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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

RESOLVING THE CO SNOW LINE IN THE DISK AROUND HD 163296

We report Submillimeter Array observations of CO (J = 2-1, 3-2, and 6-5) and its isotopologues ({sup 13}CO J = 2-1, C{sup 18}O J = 2-1, and C{sup 17}O J = 3-2) in the disk around the Herbig Ae star HD 163296 at {approx}2'' (250 AU) resolution, and interpret these data in the framework of a model that constrains the radial and vertical location of the line emission regions. First, we develop a physically self-consistent accretion disk model with an exponentially tapered edge that matches the spectral energy distribution and spatially resolved millimeter dust continuum emission. Then, we refine the vertical structure of the model using wide range of excitation conditions sampled by the CO lines, in particular the rarely observed J = 6-5 transition. By fitting {sup 13}CO data in this structure, we further constrain the vertical distribution of CO to lie between a lower boundary below which CO freezes out onto dust grains (T {approx}< 19 K) and an upper boundary above which CO can be photodissociated (the hydrogen column density from the disk surface is {approx}< 10{sup 21} cm{sup -2}). The freezeout at 19 K leads to a significant drop in the gas-phase CO column density beyond a radius of {approx}155 AU, a 'CO snow line' that we directly resolve. By fitting the abundances of all CO isotopologues, we derive isotopic ratios of {sup 12}C/{sup 13}C, {sup 16}O/{sup 18}O, and {sup 18}O/{sup 17}O that are consistent with quiescent interstellar gas-phase values. This detailed model of the HD 163296 disk demonstrates the potential of a staged, parametric technique for constructing unified gas and dust structure models and constraining the distribution of molecular abundances using resolved multi-transition, multi-isotope observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Laser-to-hot-electron conversion limitations in relativistic laser matter interactions due to multi-picosecond dynamics

High-energy short-pulse lasers are pushing the limits of plasma-based particle acceleration, x-ray generation, and high-harmonic generation by creating strong electromagnetic fields at the laser focus where electrons are being accelerated to relativistic velocities. Understanding the relativistic electron dynamics is key for an accurate interpretation of measurements. We present a unified and self-consistent modeling approach in quantitative agreement with measurements and differing trends across multiple target types acquired from two separate laser systems, which differ only in their nanosecond to picosecond-scale rising edge. Insights from high-fidelity modeling of laser-plasma interaction demonstrate that the ps-scale, orders of magnitude weaker rising edge of the main pulse measurably alters target evolution and relativistic electron generation compared to idealized pulse shapes. This can lead for instance to the experimentally observed difference between 45 MeV and 75 MeV maximum energy protons for two nominally identical laser shots, due to ps-scale prepulse variations. Our results indicate that the realistic inclusion of temporal laser pulse profiles in modeling efforts is required if predictive capability and extrapolation are sought for future target and laser designs or for other relativistic laser ion acceleration schemes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage (Task 5 Report Field Scale Stress Modeling)

This report describes research accomplishments achieved with funding provided through Department of Energy (DOE) Contract DE-FE0031686, for the project “A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage.” The purpose of this DOE funding is to develop non-invasive methods to obtain important information about subsurface stresses. The overall research goal of the project was to develop and improve methods for determining the spatial distribution of stresses, including magnitude and orientation of the three principal stress components in the subsurface, based on new methods that extract stress information from seismic data combined with well measurements, extended with well tests and logs, and unified in a numerical model that permits computation of the full stress tensor throughout the domains under investigation.

58 GEOSCIENCES↗
DOE OSTI2010

B{sub s(d)}-B{sub s(d)} mixing constraints on flavor changing decays of t and b quarks

We study those dimension 6 effective operators which generate flavor-changing quark-gluon transitions of the third generation quarks, with t{yields}g+u(c) and b{yields}g+d(s), and which could be of interest for LHC experiments. We analyze the contribution of these operators to B{sub s(d)}-B{sub s(d)} mixing and derive limits on the corresponding effective couplings from the existing experimental data. The standard model gauge invariance relates these couplings to the couplings controlling t{yields}g+u(c). On this basis we derive upper limits for the branching ratios of these processes. We further show that forthcoming LHC experiments might be able to probe the studied operators and the physics beyond the standard model related to them.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2010

CP violation makes left-right symmetric extensions with non-Hermitian mass matrices appear unnatural

