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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Application of Partial Least Squares Approaches to Pyroprocessing ER Data

Multivariate approaches show promise for application to process monitoring for safeguards of pyroprocessing. Past MPACT work explored the application of Principal Component Analysis (PCA) to detect off-normal conditions in pyroprocessing electrorefiner (ER) data from in the Hot Fuel Examination Facility (HFEF) at Idaho National Laboratory (INL) known as the Scalable Pyrochemical Recycling testbed (SPyRe) ER. PCA, however, does not consider the output variables. In FY24, multivariate analysis was extended from PCA to Partial Least Squares (PLS) analysis. PLS maximizes the variance between both the input signals and output variables. In the case of this work, PLS was applied in two different manners: Predictive PLS and Discriminant PLS. Predictive PLS maximizes the covariance between the process variables of the ER and the measured U concentration from in-situ voltammetry. Discriminant PLS maximizes the covariance between the process variables and a set of training process “states” such as known off-normal conditions. By projecting into the latent variable space in PLS, the process variables can be regressed onto the outputs and predictions can be made for new data sets. In this work, by applying predictive PLS, a penalized non-linear PLS approach was able to make predictions of concentration based on test and training data and detect when operations were off-normal. However, the predictive PLS does not classify the signals to which off-normal operations are attributable. Discriminant PLS can be used to classify off-normal operations but is inadequate to properly classify specific off-normal classes like power supply faults when the Discriminant PLS model is only specifically trained to detect that off-normal class. When all faults are trained against the observation data, all three operational classes are accurately classified and distinguished. Thus, future application of latent variable techniques should not select any given method, but should use a mixture of PCA, Predictive PLS, and Discriminant PLS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Periodic outbursts from the black hole candidate 4U 1630-47

Observational data from several observatories, including Rosat, are used to identify two previously unreported outbursts from the ultrasoft X-ray transient 4U 1630-47. These outbursts occurred in March 1979 and September 1993, which is consistent with a previously reported 600-day outburst recurrence period. This source is a member of the class of transient X-ray binary systems that are thought to contain black holes. The 601.0 +/- 2.8 day period is the shortest observed so far for this class.

Parmar, A. N.↗
NASA NTRS2003

The Evolution of Interstellar Gas: Massive Stars and the Dispersal of Neutral Material

We studied the effects of newly formed O and B stars on their surrounding interstellar material through a combination of observations and theoretical modeling. The observational data came from measurements of absorption seen in the spectra of background, newly formed stars. Particular attention was given to stellar radiation which converts molecular to atomic material. Laboratory data on absorption cross sections relevant to the analysis and interpretation of carbon monoxide formed part of the effort. The grant supported Postdoctoral Fellows, Drs. Min Yan and Yaron Sheffer, and a laboratory technician. Though the students themselves were not supported. one M.S. Thesis and two Ph.D. dissertations from the University of Toledo were based on the research done under the grant. The research accomplished under this grant led directly to other funded programs. An observing proposal to study the chemistry of diffuse molecular clouds in the Large and Small Magellanic Clouds with ESO s Very Large Telescope was another example of a successful outcome of my LTSA program.

Federman, Steven R.↗
NASA NTRS2008

Black Hole Mergers as Probes of Structure Formation

Intense structure formation and reionization occur at high redshift, yet there is currently little observational information about this very important epoch. Observations of gravitational waves from massive black hole (MBH) mergers can provide us with important clues about the formation of structures in the early universe. Past efforts have been limited to calculating merger rates using different models in which many assumptions are made about the specific values of physical parameters of the mergers, resulting in merger rate estimates that span a very wide range (0.1 - 104 mergers/year). Here we develop a semi-analytical, phenomenological model of MBH mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z 5 - 30 structure formation era. We do this by generating synthetic LISA observable data (total BH mass, BH mass ratio, redshift, merger rates), which are then analyzed using a Markov Chain Monte Carlo method. This allows us to constrain the physical parameters of the mergers. We find that our methodology works well at estimating merger parameters, consistently giving results within 1- of the input parameter values. We also discover that the number of merger events is a key discriminant among models. This helps our method be robust against observational uncertainties. Our approach, which at this stage constitutes a proof of principle, can be readily extended to physical models and to more general problems in cosmology and gravitational wave astrophysics.

