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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MultiPEM Toolbox: User Manual [Rev. 2]

This document explains use of the Multi-Phenomenology Explosion Monitoring (Multi PEM) Toolbox, a collection of R scripts for estimating the unknown device parameters of a new event with uncertainty quantification. The methodology and application used for illustration in this user manual are fully documented in a Los Alamos National Laboratory technical report hereafter designated “WPA” for reference. Additional details on the application are found in a recent journal article. Two assessment types are available: rapid and complete. Rapid assessments are conducted in two stages, as described in Section 2. In the first stage, calibration data are used to estimate forward and error model parameters (WPA, §5.1) and (if relevant) errors-in-variables yield values for calibration sources (WPA, §3, Equation (3)). In the second stage, new event data are used to estimate the unknown new event device parameters (WPA, §5.2) with uncertainty quantification. Two options for treating the inferred first stage parameters in second stage Bayesian analysis are available: fixing them at their maximum likelihood estimate (default), or multiple imputation. Multiple imputation involves utilizing several posterior samples (imputations) of the first stage parameters as fixed values in the second stage posterior sampling of the new event device parameters. Second stage sampling is conducted across imputations in parallel to improve computational efficiency. This method produces improved uncertainty quantification of the new event device parameters compared with the default treatment of the first stage parameters, at the expense of additional computation. Complete assessments are conducted in a single stage, as described in Section 3. Calibration and (if relevant) new event data are used simultaneously to estimate all forward model, error model, and (if relevant) new event device parameters with uncertainty quantification on the latter. As the name suggests, rapid assessments generally run substantially faster than complete assessments (even with multiple imputation), because the results of first stage analysis can be stored and incorporated into estimating a relatively low-dimensional space of new event device parameters whenever relevant new event data becomes available. On the other hand, complete assessments must be run on the full set of model and device parameters with calibration and new event data every time the latter becomes available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗
NASA NTRS2007

On the Long-Term Stability of Microwave Radiometers Using Noise Diodes for Calibration

Results are presented from the long-term monitoring and calibration of the National Aeronautics and Space Administration Jason Microwave Radiometer (JMR) on the Jason-1 ocean altimetry satellite and the ground-based Advanced Water Vapor Radiometers (AWVRs) developed for the Cassini Gravity Wave Experiment. Both radiometers retrieve the wet tropospheric path delay (PD) of the atmosphere and use internal noise diodes (NDs) for gain calibration. The JMR is the first radiometer to be flown in space that uses NDs for calibration. External calibration techniques are used to derive a time series of ND brightness for both instruments that is greater than four years. For the JMR, an optimal estimator is used to find the set of calibration coefficients that minimize the root-mean-square difference between the JMR brightness temperatures and the on-Earth hot and cold references. For the AWVR, continuous tip curves are used to derive the ND brightness. For the JMR and AWVR, both of which contain three redundant NDs per channel, it was observed that some NDs were very stable, whereas others experienced jumps and drifts in their effective brightness. Over the four-year time period, the ND stability ranged from 0.2% to 3% among the diodes for both instruments. The presented recalibration methodology demonstrates that long-term calibration stability can be achieved with frequent recalibration of the diodes using external calibration techniques. The JMR PD drift compared to ground truth over the four years since the launch was reduced from 3.9 to - 0.01 mm/year with the recalibrated ND time series. The JMR brightness temperature calibration stability is estimated to be 0.25 K over ten days.

noise diode (ND)↗
NASA NTRS2012

Electric Field Reconstruction in the Image Plane of a High-Contrast Coronagraph Using a Set of Pinholes around the Lyot Plane

In a setup similar to the self coherent camera, we have added a set of pinholes in the diffraction ring of the Lyot plane in a high-contrast stellar Lyot coronagraph. We describe a novel complex electric field reconstruction from image plane intensity measurements consisting of light in the coronagraph's dark hole interfering with light from the pinholes. The image plane field is modified by letting light through one pinhole at a time. In addition to estimation of the field at the science camera, this method allows for self-calibration of the probes by letting light through the pinholes in various permutations while blocking the main Lyot opening. We present results of estimation and calibration from the High Contrast Imaging Testbed along with a comparison to the pair-wise deformable mirror diversity based estimation technique. Tests are carried out in narrow-band light and over a composite 10% bandpass.

