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At least 1,549 records · Page 86

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NASA NTRS2001

The Effect of Changes in the ASCA Calibration on the Fe-K Lines in Active Galaxies

The ASCA calibration has evolved considerably since launch and indeed, is still evolving. There have been concerns in the literature that changes in the ASCA calibration have resulted in the Fe-K lines in active galaxies (AGN) now being systematically narrower than was originally thought. If this were true, a large body of ASCA results would be impacted. In particular, it has been claimed that the broad red wing (when present) of the Fe-K line has been considerably weakened by changes in the ASCA calibration. We demonstrate explicitly that changes in the, ASCA calibration over a period of about eight years have a negligible effect on the width, strength, or shape of the Fe-K lines. The reduction in both width and equivalent width is only approximately 8% or less. We confirm this with simulations and individual sources, as well as sample average profiles. The average profile for type 1 AGN is still very broad, with the red wing extending down to approximately 4 keV. The reason for the claimed, apparently large, discrepancies is that in some sources the Fe-K line is complex, and a single-Gaussian model, being an inadequate description of the line profile, picks up different portions of the profile with different calibration. However, one cannot make inferences about calibration or astrophysics of the sources using models which do not describe the data. Better modeling of the Fe-K in such cases gives completely consistent results with both old and current calibration. Thus, inadequate modeling of the Fe-K line in these sources can seriously underestimate the line width and equivalent width, and therefore lead to incorrect deductions about the astrophysical implications.

Yaqoob, T.↗

DOE OSTI2020

Keck/NIRC2 L’-band Imaging of Jovian-mass Accreting Protoplanets around PDS 70

We present L’-band imaging of the PDS 70 planetary system with Keck/NIRC2 using the new infrared pyramid wave front sensor. We detected both PDS 70 b and c in our images, as well as the front rim of the circumstellar disk. After subtracting off a model of the disk, we measured the astrometry and photometry of both planets. Placing priors based on the dynamics of the system, we estimated PDS 70 b to have a semimajor axis of 20{sub −4}{sup +3} au and PDS 70 c to have a semimajor axis of 34{sub −6}{sup +12} au (95% credible interval). We fit the spectral energy distribution (SED) of both planets. For PDS 70 b, we were able to place better constraints on the red half of its SED than previous studies and inferred the radius of the photosphere to be 2–3 R {sub Jup}. The SED of PDS 70 c is less well constrained, with a range of total luminosities spanning an order of magnitude. With our inferred radii and luminosities, we used evolutionary models of accreting protoplanets to derive a mass of PDS 70 b between 2 and 4 M {sub Jup} and a mean mass accretion rate between 3 × 10{sup −7} and 8 × 10{sup −7} M {sub Jup}/yr. For PDS 70 c, we computed a mass between 1 and 3 M {sub Jup} and mean mass accretion rate between 1 × 10{sup −7} and 5 × 10{sup −7} M {sub Jup}/yr. The mass accretion rates imply dust accretion timescales short enough to hide strong molecular absorption features in both planets’ SEDs.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1982

Regionally applicable angular reflectance models

Determination of the angular variation of the reflected radiance field in order to infer the reflected component of the Earth radiation budget from medium or narrow field of view radiometer measurements is discussed. An average angular model applicable at 250 to 1000 km is presented and evaluated. The nature of the convergence of the radiance patterns to the regional means is also discussed. Radiances measured during summer Monex 1979, from Hudson Bay to Saudi Arabia, were averaged and then normalized by multiplying by pi and dividing by the scene-averaged reflected flux density. This casts the model into the inverse of the bidirectional reflectance normalization coefficient, which has the value of unity for an isotropic surface. The reflected component of the Earth's radiation budget is inferred to an accuracy of about 2.5%.

Davis, J. M.↗

NASA NTRS1985

Electrostatic wave observation during a space simulation beam-plasma discharge

ELF waves which were observed during beam-plasma discharge in the large vacuum chamber at Johnson Space Center are studied. Phase delays as a function of radius (obtained from cross-correlation measurements of density fluctuations) along with measurements of frequency and plasma potential, density, and temperature have been compared to a zero-order slab model of nonlocal azimuthal drift wave propagation. The inferred wave phase velocity in the plasma frame after Doppler correction is found to be near one half the electron diamagnetic drift velocity. Although the measurements presented do not uniquely define a propagation mode, a model of azimuthal drift wave propagation is found to be consistent with observations.