Alicea-Munoz, E.↗
DOE OSTI2015

FAST RADIO BURSTS: COLLISIONS BETWEEN NEUTRON STARS AND ASTEROIDS/COMETS

Fast radio bursts (FRBs) are newly discovered radio transient sources. Their high dispersion measures indicate an extragalactic origin. However, due to the lack of observational data in other wavelengths, their progenitors still remain unclear. Here we suggest that the collisions between neutron stars (NSs) and asteroids/comets are promising mechanisms for FRBs. During the impact process, a hot plasma fireball forms after the material of the small body penetrates into the NS surface. The ionized matter inside the fireball then expands along the magnetic field lines. Coherent radiation from the thin shell at the top of the fireball will account for the observed FRBs. Our scenario can reasonably explain the main features of FRBs, such as their durations, luminosities, and the event rate. We argue that for a single NS, FRBs are not likely to happen repeatedly in a forseeable timespan since such impacts are of low probability. We predict that faint remnant X-ray emissions should be associated with FRBs, but it may be too faint to be detected by detectors at work.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

Dynamical implications of the observed thermal contrasts in Venus' upper atmosphere

Observational data on the Venusian upper atmosphere are analyzed to determine the dynamical implications of the large pressure change across the terminator, to study the change in diurnal contrast pattern at the 100 km level, and to investigate the viability of the most straightforward explanation of the cooling, radiative emission by CO2 in the 15 micron bands. Evidence is discussed that a major subsidence or downward vertical contraction of the upper atmosphere occurs across the terminator. The observation that supersonic velocities would be induced in horizontal, inviscid flow by the observed pressure distributions affected by the described flow subsidence is investigated by generalizing the equations for adiabatic inviscid flow along streamtubes to the case of nonhorizontal inviscid flow with heat addition. Nightside cooling is discussed, showing variations in cooling rates. Finally, zonal winds below 100 km are considered.

Seiff, A.↗
NASA NTRS1985

Trends in upper stratospheric temperatures as observed by rocketsondes (1965-1983)

Recent interest in possible anthropogenically induced changes in stratospheric ozone has led to a number of modeling studies. These studies indicate that stratospheric temperature changes would be related to stratospheric ozone changes. Therefore, this study was motivated by a concern to find out whether or not any significant trend in upper stratospheric temperatures could be ascertained from available observational data. June monthly mean values for 40 to 45 km layer were calculated for all Western Hemisphere rocketsonde stations for which data was available. Mean temperatures for each June were then used to calculate linear least squares regression coefficients with latitude of the stations as the independent variable. The resulting coefficients were used to calculate area-weighted mean temperatures for 25 deg N to 55 deg N. A two-to-three degree temperature drop in the early 1970s is indicated. It was noted, however, that this temperature decline coincides with a change in the principal observing system from the Arcasconde system to the Datasonde system. In order to study this temperature decrease more closely, similar mean temperatures were calculated for the 25 to 30 km layer using both rocketsondes and support radiosondes.

Johnson, K. W.↗
NASA NTRS2013

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗
NASA NTRSDate not supplied

Expanding the Time Dimension of Hyperspectral Infrared Sounding Observations: Designing the NUCAPS-Forecast System

Low Earth orbit (LEO) hyper-spectral infrared (IR) sounders have significant yet untapped potential for characterizing thermodynamic environments of convective initiation and ongoing convection. While LEO soundings are of enormous value to weather forecasters, they cannot provide the temporal resolution needed to resolve the rapidly evolving thermodynamics of the convective environment. A novel methodology was developed to extend snapshots of LEO soundings forward in time up to six hours into the future and has been made available within the NOAA National Weather Service Advanced Weather Interactive Processing System (AWIPS) for testing in a quasi-operational setting. This methodology is based on parcel forward-trajectory calculations from the satellite observing time to recreate future soundings of temperature and moisture at regularly gridded intervals in space and time. The soundings are based on NOAA-Unique Combined Atmospheric Processing System (NUCAPS) retrievals from the Suomi NPP and NOAA-20 satellite platforms to allow for rapid near-real time product processing. Science code was transitioned to operational production in 2019 and the product, NUCAPS-Forecast, was tested at the NOAA Hazardous Weather Testbed Spring Experiment in 2019 and 2021. Forecaster feedback has led to improving the product and processing system to address product limitations and improve its applicability for pre-convective forecasting. This presentation highlights the design of the NUCAPS-Forecast system. Solutions were tested and implemented to remove excess moisture and conjoin forward-trajected parcels into vertical profiles for calculating grids of stability indices. Additionally, use cases that explore the tendencies of derived convective available potential energy (CAPE) and convective inhibition (CIN) were investigated. When evaluated against gridded, hourly accumulated rainfall obtained from the Multi-Radar Multi-Sensor (MRMS) observational data set areas with elevated CAPE (reduced CIN) are shown to be associated with areas of precipitation and increase confidence the LEO soundings advected forward in time physically represent atmospheric processes. These results suggest that adiabatic parcel advection of LEO satellite sounding snapshots forward in time exhibits skill in discriminating locations and times that are more likely to lead to convective initiation. Leveraging trajectory modeling to increase the spatial and temporal resolution of LEO IR sounding observations today demonstrates the value of these observations from the future constellation of JPSS satellites and GeoXO mission.