Following a similar recent analysis for CP violation in the electroweak sector of the standard model, we estimate the naturalness of a magnitude of CP violation (measured by the Jarlskog invariant J) close to the observed value in extensions of the standard model with left-right symmetry, such as the Pati-Salam model, where quark mass matrices are not Hermitian in general. We construct a simple and natural measure on the space of complex matrices which is both geometrically motivated and uses the observed quark mass hierarchy. We find that, unlike in the case of the standard model where the observed value for J seemed rather typical, one would now expect to observe |J|<10{sup -7}, clearly in conflict with the observed value J{approx_equal}3x10{sup -5}. The crucial difference in the calculation lies in the non-Hermiticity of mass matrices that modifies the measure. We conclude that one would need additional assumptions modifying the measure to reproduce the observed value, and that in this sense the standard model is preferred to certain classes of left-right symmetric extensions: It does not need additional assumptions to explain the magnitude of CP violation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2001

Toward a Unified Parameterization of the Boundary Layer and Moist Convection: A New Type of Mass-Flux Model - Part 1

Higher-order closure (HOC) models have been proposed for parameterization of the turbulent planetary boundary layer (PBL). HOC models must include closures for higher-order moments (e.g., fourth moments in third-order closure models), for pressure terms, and for dissipation terms. Mass-flux closure (MFC) models have been proposed for parameterization of cumulus convection and, more recently, the convective PBL. MFC models include closures for lateral mass exchanges and for pressure terms (which are usually ignored). The authors developed a new kind of model that combines HOC and MFC, which they hope will be useful for the parameterization of both the PBL and cumulus convection, in a unified framework. Such a model is particularly well suited to regimes in which the PBL turbulence and the cumulus convection are not well separated, for example, the broken stratocumulus and shallow cumulus regimes. The model makes use of an assumed joint probability distribution for the variables of interest, and the equations typically used in HOC models can be derived by integrating over the distribution. Accordingly, the model is called Assumed-Distribution Higher-Order Closure (ADHOC). The prognostic variables of ADHOC are the mean state, the second and third moments of the vertical velocity, and the vertical fluxes of other quantities of interest. All of the parameters of the distribution can be determined from the predicted moments, thereafter the joint distribution is effectively known, and so any and all moments can be constructed as needed. In this way, the usual closure problem of "higher moments" is avoided. The pressure-term parameterizations previously developed for HOC models are used to predict the convective fluxes and the moments of the vertical velocity. In companion papers, parameterizations of lateral mass exchanges and subplume-scale fluxes are presented, and then ADHOC is applied to several observationally based tropical, subtropical, and dry convective boundary layers.

Lappen, Cara-Lyn↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electromagnetic and two-photon transition form factors of the pseudoscalar mesons: An algebraic model computation

We compute electromagnetic and two-photon transition form factors of ground-state pseudoscalar mesons: π , K , η c , η b . To this end, we employ an algebraic model based upon the coupled formalism of Schwinger-Dyson and Bethe-Salpeter equations. Within this approach, the dressed quark propagator and the relevant Bethe-Salpeter amplitude encode the internal structure of the corresponding meson. Electromagnetic properties of the meson are probed via the quark-photon interaction. The algebraic model employed by us unifies the treatment of all ground-state pseudoscalar mesons. Its parameters are carefully fitted performing a global analysis of existing experimental data including the knowledge of the charge radii of the mesons studied. We then compute and predict electromagnetic and two-photon transition form factors for a wide range of probing photon momentum-squared which is of direct relevance to the experimental observations carried out thus far or planned at different hadron physics facilities such as the Thomas Jefferson National Accelerator Facility (JLab) and the forthcoming Electron-Ion Collider. We also present comparisons with other theoretical models and approaches and lattice quantum chromodynamics. Published by the American Physical Society 2024

Higuera-Angulo, I. M. (ORCID:0000000256008875)↗
DOE OSTI2015

Dynamics of gauge field inflation

We analyze the existence and stability of dynamical attractor solutions for cosmological inflation driven by the coupling between fermions and a gauge field. Assuming a spatially homogeneous and isotropic gauge field and fermion current, the interacting fermion equation of motion reduces to that of a free fermion up to a phase shift. Consistency of the model is ensured via the Stückelberg mechanism. We prove the existence of exactly one stable solution, and demonstrate the stability numerically. Inflation arises without fine tuning, and does not require postulating any effective potential or non-standard coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Applying Model Based Systems Engineering to NASA's Space Communications Networks

System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.

