SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Apollo 15 subsatellite magnetic field observations have been used to measure both the permanent and the induced lunar dipole moments. Although only an upper limit of 1.3 x 10 to the 18th gauss-cubic centimeters has been determined for the permanent dipole moment in the orbital plane, there is a significant induced dipole moment which opposes the applied field, indicating the existence of a weak lunar ionosphere.
Novel transistors and logic devices based on nanotechnology concepts are under intense development. The potential for ultra-low-power circuitry makes nanotechnology attractive for applications such as digital electronics and sensors. For NASA applications, nanotechnology offers tremendous opportunities for increased onboard data processing, and thus autonomous decisionmaking ability, and novel sensors that detect and respond to environmental stimuli with little oversight requirements. Polyaniline/polyethylene oxide (PANi/PEO) nanofibers are of interest because they have electrical conductivities that can be changed from insulating to metallic by varying the doping levels and conformations of the polymer chain. At the NASA Glenn Research Center, we have observed field effect transistor (FET) behavior in electrospun PANi/PEO nanofibers doped with camphorsulfonic acid. The nanofibers were deposited onto Au electrodes, which had been prepatterned onto oxidized silicon substrates. The preceding scanning electron image shows the device used in the transistor measurements. Saturation channel currents are observed at surprisingly low source/drain voltages (see the following graph). The hole mobility in the depletion regime is 1.4x10(exp -4)sq cm/V sec, whereas the one-dimensional charge density (at zero gate bias) is calculated to be approximately 1 hole per 50 two-ring repeat units of polyaniline, consistent with the rather high channel conductivity (approx.10(exp -3) S/cm). Reducing or eliminating the PEO content in the fiber is expected to enhance device parameters. Electrospinning is thus proposed as a simple method of fabricating one-dimensional polymer FET's.
The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.
The relationships between the morphological parameters of lava flows and the process parameters of lava composition, eruption rate, and eruption temperature were investigated using literature data on Hawaiian lava flows. Two simple models for lava flow heat loss by Stefan-Boltzmann radiation were employed to derive eruption rate versus planimetric area relationship. For the Hawaiian basaltic flows, the eruption rate is highly correlated with the planimetric area. Moreover, this observed correlation is superior to those from other obvious combinations of eruption rate and flow dimensions. The correlations obtained on the basis of the two theoretical models, suggest that the surface of the Hawaiian flows radiates at an effective temperature much less than the inner parts of the flowing lava, which is in agreement with field observations. The data also indicate that the eruption rate versus planimetric area correlations can be markedly degraded when data from different vents, volcanoes, and epochs are combined.
The ISCCP analysis of cloud conditions during and in the vicinity of the FIRE cirrus and marine stratus Intensive Field Observations (IFOs) is presented in two forms: the standard climatology product, which is averaged to a nominal 250 km resolution and a pixel-by-pixel version that samples the original data at about 30 km spacing every three hours. These results are based on NOAA-9 and GOES-6 images covering October to November 1986 and July 1987 for the FIRE Extended Area. Comparisons of these results with other FIRE observations will serve to check the accuracy of the clear sky radiances inferred by the ISCCP analysis, which determines the accuracy of the cloud detections. Of more interest is the exploration of the dependence of the inferred cloud properties for direct evaluation of the role of small scale variability of cloud properties on the radiation field. This is illustrated by preliminary results obtained for the scales contained in the ISCCP data. The ISCCP analysis also sets the larger scale context of the FIRE data: (1) comparisons of the clouds occurring in the FIRE IFOs with nearby locations and times are presented, and (2) comparisons of the cloud conditions for the same month in other years are shown.
We report on particles and fields observed during Defense Meteorological Satellite Program (DMSP) F9 and DE 2 crossings of the polar cap/auroral oval boundary in the evening magnetic local time (MLT) sector. Season-dependent, latitudinally narrow regions of rapid, eastward plasma flows were encountered by DMSP near the poleward boundary of auroral electron precipitation. Ten DE 2 orbits exhibiting electric field spikes that drive these plasma flows were chosen for detailed analysis. The boundary region is characterized by pairs of oppositely-directed, field-aligned current sheets. The more poleward of the two current sheets is directed into the ionosphere. Within this downward current sheet, precipitating electrons either had average energies of a few hundred eV or were below polar rain flux levels. Near the transition to upward currents, DE 2 generally detected intense fluxes of accelerated electrons and weak fluxes of ions, both with average energies between 5 and 12 keV. In two instances, precipitating ions with energies greater than 5 keV spanned both current sheets. Comparisons with satellite measurements at higher altitudes suggest that the particles and fields originated in the magnetotail inside the distant reconnection region and propagated to Earth through the plasma sheet boundary layer. Auroral electrons are accelerated by parallel electric fields produced by the different pitch angle distributions of protons and electrons in this layer interacting with the near-Earth magnetic mirror. Electric field spikes driving rapid plasma flows along the poleward boundaries of intense, keV electron precipitation represent ionospheric responses to the field-aligned currents and conductivity gradients. The generation of field-aligned currents in the boundary layer may be understood qualitatively as resulting from the different rates of earthward drift for electrons and protons in the magnetotail's current sheet.