weather↗
DOE OSTI2014

Neutrinos and dark energy after Planck and BICEP2: data consistency tests and cosmological parameter constraints

The detection of the B-mode polarization of the cosmic microwave background (CMB) by the BICEP2 experiment implies that the tensor-to-scalar ratio r should be involved in the base standard cosmology. In this paper, we extend the ΛCDM r+neutrino/dark radiation models by replacing the cosmological constant with the dynamical dark energy with constant w. Four neutrino plus dark energy models are considered, i.e., the wCDM r ∑ m{sub ν}, wCDM r N{sub eff}, wCDM r ∑ m{sub ν} N{sub eff}, and wCDM r N{sub eff} m{sub ν,sterile}{sup eff} models. The current observational data considered in this paper include the Planck temperature data, the WMAP 9-year polarization data, the baryon acoustic oscillation data, the Hubble constant direct measurement data, the Planck Sunyaev-Zeldovich cluster counts data, the Planck CMB lensing data, the cosmic shear data, and the BICEP2 polarization data. We test the data consistency in the four cosmological models, and then combine the consistent data sets to perform joint constraints on the models. We focus on the constraints on the parameters w, ∑ m{sub ν}, N{sub eff}, and m{sub ν,sterile}{sup eff}.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2021

Tonlé Sap Food Security & Agriculture III: Evaluating Changes in Ecosystem Vitality and Freshwater Health in the Tonlé Sap Basin using Remotely Sensed Data

Tonlé Sap Lake, located in Cambodia, Southeast Asia, is one of the most productive inland fisheries in the world. With the unique reverse flow hydrology of the Tonlé Sap River, this freshwater system contains rich biodiversity and provides critical freshwater resources for the local community. Overfishing, stronger seasonality, drought, dam construction, forest fires, and untreated industrial domestic sewage threaten the ecosystem vitality and economic success of Tonlé Sap. In collaboration with Conservation International and the Cambodian Ministry of Water Resources and Meteorology’s Tonlé Sap Authority, we calibrated and finalized remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI). We used NASA Earth observation data from Moderate Resolution Imaging Spectroradiometer (MODIS), and the Gravity Recovery and Climate Experiment (GRACE). These datasets were used in RS proxies and a Soil and Water Assessment Tool (SWAT) model that previous teams developed for sub-indicators of FHI. They included landcover, bank modification, and water quality metrics. It was determined that the ground water storage in Tonlé Sap Lake exhibited a slight declining trend over from April 1st, 2002 to February 3rd, 2017. To calculate chlorophyll-a concentration in the Tonlé Sap Lake, we used Copernicus Global Land Service mission data which provided a Trophic State Index of the lake. Between January 1st, 2000 and December 31st, 2020, the lake and surrounding region within the study area boundary displayed a slight decrease in vegetation density and consistently high chlorophyll-a concentrations. The SWAT model calculated nitrogen and phosphorus content measured in outlet points of the lake. We demonstrated that remotely sensed data is valuable for providing additional information for the FHI, but is not fully capable of replacing its in situ counterpart. We also concluded the water quantity is on a slowly declining trend within the basin.

