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DOE OSTI2017

Solvent hold tank sample results for MCU-17-150-152 (July 2017) and MCU-17-153-155 (August 2017): Quarterly report

A trend summary that includes the last two Solvent Hold Tank (SHT) monthly samples is shown; MCU- 17-150-152 (July SHT) and MCU-17-153-155 (August SHT). Since the last SHT sample sent for analysis was the August sample the chemical state of the solvent is best approximated by the chemical analysis of the August SHT sample (MCU-17-153-155). This report mainly focused on the chemical analysis of the August SHT sample. The analysis data from the July SHT sample are presented in the “trend” plots of this report. Analysis of the August SHT sample (MCU-17-153-155) indicated that the modifier (CS-7SB) was 2% below but the extractant (MaxCalix) concentration was at its nominal recommended level (169,000 mg/L and 46,400 mg/L respectively). The suppressor (TiDG) level has decreased since the last measurement taken while the Modular Caustic-Side Solvent Extraction unit (MCU) was operating in January 2017, but has remained steady in the range of 666 (observed in April) to 715 mg/L (observed in the August 2017 sample) since February 2017, well above the minimum recommended level (479 mg/L), but below the nominal level. The “flat” trends observed in the TiDG, MaxCalix, modifier, and Gamma measurement are consistent with the solvent being idle since January 10, 2017. A strong correlation between density and modifier concentration in the solvent continues to be observed in the SHT samples. This analysis confirms the Isopar™L addition to the solvent in January 2017. This analysis also indicates the solvent did not require further additions. Based on the current monthly sample, the levels of TiDG, Isopar™L, MaxCalix, and modifier are sufficient for continuing operation but are expected to decrease with time if the Modular Caustic-Side Solvent Extraction Unit (MCU) returns to processing radioactive liquid waste. Otherwise, the levels of these components will remain steady. A future Isopar™L trimming addition to the solvent is recommended when MCU resumes processing waste. Two unknown impurities related to the modifier (but not sec-butyl phenol: a modifier degradation product observed before) at the 290 and 110 mg/L levels were observed in the August SHT sample by the Gas - Chromatography-Mass Spectrometry (GC-MS) method. They were observed in a second GC-MS re-run with a new column. Their identification can’t be ascertained at this time. No impurities were observed in the Hydrogen Nuclear Magnetic Resonance (HNMR). Another impurity observed in the samples was mercury. Based on the August SHT sample, up to 23 ± 5 micrograms of mercury per mL of solvent was detected (the average of the Cold Vapor-Atomic Adsorption [CV-AA] and X-Ray Fluorescence [XRF] methods). The higher mercury concentration in the solvent (as determined in the last three-monthly samples) is possibly due to either a higher mercury concentration in Salt Batches 8 and 9 (Tank 49H) . The gamma level (~ 2.0E4 dpm/mL) measured in the August SHT samples was one order of magnitude lower than the gamma levels observed in the December 2016 and January 2017 SHT samples. A similar level was observed in the July SHT sample (MCU-SHT-150-152). The gamma level has remained consistently steady since January 10, 2017 when MCU stopped processing radioactive liquid waste. The laboratory will continue to monitor the quality of the solvent in particularly for any new impurities or degradation of the solvent components.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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 OSTI2017

EARLY OBSERVATIONS ON THE EXPERIMENTAL STUDY OF FLUID-STRUCTURE-INTERACTIONS WHILE TESTING PLATE-TYPE-FUEL

This paper presents the methods, outcomes, and observations made from these early NQA-1 compliant flow tests, demonstrating a successful observation of plastic deformation of this plate-type fuel and a basis for its occurrence when compared against previous computational studies’ results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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 OSTI2015

Direct observation of charge mediated lattice distortions in complex oxide solid solutions

Using aberration corrected scanning transmission electron microscopy combined with advanced imaging methods, we directly observe atom column specific, picometer-scale displacements induced by local chemistry in a complex oxide solid solution. Displacements predicted from density functional theory were found to correlate with the observed experimental trends. Further analysis of bonding and charge distribution was used to clarify the mechanisms responsible for the detected structural behavior. By extending the experimental electron microscopy measurements to previously inaccessible length scales, we identified correlated atomic displacements linked to bond differences within the complex oxide structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

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↗

DOE OSTI2018

An Approach to Estimate Atmospheric Greenhouse Gas Total Columns Mole Fraction from Partial Column Sampling

This paper presents a new conceptual approach to estimate total column mole fractions of CO 2 and CH 4 using partial column data. It provides a link between airborne in situ and remote sensing observations of greenhouse gases. The method relies on in situ observations, external ancillary sources of information (e.g., atmospheric transport models), and a regression kriging framework. We evaluate our new approach using National Oceanic and Atmospheric Administration's (NOAA's) AirCore program-in situ vertical profiles of CO 2 and CH 4 collected from weather balloons. Our paper shows that under the specific conditions of this study and assumption of unbiasedness, airborne observations up to 6500-9500maltitude are required to achieve comparable total column CO 2 mole fraction uncertainty as the Total Carbon Column Observing Network (TCCON) network provides, given as a precision of the ratio between observed and true total column-integrated mole fraction, assuming 400 ppm XCO 2 (2σ, e.g., 0.8 ppm). If properly calibrated, our approach could be applied to vertical profiles of CO 2 collected from aircraft using a few flask samples, while retaining similar uncertainty level. Our total column CH 4 estimates, by contrast, are less accurate than TCCON's. Aircrafts are not as spatially constrained as TCCON ground stations, so our approach adds value to aircraft-based vertical profiles for evaluating remote sensing platforms.

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↗

NASA NTRS2022

Distributed Observation Allocation for a Large-Scale Constellation

Increased space and ground sensing is enabling dramatic new measurements of a wide range of Earth Science and Applied Earth Science phenomena, including: volcanism, flooding, wildfires, and weather. Large scale observations constellations of hundreds of assets already exist (e.g. Planet) with several constellations with 10,000’s of assets planned. New challenges exist to rapidly assimilate available data and to optimize measurements (e.g. direct assets) to best observe these complex and dynamic spatiotemporal phenomena. We describe automated centralized and distributed Artificial Intelligence methods for allocating observations within a constellation.

Harrod, Ryan↗

NASA NTRS2022

Distributed Observation Allocation for a Large-Scale Constellation

Harrod, Ryan↗

DOE OSTI2016

INTERPRETING FLUX FROM BROADBAND PHOTOMETRY

We discuss the transformation of observed photometry into flux for the creation of spectral energy distributions (SED) and the computation of bolometric luminosities. We do this in the context of supernova studies, particularly as observed with the Swift spacecraft, but the concepts and techniques should be applicable to many other types of sources and wavelength regimes. Traditional methods of converting observed magnitudes to flux densities are not very accurate when applied to UV photometry. Common methods for extinction and the integration of pseudo-bolometric fluxes can also lead to inaccurate results. The sources of inaccuracy, though, also apply to other wavelengths. Because of the complicated nature of translating broadband photometry into monochromatic flux densities, comparison between observed photometry and a spectroscopic model is best done by forward modeling the spectrum into the count rates or magnitudes of the observations. We recommend that integrated flux measurements be made using a spectrum or SED which is consistent with the multi-band photometry rather than converting individual photometric measurements to flux densities, linearly interpolating between the points, and integrating. We also highlight some specific areas where the UV flux can be mischaracterized.

79 ASTRONOMY AND ASTROPHYSICS↗