Walker, D. N.↗

NASA NTRS1990

A reduced-dynamic technique for precise orbit determination

Observations of the Global Positioning System (GPS) will enable a reduced-dynamic technique for achieving subdecimeter orbit determination of earth-orbiting satellites. With this technique, information on the transition between satellite states at different observing times is furnished by both a formal dynamic model and observed satellite positional change (which is inferred kinematically from continuous GPS carrier-phase data). The relative weighting of dynamic and kinematic information can be freely varied. Covariance studies show that in situations where observing geometry is poor and the dynamic model is good, the model dominates determination of the state transition; where the dynamic model is poor and the geometry strong, carrier phase governs the determination of the transition. When neither kinematic nor dynamic information is clearly superior, the reduced-dynamic combination of the two can substantially improve the orbit-determination solution. Guidelines are given here for selecting a near-optimal weighting for the reduced-dynamic solution, and sensitivity of solution accuracy to this weighting is examined.

Wu, S. C.↗

NASA NTRSDate not supplied

Mapping National Forest Aboveground Biomass in Mexico By Integrating GEDI and Landsat Times Series Data

Mexico is one of the countries with great potential for the UN's Reducing Emissions from Deforestation and Forest Degradation (REDD+) program, a key nature-based solution for the forest sector. To monitor carbon stock changes, there is a growing demand for unbiased Monitoring Reporting Verification (MRV) systems to facilitate effective forest management and climate change mitigation strategies. Remote sensing-based national aboveground biomass density (AGBD) estimation over Mexico is scarce and often limited to one-time static mapping, leading to spatiotemporal inconsistency in inputs. As an effort under NASA's Carbon Monitoring System (CMS) program, we have developed a remote sensing-based approach to create consistent historical AGBD maps of Mexico using multi-stream remote sensing data, including spaceborne lidar GEDI and long-term Landsat time series, as well as topographic information. We employ the continuous change detection and classification (CCDC) algorithm for temporal modeling of Landsat surface reflectance, followed by the inference of forest AGBD using a random forest machine learning algorithm with the temporal information of land surface dynamics extracted by the CCDC as input. GEDI provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. In this presentation, we share the progress made in developing a spatially explicit mapping of historical AGBD changes associated with land surface changes and post-disturbance landscapes.

Taejin Park↗

DOE OSTI2016

Revisiting Fenton Hill Phase I reservoir creation and stimulation mechanisms through the GTO code comparison effort

A series of experiments performed at the Fenton Hill hot dry rock site after stage 2 drilling of Phase I reservoir provided intriguing field observations on the reservoir’s responses to injection and venting under various conditions. Two teams participating in the US DOE Geothermal Technologies Office (GTO)’s Code Comparison Study (CCS) used different numerical codes to model these five experiments with the objective of inferring the hydraulic stimulation mechanism involved. The codes used by the two teams are based on different numerical principles, and the assumptions made were also different, due to intrinsic limitations in the codes and the modelers’ personal interpretations of the field observations. Both sets of models were able to produce the most important field observations and both found that it was the combination of the vertical gradient of the fracture opening pressure, injection volume, and the use/absence of proppant that yielded the different outcomes of the five experiments.

Fu, Pengcheng↗

DOE OSTI2024

Ecosystem Water‐Saving Timescale Varies Spatially With Typical Drydown Length

Abstract Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale ( τ ) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of τ to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of τ that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to τ are measures of the average number of dry days between rainfall events. Values of τ are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem‐level water use strategy.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

Emission Lines from the Gas Disk Around TW Hydra and the Origin of the Inner Hole

We compare line emission calculated from theoretical disk models with optical to submillimeter wavelength observational data of the gas disk surrounding TW Hya and infer the spatial distribution of mass in the gas disk. The model disk that best matches observations has a gas mass ranging from approx.10(exp −4) to 10(exp −5) M for 0.06AU < r < 3.5 AU and approx. 0.06M for 3.5AU < r < 200 AU. We find that the inner dust hole (r < 3.5 AU) in the disk must be depleted of gas by approx. 1-2 orders of magnitude compared with the extrapolated surface density distribution of the outer disk. Grain growth alone is therefore not a viable explanation for the dust hole. CO vibrational emission arises within r approx. 0.5 AU from thermal excitation of gas. [O i] 6300Å and 5577Å forbidden lines and OH mid-infrared emission are mainly due to prompt emission following UV photodissociation of OH and water at r < or approx. 0.1 AU and at r approx. 4 AU. [Ne ii] emission is consistent with an origin in X-ray heated neutral gas at r < or approx. 10 AU, and may not require the presence of a significant extreme-ultraviolet (hν > 13.6 eV) flux from TW Hya. H2 pure rotational line emission comes primarily from r approx. 1 to 30 AU. [Oi] 63microns, HCO+, and CO pure rotational lines all arise from the outer disk at r approx. 30-120 AU. We discuss planet formation and photoevaporation as causes for the decrease in surface density of gas and dust inside 4 AU. If a planet is present, our results suggest a planet mass approx. 4-7MJ situated at ∼3 AU. Using our photoevaporation models and the best surface density profile match to observations, we estimate a current photoevaporative mass loss rate of 4x10(exp −9M)/yr and a remaining disk lifetime of approx.5 million years.