Joey Lindsay↗
NASA NTRS1994

The three-dimensional structures of X-ray bright points

Recently, the Convergin Flux Model has been proposed for X-ray bright points and cancelling magnetic features. The aim of this piece of work is to try and model theoretically specific X-ray bright points in the framework of the Converging Flux Model. The observational data used includes a magnetogram showing the normal component of the magnetic field at the photosphere and a high-resolution soft X-ray image from NIXT showing the brightenings in the lower solar corona. By approximating the flux concentrations in the magnetograms with poles of the appropriate sign and sense, the overlying three-dimensional potential field structure is calculated. Deduction of plausible motions of the flux sources are made which produce brightenings of the observed shape due to reconnection between neighbouring flux regions. Also the three-dimensional separatrix and separator structure and the way the magnetic field lines reconnect in three dimensions is deduced.

Parnell, C. E.↗
NASA NTRS2008

The Spectrum of 1ES0229 + 200 and the Cosmic Infrared Background

Aims. We reexamine the implications of the recent HESS observations of the blazar 1ES0229+200 for constraining the extragalactic mid-infrared background radiation. Methods. We examine the effect of gamma-ray absorption by the extragalactic infrared radiation on predicted intrinsic spectra for this blazar and compare our results with the observational data. Results. We find agreement with our previous results on the shape of the infrared spectral energy distribution, contrary to the recent assertion of the HESS group. Our analysis indicates that 1ES0229+200 has a very hard intrinsic spectrum with a spectral index between 1.1 +/- 0.3 and 1.5 0.3 in the energy range between 0.5 TeV and 15 TeV. Conclusions. Under the assumptions that (1) the models of Stecker et al. as derived from numerous detailed infrared observations are reasonable, and (2) spectral indexes in the range 1 < Gamma < 1.5 are obtainable from relativistic shock acceleration under the astrophysical conditions extant in blazar flares, the fits to the observations of 1ES0229+200 using our previous infrared spectral energy distributions are consistent with both the infrared and -ray observations. Our analysis presents evidence indicating that the energy spectrum of relativistic particles in 1ES0229+200 is produced by relativistic shock acceleration, producing an intrinsic gamma-ray spectrum with index 1 < Gamma < 1.5 and with no evidence of a peak in the spectral energy distribution up to energies approximately 15 TeV.

Stecker, F. W.↗
NASA NTRS2023

Robustness of Gridded Precipitation Products for Vietnam Basins using the Comprehensive Assessment Framework of Rainfall

The use of satellite–based precipitation products (SPPs) have become increasingly prevalent as key inputs to provide regional rainfall for improving hydrological simulations in data–spare regions. This study introduces a new approach – Comprehensive Assessment Framework of Rainfall (CAFR) to evaluate six satellite–based precipitation products (SPPs) for eleven basins with different sizes across Vietnam (2007–2015). These SPPs include the Global Precipitation Mission (GPM) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final run Version 6 (GPM IMERGF V6), Multi–Source Weighted–Ensemble Precipitation (MSWEP) V2.2, Soil Moisture to Rain (SM2RAIN) – Advanced SCATterometer (ASCAT) V1.5, Asian Precipitation–Highly–Resolved Observational Data Integration Towards Evaluation (APHRODITE) V1901, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) V2.0, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) – Climate Data Record (CDR) V1.0. With the proposed CAFR: (1) IMERGF is suggested to have the best performance overall, especially when simulating flood peaks; (2) SM2RAIN–ASCAT demonstrates the best skills in metrics related to the dry season; (3) For streamflow simulations, SPPs' performance is sensitive to basin size, with larger basins showing better performance skills. In this study, we demonstrate the capability of our proposed framework to better understand SPP applications in hydrological modeling.

Comprehensive Assessment Framework of Rainfall (CA↗
NASA NTRS1972

Dynamical behavior of the polar topside ionosphere.

A review is given of magnetospheric interactions with the polar ionosphere using recent experimental and theoretical results. The effect of the polar wind is discussed with reference to the observational data of J. Hoffman. These and the results of other experiments support the concept of polar wind ion flows as a general feature of the topside ionosphere for all regions outside the plasmasphere. It is shown that most of the semi-permanent topside density features result from changes in plasma temperature and F2-region effects rather than being associated with changes in ion composition. Finally, the polar peak density enhancement is discussed in terms of recent observations of the polar cusp.

Banks, P. M.↗
NASA NTRS1983

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