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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

WEC-Sim Modeling of Laminar Scientific's Patented Seesaw Wave Energy Converter: Preprint

Laminar Scientific's patented seesaw wave energy converter was modeled in WEC-Sim to predict performance. The device operates by utilizing ocean surface waves to rotate a truss in pitch about a pivot. The pivot is located at the top of two pylons, which are embedded in the seafloor. The seesaw has a float on either end, and the buoyancy forces from each float cause the system to rise or fall with passing waves. Device performance relies upon seesaw length and ocean wavelength creating an antiphase effect. The seesaw truss has an adjustable length intended to achieve this effect. The operation method enforces a narrow band of wavelengths which induce the largest rotational motion from the device. The hydrodynamic analysis of the device was performed using Capytaine, and the results confirmed that the device operates best in a narrow frequency band. Four float-to-float spacing cases and three pylon radii were examined. The hydrodynamic results indicate a match between the model and the physical expectations for the device, and that varying the pylon radii by 0.1-m increments for three instances creates minimal changes in hydrodynamic properties. Power matrices for three float spacing cases of the device were simulated with Joint North Sea Wave Project spectra waves and optimal power take-off damping in WEC-Sim. The maximum average power production for the 15-m spacing case was 14.1 kW with a 5.0-s peak wave period and 4-m significant wave heights. Plots of capture-width ratios indicated that the device performance was linear and confirmed that the device is optimal in a narrow frequency band. The maximum percentage of the available wave power produced by the 15-m device was approximately 16%. Simulations of the device in regular waves were used to produce plots of average power compared to a ratio of float spacing to wavelength. These plots indicate that the power production is maximized at a ratio of 0.5, and further confirm that the device has a narrow frequency response. The device was simulated at an example field location, where the device produced an annual average power rating of 1.6 kW given an average omnidirectional wave climate of 10.3 kW m-1 and an optimal, linearized power take-off model. While the maximum predicted device performance is reliant upon a narrow band of wave frequencies, the conducted analysis provides an opportunity to improve device design prior to prototyping and testing. Modifying the design to respond to a broader frequency range would improve device performance.

numerical modeling↗
DOE OSTI2018

Assessing robustness of factor ranking for supersaturated designs

Supersaturated designs can potentially be a beneficial tool for efficiently exploring a large number of factors with a moderately sized design. However, because more factors are being considered than there are runs, the stability of the identified factors depends heavily on effect sparsity and the lack of highly influential observations. A helpful tool for the analysis of supersaturated designs is least absolute shrinkage and selection operation (LASSO), which is useful when the effects of many explanatory variables are sparse in a high-dimensional dataset. To understand the impact of individual observations on the selected factors, the LASSO influence plot was created. This work describes an application of this plot and its variants that can be used to identify influential points, increase understanding of the impact of individual observations on model parameters, and the robustness of results in analyses with supersaturated designs. These graphical methods can serve as a complement to other regression diagnostics techniques in the LASSO regression setting.

3-D LASSO influence plots↗
DOE OSTI2018

Bayesian Design of Experiments for Logistic Regression to Evaluate Multiple Forensic Algorithms

When evaluating the performance of several forensic classification algorithms, it is desirable to construct a design that considers a variety of performance levels for each of the algorithms. We describe a strategy to use Bayesian design of experiments with multiple prior estimates to capture anticipated performance. Our goal is to characterize results from the different classification algorithms as a function of multiple explanatory variables and use this to choose a design about which units to test. Bayesian design of experiments has been successful for generalized linear models, including logistic regression models. Here, we develop methodology for the case where there are several potentially nonoverlapping priors for anticipated performance under consideration. The weighted priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other candidate design choices. Additionally, we show how this can be applied in the multivariate input case and provide some useful summary measures. The shared information plot is used to evaluate design point allocation, and the D-value difference plot allows for the comparison of design performance across multiple potential parameter values in higher dimensions. Here, we illustrate the methods with several examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Recurrence analysis of friction based dry-couplant ultrasonic Lamb waves in plate-like structures

