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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

The discovery of an O subdwarf in the globular cluster NGC 6712

Spectral data for C49 in the globular cluster NGC 6712 are examined with reference to evolutionary models for low-mass stars that are contracting into white dwarfs. The spectrum of this star is found to be almost identical to that of the first sdO star found in a globular cluster, star A in NGC 6397. Analysis of the spectral data using nonlocal thermodynamic equilibrium models gives surface parameters T not less than 50,000 K, log g = 5.5 plus or minus 0.5, and N(He)/N(H) approximately equal to 0.1. The results are consistent with the models considered.

Remillard, R. A.↗
DOE OSTI2025

DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving

Time-Independent Differential Equations (TIDEs) are central to modeling equilibrium behavior across a wide range of scientific and engineering domains, from electrostatics to porous media flow. Conventional numerical solvers offer reliable solutions but incur significant computational costs due to fine-grained discretization and iterative procedures. Machine learning-based approaches address this by replacing iterative solving processes with one-time inference; however, their sophisticated models require extensive training resources that often exceed those of traditional solvers. Consequently, designing a TIDE solver that achieves high accuracy, broad applicability, and exceptional computational efficiency remains a fundamental challenge. In this paper, we propose DS-TIDE, a novel hardware solver that is inspired by, and subsequently leverages, the intrinsic connection between Dynamical Systems (DS) and Differential Equations (DEs) to efficiently and accurately solve TIDEs. DS-TIDE employs a CMOS-compatible DS-based processor, whose physical states evolve under carefully designed DE-driven dynamics and naturally converge to equilibrium -- the solution of the target TIDE -- within ~1µs on a ~1-watt DS-TIDE processor. To enhance expressivity, DS-TIDE incorporates Heterogeneous Dynamics with Temporal Layering (HDTL), which solves TIDEs through a three-stage DS evolution -- conditioning, solving, and decoding -- each governed by specialized dynamics. The entire evolution process is analogous to an infinitely deep neural network temporally unrolled, offering the system the capability of representing complex equations. Furthermore, DS-TIDE is equipped with an on-device DS-DE Auto-Alignment mechanism that dynamically adapts intrinsic hardware dynamics within milliseconds, effectively aligning the system’s dynamics to diverse target DEs. Experimental results across TIDEs from a wide range of scientific and engineering domains demonstrate that DS-TIDE achieves ~10^3× speedup, ~10^5× energy savings, and competitive or superior accuracy compared to state-of-the-art numerical and ML-based solvers.

Liu, Chuan↗
DOE OSTI2026

Nonequilibrium universality of the nonreciprocally coupled 𝑂⁡(𝑛 1 ) × 𝑂⁡(𝑛 2 ) model

Nonequilibrium dynamics play an important role in all contexts of physics, both classical and quantum as well as living and nonliving, so it is crucial to develop a foundational understanding of nonequilibrium phase transitions. In this work we investigate an important class of nonequilibrium dynamics in the form of nonreciprocal interactions. In particular we study how nonreciprocal coupling between two 𝑂⁡(𝑛𝑖) order parameters (with 𝑖 = 1,2) affects the universality at a multicritical point, extending the analysis of J. T. Young et al. [Phys. Rev. X 10, 011039 (2020)], which considered the case 𝑛 1 = 𝑛 2 = 1, i.e., a ℤ 2 × ℤ 2 model. We show that nonequilibrium fixed points (NEFPs) emerge for a broad range of 𝑛 1 ,𝑛 2 and exhibit intrinsically nonequilibrium critical phenomena, namely a violation of fluctuation-dissipation relations at all scales and underdamped oscillations near criticality in contrast to the overdamped relaxational dynamics of the corresponding equilibrium models. Furthermore, the NEFPs exhibit an emergent discrete scale invariance in certain physically relevant regimes of 𝑛 1 ,𝑛 2 , but not others, depending on whether the critical exponent 𝜈 is real or complex. The boundary between these two regions is described by an exceptional point in the renormalization group (RG) flow, leading to distinctive features in correlation functions and the phase diagram. Another contrast with the previous work is the number and stability of the NEFPs as well as the underlying topology of the RG flow. Lastly, we investigate an extreme form of nonreciprocity where one order parameter is independent of the other order parameter but not vice versa. Unlike the ℤ 2 × ℤ 2 model, which becomes nonperturbative in this case, we identify a distinct nonequilibrium universality class whose dependent field similarly violates fluctuation-dissipation relations but does not exhibit discrete scale invariance or underdamped oscillations near criticality.

