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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗
NASA NTRS1992

Modeling solar coronal streamers

Coronal streamer models must now make the transition from research projects to applications tools. SOHO (Solar and Heliospheric Observatory) will be making measurements on plasma parameters in and around streamers and a quantitative model will be required for interpreting the data. The reason for this is that a streamer is inherently a magnetohydrodynamic phenomenon; its properties are determined both by the magnetic field and the dynamics of the plasma. The purpose of the model will be to analyze the energetics of the streamer and place the results into the context of the magnetic field. Current streamer modeling, and why it has taken so long for these models to develop into useful tools, is described and indications on where further development is needed, are given.

Suess, Steven T.↗
NASA NTRS1994

Modeling actions and operations to support mission preparation

This paper describes two linked technology development projects to support Space Shuttle ground operations personnel, both during mission preparation analysis and related analyses in missions. The Space Propulsion Robust Analysis Tool (SPRAT) will provide intelligent support and automation for mission analysis setup, interpretation, reporting and documentation. SPRAT models the actions taken by flight support personnel during mission preparation and uses this model to generate an action plan. CONFIG will provide intelligent automation for procedure analyses and failure impact analyses, by simulating the interactions between operations and systems with embedded failures. CONFIG models the actions taken by crew during space vehicle malfunctions and simulates how the planned action sequences in procedures affect a device model. Jointly the SPRAT and CONFIG projects provide an opportunity to investigate how the nature of a task affects the representation of actions, and to determine a more general action representation supporting a broad range of tasks. This paper describes the problems in representing actions for mission preparation and their relation to planning and scheduling.

Malin, Jane T.↗
NASA NTRS2021

Photoionization Models for High Density Gas

Relativistically broadened and redshifted 6.4 – 6.9 keV iron K lines are observed from many accretion powered objects, including X-ray binaries and active galactic nuclei(AGN). Existence of gas close to the central engine implies large radiation intensities and correspondingly large gas densities if the gas is to remain partially ionized. Simple estimates indicate that high gas densities are needed to allow survival of iron against ionization. These are high enough that rates for many atomic processes are affected by mechanisms related to interactions with nearby ions and electrons. Radiation intensities are high enough that stimulated processes can be important. Most models currently in use for interpreting relativistic lines use atomic rate coefficients designed for use at low densities and neglect stimulated processes. In our work so far we have presented atomic structure calculations with the goal of providing physically appropriate models at densities consistent with line-emitting gas near compact objects. In this paper we apply these rates to photoionization calculations, and produce ionization balance curves and X-ray emissivities and opacities which are appropriate for high densities and high radiation intensities. The final step in our program will be presented in a subsequent paper: Model atmosphere calculations which incorporate these rates into synthetic spectra.

T Kallman↗
DOE OSTI2021

Search for dark matter produced in association with a leptonically decaying Z boson in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search for dark matter particles is performed using events with a Z boson candidate and large missing transverse momentum. The analysis is based on proton–proton collision data at a center-of-mass energy of 13$\,\text {Te}\text {V}$, collected by the CMS experiment at the LHC in 2016–2018, corresponding to an integrated luminosity of 137$\,\text {fb}^{-1}$. The search uses the decay channels ${\mathrm{Z}} \rightarrow {\mathrm{e}} {\mathrm{e}} $ and ${\mathrm{Z}} \rightarrow {{\upmu }{}{}} {{\upmu }{}{}} $. No significant excess of events is observed over the background expected from the standard model. Limits are set on dark matter particle production in the context of simplified models with vector, axial-vector, scalar, and pseudoscalar mediators, as well as on a two-Higgs-doublet model with an additional pseudoscalar mediator. In addition, limits are provided for spin-dependent and spin-independent scattering cross sections and are compared to those from direct-detection experiments. The results are also interpreted in the context of models of invisible Higgs boson decays, unparticles, and large extra dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1996

Interpretation of lidar and satellite data sets using a global photochemical model