Work under this grant has involved further development of a new aircraft instrument (the cloudscope) for real time characterization of atmospheric particulates together with field observations of such particulates, both in the form of ice and also as nuclei responsible for nucleation of both ice and water cloud particles. Part of the work involving assessment of the frequency of ice crystal shapes has been carried out in collaboration with the Meteorological Service of Canada; part of the work in a field program with the NCAR C-130. Part of the work has been interpreted in terms of laboratory simulation of ice crystal growth under a wide variety of conditions carried out under a grant from Physical Meteorology Program, National Science Foundation.
Explorer 33 magnetic field observations were analyzed to study the propagation of sudden impulses (SI) in the geomagnetic tail and the magnetosheath. Average speed of propagation in these regions is 760 km per sec with a range of 550 to 1230 km per sec. Most of the SI's have propagation speed close to that of the shock wave observed in this region. Positive SI is shown to have a positive change in the tail or magnetosheath and a negative SI has a similar negative change. Nine out of thirteen correlated SI's have their origin in the solar wind continuities, while four SI's possibly originate in the perturbations of the tail or magnetosheath field. It was found that the SI propagation is not confined to the tail region but has correlated effects in the magnetosheath. The propagation region studied was in 2000 to 0200 local time sector.
Explorer 33 magnetic field observations have been analyzed to study the propagation of sudden impulses (si) in the geomagnetic tail and the magnetosheath. Average speed of propagation in these regions is 760 km per sec with a range of 550-1230 km per sec. Most of the si's have a propagation speed which is close to that of the shock wave observed in this region. Positive si is shown to have a positive change in the tail or magnetosheath and a negative si has a similar negative change. Nine out of thirteen correlated si's have their origin in the solar wind continuities, while four si's have possible origin in the perturbations of tail or magnetosheath field.
Observations of the azimuthal component of the IMF are evaluated through the use of an MHD model which shows the effect of magnetic flux tubes opening in the outer solar system. It is demonstrated that the inferred meridional transport of magnetic flux is consistent with predictions by the MHD model. The computed azimuthal and radial magnetic flux deficits are almost identical to the observations. It is suggested that the simplest interpretation of the observations is that meridional flows are created by a direct body force on the plasma. This is consistent with the analytic model of Nerney and Suess (1975), in which such flux deficits in the IMF arise naturally from the meridional gradient in the spiralling field.
Aerosol-cloud interactions (ACIs) are vital for regulating Earth’s climate by influencing energy and water cycles. Yet, effects of ACI bear large uncertainties, evidenced by systematic discrepancies between observed and modeled estimates. This study quantifies a major bias in ACI determinations, stemming from conventional surface or space measurements that fail to capture aerosol at the cloud level unless the cloud is coupled with land surface. We introduce an advanced approach to determine radiative forcing of ACI by accounting for cloud-surface coupling. By integrating field observations, satellite data, and model simulations, this approach reveals a drastic alteration in aerosol vertical transport and ACI effects caused by cloud coupling. In coupled regimes, aerosols enhance cloud droplet number concentration across the boundary layer more homogeneously than in decoupled conditions, under which aerosols from the free atmosphere predominantly affect cloud properties, leading to marked cooling effects. Our findings spotlight cloud-surface coupling as a key factor for ACI quantification, hinting at potential underassessments in traditional estimates.
