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At least 487 records · Page 27

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DOE OSTI2023

A parallel p ‐adaptive discontinuous Galerkin method for the Euler equations with dynamic load‐balancing on tetrahedral grids

Abstract A novel p ‐adaptive discontinuous Galerkin (DG) method has been developed to solve the Euler equations on three‐dimensional tetrahedral grids. Hierarchical orthogonal basis functions are adopted for the DG spatial discretization while a third order TVD Runge‐Kutta method is used for the time integration. A vertex‐based limiter is applied to the numerical solution in order to eliminate oscillations in the high order method. An error indicator constructed from the solution of order and is used to adapt degrees of freedom in each computational element, which remarkably reduces the computational cost while still maintaining an accurate solution. The developed method is implemented with under the Charm++ parallel computing framework. Charm++ is a parallel computing framework that includes various load‐balancing strategies. Implementing the numerical solver under Charm++ system provides us with access to a suite of dynamic load balancing strategies. This can be efficiently used to alleviate the load imbalances created by p ‐adaptation. A number of numerical experiments are performed to demonstrate both the numerical accuracy and parallel performance of the developed p ‐adaptive DG method. It is observed that the unbalanced load distribution caused by the parallel p ‐adaptive DG method can be alleviated by the dynamic load balancing from Charm++ system. Due to this, high performance gain can be achieved. For the testcases studied in the current work, the parallel performance gain ranged from 1.5× to 3.7×. Therefore, the developed p ‐adaptive DG method can significantly reduce the total simulation time in comparison to the standard DG method without p ‐adaptation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Substantial Diel Changes of Cloud Adjustments to Aerosols in Ship‐Tracks

Clouds adjust their albedo, amount and liquid water path to anthropogenic aerosols, and produce a climate forcing. Such cloud adjustments are complex functions of both environmental conditions and interaction time. However, direct observations of temporal changes in cloud adjustments are limited. Here, we develop a method to show observational evidence of substantial diel changes in cloud adjustments within ship-tracks. Polluted clouds experiencing extended nighttime exposure exhibit higher increases in cloud fraction while liquid-water path adjustments follow a non-monotonic evolution. The higher cloud fraction increase persists through daytime. Such diel variations likely stem from diel changes in solar heating and background cloud precipitation, and are important because nighttime changes persist and affect solar radiation during the day. Accounting for diel variations produces a stronger aerosol forcing, by −0.1 ∼−0.4 W⁢m −2 . Our approach reveals how the temporal evolution of cloud adjustments can have important implications for aerosol-cloud interactions.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗

NASA NTRS1982

Autoionization states of SO2

Assignments are reported for the autoionizing states of SO2(+) in the 1020-630 A region. The Rydberg states of SO(+) were observed by the method of molecular beam photoionization mass spectrometry, which ensures that all the states observed are autoionizing in nature. The vibrational progressions obtained are assigned to the 4b2-3s, 4b2-3d, 7a1-3p, 7a1-3d, and 2b1-3p Rydberg states. Dips in the photoionization efficiency curves of SO2(+) and SO(+) correspond to those of a window resonance series previously observed in photoabsorption.

Wu, C. Y. R.↗

NASA NTRS1996

Automated Decomposition of Model-based Learning Problems

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Williams, Brian C.↗

NASA NTRS1983

Surface and allied studies in silicon solar cells

Two main results are presented. The first deals with a simple method that determines the minority-carrier lifetime and the effective surface recombination velocity of the quasi-neutral base of silicon solar cells. The method requires the observation of only a single transient, and is amenable to automation for in-process monitoring in manufacturing. This method, which is called short-circuit current decay, avoids distortion in the observed transient and consequent inacccuracies that arise from the presence of mobile holes and electrons stored in the p/n junction spacecharge region at the initial instant of the transient. The second main result consists in a formulation of the relevant boundary-value problems that resembles that used in linear two-port network theory. This formulation enables comparisons to be made among various contending methods for measuring material parameters of p/n junction devices, and enables the option of putting the description in the time domain of the transient studies in the form of an infinite series, although closed-form solutions are also possible.