Here, in this study, the effect of friction on the generation of dry-coupled Lamb waves is experimentally investigated. Recurrence analysis is performed to analyze the complex behavior of friction based dry-coupled Lamb waves. In particular, the effect of the normal force, which is necessary for a stronger dry-coupled Lamb wave generation and the friction, on the transmission of mechanical energy and determinism characteristics of Lamb waves are investigated. The results verify that larger friction coefficient and friction force are crucial for generation and propagation of strong Lamb waves supporting the fact that the main mechanism to transfer mechanical energy using dry-couplant is friction. The sensitivity of Lamb waves to the friction coefficient, highlights the importance of designing specific pads with respect to condition of the surface. Besides, the results show that the normal force and friction coefficient can change the determinism characteristics behavior of multimode Lamb waves. Furthermore, it is shown that the determinism value is sensitive to the friction coefficient and normal force. A similar trend is observed in the determinism values and friction coefficient. In general, a smaller friction coefficient indicates smaller determinism value. Additionally, it is shown that a normal load can change the behavior of a system, as observed from recurrence plots, owing to changes in the Lamb waves trajectories in the phase-space domain. In addition, it is shown that recurrence plots enable the detection of mode transitions in multimode Lamb waves. Recurrence analysis is a complementary tool to frequency domain methods for accurate analysis of multimode Lamb waves behavior.

42 ENGINEERING↗
DOE OSTI2016

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020

The timing of snowmelt in mountain systems is a main driver of vegetation phenology and production, as well as recharge of soil moisture and ground water. Decreases in maximum snowpack and warmer spring temperatures have led to a higher frequency of early snowmelt. This study combines a natural elevation gradient with an experimental manipulation of snowmelt timing to assess the effect of earlier melt on hillslope and watershed ecohydrological processes. This data package includes csv files with plot and sub-plot level observations of soil temperature (SM_ST.csv), soil moisture (SM_SWC.csv), air temperature (SM_AirT.csv), and relative humidity (SM_rH.csv). The date range of this dataset includes a pre-treatment year (2017), two treatment years (2018 and 2019), and a post-treatment year (2020). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018” and “Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Collaborative Research: Properties and Dynamics of the Shallow Crust (Final Report)

Ground motions recorded at one location are often extrapolated to nearby regions within a given radius. Here, we explore the appropriateness of spatial extrapolation using data from seven small aperture seismic network deployments in southern California. Six of these deployments are linear arrays of 4-13 stations, and one is a 2D array of 13 stations at Pinyon Flats Observatory. The spatial footprint array diameters are 3 km or less, and each array was operational for a year or more. From our base catalog (M2.5+ earthquakes; 4038 events; September 2010 - June 2023), automated methods remove temporally overprinted waveforms from nearby events (< 5 km) in quick succession (< 5 min) and data with nonviable waveforms. These 200 samples per second data are filtered at 0.5-25 Hz and must have signal-tonoise ratios (SNRs) of 2.5+. Peak ground acceleration (PGA) and peak ground velocity (PGV) are derived individually from the maximum absolute values of each of the 3-component waveforms (vertical, northsouth, and east-west). Five of the seven arrays traverse the San Jacinto fault, and two do not. Ground motion observations are compared with theoretical estimates from Abrahamson et al., 2014. On average, arrays deployed within and across fault zones consistently record ground motions above theoretical expectations, whereas off-fault arrays record ground motions at or slightly below theoretical expectations. We attribute these differences to site conditions because these trends prevail for the full data suites. For each network and each individual channel, the coefficient of variation indicates that the standard deviations are ~30±6% of the mean. Exploring relative ground motion contributions from all three channels (ternary plots), as expected, most data show that vertical ground motions are attenuated compared to horizontal ones. However, this is not always the case for RA array data, where vertical motions can be ~2-3 times larger than horizontal motions for select events near Cahuilla, CA. These anomalously high vertical motions are focal mechanism-related. These results suggest that ternary plots created using only a small amount of data can be used as a data quality metric and a tool to find anomalous features in three-component data.