In areas where biogenic emissions are oxidized in the presence of anthropogenic pollutants, it has become increasingly apparent that secondary organic aerosol (SOA) formation from biogenic volatile organic compounds (BVOCs) is substantially enhanced. The Amazon forest is the dominant source of BVOCs globally, and the forest is rapidly being converted to urban and agricultural uses. We participated in a collaborative field study located in the Amazon region around Manaus, Brazil, in 2014 (Green Ocean Amazon; GoAmazon). This study was designed to comprehensively examine how BVOC emissions (specifically, the most highly emitted non-methane hydrocarbon, isoprene, and lesser studied sesquiterpenes) and their interaction with anthropogenic pollution (i.e., nitrogen oxides, sulfur dioxide, and black carbon) alter the atmosphere’s oxidative capacity, influence secondary aerosol formation, atmospheric composition and, ultimately, affect the earth’s radiation balance and climate. We provide the first hourly, in-situ measurement of 30 sesquiterpenes and 4 diterpenes, roughly estimating that sesquiterpene oxidation contributes to 10-14% of ozone reactive loss by terpenes and at least 0.4–5% (median 1 %) of total submicron OA mass. However, this is likely a low-end estimate, as evidence for additional unaccounted sesquiterpenes and their oxidation products clearly exists. We also provide new perspectives on sulfate, NO x , and particle acidity influencing isoprene-derived SOA, comparing the central Amazon environment with Southeastern U.S.A. summer, representing clean to polluted conditions, respectively. We find that summed concentrations of isoprene-derived SOA tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m -3 reduction in sulfate corresponds with at least ~0.5 μg m -3 reduction in isoprene-derived SOA. We also find that SOA mass derived from isoprene oxidation in the presence of NO x is primarily comprised of aerosol sulfate bound with isoprene oxidation products (i.e. organosulfates), ~97% in the Amazon and ~55% in the Southeastern U.S. We infer under natural conditions in high isoprene emission regions, preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought as representative of anthropogenic influence. We further report the first field observations showing that particle acidity impacts the distribution of isoprene oxidation tracers in the gas and particle phases, providing physicochemical insight into isoprene SOA formation chemistry. Coupled with other co-located measurements by the DOE Atmospheric Radiation Measurement (ARM) team and collaborating PIs at our measurement site (called T3), on the G1 aircraft, and at additional field sites (T0, T1, T2) this data set has been used to understand emission, oxidation, and particle formation pathways at the molecular level, to elucidate how these pathways change when influenced by anthropogenic sources, and to evaluate their importance for the atmospheric budget of aerosols and the earth’s radiation balance on regional scales. Recommendations: Further constraint of the role of sesquiterpenes on ozone (O 3 ) reactivity and SOA formation is limited by the availability of authentic standards and synthesized compounds of sesquiterpenes and their oxidation products. Future research efforts should focus on making such standards available via custom synthesis to allow for accurate quantification and focused oxidation experiments that will fully elucidate the chemistry of these compounds in the atmosphere. Further, reductions in aerosol sulfate (via SO 2 emissions control) continues to be one of the most effective methods to reduce SOA formation from isoprene, but the concerted role of ammonia (NH 3 ) gas emissions from (agricultural) industry and other sources requires more investigation to better understand the role of aerosol acidity in SOA formation and potential controls. As GoAmazon particles can be more acidic compared to areas with greater anthropogenic NH 3 emissions, this promotes relatively greater organosulfate (OS) formation from isoprene even in the presence of NO x . Because OS and inorganic sulfate differ in water uptake properties, this implies preindustrial aerosol sulfate (albeit less abundant) may have been less reflective than current earth system models assume. Further research should investigate the radiative impacts of organic vs inorganic sulfate in aerosols to improve model representation. Finally, future work (currently underway) should include constraint of the contributions of monoterpene (C 10 H 16 ) BVOCs and biomass burning VOCs as precursors to SOA formation in the region as well as their impacts on radiative forcing in the climate system.
Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.
Abstract. Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.
Magnetic flux transfer events often show a significant increase of the magnetic field strength at the center of the events. Similar magnetic field observations have been reported for structures in or near the plasma sheet of the magnetotail at about 20 R(sub E). We have carried out two-dimensional (2D) and three-dimensional (3D) and simulations of single X line reconnection (SXR), multiple X line reconnection (MXR), and patchy reconnection to determine and compare the amplification of the magnetic field in the center of the developing flux tubes. The various processes are achieved by appropriate choices of 2D or 3D resistivity models. The simulations show that the increase in magnetic field strength depends on both the property of the initial configuration and the particular reconnection geometry. For the chosen initial conditions the MXR process leads to a larger increase in the core magnetic field than the patchy reconnection and SXR caused by larger magnetic tensions in the MXR process. The 3D processes always lead to a larger amplification than the corresponding 2D processes. In the 3D cases, force imbalance in the y direction will accelerate plasma out of the flux tube. This process reduces the thermal pressure and leads to a further compression of the flux rope, which yields an additional increase in the interior magnetic field strength.
Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.
Remote sensing maps of active layer depth derived from Unmanned Areal System (UAS) data. The UAS datasets were stepwise scaled until matching the AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer - Next Generation) and Sentinel-2 spatial resolutions. Using the field observed Active Layer Depth (ALD) measurement in combination with spectral and topographic predictors derivatives from DJI UAS imagery, we used a spatially explicit RF regression model to predict and map ALD across our study landscapes. This package includes maps for Next-Generation Ecosystem Experiment Arctic (NGEE Arctic)’s Teller Mile Marker (MM) 27, and Kougarok MM80 (aka Mile 80) watersheds. The field, map data, and metadata are provided as geoTIF and text (*.csv) formats. These datasets are provided in support of Hantson et al., 2024 (accepted) “Scaling Arctic landscape and permafrost features improves active layer depth modeling”
Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.