Planet-Disk interactions↗

DOE OSTI2014

Greenhouse Gas Source Attribution: Measurements Modeling and Uncertainty Quantification

In this project we have developed atmospheric measurement capabilities and a suite of atmospheric modeling and analysis tools that are well suited for verifying emissions of green- house gases (GHGs) on an urban-through-regional scale. We have for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate atmospheric CO 2 . This will allow for the examination of regional-scale transport and distribution of CO 2 along with air pollutants traditionally studied using CMAQ at relatively high spatial and temporal resolution with the goal of leveraging emissions verification efforts for both air quality and climate. We have developed a bias-enhanced Bayesian inference approach that can remedy the well-known problem of transport model errors in atmospheric CO 2 inversions. We have tested the approach using data and model outputs from the TransCom3 global CO 2 inversion comparison project. We have also performed two prototyping studies on inversion approaches in the generalized convection-diffusion context. One of these studies employed Polynomial Chaos Expansion to accelerate the evaluation of a regional transport model and enable efficient Markov Chain Monte Carlo sampling of the posterior for Bayesian inference. The other approach uses de- terministic inversion of a convection-diffusion-reaction system in the presence of uncertainty. These approaches should, in principle, be applicable to realistic atmospheric problems with moderate adaptation. We outline a regional greenhouse gas source inference system that integrates (1) two ap- proaches of atmospheric dispersion simulation and (2) a class of Bayesian inference and un- certainty quantification algorithms. We use two different and complementary approaches to simulate atmospheric dispersion. Specifically, we use a Eulerian chemical transport model CMAQ and a Lagrangian Particle Dispersion Model - FLEXPART-WRF. These two models share the same WRF assimilated meteorology fields, making it possible to perform a hybrid simulation, in which the Eulerian model (CMAQ) can be used to compute the initial condi- tion needed by the Lagrangian model, while the source-receptor relationships for a large state vector can be efficiently computed using the Lagrangian model in its backward mode. In ad- dition, CMAQ has a complete treatment of atmospheric chemistry of a suite of traditional air pollutants, many of which could help attribute GHGs from different sources. The inference of emissions sources using atmospheric observations is cast as a Bayesian model calibration problem, which is solved using a variety of Bayesian techniques, such as the bias-enhanced Bayesian inference algorithm, which accounts for the intrinsic model deficiency, Polynomial Chaos Expansion to accelerate model evaluation and Markov Chain Monte Carlo sampling, and Karhunen-Lo %60 eve (KL) Expansion to reduce the dimensionality of the state space. We have established an atmospheric measurement site in Livermore, CA and are collect- ing continuous measurements of CO 2 , CH 4 and other species that are typically co-emitted with these GHGs. Measurements of co-emitted species can assist in attributing the GHGs to different emissions sectors. Automatic calibrations using traceable standards are performed routinely for the gas-phase measurements. We are also collecting standard meteorological data at the Livermore site as well as planetary boundary height measurements using a ceilometer. The location of the measurement site is well suited to sample air transported between the San Francisco Bay area and the California Central Valley.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Neutron star mass estimates from gamma-ray eclipses in spider millisecond pulsar binaries

Reliable neutron star mass measurements are key to determining the equation of state of cold nuclear matter, but such measurements are rare. Black widows and redbacks are compact binaries consisting of millisecond pulsars and semi-degenerate companion stars. Spectroscopy of the optically bright companions can determine their radial velocities, providing inclination-dependent pulsar mass estimates. Although inclinations can be inferred from subtle features in optical light curves, such estimates may be systematically biased due to incomplete heating models and poorly understood variability. Using data from the Fermi Large Area Telescope, we have searched for gamma-ray eclipses from 49 spider systems, discovering significant eclipses in 7 systems, including the prototypical black widow PSR B1957+20. Gamma-ray eclipses require direct occultation of the pulsar by the companion, and so the detection, or significant exclusion, of a gamma-ray eclipse strictly limits the binary inclination angle, providing new robust, model-independent pulsar mass constraints. For PSR B1957+20, the eclipse implies a much lighter pulsar (1.81 ± 0.07 solar masses) than inferred from optical light curve modelling.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method