Lindholm, F. A.↗

NASA NTRS1999

Recent Development on O(+) - O Collision Frequency and Ionosphere-Thermosphere Coupling

The collision frequency between an oxygen atom and its singly charged ion controls the momentum transfer between the ionosphere and the thermosphere. There has been a long standing discrepancy, extending over a decade, between the theoretical and empirical determination of this frequency: the empirical value of this frequency exceeded the theoretical value by a factor of 1.7. Recent improvements in theory were obtained by using accurate oxygen ion-oxygen atom potential energy curves, and partial wave quantum mechanical calculations. We now have applied three independent statistical methods to the observational data, obtained at the MIT/Millstone Hill Observatory, consisting of two sets A and B. These methods give results consistent with each other, and together with the recent theoretical improvements, bring the ratio close to unity, as it should be. The three statistical methods lead to an average for the ratio of the empirical to the theoretical values equal to 0.98, with an uncertainty of +/-8%, resolving the old discrepancy between theory and observation. The Hines statistics, and the lognormal distribution statistics, both give lower and upper bounds for the Set A equal to 0.89 and 1.02, respectively. The related bounds for the Set B are 1.06 and 1.17. The average values of these bounds thus bracket the ideal value of the ratio which should be equal to unity. The main source of uncertainties are errors in the profile of the oxygen atom density, which is of the order of 11%. An alternative method to find the oxygen atom density is being suggested.

Omidvar, K.↗

NASA NTRSDate not supplied

Pyroscopegridding: Geo-Leo Aerosol Data Fusion (an Open-Source Package)

The retrieval of aerosol optical depths (AODs) from sun-synchronous polar orbiting satellites, such as MODISs, VIIRSs, OMI, TROPOMI, etc., has been widely adopted as a method for obtaining information regarding particulate matter (PM) and related atmospheric processes. However, the advent of recently launched geostationary satellites, such as GOES-16/17/18, Himawari-8/9, and Meteosat Third Generation (MTG), has led to an increased temporal resolution of AOD observations (order of 10 minutes), resulting in typically one or more images per hour during daylight hours, compared to the once-per-day observations obtained from LEO satellites. By integrating these observations, the diurnal cycle of global AOD can be characterized at local, regional, and global scales. The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively merging these observations with differing spatial and temporal resolutions. This presents a significant ""Big Data"" challenge, encompassing not only data storage, but also data discoverability, accessibility, and migration within cloud computing environments. This study presents our attempts at fusing Level 2 aerosol data from six satellites, three of which are geostationary (GOES-16/17 and Himawari-8) and three of which are polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS), using the Dark Target aerosol retrieval algorithm. The ability to fuse remote sensing products on demand into desired temporal and spatial domains empowers researchers and practitioners to more efficiently work with satellite and sensor data. It is our hope that through making our open-source package and accompanying functionality available, the scientific community will have improved access to aerosol data processing resources.

Jennifer Wei↗

DOE OSTI2023

Privacy-Preserving Robust Consensus for Distributed Microgrid Control Applications

Consensus-based distributed control has been proposed for coordinating distributed energy resources (DERs) in microgrids (MGs). As one key component, distributed average observers are used to estimate the average of a group of reference signals (e.g., voltage, current, or power). State-of-the-art distributed average observers could lead to loss of privacy due to information exchange on the communication channels. The DERs' reference signals, which contain private information, could be inferred by an eavesdropper. In this article, a privacy-preserving distributed average observer is proposed that is based on robust consensus and uses the state decomposition method to preserve privacy. Compared to the existing methods, the proposed observer does not require the knowledge of the reference signal's derivative and gives accurate and smooth estimation, and is thus applicable for MG distributed control applications. A detailed analysis regarding the convergence and privacy properties of the proposed observer is presented. Here, the proposed observer is implemented on hardware controllers and validated in the context of distributed MG control applications through hardware-in-the-loop (HIL) tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Multi-Level Structural Damage Characterization Using Sparse Acoustic Sensor Networks and Knowledge Transferred Deep Learning

Standard structural health monitoring techniques face well-known difficulties for comprehensive defect diagnosis in real-world structures that have structural, material, or geometric complexity. This motivates the exploration of machine-learning-based structural health monitoring methods in complex structures. However, creating sufficient training data sets with various defects is an ongoing challenge for data-driven machine (deep) learning algorithms. The ability to transfer the knowledge of a trained neural network from one component to another or to other sections of the same component would drastically reduce the required training data set. Also, it would facilitate computationally inexpensive machine learning based inspection systems. In this work, a machine-learning-based multi-level damage characterization is demonstrated with the ability to transfer trained knowledge within the sparse sensor network. A novel network spatial assistance and an adaptive convolution technique are proposed for efficient knowledge transfer within the deep learning algorithm. Proposed structural health monitoring method is experimentally evaluated on an aluminum plate with artificially induced defects. It was observed that the method improves the performance of knowledge transferred damage characterization by 50% during localization and 24% during severity assessment. Further, experiments using time windows with and without multiple edge reflections are studied. Results reveal that multiply scattered waves contain rich and deterministic defect signatures that can be mined using deep learning neural networks, improving the accuracy of both identification and quantification. In the case of a fixed sensor network, using multiply scattered waves shows 100% prediction accuracy at all levels of damage characterization.