coronagraphs↗
NASA NTRS2019

Direct Te Metallicity Calibration of R23 in Strong Line Emitters

The gas metallicity of galaxies is often estimated using strong emission lines such as the optical lines of [O iii] and [O ii]. The most common measure is "R23," defined as ([O ii]λλ3726, 3729 + [O iii]λλ4959,5007)/Hβ. Most calibrations for these strong-line metallicity indicators are for continuum selected galaxies. We report a new empirical calibration of R23 for extreme emission-line galaxies using a large sample of about 800 star-forming green pea galaxies with reliable Te -based gas-phase metallicity measurements. This sample is assembled from Sloan Digital Sky Survey (SDSS) Data Release 13 with the equivalent width of the line [O iii]λ5007 > 300 Å or the equivalent width of the line Hβ > 100 Å in the redshift range 0.011 < z < 0.411. For galaxies with strong emission lines and large ionization parameter (which manifests as log [O iii]λλ4959,5007/[O ii]λλ3726,3729 ≥0.6), R23 monotonically increases with log(O/H) and the double-value degeneracy is broken. Our calibration provides metallicity estimates that are accurate to within ~0.14 dex in this regime. Many previous R23 calibrations are found to have bias and large scatter for extreme emission-line galaxies. We give formulae and plots to directly convert R23 and [O iii]λλ4959,5007/[O ii]λλ3726,3729 to log(O/H). Since green peas are best nearby analogs of high-redshift Lyα emitting galaxies, the new calibration offers a good way to estimate the metallicities of both extreme emission-line galaxies and high-redshift Lyα emitting galaxies. We also report on 15 galaxies with metallicities less than 1/12 solar, with the lowest metallicities being 12+log(O/H) = 7.25 and 7.26.

Jiang, Tianxing↗
DOE OSTI2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The molecular dipole moment ( μ ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). Here, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting “MuML” models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A MINi Powder INjector (MINPIN) for the SMART tokamak

Here, this article presents the design and performance characterization of a MINi Powder INjector (MINPIN) developed for boron wall conditioning (boronization) in the SMall Aspect Ratio Tokamak (SMART) at the University of Seville, Spain. SMART studies positive and negative triangularity plasmas within the low aspect ratio range of 1.4 < R/a < 3, with a major radius (R) of 0.40–0.60 m and a minor radius (a) of 0.20–0.33 m. MINPIN, in design, will gravitationally deliver boron (B) powder into the plasma, which ablates and transports the injected material. Mounted on the top of the vessel, the MINPIN will drop controlled amounts of powder using a piezoelectric blade driven by a signal generator that vibrates at a set frequency. The B will then be deposited in a layer on SMART’s stainless steel vacuum vessel walls, and this boronization process reduces the influx of intrinsic wall impurities, such as oxygen, carbon, nitrogen, and iron, which radiate power and cool the plasma. In the laboratory, we calibrated the drop rate for 1–10 mg/s, which will enable controlled boronization coating while achieving efficient powder ablation. We propose MINPIN’s operational scenarios based on the calibrated drop rate and estimated drop duration, assuming the distance from MINPIN to SMART’s plasmas.

Boron powder↗
DOE OSTI2022

Photometric Redshifts and Galaxy Clusters for DES DR2, DESI DR9, and HSC-SSP PDR3 Data

Photometric redshift (photoz) is a fundamental parameter for multi-wavelength photometric surveys, while galaxy clusters are important cosmological probes and ideal objects for exploring the dense environmental impact on galaxy evolution. We extend our previous work on estimating photoz and detecting galaxy clusters to the latest data releases of the Dark Energy Spectroscopic Instrument (DESI) imaging surveys, Dark Energy Survey (DES) and Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) imaging surveys and make corresponding catalogs publicly available for more extensive scientific applications. The photoz catalogs include accurate measurements of photoz and stellar mass for about 320, 293 and 134 million galaxies with r < 23, i < 24 and i < 25 in DESI DR9, DES DR2 and HSC-SSP PDR3 data, respectively. The photoz accuracy is about 0.017, 0.024 and 0.029 and the general redshift coverage is z < 1, z < 1.2 and z < 1.6, respectively for those three surveys. Furthermore, the uncertainty of the logarithmic stellar mass that is inferred from stellar population synthesis fitting is about 0.2 dex. With the above photoz catalogs, galaxy clusters are detected using a fast cluster-finding algorithm. A total of 532,810, 86,963 and 36,566 galaxy clusters with the number of members larger than 10 is discovered for DESI, DES and HSC-SSP, respectively. Their photoz accuracy is at the level of 0.01. The total mass of our clusters is also estimated by using the calibration relations between the optical richness and the mass measurement from X-ray and radio observations. The photoz and cluster catalogs are available at ScienceDB (https://www.doi.org/10.11922/sciencedb.o00069.00003) and PaperData Repository (https://doi.org/10.12149/101089).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Analysis of ISOCS Measurements to Establish Methodology Uncertainty