In this study, an efficient Bayesian framework equipped with a multivariate adaptive regression spline (MARS) technique is developed to alleviate computational burdens encountered in a conventional Bayesian inversion of a geothermal prospect. Fast MARS models are developed from training dataset generated by CPU-intensive hydrothermal models and used as surrogate of high-fidelity physical models in Markov Chain Monte Carlo (MCMC) sampling. This Bayesian inference with MARS-enabled MCMC method is used to reduce prior estimates of uncertainty in structural or characteristic hydrothermal flow parameters of the model to posterior distributions. A geothermal prospect near Superstition Mountain in Imperial County of California in USA is used to illustrate the proposed framework and demonstrate the computational efficiency of MARS-based Bayesian inversion. The developed MARS models are also used to efficiently drive calculation of Sobol’ total sensitivity indices. Furthermore, only top sensitive parameters are included in Bayesian inference to further improve the computational efficiency of inversion. Sensitivity analysis also confirms that water circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method. The presented framework is demonstrated an efficient tool to update knowledge of geothermal prospects by inversing field data. Although only thermal data is used in this study, other type of data, such as flow and transport observations, can be jointly used in this method for underground hydrocarbon reservoirs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this study we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this work we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A second order yield-temperature relation for accurate inference of burn-averaged quantities in multi-species plasmas

Measured yields and ion temperatures inferred from the fusion product energy spectra can be used as metrics for the performance of an ICF implosion. This can be to infer species separation, thermal decoupling, flows or other effects that can cause the inferred ion temperatures to deviate from the true underlying thermal temperature and the yield ratio to deviate from the expected value. Direct inference of the impact of these effects on observed temperatures and yields can be difficult to uncover due to underlying dependence on the shape and time evolution of the temperature and density proles of the fusing plasma. Due to differences in the temperature dependence of the reactivities, different fusion products are emitted from different regions and times within the implosion. In order to properly account for this, a second order analytic expression relating the apparent temperatures and yield ratios is developed. This expression can be coupled to models of yield and/or temperature altering effects to infer their burn-averaged impact on an implosion. The second order expression shows significant improvement over lower order expressions in synthetic data studies. Demonstrations of its applications to synthetic data coupled with models of ion thermal decoupling and radial flows are presented. In the case of thermal decoupling both first and second order expressions show reasonable levels of accuracy. To consistently infer the amplitude of radial flow with <10% error the second order equation is required.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗

NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

Aiden Szeto↗

NASA NTRS1995

Statistical studies of impulsive events at high latitudes

A statistical study has been made of the high-latitude impulsive events that were observed during the 1985-1986 South Pole Balloon Campaign. The events were selected by searching for unipolar pulses greater than or equal to 10 nT above background in the vertical component of the magnetic field on the ground and/or pedestal or 'W' shaped horizontal electric field perturbations greater than or equal to 10 mV/m in amplitude and accompanied by perturbations in the vertical electric field at balloon altitude. A main event list comprising 112 events was compiled from the 468 hours of data available. Three aspects of the events were examined: the solar wind conditions prior to the event, local time of observation, and intrinsic properties of the events. The local time distribution was obtained from the 112 entry main event list and was found to be nearly uniform across the dayside, with no midday gap. The event rate found using our low-amplitude selection criteria was 0.7 event/hr, comparable to expectations based on in situ studies of the magnetopause. A total of 42 events were found for which data were available from Interplanetary Monitoring Platform (IMP) 8. Of these events, 12 occurred when the Z(sub GSM) component (B(sub Z)) of the interplanetary magnetic field (IMF) was northward and 30 occurred when B(sub Z) was southward or fluctuating. Only three of the B(sub Z) northward cases and only five of the B(sub Z) southward cases were preceded by pressure pulses greater than 0.4 nPa in amplitude. Ten of the events were studied in detail by means of a model-fitting method discussed elsewhere. This method infers values of several parameters, including the total current flowing in a coaxial or monopole system and a two-dimensional dipole system. The intrinsic properties of the events showed that only approximately 10% of the total current contributed to momentum transfer to the high-latitude ionosphere, that the direction of the motion depended more on local time of observation than IMF B(sub y), and that events were usually several hundred kilometers in size. The observed B(sub z) control found in the 42 event list and the prevalence of coaxial current dominated events are inconsistent with the predictions of the pressure pulse model.

Lin, Z. M.↗