58 GEOSCIENCES↗
DOE OSTI2017

Physical Interpretation of Mixing Diagrams: Interpretation of Mixing Diagrams

Type of mixing at cloud edges is often determined by means of mixing diagrams showing the dependence of normalized cube of the mean volume radius on the dilution level. The mixing diagrams correspond to the final equilibrium state of mixing between two air volumes. While interpreting in situ measurements, scattering diagrams are plotted in which normalized droplet concentration is used instead of dilution level. Utilization of such scattering diagrams for interpretation of in situ observations faces significant difficulties and often leads to misinterpretation of the mixing process and to uncertain conclusions concerning the mixing type. In this study we analyze the scattering diagrams obtained by means of a Lagrangian-Eulerian model of a stratocumulus cloud. The model consists of 2,000 interacting Largangian parcels which mix with their neighbors during their motion in the atmospheric boundary layer. In the diagram, each parcel is denoted by a point. Changes of microphysical parameters of the parcel are represented by movements of the point in the scattering diagram. The method of plotting the scattering diagrams using the model is in many aspects similar to that used in in situ measurements. It is shown that a scattering diagram shows snapshots of a transient mixing process. The location of points in the scattering diagrams reflects largely the history and the origin of air parcels. Location of points on scattering diagram characterizes intensity of entrainment, and different parameters of droplet size distributions (DSDs) like concentration, mean volume (or effective) radius, and DSD width.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Methane flux measurements in rice by static flux chamber and eddy covariance

Abstract Understanding methane (CH 4 ) fluxes from rice ( Oryza sativa L.) at the field scale is paramount to reducing environmental impacts while ensuring global food security. Greenhouse gas (GHG) measurements at the plot scale using static flux chambers (SFC) have long informed the understanding of flux dynamics and have largely been the basis of global flux estimates. However, in many parts of the world, the landscapes where agricultural fluxes are generated come from larger fields. Eddy covariance (EC) can measure trace gases on larger fields, but there are few studies available quantifying CH 4 emissions under typical practices at a field scale. Furthermore, few of these studies are from the U.S. Midsouth, the largest producer of U.S. rice. This study compares and quantifies field‐scale SFC and EC flux measurements on a large commercial system in northeastern Arkansas during the 2015 and 2016 growing seasons, following typical producer practices. Daily measured SFC CH 4 fluxes did not differ from EC‐daily CH 4 fluxes ( p = .108). Total season CH 4 emissions, calculated as the sum of daily fluxes ranged from 50 to 156 kg CH 4 ha −1 season −1 , with SFC reporting greater emissions than EC. Although SFC and EC‐daily flux measurements were similar early ( p = .382) and late ( p = .543) in the season, they differed mid‐season ( p < .001) with SFC consistently reporting greater fluxes than EC. The findings of this study help unify season long plot‐scale and field‐scale flux measurements and signify an advancement of our understanding of GHG fluxes from rice systems.

Reba, Michele L.↗
DOE OSTI2020

Tensile testing and fracture mechanism analysis of polyvinyl alcohol nanofibrous webs

Abstract A tensile properties testing study was conducted to understand the influence of thickness, cross‐head speed (speed of testing), gauge length (GL; specimen test length), and sample shape on important tensile properties of polyvinyl alcohol (PVA) nanofiber webs. The effects of each testing parameter on load at break, extension at break, Young's modulus, and tensile stress–strain curve of PVA nanofiber webs are analyzed. The Welch two sample t ‐tests show the significant difference among tested data. Using interaction plots, two‐way analysis of variance, and margin mean plots, the interaction effects among testing parameters have been analyzed. Of all the factors, cross‐head speed, the interaction among GL, and sample thickness (GL: Thickness) and the interaction among GL, testing speed and sample thickness (GL: Speed: Thickness) have significant influence on the tensile properties of PVA nanofiber webs. Moreover, the hypothesized model of mechanism of tensile strain–stress curve of PVA nanofiber webs has been proposed. Based on the model, the tensile strain–stress curve can be split into three stages: linear elastic, partial break up, and complete breakage. This study will provide a better understanding of tensile testing parameters' effects and their interaction effects on the tensile properties of nanowebs.