Qualification measurements were performed at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) on a variety of measurement standards. These measurements will be used to qualify the In-Situ Object Counting System (ISOCS) measurement method with a high-purity germanium (HPGe) detector for use at ORNL. Measured items include uranium isotopic standards, filter papers coated with uranium oxide (U 3 O 8 ), U 3 O 8 line sources, and a uranium tetrafluoride (UF 4 ) source. The 235 U mass was estimated using the ISOCS calibration software for each source and compared with the declared isotope mass value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Chemical ionization mass spectrometry utilizing benzene cations for measurements of volatile organic compounds and nitric oxide

We evaluate the capability of chemical ionization mass spectrometry (CIMS) using benzene cations as reagent ions (benzene CIMS) for detecting atmospheric trace gases. We characterize the ionization pathways and product ion distributions for 27 analytes spanning diverse chemical classes. To interpret the complex ion chemistry involving two reagent ions (C 6 H$^{+}_{6}$ and (C 6 H 6 )$^{+}_{2}$) and multiple ionization pathways (charge transfer, proton transfer, adduct formation, and hydride abstraction), we introduce a thermodynamics-based framework that classifies analytes into three categories based on their ionization energy (IE), relative to those of benzene monomer (9.24 eV) and dimer (8.69 eV). Each class exhibits distinct ionization mechanisms and product ions. Analytes with IE smaller than 8.69 eV (low IE) undergo charge transfer with both reagent ions; analytes with IE between 8.69 and 9.24 eV (mid IE) undergo charge transfer with C 6 H$^{+}_{6}$ and potential adduct formation with (C 6 H 6 )$^{+}_{2}$; analytes with IE larger than 9.24 eV (high IE) could undergo adduct formation, proton transfer, or hydride abstraction. Analytes within each class also show similar sensitivity, enabling sensitivity estimation for compounds lacking calibration standards. In addition to volatile organic compounds (VOCs), benzene CIMS detects nitric oxide (NO) with a detection limit of 5 pptv for 1 min integration time, exceeding the performance of most commercial NOx analyzers. Field deployments in Chicago and St. Louis demonstrate good agreement with reference NO measurements. Isoprene measurements show good agreement with a co-located gas chromatography–photoionization detector (GC-PID) in St. Louis, but exhibit substantial positive bias in Chicago, likely due to interferences from anthropogenic VOCs in the polluted urban environment. These results highlight the potential of benzene CIMS for concurrent measurements of NO, VOCs, and their oxidation products using a single instrument, while also underscoring challenges in complex atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A new large-scale suspended sediment model and its application over the United States

Abstract. Suspended sediment plays a vital role in the regional and global cycling of carbon and nutrients by carrying carbon and nutrients from headwaters into lowland rivers and the oceans. Sediment transport through river systems is often fundamentally modified by human activities such as reservoir management. However, a physically based representation of sediment transport is still missing in most existing Earth system models (ESMs), which are essential tools for modeling and predicting Earth system changes. Here, we introduce a multi-process river sediment module for ESMs, which includes (1) hillslope soil erosion and sediment discharge into streams, (2) sediment transport processes through river networks, (3) reservoir operation based on the inflows from upstream areas and water demand from downstream areas, and (4) sediment trapping by reservoirs. All model parameters are estimated a priori without calibration. We apply this new sediment modeling framework to the contiguous United States and validate it against historical observations of monthly streamflow and sediment discharges at 35 river gauges. The model reasonably well captures the long-term balance and seasonal variations of suspended sediment in large river systems. Furthermore, our model results show that suspended sediment discharge in managed rivers is affected more by reservoirs' direct trapping of sediment particles than by their flow regulation. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

On the unification of geodetic leveling datums using satellite altimetry

Techniques are described for determining the height of Mean Sea Level (MSL) at coastal sites from satellite altimetry. Such information is of value in the adjustment of continental leveling networks. Numerical results are obtained from the 1977 GEOS-3 altimetry data bank at Goddard Space Flight Center using the Bermuda calibration of the altimeter. Estimates are made of the heights of MSL at the leveling datums for Australia and a hypothetical Galveston datum for central North America. The results obtained are in reasonable agreement with oceanographic estimates obtained by extrapolation. It is concluded that all gravity data in the Australian bank AUSGAD 76 and in the Rapp data file for central North America refer to the GEOS-3 altimeter geoid for 1976.0 with uncertainties which do not exceed + or - 0.1 mGal.