Critical phenomena↗
DOE OSTI2021

Thermal effects mediating the flow induced by laser-induced optical breakdown

Here, a short focused laser pulse can generate a hot plasma, which expands then contracts and can eject a hot jet, the speed and direction of which is sensitive to the details of the plasma kernel. The coupling of thermal and chemical nonequilibrium plasma mechanisms with this hydrodynamic development is assessed with detailed simulations of a two-temperature, three-species plasma model. Time scales for electron recombination, thermal relaxation, and diffusion are compared to that of the plasma expansion to anticipate conditions in which these mechanisms might affect the vorticity generation that leads to the ultimate flow pattern. The effect of these mechanisms are analyzed through comparison with corresponding inert-gas and equilibrium models. Thermal-nonequilibrium effects are found to be weak due to rapid relaxation of the heavy-particle and electronic temperatures. In contrast, chemical equilibration occurs at a rate comparable to the expansion and thereby enhance both it and subsequent hydrodynamic mechanisms as the energy stored in ion formation during the preceding breakdown is released by electron recombination. Thermal conduction, enhanced by high-temperature free electrons, weakens the ejection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Development of Explainable, Knowledge-Guided AI Models to Enhance the E3SM Land Model Development and Uncertainty Quantification

Focal Area(s): (2)Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models. (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge- guided AI. Science Challenge: The Energy Exascale Earth System Model (E3SM) is a fully coupled, state-of-the-science Earth system model that uses code optimized for DOE's advanced computers to address the most critical scientific questions facing our nation and society (Golaz et al., 2019). The E3SM Land model (ELM) is designed to understand how the changes in terrestrial land surfaces will interact with other Earth system components and has been used to understand hydrologic cycles, biogeophysics, and ecosystem dynamics. In spite of great successes, the ELM has several known issues that restrain rapid improvements. For example, the ELM uses equilibrium models to simulate dynamic land-climate interactions and it requires long model spin-up time to identify suitable initial conditions for transient simulations. The ELM lacks built-in uncertainty mechanisms that can improve the robustness of model predictions. The ELM is a holistic, deterministic model system with a rigid design, and in many situations, it is hard to modify the ELM system to incorporate new theory/hypothesis and new data across scales to address emerging science problems (such as predicting the impacts of water cycle extremes). In addition, The ELM is technically optimized for traditional CPU-centric computers and it cannot fully utilize the current and incoming leadership computers for model simulations and uncertainty quantification (UQ). The success of artificial intelligence (AI) has inspired scientists to use AI models to discover intrinsic features from simulation data (Chattopadhyay et al., 2020) and observational data (Reichstein et al., 2019) to gain further process understanding of Earth science problems. However, autonomous AI model training through deep learning usually requires a huge amount of annotated data. To overcome the limitations from the data and computing resources, knowledge-guided AI models are necessary where human-knowledge is ingested in model construction (Banino et al., 2018) and training process (Silver et al., 2016) for efficient learning. Herein, we present a new way that leverages the process understanding from the ELM to guide AI model development for the ELM enhancement and UQ. We hope this study can inspire further Earth and environmental system model developments and transformations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

Opacity probability distribution functions for electronic systems of CN and C2 molecules including their stellar isotopic forms.

The basis and techniques are presented for generating opacity probability distribution functions for the CN molecule (red and violet systems) and the C2 molecule (Swan, Phillips, Ballik-Ramsay systems), two of the more important diatomic molecules in the spectra of carbon stars, with a view to including these distribution functions in equilibrium model atmosphere calculations. Comparisons to the CO molecule are also shown. T he computation of the monochromatic absorption coefficient uses the most recent molecular data with revision of the oscillator strengths for some of the band systems. The total molecular stellar mass absorption coefficient is established through fifteen equations of molecular dissociation equilibrium to relate the distribution functions to each other on a per gram of stellar material basis.