Lou, Lihua↗
DOE OSTI2016

Estimating heterotrophic respiration at large scales: challenges, approaches, and next steps

Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of "Decomposition Functional Types" (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing models to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present and discuss an example clustering analysis to show how model-produced annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from already-existing PFTs. A similar analysis, incorporating observational data, could form a basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with high-performance computing; rigorous testing of analytical results; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR at large scales.

carbon cycle↗
DOE OSTI2018

Restoration increases bee abundance and richness but not pollination in remnant and post-agricultural woodlands

Human land use, including agriculture, is a leading contributor to declining biodiversity worldwide and can leave long-lasting legacies on ecosystems after cessation. Ecological restoration is an approach to mitigate these impacts. However, little is known about how animal communities and plant–animal interactions respond to the combined effects of land-use legacies and restoration. We investigated how restoration and agricultural history affect bee (Hymenoptera: Apoidea: Anthophila) communities and pollination function. In 27 paired remnant (no history of agriculture) and post-agricultural longleaf pine (Pinus palustris Mill.) woodlands, we established 4–10 1-ha plots (126 total) and experimentally restored half of them, while the other half were left as unrestored controls. Restoration was accomplished through canopy thinning which reinstates open savanna-like conditions. We collected bees in each plot using a combination of bowl trapping and standardized netting transects. Thinning increased bee abundance by 169% and bee richness by 110%, but agricultural land use had no effect on these variables. Bee community composition was affected by restoration and was marginally affected by agricultural history. To measure pollination function, we conducted a sentinel plant experiment in which potted black mustard (Brassica nigra L.) plants were placed out in a subset of these sites (n = 10) and either bagged to exclude pollinators or left open for pollinator access. Then, we measured fruit and seed set of sentinel plants to compare pollination function among the restoration and land-use history treatments. Seed set and fruit set of sentinel plants were higher in open than bagged plants, indicating that this model system effectively measured pollination, but we found no differences in pollination based on restoration or agricultural history. These results indicate that although pollinator communities may show clear responses to restoration that are largely independent of prior land-use impacts, this does not necessarily translate into differences in pollination function after restoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Trait relationships of fungal decomposers in response to drought using a dual field and laboratory approach

Abstract Decomposer fungi play a fundamental role in terrestrial ecosystem dynamics. In the southwestern United States, climate change is causing more frequent and severe droughts, which may alter fungal community composition and activity. Investigating relationships between fungal traits may improve the prediction of fungal responses to drought. In this dual field and laboratory experiment, we examine whether trade‐offs occur between traits associated with drought. Specifically, we test the hypothesis that fungi sort into lifestyles specializing in growth y ield, resource a cquisition, and drought s tress tolerance (“YAS” framework). For the field experiment, we constructed microbial “cages” containing sterilized litter and 1 of 10 fungal isolates. These cages were placed in long‐term drought and control plots in a southern Californian grassland for 6 and 12 months. We measured fungal hyphal length per unit litter mass loss for growth yield, the potential activities of four extracellular enzymes for resource acquisition, and the ability to grow in the drought versus control plots for drought stress tolerance. We compared these results with a laboratory microcosm experiment constructed with the same fungal isolates and that measured the same fungal traits. The field experiment corroborated our laboratory results, in that no trade‐offs were observed between growth yield and resource acquisition traits. However, in contrast to the laboratory experiment, drought tolerance was negatively related to extracellular enzyme activity and growth yield in the field, implying a trade‐off. Despite this observed trade‐off in the field, growth yield was not hindered by drought. We propose a modification to the YAS framework, by combining the growth yield and resource acquisition lifestyles, which may be more appropriate for this arid system. This joint laboratory and field approach contextualizes a theoretical framework in microbial ecology and improves understanding of fungal community response to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Corn stover‐derived porous carbon for asymmetric supercapacitors

In this investigation, hydrothermal liquefaction‐derived hydrochar from pulverized corn stover (avg. particle size 1.12 mm and ash content 6.75 wt%) is chemically activated with aqueous KOH in the presence of Pluronic F127 surfactant and thermally treated further up to 800°C to generate porous carbon (POC) with higher specific surface area and porosity. POC obtained under different processing conditions is thoroughly characterized by Brunauer‐Emmett‐Teller surface area analyzer, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy. Metallic impurity present in POC is characterized by inductively coupled plasma mass spectrometry. Higher specific surface area POC is observed with the use of the surfactant during the activation process. Fully characterized POC is used with (Mn, Ti)‐mixed oxide electrode to fabricate asymmetric supercapacitor (ASC). Specific capacitance of ASC is measured by cyclic voltammetry (CV) technique using Gamry G‐300 potentiostat/galvanostat/ZRA. CV plots are obtained with different voltage scan rates whereas galvanostatic charge‐discharge plots are studied by varying the current density. Renewable corn stover‐derived POC prepared using Pluronic F127/KOH activation method is found to be highly suitable as an electrode material because of higher capacitance and electrochemical stability over 100 charging‐discharging cycles.