The status in the beginning of the report period was that the existing General Circulation Model (GCM) was running with a chemistry module compiled for stratospheric simulation studies. The chemistry simulation was not working sufficiently in the troposphere and any tropospheric trace gas sources or dry deposition sinks were not yet incorporated. The current status concerning the chemistry module is that the chemistry simulation has been modified to also simulate the chemistry in the troposphere with resulting mixing ratios close to other model simulations as described in Olson et al. (1996). The mechanism to incorporate trace gas source and dry deposition sinks, testing for H202, CH300H, 03, HCHO, HN03, and N02, are incorporated and is currently being tested. Existing model and development versions include: the full GCM model, currently still running with the original stratospheric chemistry module; an off-line version of the GCM, i.e. wind and photolysis rates are pre-calculated and prescribed in read-in arrays; a box model version of the modified chemistry module for developments and first tests of new modifications; and a box model with the same chemistry simulated but flexible partitioning and integration methods for test purposes of those. The grantee's work focused mainly on three areas: trace gas sources and dry deposition; method to introduce a NO source instead of a NO(x) source; and investigating integration methods.

Chyba, Thomas↗
DOE OSTI2026

Experimental protocol for phase 1 of the APARC QUOCA (QUasibiennial oscillation and Ozone Chemistry interactions in the Atmosphere) working group

The quasi-biennial oscillation (QBO) is the main mode of variability in the tropical stratosphere, influencing the predictability of other regions in the atmosphere through its teleconnections to the stratospheric polar vortices and coupling to surface tropical and extratropical variability. However, climate and forecasting models consistently underestimate QBO amplitudes in the lower stratosphere, likely contributing to their failure to simulate these teleconnections. One underexplored contributor to model biases is missing representation of ozone-radiative feedbacks, which enhance temperature variability in the lower stratosphere, particularly at periods at and greater than the QBO (>28 months). While previous studies suggest that ozone-radiative feedbacks can impact QBO periods, amplitudes and the associated secondary circulation in the lower stratosphere, the reported impacts differ widely among models and are hard to interpret due to differences in methodology. To this end, here we propose a coordinated experimental protocol – held joint between the Atmospheric Processes and their Role in Climate (APARC) Quasi-Biennial Oscillation Initiative (QBOi) and Chemistry Climate Modeling Initiative (CCMI) activities – which is aimed at assessing the coupling between stratospheric ozone, temperature and the circulation. We use the proposed experiments to define the ozone feedback on the QBO in both present-day and idealized (abrupt quadrupling of carbon dioxide) climates. While primary focus is on the QBO, the proposed protocol also enables analysis of other aspects of ozone-radiative-dynamical coupling in the atmosphere, including impacts on the Brewer-Dobson Circulation and tropospheric eddy-driven jet responses to future climate change. Here we document the scientific rationale and design of the QUOCA Phase 1 experiments, summarize the data request, and give a brief overview of participating models. Preliminary results using the NASA Goddard Institute for Space Studies E2-2 climate model are used to illustrate sensitivities to certain methodological choices.

Environmental sciences↗
NASA NTRS2009

Modeling of the 22 July 2009 Storm

The magnetic storm on 22 July 2009 is the greatest storm observed since the summer of 2008 when TWINS began its stereo imaging of the magnetosphere, On 22 July 2009, the Dst dropped to nearly -80 nT at 07:00 and 10:00 UT. During the main phase and at the peak of the storm, TWINS 1 and 2 were near apogee and moving from pre-dawn to post-dawn local time. The energetic neutral atom (ENA) Imagers on the 2 spacecraft captured the storm intensification and the formation of the partial ring current. The development of this storm has been simulated using the Comprehensive Ring Current Model (CRCM) to understand and interpret the observed signatures. The CRCM reproduced the double-dip in the Dst index and the simulated ENA flux intensities agree very well with the TWINS images. However, the peak of ion flux predicted by the model is always eastward of the observed maximum by TWINS. This discrepancy posts a challenge to reexamine the physical models employed in the CRCM.