Querci, F.↗
NASA NTRSDate not supplied

High-Fidelity Simulations of HyMETS Arc-Jet Flows for PICA-N Modeling

Arc-jet testing is a fundamental tool in the screening of thermal protection systems under atmospheric entry conditions. In this work, high-fidelity computational fluid dynamics simulations coupled with machine learning methods for the Hypersonic Materials Environmental Test System arc-jet facility have been carried out. This effort improves the MEDLI-2 data reconstruction fidelity by understanding the impact of the NuSil coating over the PICA thermocouple plugs. Thermochemical non-equilibrium models are employed to simulate the flows inside the arc-jet nozzle and chamber and machine learning techniques are used to calibrate the arc-jet inflow conditions. The material response is simulated with the recession and in-depth numerical results compared to experimental measurements.

STMD↗
DOE OSTI2020

Microsecond Molecular Dynamics Simulations of Proteins Using a Quasi-Equilibrium Solvation Shell Model

In this work, we describe the development and implementation of a quasi-equilibrium hydration shell model of biomolecular solvation with adaptive boundaries. Applying the model to microsecond-long molecular dynamics simulations of several protein systems of varying complexity, we find that the model simulation results are of comparable quality to those obtained from simulations of fully solvated systems, but at a reduced computational cost. We discuss the dominant sources of error in the model and outline directions for future improvements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

One-dimensional hybrid satellite track model for the Dynamics Explorer 2 (DE 2) satellite

A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. (1985) satellite track code but also includes elements of Roble et al. (1987b) global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the Mass Spectrometer Incoherent Scatter 1990 (MSIS-90) model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule heating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model calculations. A good agreement was found in lower thermospheric conductivities and Joule heating rate.

Deng, Wei↗
NASA NTRS1995

One-Dimensional Hybrid Satellite Track Model for the Dynamics Explorer 2 (DE 2) Satellite

A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. satellite track code but also includes elements of Roble et al. global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the MSIS-90 model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule beating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model calculations. A good agreement was found in lower thermospheric conductivities and Joule heating rate.

Deng, Wei↗
DOE OSTI2020

GCAM v4.3 SSP-RCP-GCM Output Products

Supplemental dataset to: Graham N.T., M.I. Hejazi, M. Chen, E. Davies, J.A. Edmonds, S.H. Kim, and S. Turner, et al. 2020. "Humans drive future water scarcity changes across all Shared Socioeconomic Pathways." Environmental Research Letters 15, no. 1:Article No. 014007. PNNL-SA-151297. doi:10.1088/1748-9326/ab639b This analysis makes deterministic classifications of how, when water resources are limited and constrained, the human and climate systems interact. The relative effects of both systems on water scarcity are quantified at global and basin scales across 15 global futures that include five different socioeconomic conditions (the Shared Socioeconomic Pathways, SSPs) and four different climatic conditions (the Representative Concentration Pathways, RCPs). These 15 scenarios are used to first analyze a 'Human Alone' component by isolating the human impact on future scarcity. This is accomplished by holding all climate variables to their 2005 levels while altering socioeconomic growth and technological change. General circulation model (GCM) derived climate impacts for five models are applied to establish 75 'Human and Climate' scenarios which allows for the quantification of climate impacts. Climatic impacts to water supply, agricultural productivity and change, hydropower availability, and building energy demands are applied from 5 different bias-corrected GCMs to make a suite of 75 climate runs. By subtracting the human derived impacts from the 'Human Alone' scenarios, from the 'Human and Climate' scenarios the climate impact is isolated. First, the drivers of future water scarcity are evaluated by isolating the impacts that both humans and climate have while accounting for feedbacks between humans, energy, and land. Secondly, the simultaneous impacts that human and climate systems have on water scarcity are analyzed by determining whether each system is increasing or decreasing scarcity in all global water basins. Below we describe the GCAM model, the scenario components, climate derived impacts, and the calculations of scarcity changes and attribution. This study uses the global change assessment model (GCAM), with inclusions of water constraints to both renewable and nonrenewable sources of water, to investigate the relative contributions of climate and human systems on water scarcity regionally and globally under a wide range of scenarios. GCAM links socioeconomics, the energy system, land-use change, climate, and the water sector. GCAM is a market-equilibrium model that allows for prices to be adjusted within each time step to ensure that the supply and demand of goods and services remains equilibrated at each time step allowing for simultaneous market clearing across sectors. This study accounts for a limited supply of water by employing cost resource curves across all 235 basins that follow a logit formulation to determine the share of each water source (renewable surface water, nonrenewable groundwater, and desalinated water) needed to meet the water demands within all basins. As depletion of various water sources increases the extraction price increases, which leads to compounding price increases on the goods and services that require higher-priced water sources.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Uncovering turbulent plasma dynamics via deep learning from partial observations