Mather, R. S.↗
NASA NTRS1980

Progress report on the Block 1 VLBI correlator implementation

The Block 1 VLBI Processor Subsystem (VPS) of the Very Long Baseline Interferometry (VLBI) System for the determination of station clock-sync parameters, UT1 and polar motion, and station platform parameters and for use in spacecraft tracking is discussed. The Block 1 VPS performs three basic functions: it receives the 500 kbit/sec video data over the GCF wideband data lines from each of the three DSN 64 m antennas; it cross correlates data; and it performs several postcorrelation data reduction operations on the correlated data including calibration, editing, and parameter estimation.

Peterson, J. C.↗
NASA NTRS1978

Signal detection in l/f noise of SQUID magnetometers

It is shown that the variance on the SQUID power spectrum in the l/f low frequency region is well behaved, i.e., any small frequency band may be treated as white noise in standard power spectrum estimation theory. Specifically a calibration signal is examined at 0.017 Hz with an equivalent energy referred to the SQUID input coil of 1 times 10 to the -30th J and a digitally recorded and analyzed record of 140 hr duration obtained an optimum S/N better than 400. The results are in good agreement with theory. In addition no deviation from the l/f dependence of the noise energy spectrum is seen down to frequencies below 10 to the -5th Hz. A commercially available SQUID and electronics system were used.

Cabrera, B.↗
NASA NTRS1982

Pulsed multiwavelength laser ranging system

A pulsed multiwavelength laser ranging system for measuring atmospheric delay was built and tested, and its theoretical performance limits were calculated. The system uses a dye modelocked ND:YAG laser, which transmits 70 psec wide pulses simultaneously at 1064, 532, and 355 nm. The differential delay of the 1064 and 355 nm pulses is measured by a specially calibrated waveform digitizer to estimate the dry atmospheric delay. The delay time of the 532 nm pulse is used to measure the target distance. Static crossed field photomultipliers are used as detectors for all wavelengths. Theoretical analysis shows that path curvature and atmospheric turbulence are fundamental limits to the ranging accuracy of both single and multicolor systems operating over horizontal paths. For two color systems, an additional error is caused by the uncertainty in the path averaged water vapor. The standard deviation of the multicolor instrument's timing measurements is directly proportional to the laser pulse width plus photomultiplier jitter divided by the square root of the received photoelectron number. The prototype system's maximum range is km, which is limited by atmospheric and system transmission losses at 355 nm. System signal detection and false alarm calculations are also presented.

Abshire, J. B.↗
NASA NTRS1981

Quadrennial International Ozone Symposium, Boulder, CO, August 4-9, 1980, Proceedings. Volumes 1 & 2

Recent developments in observational techniques are examined, taking into account a review of some unresolved problems in the measurement/estimation of total ozone and the vertical ozone profile, the sensitivity of Dobson total ozone estimations to wavelength band calibration uncertainties, errors in Dobson total measurements arising from aerosol attenuation, and optical stop and focussing effects in the Dobson instrument. Other subjects considered are related to total ozone observations, tropospheric ozone, upper air ozone observations, observations of trace gases in the atmosphere, ozone photochemistry and directly related photochemical models, the interaction of ozone and atmospheric circulation, ozone effects on climate, and solar activity and ozone variations. Programs and recommendations involving ozone theory and observations are also discussed, giving attention to current problems of ozone chemistry, the upper atmosphere research satellite program, a French contribution to ozone related studies, and ozone and the middle atmosphere program.

London, J.↗
NASA NTRS1998

Autonomous Attitude Sensor Calibration (ASCAL)

In this paper, an approach to increase the degree of autonomy of flight software is proposed. We describe an enhancement of the Attitude Determination and Control System by augmenting it with self-calibration capability. Conventional attitude estimation and control algorithms are combined with higher level decision making and machine learning algorithms in order to deal with the uncertainty and complexity of the problem.

Peterson, Chariya↗