Fok, Mei-Ching↗
DOE OSTI2025

Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification

Critical heat flux (CHF) is a key quantity in nuclear system modeling due to its impact on heat transfer, safety margins, and reactor performance. This study develops and validates an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models to predict CHF in cases of dryout. The Biasi and Bowring empirical correlations were paired with three ML uncertainty quantification (UQ) techniques: deep neural network (DNN) ensembles, Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). A pure ML model without a base model was evaluated for comparison. Model performance was assessed under plentiful (7,350 points) and limited (9 points) training data scenarios using parity, uncertainty distributions, and calibration curves. Results show that the Biasi hybrid DNN ensemble achieved the best overall performance, with a mean absolute relative error of 1.846%, and well-calibrated uncertainty estimates. The BNN-based hybrids showed slightly higher error (2.14%) but superior uncertainty calibration. DGP models underperformed, with over 6% error and poor uncertainty calibration. All hybrid models outperformed pure machine learning configurations, demonstrating resistance against data scarcity. These findings indicate that hybrid modeling significantly improves predictive accuracy, interpretability, and resilience to data scarcity. The integration of uncertainty awareness provides actionable confidence in CHF predictions, which is vital for safety-critical decisions in nuclear applications. This hybrid approach offers a viable pathway for deploying ML models in reactor analysis tools while preserving domain knowledge and physical consistency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Correlation function studies for snow and ice

The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

Vallese, F.↗
NASA NTRS2022

The extended atmosphere and circumstellar environment of the cool evolved star VX Sagittarii as seen by MATISSE

Context. VX Sgr is a cool, evolved, and luminous red star whose stellar parameters are difficult to determine, which affects its classification. Aims. We aim to spatially resolve the photospheric extent as well as the circumstellar environment. Methods. We used interferometric observations obtained with the MATISSE instrument in the L (3–4 μm), M (4.5–5 μm), and N (8–13 μm) bands. We reconstructed monochromatic images using the MIRA software. We used 3D radiation-hydrodynamics simulations carried out with CO5BOLD and a uniform disc model to estimate the apparent diameter and interpret the stellar surface structures. Moreover, we employed the radiative transfer codes OPTIM3D and RADMC3D to compute the spectral energy distribution for the L, M, and N bands, respectively. Results. MATISSE observations unveil, for the first time, the morphology of VX Sgr across the L, M, and N bands. The reconstructed images show a complex morphology with brighter areas whose characteristics depend on the wavelength probed. We measured the angular diameter as a function of the wavelength and showed that the photospheric extent in the L and M bands depends on the opacity through the atmosphere. In addition to this, we also concluded that the observed photospheric inhomogeneities can be interpreted as convection-related surface structures. The comparison in the N band yielded a qualitative agreement between the N-band spectrum and simple dust radiative transfer simulations. However, it is not possible to firmly conclude on the interpretation of the current data because of the difficulty in constraing the model parameters using the limited accuracy of our absolute flux calibration. Conclusions. MATISSE observations and the derived reconstructed images unveil the appearance of VX Sgr’s stellar surface and circumstellar environment across a very large spectral domain for the first time.

stars: atmospheres↗
NASA NTRS1984

Spectral formation in compact X-ray sources

The gas flows responsible for X-ray spectral emission in compact X-ray sources are complex and likely to be optically thick. In galactic sources these flows include: stellar wind, accretion disk and corona, magnetosphere, and shock at the compact object surface. Active galactic nuclei are surrounded by many dense clouds responsible for the broad optical and UV emission lines. The nature of these flows can be discovered through observations of their X-ray spectra and time variability. Theoretical models for the formation of line and continuum spectra in these sources are described, emphasizing atomic photoabsorption, line emission, and Comptonization. Current observations of X-ray and UV spectra of compact galactic sources and active galactic nuclei are interpreted in terms of these models. Great advances in the understanding of these systems will result from future missions capable of observing their spectra at higher resolution. Observations of the complex of iron K-alpha lines at 6.4-6.7 keV will be particularly valuable.