One of the most intensely studied aspects of magnetic confinement fusion is edge plasma turbulence which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied to model boundary plasmas with varying success. Towards better understanding edge turbulence in both theory and experiment, we demonstrate that a novel multi-network physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent with the two-fluid theory from partial observations of electron pressure which is not otherwise possible using conventional equilibrium models. Furthermore, this technique presents a novel paradigm for the advanced design of plasma diagnostics and validation of magnetized plasma turbulence theories in challenging thermonuclear environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Uncovering turbulent plasma dynamics via deep learning from partial observations

One of the most intensely studied aspects of magnetic confinement fusion is edge plasma turbulence which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied to model boundary plasmas with varying success. Towards better understanding edge turbulence in both theory and experiment, we demonstrate that a novel multi-network physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent with the two-fluid theory from partial observations of electron pressure which is not otherwise possible using conventional equilibrium models. This technique presents a novel paradigm for the advanced design of plasma diagnostics and validation of magnetized plasma turbulence theories in challenging thermonuclear environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2021

Assessment of Governing Heat and Mass Transfer Coefficients for Cryogenic No-Vent Top-Off Modeling

No-vent fill / no-vent top-off (NVF/NVTO) is a method to enable the trans-fer of cryogenic propellants without the need to vent. Transferring propellants inmicrogravity environments is necessary to support the long-duration space missionsplanned for the coming decades. A key developmental milestone to developing thiscapability fully is the simulation and experimentation of NVF/NVTO in 1-g settings.This work seeks to advance the former by assessing the effectiveness of different heattransfer correlations used in a 1-g non-equilibrium model. Heat transfer correlationsfor natural convection and two-phase boiling heat transfer are compared against ex-perimental results for 34 different tests. Two distinct experiments, comprised of 21tests, are presented in detail here. These tests cover a variety of different injectionmethods, receiver tank geometries, receiver tank materials, cryogenic propellants, andinitial tank states. Overall for the cases tested in this work, the model was able topredict the pressure response within the receiver tank to a mean absolute percentageerror of 25.9%. The temperature response error rate was 29.5% and 24.9% for wall-gasand two-phase nodes, respectively. Compared to the worst case correlation set tested,the pressure prediction error rate represents a 31% improvement. For the cases pre-sented in this work, the mean pressure prediction error rate was 15.5%. Future workcould evaluate the effectiveness of this model against experiments conducted withdifferent propellants or different initial conditions. In its current form, however, themodel can still be used to help reduce design and testing time for 1-g experiments,enabling the quicker iteration that is necessary to meet the technological demands offuture space missions.