36 MATERIALS SCIENCE↗

NASA NTRS1992

The mass of (1) Ceres from perturbations on (348) May

The most promising ground-based technique for determining the mass of a minor planet is the observation of the perturbations it induces in the motion of another minor planet. This method requires careful observation of both minor planets over extended periods of time. The mass of (1) Ceres has been determined from the perturbations on (348) May, which made three close approaches to Ceres at intervals of 46 years between 1891 and 1984. The motion of May is clearly influenced by Ceres, and by using different test masses for Ceres, a search was made to determine the mass of Ceres that minimizes the residuals in the observations of May.

Williams, Gareth V.↗

NASA NTRS2005

On the determination of atmospheric minor gases by the method of vanishing partial derivatives with application to CO2

We present a general method for the determination of minor gases in the troposphere from high spectral resolution observations. In this method, we make use of a general property of the total differential of multi-variable functions to separate the contributions of each individual minor gas. We have applied this method to derive the mixing ratio of carbon dioxide in the mid-troposphere using data from the Atmospheric Infrared Sounder (AIRS) currently flying on the NASA Aqua Mission. We compare our results to the aircraft flask CO2 measurements obtained by H. Matsueda et al. over the western Pacific and demonstrate skill in tracking the measured 5 ppmv seasonal variation with an accuracy of 0.43 +/- 1.20 ppmv.

Atmospheric Infrared Sounder (AIRS)↗

DOE OSTI2023

Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers

The complex events observed at the NOvA long-baseline neutrino oscillation experiment contain vital information for understanding the most elusive particles in the standard model. The NOvA detectors observe interactions of neutrinos from the NuMI beam at Fermilab. Associating the particles produced in these interaction events to their source particles, a process known as reconstruction, is critical for accurately measuring key parameters of the standard model. Events may contain several particles, each producing sparse high-dimensional spatial observations, and current methods are limited to evaluating individual particles. To accurately label these numerous, high-dimensional observations, we present a novel neural network architecture that combines the spatial learning enabled by convolutions with the contextual learning enabled by attention. This joint approach, TransformerCVN, simultaneously classifies each event and reconstructs every individual particle's identity. TransformerCVN classifies events with 90% accuracy and improves the reconstruction of individual particles by 6% over baseline methods which lack the integrated architecture of TransformerCVN. In addition, this architecture enables us to perform several interpretability studies which provide insights into the network's predictions and show that TransformerCVN discovers several fundamental principles that stem from the standard model.

Shmakov, Alexander↗

NASA NTRS2002

Real Time Monitoring of Flooding from Microwave Satellite Observations

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

Galantowicz, John F.↗

DOE OSTI2022

A new method for inferring city emissions and lifetimes of nitrogen oxides from high-resolution nitrogen dioxide observations: a model study

We present a new method to infer emissions and lifetimes of nitrogen oxides (NO x ) based on tropospheric nitrogen dioxide (NO 2 ) observations together with reanalysis wind fields for cities located in polluted backgrounds. Since the accuracy of the method is difficult to assess due to lack of “true values” that can be used as a benchmark, we apply the method to synthetic NO 2 observations derived from the NASA-Unified Weather Research and Forecasting (NU-WRF) model at a high horizontal spatial resolution of 4 km × 4 km for cities over the continental United States. We compare the inferred emissions and lifetimes with the values given by the NU-WRF model to evaluate the method. The method is applicable to 26 US cities. The derived results are generally in good agreement with the values given by the model, with the relative differences of 2 % ± 17 % (mean ± standard deviation) and 15 % ± 25 % for lifetimes and emissions, respectively. Our investigation suggests that the use of wind data prior to the satellite overpass time improves the performance of the method. The correlation coefficients between inferred and NU-WRF lifetimes increase from 0.56 to 0.79 and for emissions increase from 0.88 to 0.96 when comparing results based on wind fields sampled simultaneously with satellite observations and averaged over 9 h data prior to satellite observations, respectively. We estimate that uncertainties in NO x lifetime and emissions arising from the method are approximately 15 % and 20 %, respectively, for typical (US) cities. The total uncertainties reach up to 43% (lifetimes) and 45% (emissions) by considering the additional uncertainties associated with satellite NO 2 observations and wind data. We expect this new method to be applicable to NO 2 observations from the TROPOspheric Monitoring Instrument (TROPOMI) and geostationary satellites, such as Geostationary Environment Monitoring Spectrometer (GEMS) or the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument, to estimate urban NO x emissions and lifetimes globally.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Removal of seeing and instrumental blur effects from astronomical scanner observations