Bhasin, Kul↗
DOE OSTI2020

Accelerating Finite-temperature Kohn-Sham Density Functional Theory\ with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electrochemical Modeling of PID Leakage Current of PV Modules: Steady-State Current, Transient Current, and RC-Equivalent Circuit

Potential-induced degradation (PID) remains a significant reliability concern for photovoltaic (PV) modules, arising when a voltage difference between the module frame and the solar cells drives unintended leakage current through the glass-encapsulant stack. Although PID ultimately manifests as PID-s, PID-p, or PID-c, the underlying behavior of the leakage current-its magnitude and time dependence-requires clearer electrochemical interpretation. Traditional explanations attribute the initial transient current to bulk capacitive elements of the glass, encapsulant, and antireflection coatings, and the steady-state current according to their effective ohmic resistance. More recent studies, however, indicate that electrochemical charge-transfer processes at the encapsulant-metallization interface can play a dominant role in defining the leakage-current path. This paper develops a unified electrochemical framework for modeling PID leakage current. First, an RC-equivalent circuit is formulated by combining conventional RC elements with a Randles-type interface to capture transient leakage current through double-layer capacitance and faradaic processes at ionic-electronic boundaries. Second, the steady-state current-voltage behavior is explained using a linearized Butler-Volmer relationship, showing that the measured ohmic response corresponds to the low-overpotential limit of charge-transfer kinetics. Analytical results demonstrate that, for typical module materials-3.2-mm soda-lime glass and 0.45-mm encapsulant-the dominant modulators to PID leakage current are the glass surface resistance (under dry-surface conditions), the glass bulk capacitance, and the encapsulant resistance (under wet-surface conditions), with soda lime glass surface and EVA/POE encapsulant resistances primarily governing steady-state current. The proposed electrochemical model is validated against measured leakage-current data, showing good agreement in both the magnitude and the time-dependent evolution of PID leakage current.

14 SOLAR ENERGY↗
DOE OSTI2011

Discussing direct search of dark matter particles in the minimal supersymmetric extension of the standard model with light neutralinos

We examine the status of light neutralinos in an effective minimal supersymmetric extension of the standard model at the electroweak scale which was considered in the past and discussed in terms of the available data of direct searches for dark matter particles. Our reanalysis is prompted by new measurements at the Tevatron and B factories which might potentially provide significant constraints on the minimal supersymmetric extension of the standard model. Here we examine in detail all these new data and show that the present published results from the Tevatron and B factories have only a mild effect on the original light-neutralino population. This population, which fits quite well the DAMA/LIBRA annual modulation data, would also agree with the preliminary results of CDMS, CoGeNT, and CRESST, should these data, which are at present only hints of excesses of events over the expected backgrounds, be interpreted as authentic signals of dark matter. For the neutralino mass we find a lower bound of 7-8 GeV. Our results differ from some recent conclusions by other authors because of a few crucial points which we try to single out and elucidate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Double Pomeron Exchange: from the ISR to the LHC

I discuss Double Pomeron Exchange processes from their first observation at the CERN Intersecting Storage Rings, focusing on glueball searches, through the observations of exclusive {chi}{sub c0},{gamma}{gamma} and di-jets at the Tevatron, to prospects at the LHC for exclusive Higgs boson production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

P and T Violating Form Factors of the Deuteron

We calculate the electric-dipole and magnetic-quadrupole form factors of the deuteron that arise as a low-energy manifestation of parity and time-reversal violation in quark-gluon interactions. We consider the QCD vacuum angle and the dimension-six operators that originate from physics beyond the standard model: the quark electric and chromoelectric dipole moments and the gluon chromoelectric dipole moment. Within the framework of two-flavor chiral perturbation theory, we show that in combination with the nucleon electric dipole moment, the deuteron moments would allow an identification of the dominant source(s) of symmetry violation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Methodology for assessing the safety of Hydrogen Systems: HyRAM 1.1 technical reference manual

The HyRAM software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM is designed to facilitate the use of state-of-the-art science and engineering models to conduct robust, repeatable assessments of hydrogen safety, hazards, and risk. HyRAM is envisioned as a unifying platform combining validated, analytical models of hydrogen behavior, a stan- dardized, transparent QRA approach, and engineering models and generic data for hydrogen installations. HyRAM is being developed at Sandia National Laboratories for the U. S. De- partment of Energy to increase access to technical data about hydrogen safety and to enable the use of that data to support development and revision of national and international codes and standards. This document provides a description of the methodology and models contained in the HyRAM version 1.1. HyRAM 1.1 includes generic probabilities for hydrogen equipment fail- ures, probabilistic models for the impact of heat flux on humans and structures, and computa- tionally and experimentally validated analytical and first order models of hydrogen release and flame physics. HyRAM 1.1 integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing hydrogen hazards (thermal effects from jet fires, overpressure effects from deflagrations), and assessing impact on people and structures. HyRAM is a prototype software in active development and thus the models and data may change. This report will be updated at appropriate developmental intervals.

97 MATHEMATICS AND COMPUTING↗