No-Vent Top Off↗
DOE OSTI2020

Characterization of the Atmosphere of Super-Earth 55 Cancri e Using High-resolution Ground-based Spectroscopy

The nearby super-Earth 55 Cnc e orbits a bright (V = 5.95 mag) star with a period of -18 hr and a mass of -8M {sub ⊕}. Its atmosphere may be water-rich and have a large-scale height; though, attempts to characterize it have yielded ambiguous results. Here we present a sensitive search for water and TiO in its atmosphere at high spectral resolution using the Gemini North telescope and the GRACES spectrograph. We combine observations with previous observations from Subaru and CFHT, improving the constraints on the presence of water vapor. We adopt parametric models with an updated planet radius based on recent measurements, and use a cross-correlation technique to maximize sensitivity. Our results are consistent with atmospheres that are cloudy or contain minimal amounts of water and TiO. Using these parametric models, we rule out a water-rich atmosphere (VMR ≥ 0.1%) with a mean molecular weight of ≤ 15 g mol{sup -1} at a 3σ confidence level, improving on the previous limit by a significant margin. For TiO, we rule out a mean molecular weight of ≤ 5 g mol{sup -1} with a 3σ confidence level for a VMR greater than 10{sup -8}; for a VMR of greater than 10{sup -7}, the limit rises to a mean molecular weight of ≤ 10 g mol{sup -1}. We can rule out low mean-molecular-weight chemical equilibrium models both including and excluding TiO/VO at very high confidence levels (>10σ). Overall, our results are consistent with an atmosphere with a high mean molecular weight and/or clouds, or no atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Stellar model chromospheres. V - Alpha Centauri A /G2 V/ and Alpha Centauri B /K1 V/

Models for the upper photospheres and lower chromospheres of Alpha Centauri A and B are derived from high-dispersion spectrograms of the Ca II K-line emission cores and damping wings. Effective temperatures, surface gravities, and ages consistent with the measured broadband colors, metallicities, and absolute magnitudes are estimated for the two stars. The spectrograms are calibrated by fitting the far-wing K profiles with synthetic fluxes based on radiative-equilibrium models, and the model atmospheres are obtained through a partial-redistribution analysis of the line cores and damping wings. These models are compared with those previously proposed for Procyon, Arcturus, and the sun. Many features in all the models are found to be quite similar, and some evidence suggests that Alpha Cen A may be significantly older and more evolved than the sun, even though both stars exhibit similar chromospheric properties.

Ayres, T. R.↗
NASA NTRS1983

Dielectronic recombination rates, ionization equilibrium, and radiative emission rates for Mn ions in low-density high-temperature plasmas

The analysis of optically-thin far-ultraviolet and X-ray emission lines of multiply-charged ions is one of the basic methods for determining the temperatures and densities of laboratory and astrophysical plasmas. In addition, the energy balance in these plasmas can be significantly influenced by the emission of radiation from relatively low concentrations of multiple-charged atomic ions. Because the populations of the excited levels are expected to depart substantially from their local thermodynamic equilibrium values a detailed treatment of the elementary collisional and radiative processes must be employed in order to predict the emission line intensities. In this investigation the authors present the results of calculations based on a corona equilibrium model in which a detailed evaluation is made of the dielectronic recombination rate coefficients. The ionization and autoionization following inner-shell electron excitation from each ground state are balanced by direct radiative and dielectronic recombination. The spectral line intensities emitted by the low-lying excited states, which are assumed to undergo spontaneous radiative decay in times that are short compared with the collision time, are evaluated in terms of the corona ionization equilibrium distributions of the ground states and their electron-impact excitation states.

Jacobs, V. L.↗
NASA NTRS2023

Thermal Electron Heat Fluxes Associated with Precipitated Auroral Electrons During the Saint Patrick's Days 2013 and 2015 Geomagnetic Storms

The Rice Convection Model-Equilibrium (RCM-E) and SuperThermal Electron Transport (STET) are combined to investigate electron heat flux formation in the region of the diffuse aurora for the geomagnetic storms of 17 March 2013 and 17 March 2015. The primary electron precipitation into the atmosphere resulting from wave particle scattering in the magnetosphere are simulated by the magnetically and electrically RCM-E during these two geomagnetic storms. The primary precipitating electron fluxes are modified by the STET model by taking into account atmospheric backscatter processes. The modified electron energy fluxes and their mean energies are coupled to the STET code to calculate electron thermal fluxes associated with diffuse aurora on a global scale. We use the simulated heat flux to estimate electron temperatures at the upper ionospheric altitudes and compare them with corresponding observations from the Defense Meteorological Satellite Program satellite.

George V. Khazanov↗