The Phillips-Twomey method for solving simultaneous integral equations is applied to the problem of removing blur effects arising from atmospheric and instrumental sources from astronomical observations made with photoelectric area-scanning instruments. Details of the method and the effects of observational errors on the quality of the results are discussed in the context of applications to actual observations of stars and the planet Saturn.

Clements, A. E.↗

DOE OSTI2023

Assessing North Atlantic Tropical Cyclone Rainfall Hazard Using Engineered-Synthetic Storms and a Physics-Based Tropical Cyclone Rainfall Model

In this study, we design a statistical method to couple observations with a physics-based tropical cyclone (TC) rainfall model (TCR) and engineered-synthetic storms for assessing TC rainfall hazard. We first propose a bias-correction method to minimize the errors induced by TCR via matching the probability distribution of TCR-simulated historical TC rainfall with gauge observations. Then we assign occurrence probabilities to engineered-synthetic storms to reflect local climatology, through a resampling method that matches the probability distribution of a newly proposed storm parameter named rainfall potential (POT) in the synthetic dataset with that in the observation. POT is constructed to include several important storm parameters for TC rainfall such as TC intensity, duration, and distance and environmental humidity near landfall, and it is shown to be correlated with TCR-simulated rainfall. The proposed method has a satisfactory performance in reproducing the rainfall hazard curve in various locations in the continental United States; it is an improvement over the traditional joint probability method (JPM) for TC rainfall hazard assessment.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

The Relationship of Subvisible Cirrus Clouds Observed During NASA's Tropical Ozone

Pfister, L.↗

NASA NTRS1998

Observations of Subvisible Cirrus Clouds and Gravity Waves at the Tropical Tropopause

Thin, subvisible cirrus (SVC) clouds at the tropical tropopause have been observed by a number of methods in a variety of observational programs, including in situ sampling and aircraft and space-based lidar. Modeling studies suggest that these clouds play an important role in dehydrating tropospheric air as it enters the stratosphere. This is because particles large enough to have significant fall speeds can form under the conditions of slow cooling that are implied by the large horizontal extent of the SVC sheets. The IR radiation that these clouds absorb, and the upward vertical motion this implies, also makes them candidates for a tropical troposphere-to-stratosphere mass transfer mechanism. They may also play a role in the earth's radiation budget. These sheets were observed on five flights during the Tropical Ozone Transport Experiment (TOTE) by the NASA Langley DIAL lidar aboard NASA's DC-8 research aircraft operating during December 1995 and February 1996 south of Hawaii. The relationship of the SVC's observed during TOTE to convection was not a simple one. One class of SVC's are within 1000 km of the persistent strong convection near 15S (the SPCZ). Trajectory analyses indicated that the SVC air masses have in fact passed through the SPCZ within a few days of observation. These clouds are very close to the tropopause, with maximum potential temperatures not much higher than 370K, consistent with in situ water and total water measurements near the tropopause made during the Stratosphere Troposphere Exchange Project in January 1987 at Darwin, Australia. A second class of SVC's are not immediately downstream of convection. These clouds tend to be higher, reaching potential temperatures of 390K or more. Trajectory analyses indicate that the air in these SVC's originates either in the equatorial western Pacific or along the subtropical jet. In any case, the warm temperatures the SVC air masses encounter just prior to the observation time along the back trajectory imply that the clouds cannot be residual particles from cirrus blowoff, but must form locally as the air move upward and equatorward south of Hawaii. Since all the parcels have encountered colder temperatures than those at the time of observation early in their history, subsynoptic scale temperatures colder than the analysis temperatures appear to be required to explain the formation of ice particles. In fact, the sloping shapes of the SVC's do suggest that they are gravity or inertia-gravity waves. In situ meteorological measurements made by the ER-2 within a day of the DC-8 remote lidar observations show a gravity wave structure near the equator with an estimated period of about 30 hours. This is sufficiently long to allow large particles to form and fall out (thus allowing dehydration). Other ER-2 flights south of Hawaii at other times of year show gravity and inertia-gravity waves with a poleward wavenumber component and significant (5 degrees peak to peak) temperature perturbation.

Pfister, Leonhard↗