuracy of the heat transfer rate predictions by these approximations was evaluated by means of both experimental and numerical investigations. Experiments were conducted at free stream Mach number of 6 with several cooling passages. Heat transfer measurements were made and corresponding theoretical analysis were performed for comparison in evaluating both local and overall deviations in the heat transfer rate.

Piva, R.↗
NASA NTRS1979

Generalized lower-hybrid-drift instability

The theory of lower-hybrid-drift instability is extended to include a finite value of the component of wave vector parallel to the ambient magnetic field so that the analysis bridges the usual lower-hybrid-drift instability of flute modes and the modified-two-stream instability. The present theory also includes electromagnetic and ambient magnetic field-gradient effects. It is found that in the cold-electron limit the density and magnetic gradients can qualitatively modify the conclusion obtained in the early theory of the modified-two-stream instability. For example, even if the relative drift far exceeds the Alfven speed of the plasma, the instability may still persist. This result is in contrast to that established in the literature. When the electron temperature is finite, the problem is complicated. Numerical solutions are obtained for a number of cases.

Hsia, J. B.↗
NASA NTRS1983

Dilution Zone Mixing

Studies to characterize dilution zone mixing; experiments on the effects of free-stream turbulence on a jet in crossflow; and the development of an interactive computer code for the analysis of the mixing of jets with a confined crossflow are reviewed.

Holdeman, J. D.↗
NASA NTRS1983

Saturn meteorology - A diagnostic assessment of thin-layer configurations for the zonal flow

Voyager imaging, infrared, and radio observations for Saturn have been recently interpreted by Smith et al. (1982) as an indication that the jet streams observed at the cloud tops extend to depths greater than the 10,000-bar level. This analysis assumes a maximum latitudinal temperature contrast of a few percent, a mean atmospheric rotation rate at depth given by Saturn's ratio period, and no variation with latitude of the bottom pressure level for the zonal flow system. These assumptions are not, however, firmly constrained by observation. The diagnostic analysis of plausible alternative configurations for Saturn's atmospheric structure demonstrates that a thin weather layer system (confined at mid to high latitudes to levels above 200 bar) cannot be excluded by any of the available observations. A quantitative estimate of the effects of moisture condensation (including the differentiation of mean molecular weight) suggests that these might provide the buoyancy contrasts necessary to support a thin-layer flow provided that Saturn's outer envelope is enriched approximately 10 times in water abundance relative to a solar composition atmosphere and strongly differentiated with latitude at the condensation level.

Allison, M.↗
NASA NTRS1983

Backstreaming ions from oblique earth bow shocks

One-dimensional, hybrid (particle ions, fluid electrons) numerical simulations of oblique shock structure are used to analyze the mechanism by which solar wind ions can be reflected off the earth's bow shock front and escape upstream. It is shown that no backstreaming ions are produced in the simulation over 50-90 degrees of theta(nB), the angle between the interplanetary magnetic field and the shock normal. Backstreaming ions are emitted for theta(nB) of 45 degrees or less, with characteristics in reasonable agreement with those of observed reflected ion streams. The simulated shock structure becomes rather turbulent as theta(nB) decreases from 45 to 30 degrees. Analysis of the backstreaming ion trajectories shows that all backstreaming ions are originally specularly reflected. The oblique shock structure and effects such as whistler formation and ion heating are discussed.

Leroy, M. M.↗