Mccray, R.↗
NASA NTRS2012

A Quantum Band Model of the nu3 Fundamental of Methanol (CH3OH) and Its Application to Fluorcescence Spectra of Comets

Methanol (CH3OH) radiates efficiently at infrared wavelengths, dominating the C-H stretching region in comets, yet inadequate quantum-mechanical models have imposed limits on the practical use of its emission spectra. Accordingly, we constructed a new line-by-line model for the 3 fundamental band of methanol at 2844 / cm (3.52 micron) and applied it to interpret cometary fluorescence spectra. The new model permits accurate synthesis of line-by-line spectra for a wide range of rotational temperatures, ranging from 10 K to more than 400 K.We validated the model by comparing simulations of CH3OH fluorescent emission with measured spectra of three comets (C/2001 A2 LINEAR, C/2004 Q2 Machholz and 8P/Tuttle) acquired with high-resolution infrared spectrometers at high-altitude sites. The new model accurately describes the complex emission spectrum of the nu3 band, providing distinct rotational temperatures and production rates at greatly improved confidence levels compared with results derived from earlier fluorescence models. The new model reconciles production rates measured at infrared and radio wavelengths in C/2001 A2 (LINEAR). Methanol can now be quantified with unprecedented precision and accuracy in astrophysical sources through high-dispersion spectroscopy at infrared wavelengths

Villanueva, Geronimo L.↗
DOE OSTI2025

Structural Evolution of the Hogback Monocline and Its Tectonic Significance in the San Juan Basin

The San Juan Basin is recognized as a Laramide foreland basin. It is located within the Colorado Plateau, a broad tectonic province characterized by a thick sedimentary sequence that was segmented into smaller sub basins during the Late Cretaceous to Paleogene Laramide orogeny. The Hogback Monocline lies along the northwestern margin of the San Juan Basin and is considered a Laramide-age structure formed in response to compressional stress. In this study, we interpret surface and subsurface datasets to construct a structural geological model and evaluate its tectonic significance. Through seismic data, we identify key fault and fold geometries at depth. The seismic dataset used in this study was reprocessed in depth and constrained with well log velocity data to enhance seismic imaging quality. Additionally, we performed well log correlations to identify formation tops and assess variations in basin infill and thickness geometry. A series of structural cross-sections, constructed using seismic data and a high density of boreholes, are presented to evaluate geometric variations along the structure and its evolution during basin development. Furthermore, kinematic restoration and forward modeling analyses were conducted to validate our structural interpretation. This work suggests that the Hogback Monocline formed through fault-propagation folding and flexural slip affecting the pre-Laramide sedimentary sequence under compressional stresses associated with the Laramide orogeny. This structure is interpreted as a high-angle reverse fault that influenced the geometry of the late basin infill. Additionally, monocline bending along the structure may have been controlled by fault relay systems and, in some cases, influenced by strike-slip faulting.

Reyes, Martin [New Mexico Bureau o fGeology and Mi↗
NASA NTRS1991

A drag measurement technique for free piston shock tunnels

A new technique is described for measuring drag with 100-microsecond rise time on a nonlifting model in a free piston shock tunnel. The technique involves interpretation of the stress waves propagating within the model and its support. A finite element representation and spectral methods are used to obtain a mean square optimal estimate of the time history of the aerodynamic loading. Thus, drag is measured instantaneously and the previous restriction caused by the mechanical time constant of balances is overcome. The effectiveness of the balance is demonstrated by measuring the drag on cones with 5 and 15 deg semi-vertex angles in nominally Mach 5.6 flow with stagnation enthalpies from 2.6 to 33 MJ/kg.

Sanderson, S. R.↗
DOE OSTI2024

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH 4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH 4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH 4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH 4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH 4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

Environmental Sciences & Ecology↗
DOE OSTI2024

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 5: Utah FORGE Well 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