25 ENERGY STORAGE↗
DOE OSTI2023

Spatial and temporal variation in forest transpiration across a forested boreal peatland complex

Transpiration is a globally important component of evapotranspiration. Careful upscaling of transpiration from point measurements is thus crucial for quantifying water and energy fluxes. In spatially heterogeneous landscapes common across the boreal biome, upscaled transpiration estimates are difficult to determine due to variation in local environmental conditions (e.g., basal area, soil moisture, permafrost). Here, we sought to determine stand-level attributes that influence transpiration scalars for a forested boreal peatland complex consisting of sparsely treed wetlands and densely treed permafrost plateaus as land cover types. The objectives were to quantify spatial and temporal variability in stand-level transpiration, and to identify sources of uncertainty when scaling point measurements to the stand-level. Using heat ratio method sap flow sensors, we determined sap velocity for black spruce and tamarack for 2-week periods during peak growing season in 2013, 2017 and 2018. We found greater basal area, drier soils, and the presence of permafrost increased daily sap velocity in individual trees, suggesting that local environmental conditions are important in dictating sap velocity. When sap velocity was scaled to stand-level transpiration using gridded 20 × 20 m resolution data across the ~10 ha Scotty Creek ForestGEO plot, we observed significant differences in daily plot transpiration among years (0.17–0.30 mm), and across land cover types. Daily transpiration was lowest in grid-cells with sparsely treed wetlands compared to grid-cells with well-drained and densely treed permafrost plateaus, where daily transpiration reached 0.80 mm, or 30% of the daily evapotranspiration. When transpiration scalars (i.e., sap velocity) were not specific to the different land cover types (i.e., permafrost plateaus and wetlands), scaled stand-level transpiration was overestimated by 42%. To quantify the relative contribution of tree transpiration to ecosystem evapotranspiration, we recommend that sampling designs stratify across local environmental conditions to accurately represent variation associated with land cover types, especially with different hydrological functioning as encountered in rapidly thawing boreal peatland complexes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A systematic study of minima in alanine dipeptide

The alanine dipeptide is a standard system to model dihedral angles in proteins. It is shown that obtaining the Ramachandran plot accurately is a hard problem because of many local minima; depending on the details of geometry optimizations, different Ramachandran plots can be obtained. To locate all energy minima, starting from geometries from MD simulations, 250,000 geometry optimizations were performed at the level of RHF/6-31G*, followed by re-optimizations of the located 827 minima at the level of MP2/6-311++G**, yielding 30 unique minima, most of which were not previously reported in literature. Both in vacuo and solvated structures are discussed. The minima are systematically categorized based on four backbone dihedral angles. The Gibbs energies are evaluated and the structural factors determining the relative stabilities of conformers are discussed. (c) 2018 Wiley Periodicals, Inc.

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

Differential effects of press vs. pulse seawater intrusion on microbial communities of a tidal freshwater marsh

Abstract Tidal freshwater marshes (TFMs) are threatened by seawater intrusion, which can affect microbial communities and alter biogeochemical processes. Here, we report on a long‐term, large‐scale manipulative field experiment that investigated continuous (press) and episodic (pulse, 2 months/yr) inputs of brackish water on microbial communities in a TFM. After 2.5 yr, microbial diversity was lower in press treatments than in control (untreated) plots whereas diversity in pulse plots was unaffected by brackish water additions. Sulfate reducer abundance increased in response to both press and pulse treatments whereas methanogens did not differ among treatments. Our results, along with other lab and field measurements that show reduced soil respiration and extracellular enzyme activity suggest that continuous seawater intrusion will decrease macrophyte C inputs that reduce bacterial diversity in ways that also diminish ecosystem carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